Binding to ACE2

1403-66-3

Gentamicin

Gentacycol Gentalline gentamicina gentamicine GENTAMYCIN Gentavet Lyramycin Oksitselanim Septigen Centicin Gentamycins

DTXSID5034642

PR:000003622

PR angiotensin-converting enzyme 2

PR:000016456

PR transmembrane protease serine 2

PR:P07711

PR cathepsin L1 (human)

GO:0019015

GO viral genome

PR:000036197

PR viral protein

PR:000024938

PR interferon alpha

PR:000024939

PR interferon beta

GO:0019022

GO RNA viral genome

GO:0031381

GO viral RNA-directed RNA polymerase complex

GO:0072516

GO viral assembly compartment

GO:0019024

GO ssRNA viral genome

FMA:84050

FMA Cytokine

FMA:241981

FMA Chemokine

FMA:86578

FMA Interleukin

CL:0009002

CL inflammatory cell

CL:0000235

CL macrophage

PR:000001393

PR interleukin-6

PR:000001136

PR interleukin-1 beta

PR:000000134

PR tumor necrosis factor alpha

CHEBI:82594

CHEBI Ferritin

PR:000005897

PR C-reactive protein

CL:0000542

CL lymphocyte

GO:0005102

GO receptor binding

GO:0061025

GO membrane fusion

GO:0075509

GO endocytosis involved in viral entry into host cell

GO:0046718

GO viral entry into host cell

GO:0060337

GO type I interferon signaling pathway

GO:0071360

GO cellular response to exogenous dsRNA

GO:0039694

GO viral RNA genome replication

GO:0039690

GO positive stranded viral RNA replication

GO:0019074

GO viral RNA genome packaging

GO:0009299

GO mRNA transcription

GO:0019081

GO viral translation

GO:0002534

GO cytokine production involved in inflammatory response

GO:0090195

GO chemokine secretion

GO:0006956

GO complement activation

GO:0006954

GO inflammatory response

GO:0042116

GO macrophage activation

GO:0002544

GO chronic inflammatory response

GO:0002676

GO regulation of chronic inflammatory response

GO:0032635

GO interleukin-6 production

GO:0032611

GO interleukin-1 beta production

GO:1990774

GO tumor necrosis factor secretion

HP:0012649

HP Increased inflammatory response

HP:0003281

HP Increased serum ferritin

GO:0004457

GO lactate dehydrogenase activity

HP:0011227

HP Elevated C-reactive protein level

HP:0001888

HP Lymphopenia

WIKI occurrence

WIKI decreased

WIKI increased

Sars-CoV-2 Virus from the coronaviridae family related to SARS-CoV, 229E, NL63, OC43, HKU1 and MERS.

Transmitted by aerosols

2021-02-23T04:50:40

2022-09-09T05:09:36

Stressor:624 SARS-CoV-2

2021-04-20T03:40:36

Food deprivation

2021-09-06T07:33:54

Gentamicin

2017-10-25T08:30:15

SARS-CoV

2020-03-01T10:42:46

9606

NCBI Homo sapiens

10090

NCBI mouse

9666

NCBI Mustela lutreola

9685

NCBI Felis catus

9694

NCBI Panthera tigris

9615

NCBI Canis familiaris

9974

NCBI Manis javanica

9541

NCBI Macaca fascicularis

10036

NCBI Mesocricetus auratus

9669

NCBI Mustela putorius furo

WCS_452646

common ecological species Neovison vison

WCS_9606

common toxicological species humans

9666

NCBI mink

9685

NCBI cat

9544

NCBI rhesus macaque

WCS_9615

common toxicological species dog

WikiUser_17

mammals

10090

NCBI Mus musculus

WCS_7955

common ecological species zebrafish

WCS_9606

common toxicological species human

10116

NCBI rat

10116

NCBI rats

Binding to ACE2

Molecular

Angiotensin-converting enzyme 2 (<a href="https://www.genecards.org/cgi-bin/carddisp.pl?gene=ACE2">ACE2</a>) is an enzyme that can be found either attached to the membrane of the cells (mACE2) in many tissues and in a soluble form form (sACE2). A table on ACE2 expression levels according to tissues (Kim et al.) <table cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:medium none; height:806px; width:1049px"> <tbody> <tr> <td style="background-color:#a6a6a6; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:146px">   </td> <td style="background-color:#a6a6a6; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:146px"> Sample size </td> <td style="background-color:#a6a6a6; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:147px"> ACE2 mean expression </td> <td style="background-color:#a6a6a6; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:147px"> Standard deviation of expression </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Intestine </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 51 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 9.50 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.183 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Kidney </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 129 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 9.20 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 2.410 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Stomach </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 35 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 8.25 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 3.715 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Bile duct </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 9 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 7.23 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.163 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Liver </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 50 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 6.86 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.351 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Oral cavity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 32 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 6.23 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.271 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Lung </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 110 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 5.83 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 0.710 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Thyroid </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 59 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 5.65 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 0.646 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Esophagus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 11 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 5.31 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.552 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Bladder </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 19 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 5.10 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.809 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Breast </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 113 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 4.61 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 0.961 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Uterus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 25 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 4.37 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.125 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> Protaste </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:146px"> 52 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 4.35 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:147px"> 1.905 </td> </tr> </tbody> </table> ACE2 receptors in the brain (endothelial, neuronal and glial cells): The highest ACE2 expression level in the brain was found in the pons and medulla oblongata in the human brainstem, containing the medullary respiratory centers (Lukiw et al., 2020). High ACE2 receptor expression was also found in the amygdala, cerebral cortex and in the regions involved in cardiovascular function and central regulation of blood pressure including the sub-fornical organ, nucleus of the tractus solitarius, paraventricular nucleus, and rostral ventrolateral medulla (Gowrisankar and Clark 2016; Xia and Lazartigues 2010). The neurons and glial cells, like astrocytes and microglia also express ACE-2. In the brain, ACE2 is expressed in endothelium and vascular smooth muscle cells (Hamming et al., 2004), as well as in neurons and glia (Gallagher et al., 2006; Matsushita et al., 2010; Gowrisankar and Clark, 2016; Xu et al., 2017; de Morais et al., 2018) (from Murta et al., 2020). Astrocytes are the main source of angiotensinogen and express ATR1 and MasR; neurons express ATR1, ACE2, and MasR, and microglia respond to ATR1 activation (Shi et al., 2014; de Morais et al., 2018). ACE2 receptors in the intestines The highest levels of ACE2 are found at the luminal surface of the enterocytes, the differentiated epithelial cells in the small intestine, lower levels in the crypt cells and in the colon (Liang et al, 2020; Hashimoto et al., 2012, Fairweather et al. 2012; Kowalczuk et al. 2008).

In vitro methods supporting interaction between ACE2 and SARS-CoV-2 spike protein Several reports using surface plasmon resonance (SPR) or biolayer interferometry binding (BLI) approaches. to study the interaction between recombinant ACE2 and S proteins have determined a dissociation constant (Kd) for SARS-CoV S and SARS-CoV-2 S as follow, <table cellspacing="0" class="Table" style="border-collapse:collapse; width:568px"> <tbody> <tr> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; height:28px; width:176px"> Reference </td> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:28px; width:102px"> ACE2 protein </td> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:28px; width:140px"> SARS-CoV S </td> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:28px; width:151px"> SARS-CoV2 S </td> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:28px; width:128px"> Method </td> <td style="background-color:#f7f7f7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:28px; width:156px"> Measured Kd </td> </tr> <tr> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; width:176px"> doi:<a class="id-link" href="https://doi.org/10.1126/science.abb2507" rel="noopener" target="_blank">10.1126/science.abb2507</a> </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:102px"> 1–615 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px"> 306–577 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px">   </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:128px"> SPR </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 325.8 nM </td> </tr> <tr> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px">   </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px"> 1–1208 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 14.7 nM </td> </tr> <tr> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; width:176px"> doi:<a class="id-link" href="https://doi.org/10.1001/jama.2020.3786" rel="noopener" target="_blank">10.1001/jama.2020.3786</a> </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:102px"> 19–615 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px"> 306–527 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px">   </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:128px"> SPR </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 408.7 nM </td> </tr> <tr> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px">   </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px"> 319–541 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 133.3 nM </td> </tr> <tr> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; width:176px"> <a href="https://elifesciences.org/articles/61390#bib67" style="color:blue; text-decoration:underline">Lan et al., 2020</a> </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:102px"> 19–615 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px"> 306–527 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px">   </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:128px"> SPR </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 31.6 nM </td> </tr> <tr> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px">   </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px"> 319–541 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 4.7 nM </td> </tr> <tr> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; width:176px"> doi:<a class="id-link" href="https://doi.org/10.1016/j.cell.2020.02.058" rel="noopener" target="_blank">10.1016/j.cell.2020.02.058</a> </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:102px"> 1–614 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px"> 306–575 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px">   </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:128px"> BLI </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 1.2 nM </td> </tr> <tr> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px">   </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px"> 328–533 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 5 nM </td> </tr> <tr> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; width:176px"> doi:<a class="id-link" href="https://doi.org/10.1126/science.abb2507" rel="noopener" target="_blank">10.1126/science.abb2507</a> </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:102px"> 1–615 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px"> 306–577 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px">   </td> <td rowspan="2" style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:128px"> BLI </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 13.7 nM </td> </tr> <tr> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:140px">   </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:151px"> 319–591 aa </td> <td style="background-color:white; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; width:156px"> 34.6 nM </td> </tr> </tbody> </table> Pseudo typed vesicular stomatitis virus expressing SARS-CoV-2 S (VSV-SARS-S2) expression system can be used efficiently infects cell lines, with Calu-3 human lung adenocarcinoma epithelial cell line, CaCo-2 human colorectal adenocarcinoma colon epithelial cell line and Vero African grey monkey kidney epithelial cell line being the most permissive (Hoffmann et al., 2020; Ou et al., 2020).  It can be measured using a wide variety of assays targeting different biological phases of infection and altered cell membrane permeability and cell organelle signaling pathway. Other assay measured alteration in the levels of permissive cell lines all express ACE2 or hACE2-expressing 293T cell (e.g. pNUO1-hACE2, pFUSE-hIgG1-Fc2), as previously demonstrated by indirect immunofluorescence (IF) or by immunoblotting are associated with ELISA(W Tai et al., nature 2020). To prioritize the identified potential KEs for selection and to select a KE to serve as a case study, further in-silico data that ACE2 binds to SARS-CoV-2 S is necessary for virus entry. The above analysis outlined can be used evidence-based assessment of molecular evidence as a MIE.

UBERON:0000062

UBERON organ

CL:0000000

CL cell

High Mixed

High

Adult, reproductively mature

High

During development and at adulthood

High High High Moderate Moderate Low

de Morais SDB, et al. Integrative Physiological Aspects of Brain RAS in Hypertension. Curr Hypertens Rep. 2018 Feb 26; 20(2):10. Gallagher PE, et al. Distinct roles for ANG II and ANG-(1-7) in the regulation of angiotensin-converting enzyme 2 in rat astrocytes. Am J Physiol Cell Physiol. 2006 Feb; 290(2):C420-6. Gowrisankar YV, Clark MA. Angiotensin II regulation of angiotensin-converting enzymes in spontaneously hypertensive rat primary astrocyte cultures. J Neurochem. 2016 Jul; 138(1):74-85. Hamming I et al. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol. 2004 Jun;203(2):631-7. Jakhmola S, et al. SARS-CoV-2, an Underestimated Pathogen of the Nervous System. SN Compr Clin Med. 2020. Lukiw WJ et al. SARS-CoV-2 Infectivity and Neurological Targets in the Brain. Cell Mol Neurobiol. 2020 Aug 25;1-8. Matsushita T, et al. CSF angiotensin II and angiotensin-converting enzyme levels in anti-aquaporin-4 autoimmunity. J Neurol Sci. 2010 Aug 15; 295(1-2):41-5. Murta et al. Severe Acute Respiratory Syndrome Coronavirus 2 Impact on the Central Nervous System: Are Astrocytes and Microglia Main Players or Merely Bystanders? ASN Neuro. 2020. PMID: 32878468 Shi A, et al. Isolation, purification and molecular mechanism of a peanut protein-derived ACE-inhibitory peptide. PLoS One. 2014; 9(10):e111188. Xia, H. and Lazartigues, E.  Angiotensin-Converting Enzyme 2: Central Regulator for Cardiovascular Function. Curr. Hypertens. 2010  Rep. 12 (3), 170– 175 AOPWiki 2020-03-02T03:18:47

2023-04-03T04:03:07

SARS-CoV-2 cell entry

Cellular

Coronavirus is recognized by the binding of S protein on the viral surface and angiotensin-converting enzyme 2 (ACE2) receptor on the cellular membrane, followed by viral entry via processing of S protein by transmembrane serine protease 2 (TMPRSS2) (Hoffmann et al., 2020b). ACE2 is expressed on epithelial cells of the lung and intestine, and also can be found in the heart, kidney, adipose, and male and female reproductive tissues (Lukassen et al., 2020, Lamers et al., 2020, Chen et al., 2020, Jing et al., 2020, Subramanian et al., 2020). SARS-CoV-2 is an enveloped virus characterized by displaying spike proteins at the viral surface (Juraszek et al., 2021). Spike is critical for viral entry (Hoffmann et al., 2020b) and is the primary target of vaccines and therapeutic strategies, as this protein is the immunodominant target for antibodies (Yuan et al., 2020, Ju et al., 2020, Robbiani et al., 2020, Premkumar et al., 2020, Liu et al., 2020). Spike is composed of S1 and S2 subdomains. S1 contains the N-terminal (NTD) and receptor-binding (RBD) domains, and the S2 contains the fusion peptide (FP), heptad repeat 1 (HR1) and HR2, the transmembrane (TM) and cytoplasmic domains (CD) (Lan et al., 2020). S1 leads to the recognition of the angiotensin-converting enzyme 2 (ACE2) receptor and S2 is involved in membrane fusion (Hoffmann et al., 2020b, Letko et al., 2020, Shang et al., 2020). Upon binding to ACE2, the spike protein needs to be activated (or primed) through proteolytic cleavage (by a host protease) to allow membrane fusion. Fusion is a key step in viral entry as it is the way to release SARS-CoV-2 genetic material inside the cell. Cleavage happens between its spike’s S1 and S2 domains, liberating S2 that inserts its N-terminal domain into a host cell membrane and mediates membrane fusion (Millet and Whittaker, 2018). Many proteases were identified to activate coronaviruses including furin, cathepsin L, trypsin-like serine proteases TMPRSS2, TMPRSS4, TMPRSS11, and human airway trypsin-like protease (HATs). These may operate at four different stages of the<a href="https://www.wikipathways.org/index.php/Pathway:WP4846"> virus infection cycle</a>: (a) pro-protein convertases (e.g., furin) during virus packaging in virus-producing cells, (b) extracellular proteases (e.g., elastase) after virus release into extracellular space, (c) cell surface proteases [e.g., type II transmembrane serine protease (TMPRSS2)] after virus attachment to virus-targeting cells, and (d ) lysosomal proteases (e.g., cathepsin L) after virus endocytosis in virus-targeting cells (Li, 2016). SARS-CoV-2 lipidic envelope may fuse with two distinct membrane types, depending on the host protease(s) responsible for cleaving the spike protein: (i) cell surface following activation by serine proteases such as TMPRSS2 and furin (Hoffmann et al., 2020b); or (ii) endocytic pathway within the endosomal–lysosomal compartments including processing by lysosomal cathepsin L (Yang and Shen, 2020). These flexibility for host cell factors mediating viral entry, highlights that the availability of factors existing in a cell type dictates the mechanism of viral entry (Kawase et al., 2012). When TMPRSS2 (or other serine proteases such as TMPRSS4 (Zang et al., 2020) or human airway trypsin-like protease [HAT] (Bestle et al., 2020a)) is expressed, fusion of the virus with the cell surface membrane is preferred (Shirato et al., 2018), while in their absence, the virus can penetrate the cell by endocytosis (Kawase et al., 2012). A third factor has also been shown to facilitate SARS-CoV-2 entry in cells that have ACE2 and even promote, although to very low levels, SARS-CoV-2 entry in cells that lack ACE2 and TMPRSS2 which is the neuropilin-1 (NRP-1) (Cantuti-Castelvetri et al., 2020). This key event deals with SARS-CoV-2 entry in host cells and is divided in three categories: TMPRSS2, capthesin L and NRP-1. TMPRSS2 Spike cleavage: TMPRSS2 (transmembrane serine protease 2, (<a href="https://www.ncbi.nlm.nih.gov/gene/7113" style="color:blue; text-decoration:underline">https://www.ncbi.nlm.nih.gov/gene/7113</a>) is a cell-surface protease (Hartenian et al., 2020) that facilitates entry of viruses into host cells by proteolytically cleaving and activating viral envelope glycoproteins. Viruses found to use this protein for cell entry include Influenza virus and the human coronaviruses HCoV-229E, MERS-CoV, SARS-CoV and SARS-CoV-2 (COVID-19 virus). TMPRSS2 is a membrane bound serine protease also known as epitheliasin. TMPRSS2 belongs to the S1A class of serine proteases alongside proteins such as factor Xa and trypsin. Whilst there is evidence that TMPRSS2 autoclaves to generate a secreted protease, its physiological function has not been clearly identified. However, it is known to play a crucial role in facilitating entry of coronavirus particles into cells by cleaving the spike protein (Huggins, 2020). After ACE2 receptor binding, SARS-CoV-2 S proteins can be subsequently cleaved and activated by host cell-surface protease at the S1/S2 and S2’ sites, generating the subunits S1 and S2 that remain non-covalently linked. Cleavage leads to activation of the S2 domain that drives fusion of the viral and host membranes (Hartenian et al., 2020, Walls et al., 2016). For other coronaviruses, processing of spike was proposed to be sequential with S1/S2 cleavage preceding that of S2. Cleavage at S1/S2 may be crucial for inducing conformational changes required for receptor binding or exposure of the S2 site to host proteases. The S1/S2 site of SARS-CoV-2 S protein contains an insertion of four amino acids providing a minimal furin cleavage site (RRAR685↓) (that is absent in SARS-CoV). Interestingly, the furin cleavage site has been implicated in increased viral pathogensis (Bestle et al., 2020b, Huggins, 2020). Processing of the spike protein by furin at the S1/S2 cleavage site is thought to occur following viral replication in the endoplasmic reticulum Golgi intermediate compartment (ERGIC) (Hasan et al., 2020). The spike S2’ cleavage site of SARS-CoV-2 possesses a paired dibasic motif with a single KR segment (KR815↓) (as SARS-CoV) that is recognized by trypsin-like serine proteases such as TMPRSS2. The current data support a model for SARS-CoV-2 entry in which furin-mediated cleavage at the S1/S2 site pre-primes spike during biogenesis, facilitating the activation for membrane fusion by a second cleavage event at S2’ by TMPRSS2 following ACE2 binding (Bestle et al., 2020b, Johnson et al., 2020). <table cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:166px"> Virus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:233px"> S1/S2 site </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:236px"> S2’ site </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:166px"> SARS-CoV-2 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:233px"> TNSPRRAR|SVA </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:236px"> PSKPSKR|SFIEDL </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:166px"> SARS-CoV </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:233px"> S----LLR|STS </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:236px"> PLKPTKR|SFIEDL </td> </tr> </tbody> </table> Camostat mesylate, an inhibitor of TMPRSS2, blocks SARS-CoV-2 infection of lung cells like Calu-3 cells but not Huh7.5 and Vero E6 cells. Cell entry was assessed using a viral isolate and viral pseudotypes (artificial viruses) expressing the COVID-19 spike (S) protein. The ability of the viral pseudotypes (expressing S protein from SARS-CoV and SARS-CoV-2) to enter human and animal cell lines was demonstrated, showing that SARS-CoV-2 can enter similar cell lines as SARS-CoV. Amino acid analysis and cell culture experiments showed that, like SARS-CoV, SARS-CoV-2 spike protein binds to human and bat angiotensin-converting enzyme 2 (ACE2) and uses a cellular protease TMPRSS2 for priming. Priming activates the spike protein to facilitate viral fusion and entry into cells. Cell culture experiments were performed using immortalized cell lines and primary human lung cells (Hoffmann et al., 2020b, Rahman et al., 2020).   Spike binding to neuropilin-1: Neuropilin-1 (NRP1) is a transmembrane glycoprotein that serves as a cell surface receptor for semaphorins and various ligands involved in angiogenesis in vertebrates. NRP1 is expressed in neurons, blood vessels (endothelial cells), immune cells and many other cell types in the mammalian body (maternal fetal interface) and binds a range of structurally and functionally diverse extracellular ligands to modulate organ development and function (Raimondi et al., 2016).  NRP1 is well described as a co-receptor for members of the class 3 semaphorins (SEMA3) or vascular endothelial growth factors (VEGFs) (Gelfand et al., 2014). Structurally, NRP1 comprises seven sub-domains, of which the first five are extracellular; two CUB domains (a1 and a2), two coagulation factor V/VIII domains (FV/VIII; b1 and b2) and a meprin, A5 μ-phosphatase domain (MAM; c). NRP1 contains only a short cytosolic tail with a PDZ-binding domain lacking internal signaling activity. The different ligand families bind to different sites of NRP1; SEMA3A binding requires the first three sub-domains of NRP1 (a1, a2, and b1), whereas binding of VEGF-A requires the b1 and b2 domains (Muhl et al., 2017). Additional studies conducted by means of in silico computational technology to identify and validate inhibitors of the interaction between NRP1 and SARS-CoV-2 Spike protein are reported in (Perez-Miller et al., 2020).  Represents a schematic picture of VEGF-A triggered phosphorylation of VEGF-R2. Screening of NRP-1/VEGF-A165 inhibitors by in-cell Western (Perez-Miller et al., 2020).v NRP1 acts as a co-receptor for SARS-CoV-2. NRP1 is a receptor for furin-cleaved SARS-CoV-2 spike peptide (Cantuti-Castelvetri et al., 2020, Daly et al., 2020, Johnson et al., 2020). Blockade of NRP1 reduces infectivity and entry, and alteration of the furin site leads to loss of NRP1 dependence, reduced replication in Calu3, augmented replication in Vero E6, and attenuated disease in a hamster pathogenesis disease model (Johnson et al., 2020). In fact, a small sequence of amino acids was found that appeared to mimic a protein sequence found in human proteins that interact with NRP1. The spike protein of SARS-CoV-2 binding with NRP1 aids viral infection of human cells. This was confirmed by applying a range of structural and biochemical approaches to establish that the spike protein of SARS-CoV-2 does indeed bind to NRP1. The host protease furin cleaves the full-length precursor S glycoprotein into two associated polypeptides: S1 and S2. Cleavage of S generates a polybasic RRAR C-terminal sequence on S1, which conforms to a C-end rule (CendR) motif that binds to cell surface neuropilin-1 (NRP1) and neuropilin-2 (NRP2) receptors. It was reported that the S1 CendR motif directly bound NRP1 by X-ray crystallography and biochemical approaches. Blocking this interaction using RNAi or selective inhibitors reduced SARS-CoV-2 entry and infectivity in cell culture (Daly et al., 2020). NRP1, known to bind furin-cleaved substrates, significantly potentiates SARS-CoV-2 infectivity, which was revealed by a monoclonal blocking antibody against NRP1. It was found that a SARS-CoV-2 mutant with an altered furin cleavage site did not depend on NRP1 for infectivity. Pathological analysis of olfactory epithelium obtained from human COVID-19 autopsies revealed that SARS-CoV-2 infected NRP1-positive cells faced the nasal cavity (Cantuti-Castelvetri et al., 2020). Furthermore, it has been found that NRP1 is a new potential SARS‑CoV‑2 infection mediator implicated in the neurologic features and central nervous system involvement of COVID‑19.  Preclinical studies have suggested that NRP1, a transmembrane receptor that lacks a cytosolic protein kinase domain and exhibits high expression in the respiratory and olfactory epithelium, may also be implicated in COVID‑19 by enhancing the entry of SARS‑CoV‑2 into the brain through the olfactory epithelium. NRP1 is also expressed in the CNS, including olfactory‑related regions such as the olfactory tubercles and paraolfactory gyri. Supporting the potential role of NRP1 as an additional SARS‑CoV‑2 infection mediator implicated in the neurologic manifestations of COVID‑19. Accordingly, the neurotropism of SARS‑CoV‑2 via NRP1‑expressing cells in the CNS merits further investigation (Davies et al., 2020).   Up-regulation of NRP1 protein in diabetic kidney cells hints at its importance in a population at risk of severe COVID-19. Involvement of NRP-1 in immune function is compelling, given the role of an exaggerated immune response in disease severity and deaths due to COVID-19. NRP-1 has been suggested to be an immune checkpoint of T cell memory. It is unknown whether involvement and up-regulation of NRP-1 in COVID-19 may translate into disease outcome and long-term consequences, including possible immune dysfunction (Mayi et al., 2021). The main feature of NRP1 co-receptor is to form complexes with multiple other receptors. Hence, there is a competition between receptors to complex with NRP-1, which may determine their abilities both quantitatively and qualitatively to transduce signals. It is tempting to hypothesize that the occupancy of NRP-1 with one receptor may thus decrease its availability for virus entry. Recent proteomics work has shown that NRP-1 can form a complex with the α7 nicotinic receptor in mice. Both receptors are expressed in the human nasal and pulmonary epithelium (Mayi et al., 2021). NRP1, is highly expressed in the respiratory and olfactory epithelium; it is also expressed in the CNS, including olfactory related regions such as the olfactory tubercles and paraolfactory gyri (Davies et al., 2020). More information on tissue distribution and protein expression of NRP1 can be found in https://www.proteinatlas.org/ENSG000000992 50-NRP1 Spike entry via lysosomal cathepsins and endocytosis: Evidence shows the role of TMPRSS2 and other serine proteases in activating the coronavirus spike protein for plasma membrane fusion. However, studies using various cell culture systems showed that SARS-CoV2 could enter cells via an alternative endosomal–lysosomal pathway. Evidence came from studies demonstrating that lysosomotropic agents reduced SARS-CoV replication in cells lacking TMPRSS2 and other studies, using highly potent and specific small-molecule cathepsin inhibitors, to understand the role of cathepsins in processing and activating the spike for membrane fusion, mainly of cathepsin L (one of the 11 cathepsins) (Rossi et al., 2004, Simmons et al., 2005). SARS-CoV-2 and other coronaviruses can establish infection through endosomal entry in commonly used in vitro cell culture systems. Of relevance, inhibitors of the endosomal pathway, as the cathepsin inhibitor Z-FA-FMK and PIKfyve inhibitor apilimod, blocked viral entry in Huh7.5 and Vero E6 cells but not Calu-3 cells. Viral entry leads to delivery of virion proteins and translation of viral proteins immediately: Coronavirus is a class of viruses that have single-stranded positive-sense RNA genomes in their envelopes [Kim D, et al., 2020]. The virus contains a 29.7 kB positive-sense RNA genome flanked by 5' and 3' untranslated regions of 265 and 342 nucleotides, respectively that contain cis-acting secondary RNA structures essential for RNA synthesis [Huston N. C. et al., 2021]. The genome just prior to the 5′ end contains the transcriptional regulatory sequence leader (TRS-L) [Budzilowicx C.J., et al., 1985]. The SARS-CoV genome is polycistronic and contains 14 open reading frames (ORFs) that are expressed by poorly understood mechanisms [Snijder E. J., et al., 2003]. Preceding each ORF there are other TRSs called the body TRS (TRS B). The 5′ two-thirds of the genome contains two large, overlapping, nonstructural ORFs and the 3′ third contains the remainder ORFs [Di H., et al., 2018]. Genome expression starts with the translation of two large ORFs of the 5’ two-thirds: ORF1a of 4382 amino acids and ORF1ab of 7073 amino acid that occurs via a programmed (- 1) ribosomal frameshifting [Snijder E. J., et al., 2003], yielding pp1a and pp1ab. These two polyproteins are cleaved into 16 subunits by two viral proteinases encoded by ORF1a, nsp3, and nsp5 that contain a papain-like protease domain and a 3C-like protease domain [Sacco M. D. et al., 2020]. The processing products are a group of replicative enzymes, named nsp1-nsp16, that assemble into a viral replication and transcription complex (RTC) associated with membranes of endoplasmic reticulum (ER) with the help of various membrane-associated viral proteins [Klein S., et al., 2021, Snijder E. J., et al., 2020, V'Kovski P. , et al., 2021]. This association leads to replication factories or organelles, that are originate new membranous structures that are observed by electron mciroscopy . They are a feature of all coronaviridae and the site of viral replication and transcription hidden from innate immune molecules.

SARS-CoV2 entry can be determined by many different ways: 1) quantitative RT-PCR specific to the subgenomic mRNA of the N transcript, in cells manipulated with host factors that express of not TMPRSS2, cathepsinL, neuropilin-1, hACE2 [Glowacka I, et al. (2011)], or exogenous addition of HAT or furin. 2) using spike-pseudotyped viral particles expressing GFP/luciferase/bgalactosidase and comparing with vesicular stomatitis virus G seudotyped particles expressing the same reporter analysed in manipulated cultured with cell lines, followed by determining fluorescence, biolumincescence, luciferase activity in cell lysates  [Hoffmann M, et al. (2020)]. TMPRSS2: TMPRSS2 gene expression can be measured by RNAseq and microarray (Baughn et al., 2020). Expression levels of TMPRSS2 can be measured by RNA in situ hybridization (RNA-ISH) (Qiao et al., 2020) NRP-1: Several methods have been identified in the literature for measuring and detecting NRP1 receptor binding. Briefly described: <ol> <li>X-ray crystallography  and biochemical approaches help to show that the S1 CendR motif directly bound NRP1 (1).  Binding of the S1 fragment to NRP1 was assessed and ability of SARS-CoV-2 to use NRP1 to infect cells was measured in angiotensin-converting enzyme-2 (ACE-2)-expressing cell lines by knocking out NRP1 expression, blocking NRP1 with 3 different anti-NRP1 monoclonal antibodies, or using NRP1 small molecule antagonists (Centers for Disease Control and Prevention, 2020, Daly et al., 2020).</li> </ol> Key findings (Centers for Disease Control and Prevention, 2020, Daly et al., 2020): • The S1 fragment of the cleaved SARS-CoV-2 spike protein binds to the cell surface receptor neuropilin-1 (NRP1). • SARS-CoV-2 utilizes NRP1 for cell entry as evidenced by decreased infectivity of cells in the presence of: NRP1 deletion (p <0.01). Three different anti-NRP1 monoclonal antibodies (p <0.001). Selective NRP1 antagonist, EG00229 (p <0.01). <ol start="2"> <li>Cell lines were modified to express ACE2 and TMPRSS2, the two known SARS-CoV-2 host factors, and NRP1 to assess the contribution of NRP1 to infection. Autopsy specimens from multiple airway sites were stained with antibodies against SARS-CoV-2 proteins, ACE2, and NRP1, to visualize co-localization of proteins (6, 15).</li> </ol> Key findings (Cantuti-Castelvetri et al., 2020, Centers for Disease Control and Prevention, 2020): • Infectivity of cells expressing angiotensin converting enzyme-2 (ACE2, receptor for SARS-CoV-2), transmembrane protease serine-2 (TSS2, primes the Spike [S] protein), and neuropilin-1 (NRP1) with pseudovirus expressing the SARS-CoV-2 S1 protein was approximately 3-fold higher than in cells expressing either ACE2 or TSS2 alone (p<0.05). • Analysis of autopsy tissue from COVID-19 patients showed co-localization of the SARS-CoV-2 spike (S) protein and NRP1 in olfactory and respiratory epithelium. Virtual screen of nearly 0.5 million compounds against the NRP-1 CendR site, resulting in nearly 1,000 hits. A pharmacophore model was derived from the identified ligands, considering both steric and electronic requirements. Preparation of receptor protein and grid for virtual screening, docking of known NRP-1 targeting compounds, ELISA based NRP1-VEGF-A165 protein binding assay; more details on methodology in the referenced paper (Perez-Miller et al., 2020)

TMPRSS2 vertebrates (Lam et al., 2020) NRP1 in human & rodents (but also present in monkey and other vertebrates (Lu and Meng, 2015) The ability for SARS-CoV-2 to use multiple host pathways for viral entry, means that it is critical to map which viral entry pathway is prevalent in specific cell types. This is key for understanding coronavirus biology, but also use informed decisions to select cells for cell-based genetic and small-molecule screens and to interpret data. In fact, a combination of protease inhibitors that block both TRMPSS2 and cathepsin L is the most efficient combination to block coronavirus infection (Yamamoto et al., 2020, Shang et al., 2020, Shirato et al., 2018). In accordance, SARS-CoV-2 entry processes are highly dependent on endocytosis and endocytic maturation in cells that do not express TMPRSS2, such as VeroE6 or 293T cells (Murgolo et al., 2021, Kang et al., 2020, Mirabelli et al., 2020, Riva et al., 2020). However, even in these cells, heterologous expression of TMPRSS2 abrogates the pharmacological blockade of cathepsin inhibitors (Kawase et al., 2012, Hoffmann et al., 2020a). Treatment of SARS-CoV-2 with trypsin enables viral cell surface entry, even when TMPRSS2 is absent. Moreover, TMPRSS2 is more efficient to promote viral entry than cathepsins (Lamers et al., 2020), as when both factors are present,d cathepsin inhibitors are less effective than TMPRSS2 inhibitors (Hoffmann et al., 2020b). Therefore it is critical to map which cells contain the different types of proteases. In summary, TMPRSS2 appears to be expressed in a wide range of healthy adult organs, but in restricted cell types, including: <ul> <li>AT2 and clara cells of lungs</li> <li>sinusoidal endothelium, and hepatocyte of the liver, </li> <li>endocrine cells of the prostate, </li> <li>goblet cells , and enterocytes of the small intestine, </li> <li>intercalated cells, and the proximal tubular of the kidney.</li> <li>Ciliated, secretory and suprabasal of nasal</li> <li>spermatogonial stem cells of testes</li> <li>cyto tropoblast and peri vascular cells of placenta</li> <li>The nasal epithelium expresses various combinations of factors that, in principle, could facilitate SARS-CoV-2 infection, but it also expresses robust basal levels of RFs, which may act as a strong protective barrier in this tissue.</li> </ul> There is a shift in TMPRSS2 regulation during nasal epithelium differentiation in young individuals that is not occurring in old individuals (Lin et al., 1999, Lucas et al., 2008, Singh et al., 2020). Only a small minority of human respiratory and intestinal cells have genes that express both ACE2 and TMPRSS2. Amongst the ones that do, three main cell types were identified: A) lung cells called type II pneumocytes (which help maintain air sacs, known as alveoli); B) intestinal cells called enterocytes, which help the body absorb nutrients; and C) goblet cells in the nasal passage, which secrete mucus (Ziegler et al., 2020). The clinical manifestations of COVID‐19 include not only complications from acute myocardial injury, elevated liver enzymes, and acute kidney injury in patients presenting to hospitals, but also gastrointestinal symptoms in community patients experiencing milder forms of the disease (Madjid et al., 2020, Pan et al., 2020).   NRP-1: All life stages The expression of isoforms 1 (NRP1) and 2 (NRP2) does not seem to overlap. Isoform 1 is expressed by the blood vessels of different tissues. In the developing embryo it is found predominantly in the nervous system. In adult tissues, it is highly expressed in heart and placenta; moderately in lung, liver, skeletal muscle, kidney and pancreas; and low in adult brain. Isoform 2 is found in liver hepatocytes, kidney distal and proximal tubules. Expressed in colon and 234 other tissues with Low tissue specificity (UniProtKB). The expression of NRP1 protein in gastric cancer was not related to gender or age (Cao et al., 2020).   Sex Applicability: TMPRSS2: Androgen receptors (ARs) play a key role in the transcription of TMPRSS2 (Fig. 1). This may explain the predominance of males to COVID-19 infection, fatality, and severity because males tend to have a higher expression and activation of ARs than females, which is due to the presence of dihydrotestosterone (DHT). Regulation of COVID-19 severity and fatality by sex hormones. Females have aromatase, the enzyme that converts androgen substrates into estrogen. On the other hand, males have steroid 5α reductase, the enzyme that is responsible for the conversion of testosterone into dihydrotestosterone (DHT). In case of males, DHT activates androgen receptor (AR) that binds to the androgen response element (ARE) present in the promoter of TMPRSS2 gene, leading to its transcription. This ultimately results into enhanced processing of viral spike protein for greater entry and spread of SARS-CoV-2 into host cells. On the other hand,in females, estrogen activates estrogen receptor (ER), which binds to the estrogen response element (ERE) present in the promoter of eNOS gene to drive its transcription and catalyze the formation of nitric oxide (NO) from L-arginine. This NO is involved in vasodilation as well as inhibition of viral replication. NRP-1: For more information difference of NRP1 expression between male and female see <a href="https://www.proteinatlas.org/ENSG00000099250-NRP1/tissue">https://www.proteinatlas.org/ENSG00000099250-NRP1/tissue</a>. The expression of NRP1 protein in gastric cancer was not related to gender, age. The expression of NRP1 protein in gastric cancer is closely correlated to clinical stage, tumor size, TNM stage, differentiation, and lymph node metastasis (Cao et al., 2020). SARS-CoV-2 Spike protein co-opts VEGF-A/Neuropilin-1 receptor signalling to induce analgesia had same results on both male and female rodents (Moutal et al., 2020).

UBERON:0000062

UBERON organ

CL:0000000

CL cell

High Unspecific

High

All life stages

High Low Moderate Not Specified Not Specified Not Specified Moderate High High Moderate

BAUGHN, L. B., SHARMA, N., ELHAIK, E., SEKULIC, A., BRYCE, A. H. & FONSECA, R. 2020. Targeting TMPRSS2 in SARS-CoV-2 Infection. Mayo Clin Proc, 95, 1989-1999. BESTLE, D., HEINDL, M. R., LIMBURG, H., VAN LAM VAN, T., PILGRAM, O., MOULTON, H., STEIN, D. A., HARDES, K., EICKMANN, M., DOLNIK, O., ROHDE, C., KLENK, H.-D., GARTEN, W., STEINMETZER, T. & BÖTTCHER-FRIEBERTSHÄUSER, E. 2020a. TMPRSS2 and furin are both essential for proteolytic activation of SARS-CoV-2 in human airway cells. Life Science Alliance, 3. BESTLE, D., HEINDL, M. R., LIMBURG, H., VAN LAM VAN, T., PILGRAM, O., MOULTON, H., STEIN, D. A., HARDES, K., EICKMANN, M., DOLNIK, O., ROHDE, C., KLENK, H. D., GARTEN, W., STEINMETZER, T. & BOTTCHER-FRIEBERTSHAUSER, E. 2020b. TMPRSS2 and furin are both essential for proteolytic activation of SARS-CoV-2 in human airway cells. Life Sci Alliance, 3. BUDZILOWICZ, C.J., WILCZYNSKI, S.P., AND WEISS, S.R. (1985). Three intergenic regions of coronavirus mouse hepatitis virus strain A59 genome RNA contain a common nucleotide sequence that is homologous to the 3' end of the viral mRNA leader sequence. J Virol 53, 834-840. CANTUTI-CASTELVETRI, L., OJHA, R., PEDRO, L. D., DJANNATIAN, M., FRANZ, J., KUIVANEN, S., VAN DER MEER, F., KALLIO, K., KAYA, T., ANASTASINA, M., SMURA, T., LEVANOV, L., SZIROVICZA, L., TOBI, A., KALLIO-KOKKO, H., OSTERLUND, P., JOENSUU, M., MEUNIER, F. A., BUTCHER, S. J., WINKLER, M. S., MOLLENHAUER, B., HELENIUS, A., GOKCE, O., TEESALU, T., HEPOJOKI, J., VAPALAHTI, O., STADELMANN, C., BALISTRERI, G. & SIMONS, M. 2020. Neuropilin-1 facilitates SARS-CoV-2 cell entry and infectivity. Science, 370, 856-860. CAO, H., LI, Y., HUANG, L., BAI, B. & XU, Z. 2020. Clinicopathological Significance of Neuropilin 1 Expression in Gastric Cancer: A Meta-Analysis. Dis Markers, 2020, 4763492. CENTERS FOR DISEASE CONTROL AND PREVENTION, U. S. D. O. H. A. H. S. 2020. Covid-19 Science Update 2020. CHEN, L., LI, X., CHEN, M., FENG, Y. & XIONG, C. 2020. The ACE2 expression in human heart indicates new potential mechanism of heart injury among patients infected with SARS-CoV-2. Cardiovasc Res, 116, 1097-1100. DALY, J. L., SIMONETTI, B., KLEIN, K., CHEN, K. E., WILLIAMSON, M. K., ANTON-PLAGARO, C., SHOEMARK, D. K., SIMON-GRACIA, L., BAUER, M., HOLLANDI, R., GREBER, U. F., HORVATH, P., SESSIONS, R. B., HELENIUS, A., HISCOX, J. A., TEESALU, T., MATTHEWS, D. A., DAVIDSON, A. D., COLLINS, B. M., CULLEN, P. J. & YAMAUCHI, Y. 2020. Neuropilin-1 is a host factor for SARS-CoV-2 infection. Science, 370, 861-865. DAVIES, J., RANDEVA, H. S., CHATHA, K., HALL, M., SPANDIDOS, D. A., KARTERIS, E. & KYROU, I. 2020. Neuropilin1 as a new potential SARSCoV2 infection mediator implicated in the neurologic features and central nervous system involvement of COVID19. Mol Med Rep, 22, 4221-4226. DI, H., MCINTYRE, A.A., AND BRINTON, M.A. (2018). New insights about the regulation of Nidovirus subgenomic mRNA synthesis. Virology 517, 38-43. GELFAND, M. V., HAGAN, N., TATA, A., OH, W. J., LACOSTE, B., KANG, K. T., KOPYCINSKA, J., BISCHOFF, J., WANG, J. H. & GU, C. 2014. Neuropilin-1 functions as a VEGFR2 co-receptor to guide developmental angiogenesis independent of ligand binding. Elife, 3, e03720. HARTENIAN, E., NANDAKUMAR, D., LARI, A., LY, M., TUCKER, J. M. & GLAUNSINGER, B. A. 2020. The molecular virology of coronaviruses. J Biol Chem, 295, 12910-12934. HASAN, A., PARAY, B. A., HUSSAIN, A., QADIR, F. A., ATTAR, F., AZIZ, F. M., SHARIFI, M., DERAKHSHANKHAH, H., RASTI, B., MEHRABI, M., SHAHPASAND, K., SABOURY, A. A. & FALAHATI, M. 2020. A review on the cleavage priming of the spike protein on coronavirus by angiotensin-converting enzyme-2 and furin. J Biomol Struct Dyn, 1-9. HOFFMANN, M., KLEINE-WEBER, H. & POHLMANN, S. 2020a. A Multibasic Cleavage Site in the Spike Protein of SARS-CoV-2 Is Essential for Infection of Human Lung Cells. Mol Cell, 78, 779-784 e5. HOFFMANN, M., KLEINE-WEBER, H., SCHROEDER, S., KRUGER, N., HERRLER, T., ERICHSEN, S., SCHIERGENS, T. S., HERRLER, G., WU, N. H., NITSCHE, A., MULLER, M. A., DROSTEN, C. & POHLMANN, S. 2020b. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell, 181, 271-280 e8. HUGGINS, D. J. 2020. Structural analysis of experimental drugs binding to the SARS-CoV-2 target TMPRSS2. J Mol Graph Model, 100, 107710. HUSTON, N.C., WAN, H., STRINE, M.S., DE CESARIS ARAUJO TAVARES, R., WILEN, C.B., AND PYLE, A.M. (2021). Comprehensive in vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms. Mol Cell 81, 584-598 e585. JING, Y., RUN-QIAN, L., HAO-RAN, W., HAO-RAN, C., YA-BIN, L., YANG, G. & FEI, C. 2020. Potential influence of COVID-19/ACE2 on the female reproductive system. Mol Hum Reprod, 26, 367-373. JOHNSON, B. A., XIE, X., KALVERAM, B., LOKUGAMAGE, K. G., MURUATO, A., ZOU, J., ZHANG, X., JUELICH, T., SMITH, J. K., ZHANG, L., BOPP, N., SCHINDEWOLF, C., VU, M., VANDERHEIDEN, A., SWETNAM, D., PLANTE, J. A., AGUILAR, P., PLANTE, K. S., LEE, B., WEAVER, S. C., SUTHAR, M. S., ROUTH, A. L., REN, P., KU, Z., AN, Z., DEBBINK, K., SHI, P. Y., FREIBERG, A. N. & MENACHERY, V. D. 2020. Furin Cleavage Site Is Key to SARS-CoV-2 Pathogenesis. bioRxiv. JU, B., ZHANG, Q., GE, J., WANG, R., SUN, J., GE, X., YU, J., SHAN, S., ZHOU, B., SONG, S., TANG, X., YU, J., LAN, J., YUAN, J., WANG, H., ZHAO, J., ZHANG, S., WANG, Y., SHI, X., LIU, L., ZHAO, J., WANG, X., ZHANG, Z. & ZHANG, L. 2020. Human neutralizing antibodies elicited by SARS-CoV-2 infection. Nature, 584, 115-119. JURASZEK, J., RUTTEN, L., BLOKLAND, S., BOUCHIER, P., VOORZAAT, R., RITSCHEL, T., BAKKERS, M. J. G., RENAULT, L. L. R. & LANGEDIJK, J. P. M. 2021. Stabilizing the closed SARS-CoV-2 spike trimer. Nat Commun, 12, 244. KANG, Y.-L., CHOU, Y.-Y., ROTHLAUF, P. W., LIU, Z., SOH, T. K., CURETON, D., CASE, J. B., CHEN, R. E., DIAMOND, M. S., WHELAN, S. P. J. & KIRCHHAUSEN, T. 2020. Inhibition of PIKfyve kinase prevents infection by Zaire ebolavirus and SARS-CoV-2. bioRxiv, 2020.04.21.053058. KAWASE, M., SHIRATO, K., VAN DER HOEK, L., TAGUCHI, F. & MATSUYAMA, S. 2012. Simultaneous treatment of human bronchial epithelial cells with serine and cysteine protease inhibitors prevents severe acute respiratory syndrome coronavirus entry. J Virol, 86, 6537-45. KIM, D., LEE, J.Y., YANG, J.S., KIM, J.W., KIM, V.N., AND CHANG, H. (2020). The Architecture of SARS-CoV-2 Transcriptome. Cell 181, 914-921 e910. KLEIN, S., CORTESE, M., WINTER, S.L., WACHSMUTH-MELM, M., NEUFELDT, C.J., CERIKAN, B., STANIFER, M.L., BOULANT, S., BARTENSCHLAGER, R., AND CHLANDA, P. (2020). SARS-CoV-2 structure and replication characterized by in situ cryo-electron tomography. Nat Commun 11, 5885. LAM, S. D., BORDIN, N., WAMAN, V. P., SCHOLES, H. M., ASHFORD, P., SEN, N., VAN DORP, L., RAUER, C., DAWSON, N. L., PANG, C. S. M., ABBASIAN, M., SILLITOE, I., EDWARDS, S. J. L., FRATERNALI, F., LEES, J. G., SANTINI, J. M. & ORENGO, C. A. 2020. SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. Sci Rep, 10, 16471. LAMERS, M. M., BEUMER, J., VAN DER VAART, J., KNOOPS, K., PUSCHHOF, J., BREUGEM, T. I., RAVELLI, R. B. G., PAUL VAN SCHAYCK, J., MYKYTYN, A. Z., DUIMEL, H. Q., VAN DONSELAAR, E., RIESEBOSCH, S., KUIJPERS, H. J. H., SCHIPPER, D., VAN DE WETERING, W. J., DE GRAAF, M., KOOPMANS, M., CUPPEN, E., PETERS, P. J., HAAGMANS, B. L. & CLEVERS, H. 2020. SARS-CoV-2 productively infects human gut enterocytes. Science, 369, 50-54. LAN, J., GE, J., YU, J., SHAN, S., ZHOU, H., FAN, S., ZHANG, Q., SHI, X., WANG, Q., ZHANG, L. & WANG, X. 2020. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature, 581, 215-220. LETKO, M., MARZI, A. & MUNSTER, V. 2020. Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses. Nat Microbiol, 5, 562-569. LI, F. 2016. Structure, Function, and Evolution of Coronavirus Spike Proteins. Annu Rev Virol, 3, 237-261. LIN, B., FERGUSON, C., WHITE, J. T., WANG, S., VESSELLA, R., TRUE, L. D., HOOD, L. & NELSON, P. S. 1999. Prostate-localized and androgen-regulated expression of the membrane-bound serine protease TMPRSS2. Cancer Res, 59, 4180-4. LIU, L., WANG, P., NAIR, M. S., YU, J., RAPP, M., WANG, Q., LUO, Y., CHAN, J. F., SAHI, V., FIGUEROA, A., GUO, X. V., CERUTTI, G., BIMELA, J., GORMAN, J., ZHOU, T., CHEN, Z., YUEN, K. Y., KWONG, P. D., SODROSKI, J. G., YIN, M. T., SHENG, Z., HUANG, Y., SHAPIRO, L. & HO, D. D. 2020. Potent neutralizing antibodies against multiple epitopes on SARS-CoV-2 spike. Nature, 584, 450-456. LU, Y. & MENG, Y. G. 2015. Quantitation of Circulating Neuropilin-1 in Human, Monkey, Mouse, and Rat Sera by ELISA. Methods Mol Biol, 1332, 39-48. LUCAS, J. M., TRUE, L., HAWLEY, S., MATSUMURA, M., MORRISSEY, C., VESSELLA, R. & NELSON, P. S. 2008. The androgen-regulated type II serine protease TMPRSS2 is differentially expressed and mislocalized in prostate adenocarcinoma. J Pathol, 215, 118-25. LUKASSEN, S., CHUA, R. L., TREFZER, T., KAHN, N. C., SCHNEIDER, M. A., MULEY, T., WINTER, H., MEISTER, M., VEITH, C., BOOTS, A. W., HENNIG, B. P., KREUTER, M., CONRAD, C. & EILS, R. 2020. SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells. EMBO J, 39, e105114. MADJID, M., SAFAVI-NAEINI, P., SOLOMON, S. D. & VARDENY, O. 2020. Potential Effects of Coronaviruses on the Cardiovascular System: A Review. JAMA Cardiol, 5, 831-840. MAYI, B. S., LEIBOWITZ, J. A., WOODS, A. T., AMMON, K. A., LIU, A. E. & RAJA, A. 2021. The role of Neuropilin-1 in COVID-19. PLoS Pathog, 17, e1009153. MILLET, J. K. & WHITTAKER, G. R. 2018. Physiological and molecular triggers for SARS-CoV membrane fusion and entry into host cells. Virology, 517, 3-8. MIRABELLI, C., WOTRING, J. W., ZHANG, C. J., MCCARTY, S. M., FURSMIDT, R., FRUM, T., KADAMBI, N. S., AMIN, A. T., O’MEARA, T. R., PRETTO, C. D., SPENCE, J. R., HUANG, J., ALYSANDRATOS, K. D., KOTTON, D. N., HANDELMAN, S. K., WOBUS, C. E., WEATHERWAX, K. J., MASHOUR, G. A., O’MEARA, M. J. & SEXTON, J. Z. 2020. Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19. bioRxiv, 2020.05.27.117184. MOUTAL, A., MARTIN, L. F., BOINON, L., GOMEZ, K., RAN, D., ZHOU, Y., STRATTON, H. J., CAI, S., LUO, S., GONZALEZ, K. B., PEREZ-MILLER, S., PATWARDHAN, A., IBRAHIM, M. M. & KHANNA, R. 2020. SARS-CoV-2 Spike protein co-opts VEGF-A/Neuropilin-1 receptor signaling to induce analgesia. bioRxiv. MUHL, L., FOLESTAD, E. B., GLADH, H., WANG, Y., MOESSINGER, C., JAKOBSSON, L. & ERIKSSON, U. 2017. Neuropilin 1 binds PDGF-D and is a co-receptor in PDGF-D-PDGFRbeta signaling. J Cell Sci, 130, 1365-1378. MUKHERJEE, S. & PAHAN, K. 2021. Is COVID-19 Gender-sensitive? J Neuroimmune Pharmacol, 16, 38-47. MURGOLO, N., THERIEN, A. G., HOWELL, B., KLEIN, D., KOEPLINGER, K., LIEBERMAN, L. A., ADAM, G. C., FLYNN, J., MCKENNA, P., SWAMINATHAN, G., HAZUDA, D. J. & OLSEN, D. B. 2021. SARS-CoV-2 tropism, entry, replication, and propagation: Considerations for drug discovery and development. PLoS Pathog, 17, e1009225. PAN, X. W., XU, D., ZHANG, H., ZHOU, W., WANG, L. H. & CUI, X. G. 2020. Identification of a potential mechanism of acute kidney injury during the COVID-19 outbreak: a study based on single-cell transcriptome analysis. Intensive Care Med, 46, 1114-1116. PEREZ-MILLER, S., PATEK, M., MOUTAL, A., CABEL, C. R., THORNE, C. A., CAMPOS, S. K. & KHANNA, R. 2020. In silico identification and validation of inhibitors of the interaction between neuropilin receptor 1 and SARS-CoV-2 Spike protein. bioRxiv. PREMKUMAR, L., SEGOVIA-CHUMBEZ, B., JADI, R., MARTINEZ, D. R., RAUT, R., MARKMANN, A., CORNABY, C., BARTELT, L., WEISS, S., PARK, Y., EDWARDS, C. E., WEIMER, E., SCHERER, E. M., ROUPHAEL, N., EDUPUGANTI, S., WEISKOPF, D., TSE, L. V., HOU, Y. J., MARGOLIS, D., SETTE, A., COLLINS, M. H., SCHMITZ, J., BARIC, R. S. & DE SILVA, A. M. 2020. The receptor binding domain of the viral spike protein is an immunodominant and highly specific target of antibodies in SARS-CoV-2 patients. Sci Immunol, 5. QIAO, Y., WANG, X. M., MANNAN, R., PITCHIAYA, S., ZHANG, Y., WOTRING, J. W., XIAO, L., ROBINSON, D. R., WU, Y. M., TIEN, J. C., CAO, X., SIMKO, S. A., APEL, I. J., BAWA, P., KREGEL, S., NARAYANAN, S. P., RASKIND, G., ELLISON, S. J., PAROLIA, A., ZELENKA-WANG, S., MCMURRY, L., SU, F., WANG, R., CHENG, Y., DELEKTA, A. D., MEI, Z., PRETTO, C. D., WANG, S., MEHRA, R., SEXTON, J. Z. & CHINNAIYAN, A. M. 2020. Targeting transcriptional regulation of SARS-CoV-2 entry factors ACE2 and TMPRSS2. Proc Natl Acad Sci U S A. RAHMAN, N., BASHARAT, Z., YOUSUF, M., CASTALDO, G., RASTRELLI, L. & KHAN, H. 2020. Virtual Screening of Natural Products against Type II Transmembrane Serine Protease (TMPRSS2), the Priming Agent of Coronavirus 2 (SARS-CoV-2). Molecules, 25. RAIMONDI, C., BRASH, J. T., FANTIN, A. & RUHRBERG, C. 2016. NRP1 function and targeting in neurovascular development and eye disease. Prog Retin Eye Res, 52, 64-83. RIVA, L., YUAN, S., YIN, X., MARTIN-SANCHO, L., MATSUNAGA, N., BURGSTALLER-MUEHLBACHER, S., PACHE, L., DE JESUS, P. P., HULL, M. V., CHANG, M., CHAN, J. F.-W., CAO, J., POON, V. K.-M., HERBERT, K., NGUYEN, T.-T., PU, Y., NGUYEN, C., RUBANOV, A., MARTINEZ-SOBRIDO, L., LIU, W.-C., MIORIN, L., WHITE, K. M., JOHNSON, J. R., BENNER, C., SUN, R., SCHULTZ, P. G., SU, A., GARCIA-SASTRE, A., CHATTERJEE, A. K., YUEN, K.-Y. & CHANDA, S. K. 2020. A Large-scale Drug Repositioning Survey for SARS-CoV-2 Antivirals. bioRxiv, 2020.04.16.044016. ROBBIANI, D. F., GAEBLER, C., MUECKSCH, F., LORENZI, J. C. C., WANG, Z., CHO, A., AGUDELO, M., BARNES, C. O., GAZUMYAN, A., FINKIN, S., HAGGLOF, T., OLIVEIRA, T. Y., VIANT, C., HURLEY, A., HOFFMANN, H. H., MILLARD, K. G., KOST, R. G., CIPOLLA, M., GORDON, K., BIANCHINI, F., CHEN, S. T., RAMOS, V., PATEL, R., DIZON, J., SHIMELIOVICH, I., MENDOZA, P., HARTWEGER, H., NOGUEIRA, L., PACK, M., HOROWITZ, J., SCHMIDT, F., WEISBLUM, Y., MICHAILIDIS, E., ASHBROOK, A. W., WALTARI, E., PAK, J. E., HUEY-TUBMAN, K. E., KORANDA, N., HOFFMAN, P. R., WEST, A. P., JR., RICE, C. M., HATZIIOANNOU, T., BJORKMAN, P. J., BIENIASZ, P. D., CASKEY, M. & NUSSENZWEIG, M. C. 2020. Convergent antibody responses to SARS-CoV-2 in convalescent individuals. Nature, 584, 437-442. ROSSI, A., DEVERAUX, Q., TURK, B. & SALI, A. 2004. Comprehensive search for cysteine cathepsins in the human genome. Biol Chem, 385, 363-72. SACCO, M.D., MA, C., LAGARIAS, P., GAO, A., TOWNSEND, J.A., MENG, X., DUBE, P., ZHANG, X., HU, Y., KITAMURA, N., et al. (2020). Structure and inhibition of the SARS-CoV-2 main protease reveal strategy for developing dual inhibitors against M(pro) and cathepsin L. Sci Adv 6(50):eabe0751. SHANG, J., WAN, Y., LUO, C., YE, G., GENG, Q., AUERBACH, A. & LI, F. 2020. Cell entry mechanisms of SARS-CoV-2. Proc Natl Acad Sci U S A, 117, 11727-11734. SHIRATO, K., KAWASE, M. & MATSUYAMA, S. 2018. Wild-type human coronaviruses prefer cell-surface TMPRSS2 to endosomal cathepsins for cell entry. Virology, 517, 9-15. SIMMONS, G., GOSALIA, D. N., RENNEKAMP, A. J., REEVES, J. D., DIAMOND, S. L. & BATES, P. 2005. Inhibitors of cathepsin L prevent severe acute respiratory syndrome coronavirus entry. Proc Natl Acad Sci U S A, 102, 11876-81. SINGH, M., BANSAL, V. & FESCHOTTE, C. 2020. A single-cell RNA expression map of human coronavirus entry factors. bioRxiv. SNIJDER, E.J., BREDENBEEK, P.J., DOBBE, J.C., THIEL, V., ZIEBUHR, J., POON, L.L.M., GUAN, Y., ROZANOV, M., SPAAN, W.J.M., AND GORBALENYA, A.E. (2003). Unique and Conserved Features of Genome and Proteome of SARS-coronavirus, an Early Split-off From the Coronavirus Group 2 Lineage. Journal of Molecular Biology 331, 991-1004. SNIJDER, E.J., LIMPENS, R., DE WILDE, A.H., DE JONG, A.W.M., ZEVENHOVEN-DOBBE, J.C., MAIER, H.J., FAAS, F., KOSTER, A.J., AND BARCENA, M. (2020). A unifying structural and functional model of the coronavirus replication organelle: Tracking down RNA synthesis. PLoS Biol 18, e3000715. SUBRAMANIAN, A., VERNON, K. A., SLYPER, M., WALDMAN, J., LUECKEN, M. D., GOSIK, K., DUBINSKY, D., CUOCO, M. S., KELLER, K., PURNELL, J., NGUYEN, L., DIONNE, D., ROZENBLATT-ROSEN, O., WEINS, A., REGEV, A. & GREKA, A. 2020. RAAS blockade, kidney disease, and expression of ACE2, the entry receptor for SARS-CoV-2, in kidney epithelial and endothelial cells. UNIPROTKB - O14786 (NRP1_HUMAN) V'KOVSKI, P., KRATZEL, A., STEINER, S., STALDER, H., AND THIEL, V. (2021). Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol. 19, 155–170. WALLS, A. C., TORTORICI, M. A., BOSCH, B. J., FRENZ, B., ROTTIER, P. J. M., DIMAIO, F., REY, F. A. & VEESLER, D. 2016. Cryo-electron microscopy structure of a coronavirus spike glycoprotein trimer. Nature, 531, 114-117. WANG, Y., LIU, M. & GAO, J. 2020. Enhanced receptor binding of SARS-CoV-2 through networks of hydrogen-bonding and hydrophobic interactions. Proc Natl Acad Sci U S A, 117, 13967-13974. YAMAMOTO, M., KISO, M., SAKAI-TAGAWA, Y., IWATSUKI-HORIMOTO, K., IMAI, M., TAKEDA, M., KINOSHITA, N., OHMAGARI, N., GOHDA, J., SEMBA, K., MATSUDA, Z., KAWAGUCHI, Y., KAWAOKA, Y. & INOUE, J. I. 2020. The Anticoagulant Nafamostat Potently Inhibits SARS-CoV-2 S Protein-Mediated Fusion in a Cell Fusion Assay System and Viral Infection In Vitro in a Cell-Type-Dependent Manner. Viruses, 12. YANG, N. & SHEN, H.-M. 2020. Targeting the Endocytic Pathway and Autophagy Process as a Novel Therapeutic Strategy in COVID-19. International Journal of Biological Sciences, 16, 1724-1731. YUAN, M., WU, N. C., ZHU, X., LEE, C. D., SO, R. T. Y., LV, H., MOK, C. K. P. & WILSON, I. A. 2020. A highly conserved cryptic epitope in the receptor binding domains of SARS-CoV-2 and SARS-CoV. Science, 368, 630-633. ZANG, R., GOMEZ CASTRO, M. F., MCCUNE, B. T., ZENG, Q., ROTHLAUF, P. W., SONNEK, N. M., LIU, Z., BRULOIS, K. F., WANG, X., GREENBERG, H. B., DIAMOND, M. S., CIORBA, M. A., WHELAN, S. P. J. & DING, S. 2020. TMPRSS2 and TMPRSS4 promote SARS-CoV-2 infection of human small intestinal enterocytes. Sci Immunol, 5. ZIEGLER, C. G. K., ALLON, S. J., NYQUIST, S. K., MBANO, I. M., MIAO, V. N., TZOUANAS, C. N., CAO, Y., YOUSIF, A. S., BALS, J., HAUSER, B. M., FELDMAN, J., MUUS, C., WADSWORTH, M. H., 2ND, KAZER, S. W., HUGHES, T. K., DORAN, B., GATTER, G. J., VUKOVIC, M., TALIAFERRO, F., MEAD, B. E., GUO, Z., WANG, J. P., GRAS, D., PLAISANT, M., ANSARI, M., ANGELIDIS, I., ADLER, H., SUCRE, J. M. S., TAYLOR, C. J., LIN, B., WAGHRAY, A., MITSIALIS, V., DWYER, D. F., BUCHHEIT, K. M., BOYCE, J. A., BARRETT, N. A., LAIDLAW, T. M., CARROLL, S. L., COLONNA, L., TKACHEV, V., PETERSON, C. W., YU, A., ZHENG, H. B., GIDEON, H. P., WINCHELL, C. G., LIN, P. L., BINGLE, C. D., SNAPPER, S. B., KROPSKI, J. A., THEIS, F. J., SCHILLER, H. B., ZARAGOSI, L. E., BARBRY, P., LESLIE, A., KIEM, H. P., FLYNN, J. L., FORTUNE, S. M., BERGER, B., FINBERG, R. W., KEAN, L. S., GARBER, M., SCHMIDT, A. G., LINGWOOD, D., SHALEK, A. K., ORDOVAS-MONTANES, J., LUNG-NETWORK@HUMANCELLATLAS.ORG, H. C. A. L. B. N. E. A. & NETWORK, H. C. A. L. B. 2020. SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues. Cell, 181, 1016-1035 e19. AOPWiki 2020-03-01T10:29:31

2023-04-04T07:39:34

Interferon-I antiviral response, antagonized by SARS-CoV-2

IFN-I response, antagonized

Cellular

SARS-CoV-2 is an enveloped virus with a single-stranded RNA genome of ~30 kb, sequence orientation in a 5’ to 3’ direction typical of positive sense and reflective of the resulting mRNA (doi:<a class="article-header__doi__value" href="https://doi.org/10.1016/j.cell.2020.04.011">https://doi.org/10.1016/j.cell.2020.04.01</a>). The SARS-CoV-2 genome contains a 5’-untranslated region (UTR; 265 bp), <a href="https://www.ncbi.nlm.nih.gov/gene/?term=ORF1a+SARS-CoV-2">ORF1ab</a> (21,289 bp) holding two overlapping open reading frames (13,217 bp and 21,289 bp, respectively) that encode two polyproteins (Kim et al. 2020; O’Leary et al. 2020). Viral transcription and replication is explained in depth in <a href="https://aopwiki.org/events/1847" style="color:blue; text-decoration:underline">KE1847</a>. Briefly, the first event upon cell entry is the primary translation of the ORF1a and ORF1b genomic RNA to produce non-structural proteins (NSPs). The ORF1a produces polypeptide 1a (pp1a, 440–500 kDa) that is cleaved into NSP-1 through NSP-11. A -1-ribosome frameshift occurs immediately upstream of the ORF1a stop codon, to allow translation through ORF1b, yielding 740–810 kDa polypeptide pp1ab, which is cleaved into 15 NSPs (duplications of NSP1-11 and five additional proteins, NSP12-16). Viral proteases NSP3 and NSP5 cleave the polypeptides through domains functioning as a papain-like protease and a 3C-like protease, respectively (doi:<a class="article-header__doi__value" href="https://doi.org/10.1016/j.cell.2020.04.011">https://doi.org/10.1016/j.cell.2020.04.01</a>). The NSPs, structural proteins, and accessory proteins are encoded by 10 ORFs in the SARS-CoV-2 RNA genome. They may have multiple functions during viral replication as well as in evasion of the host innate immune response, thus augmenting viral replication and spread (Amor et al. 2020). Extensive protein-protein interaction (Gordon et al. 2020) and viral protein-host RNA interaction networks have been demonstrated between the viral NSPs and accessory proteins and host molecules.  This key event is focused on the specific viral:host protein interactions within the infected cell that are involved in the <a href="https://www.wikipathways.org/index.php/Pathway:WP4868">IFN-I antiviral response pathways</a>. IFN-I is the main component of the innate immune system that is suppressed by the SARS-CoV-2 coronavirus early in infection. The primary form of host intracellular virus surveillance detects viral components to induce an immediate systemic type I interferon (IFN) response. Cellular RNA sensors called pattern recognition receptors (PRRs) such as RIG-I, MDA5 and LGP2 detect the presence of viral RNAs and promote nuclear translocation of the transcription factor IRF3, leading to transcription, translation, and secretion of IFN-α and IFN-β. This in turn leads to interaction with the IFN receptor (IFNAR), phosphorylation of STAT1 and 2, and transcription and translation of hundreds of antiviral genes (Quarleri and Delpino, 2021). Interactions between SARS-CoV-2 proteins and human RNAs thwart the IFN response upon infection: NSP1 binds to 40S ribosomal RNA in the mRNA entry channel of the ribosome to inhibit host mRNA translation; NSP8 and NSP9 displace signal recognition particle proteins (SRP54, 27 and 19) to bind to the 7SL RNA and block protein trafficking to the cell membrane (Banerjee et al. 2020; Gordon et al. 2020). Xia et al. (2020) found that NSP6 and NSP13 antagonize IFN-I production via distinct mechanisms: NSP6 binds TANK binding kinase 1 (TBK1) to suppress interferon regulatory factor 3 (IRF3) phosphorylation, and NSP13 binds and blocks TBK1 phosphorylation. NSP14 induces lysosomal degradation of type 1 IFNAR to prevent STAT activation (Hayn et al. 2021). ORF6 hijacks KPNA2 to block IRF3, and Nup98/RAE1 to block STAT nuclear import, to silence IFN-I gene expression (Xia and Shi, 2020). ORF7a suppresses STAT2 phosphorylation and ORF7b suppresses STAT1 and STAT2 phosphorylation to block ISGF3 complex formation with IRF9 (Xia and Shi, 2020). ORF8 interacts and downregulates MHC-I (Zhang et al 2020), and has been reported to block INFβ expression, but the mechanism has not been identified (Rashid et al. 2021; Li et al. 2020). ORF9b antagonizes Type I Interferons by targeting multiple components of RIG-I/MDA-5-MAVS, TOMM70, NEMO and cGAS-STING signalling (Han et al. 2020; Jiang et al. 2020; Wu et al. 2021; Gordon et al 2020). Following is a table of the current state of knowledge of SARS-CoV-2 protein putative functions in relation to IFN-I antiviral response antagonism.   <table cellspacing="0" class="Table" style="border-collapse:collapse; width:594px"> <tbody> <tr> <td style="border-bottom:3px double black; border-left:none; border-right:none; border-top:1px solid black; height:21px; vertical-align:top; width:58px"> Gene </td> <td style="border-bottom:3px double black; border-left:none; border-right:none; border-top:1px solid black; height:21px; vertical-align:top; width:108px"> Protein </td> <td style="border-bottom:3px double black; border-left:none; border-right:none; border-top:1px solid black; height:21px; vertical-align:top; width:162px"> Function </td> <td style="border-bottom:3px double black; border-left:none; border-right:none; border-top:1px solid black; height:21px; vertical-align:top; width:266px"> Role in early innate immune evasion </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px">   </td> <td style="height:21px; vertical-align:top; width:162px">   </td> <td style="height:21px; vertical-align:top; width:266px">   </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px"> ORF1a </td> <td style="height:21px; vertical-align:top; width:108px"> NSP1 </td> <td style="height:21px; vertical-align:top; width:162px"> NSP1 antagonizes interferon induction to suppress host antiviral response. </td> <td style="height:21px; vertical-align:top; width:266px"> DNA Polymerase Alpha Complex: Regulates the activation of IFN-I through cytosolic RNA-DNA synthesis (POLA1/2-PRIM1/2) and primes DNA replication in the nucleus (Gordon et al. 2020; Chaudhuri et al. 2020). Can also inhibit host gene expression by binding to ribosomes and modifying host mRNAs (Shi et al. 2020; Schubert et al. 2020; Thoms et al. 2020). </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP2 </td> <td style="height:21px; vertical-align:top; width:162px"> While not essential for viral replication, deletion of NSP2 diminishes viral growth and RNA synthesis </td> <td style="height:21px; vertical-align:top; width:266px"> Translation repression through binding GIGYF2and EIF4E2 (4EHP) (Gupta et al. 2021) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP3 </td> <td style="height:21px; vertical-align:top; width:162px"> Papain-like protease (Plpro); Cleaves the ORF1a and 1ab polypeptides </td> <td style="height:21px; vertical-align:top; width:266px"> Suppresses IFN-I: Cleaves IRF3 (Moustaqil et al. 2021); binds/cleaves ISG15 (Rui et al. 2021; Shin et al. 2020; Liu et al. 2021; Klemm et al. 2020) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP5 </td> <td style="height:21px; vertical-align:top; width:162px"> 3C-like protease (3CLpro); Cleaves the ORF1a and 1ab polypeptides </td> <td style="height:21px; vertical-align:top; width:266px"> Binds STING (Rui et al. 2021) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP6 </td> <td style="height:21px; vertical-align:top; width:162px"> Limits autophagosome expansion </td> <td style="height:21px; vertical-align:top; width:266px"> Suppresses IFN-I expression: Binds TBK-1 to supress IRF3 phosphorylation (Xia et al. 2020; Quarleri and Delpino, 2021) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP7 </td> <td style="height:21px; vertical-align:top; width:162px"> In complex with NSP8 forms primase as part of multimeric RNA-dependent RNA replicase (RdRp) </td> <td style="height:21px; vertical-align:top; width:266px">   </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP8 </td> <td style="height:21px; vertical-align:top; width:162px"> Replication complex with NSP7, NSP9 and NSP12 </td> <td style="height:21px; vertical-align:top; width:266px"> Binds SRP72/54/19 (Gordon et al. 2020) and 7SL RNA to block IFN membrane transport (Banerjee et al. 2020) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP9 </td> <td style="height:21px; vertical-align:top; width:162px"> Replication complex with NSP7, NSP8 and NSP12 </td> <td style="height:21px; vertical-align:top; width:266px"> Binds SRP and 7SL RNA with NSP8 to block IFN membrane transport (Banerjee et al. 2020) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px"> ORF1b </td> <td style="height:21px; vertical-align:top; width:108px"> NSP13 </td> <td style="height:21px; vertical-align:top; width:162px"> Helicase and triphosphatase that initiates the first step in viral mRNA capping. </td> <td style="height:21px; vertical-align:top; width:266px"> Binds TBK1 (Xia et al. 2020) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px">   </td> <td style="height:21px; vertical-align:top; width:108px"> NSP14 </td> <td style="height:21px; vertical-align:top; width:162px">   </td> <td style="height:21px; vertical-align:top; width:266px"> Induces lysosomal degradation of IFNAR1 (Hayn et al. 2021) </td> </tr> <tr> <td style="height:21px; vertical-align:top; width:58px"> ORF2 </td> <td style="height:21px; vertical-align:top; width:108px"> Spike (S) </td> <td style="height:21px; vertical-align:top; width:162px"> ACE2 interaction, cell entry </td> <td style="height:21px; vertical-align:top; width:266px"> </td> </tr> <tr> <td style="height:35px; vertical-align:top; width:58px"> ORF3a </td> <td style="height:35px; vertical-align:top; width:108px"> ORF3a </td> <td style="height:35px; vertical-align:top; width:162px"> Interacts with M, S, E and 7a; form viroporins; immune evasion </td> <td style="height:35px; vertical-align:top; width:266px"> Binds STING (Rui et al 2021) </td> </tr> <tr> <td style="height:20px; vertical-align:top; width:58px"> ORF4 </td> <td style="height:20px; vertical-align:top; width:108px"> Envelope (E) </td> <td style="height:20px; vertical-align:top; width:162px"> Viral assembly and budding </td> <td style="height:20px; vertical-align:top; width:266px"> </td> </tr> <tr> <td style="height:20px; vertical-align:top; width:58px"> ORF5 </td> <td style="height:20px; vertical-align:top; width:108px"> Membrane (M) </td> <td style="height:20px; vertical-align:top; width:162px"> Viral assembly </td> <td style="height:20px; vertical-align:top; width:266px"> Interacts with RIG-I and MAVS sensors of viral RNA (Fu et al 2020) </td> </tr> <tr> <td style="height:70px; vertical-align:top; width:58px"> ORF6 </td> <td style="height:70px; vertical-align:top; width:108px"> ORF6 </td> <td style="height:70px; vertical-align:top; width:162px"> Viral pathogenesis and virulence; interacts with ORF8; promotes RNA polymerase activity </td> <td style="height:70px; vertical-align:top; width:266px"> Hijacks the nuclear importin Karyopherin a 2 (KPNA2) to block IRF3 (Xia and Shi, 2020) and Nup98/RAE1 to block STAT nuclear import (Miorin et al. 2020; Kato et al. 2020), leading to the silence of downstream ISGs </td> </tr> <tr> <td style="height:43px; vertical-align:top; width:58px"> ORF7a </td> <td style="height:43px; vertical-align:top; width:108px"> ORF7a </td> <td style="height:43px; vertical-align:top; width:162px"> Interacts with S, ORF3a; immune evasion </td> <td style="height:43px; vertical-align:top; width:266px"> Suppresses STAT2 phosphorylation to block IFN-I response (Xia and Shi, 2020). </td> </tr> <tr> <td style="height:35px; vertical-align:top; width:58px"> ORF7b </td> <td style="height:35px; vertical-align:top; width:108px"> ORF7b </td> <td style="height:35px; vertical-align:top; width:162px"> Structural component of virion </td> <td style="height:35px; vertical-align:top; width:266px"> Suppresses STAT1 and STAT2 phosphorylation to block IFN-I response (Xia and Shi, 2020) </td> </tr> <tr> <td style="height:70px; vertical-align:top; width:58px"> ORF8 </td> <td style="height:70px; vertical-align:top; width:108px"> ORF8 </td> <td style="height:70px; vertical-align:top; width:162px"> Immune evasion </td> <td style="height:70px; vertical-align:top; width:266px"> Interacts and downregulates MHC-I (Zhang et al. 2020).  May inhibit type I interferon (IFN-β) and interferon-stimulated response element (ISRE) (Rashid et al. 2020; Li et al. 2020) </td> </tr> <tr> <td style="height:20px; vertical-align:top; width:58px"> ORF9 </td> <td style="height:20px; vertical-align:top; width:108px"> Nucleocapsid (N) </td> <td style="height:20px; vertical-align:top; width:162px"> Stabilizes viral RNA </td> <td style="height:20px; vertical-align:top; width:266px"> Attenuates stress granule formation: G3BP1/2 (Chen et al. 2020; Cascarina et al. 2020); G3BP1 also interacts with RIG-I (Kim et al. 2019) and STAT1/2 (Mu et al. 2020) </td> </tr> <tr> <td style="height:70px; vertical-align:top; width:58px"> ORF9b </td> <td style="height:70px; vertical-align:top; width:108px"> ORF9b </td> <td style="height:70px; vertical-align:top; width:162px"> Immune evasion </td> <td style="height:70px; vertical-align:top; width:266px"> Membrane protein antagonizes Type I Interferons by targeting multiple components of RIG-I/MDA-5-MAVS, TOMM70, NEMO, and cGAS-STING signaling pathways (Fu et al. 2020; Chen et al. 2020; Han et al. 2020; Jiang et al. 2020; Wu et al. 2021; Gordon et al 2020) </td> </tr> </tbody> </table>

Detection of IFN-I suppression involves measuring gene promoter/transcription activation (luciferase assays), gene up/down regulation (quantitative PCR), protein-protein interaction (immunoprecipitation, immunoblotting) or in-situ co-location of viral and host proteins (immunofluorescent or confocal microscopy) in cell culture. Examples of methods used include the following: Interferon I decrease (Xia et al. 2020): <ul> <li>IFN-I production and signaling luciferase reporter assays</li> <li>Co-immunoprecipitation and western blot</li> <li>Indirect immunofluorescence assays</li> <li>DNA assembly and RNA transcription of a luciferase replicon for SARS-CoV-2</li> <li>Replicon RNA electroporation and luciferase reporter assay</li> </ul> SARS-CoV-2 ORF9b inhibits RIG-I-MAVS antiviral signaling (Wu et al. 2021) <ul> <li>Viral- and host-protein-specific antibodies</li> <li>Immunoprecipitation</li> <li>Immunofluorescent microscopy</li> <li>Dual-luciferase reporter assays</li> <li>Fluorescence quantification immunoblotting</li> </ul> SARS-CoV-2-Human Protein-Protein Interaction Map (Gordon et al. 2020) <ul> <li>Cloning and expression of viral proteins via plasmid transfection into HEK293T cell line</li> <li>Protein affinity purification using MagStrep beads with detection by anti-strep western blot of cell lysate</li> <li>Global analysis of SARS-CoV-2 host interacting proteins using affinity purification-mass spectrometry</li> </ul>

Broad mammalian host range based on spike protein tropism for and binding to ACE2 (Conceicao et al. 2020; Wu et al. 2020) and cross-species ACE2 structural analysis (Damas et al. 2020). Some literature found on non-human hosts indicates that NSPs and accessory proteins can interact in a similar manner with bird (chicken) and other mammal proteins in the IFN-I pathway (Moustaqil et al. 2021; Rui et al. 2021).

UBERON:0000062

UBERON organ

CL:0000066

CL epithelial cell

High Unspecific

High

All life stages

High High High High Moderate High

Amor et al. 2020. Innate immunity during SARS-CoV-2: evasion strategies and activation trigger hypoxia and vascular damage. Clinical and Experimental Immunology, 202: 193–209. doi: 10.1111/cei.13523 Andres et al. 2020. SARS-CoV-2 ORF9c Is a Membrane-Associated Protein that Suppresses Antiviral Responses in Cells. bioRxiv preprint doi: <a href="https://doi.org/10.1101/2020.08.18.256776" style="color:blue; text-decoration:underline">https://doi.org/10.1101/2020.08.18.256776</a> Banerjee et al. 2020. SARS-CoV-2 disrupts splicing, translation, and protein trafficking to supress host defenses. Cell 183, 1325–1339. <a href="https://doi.org/10.1016/j.cell.2020.10.004" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.cell.2020.10.004</a> Cascarina and Ross, 2020. A proposed role for the SARS-CoV-2 nucleocapsid protein in the formation and regulation of biomolecular condensates. The FASEB Journal, 34:9832–9842. DOI: 10.1096/fj.202001351 Chaudhuri, A. 2021. Comparative analysis of non-structural protein 1 of SARS-CoV2 with SARS-CoV1 and MERS-CoV: An in-silico study. Journal of Molecular Structure, Volume 1243, 130854, https://doi.org/10.1016/j.molstruc.2021.130854. Chen et al. 2021. SARS-CoV-2 Nucleocapsid Protein Interacts with RIG-I and Represses RIG-Mediated IFN-β Production. Viruses. 13(1):47. <a href="https://doi.org/10.3390/v13010047" style="color:blue; text-decoration:underline">https://doi.org/10.3390/v13010047</a> Conceicao et al. 2020. The SARS-CoV-2 Spike protein has a broad tropism for mammalian ACE2 proteins. PLoS Biol 18(12): e3001016. <a href="https://doi.org/10.1371/journal.pbio.3001016" style="color:blue; text-decoration:underline">https://doi.org/10.1371/journal.pbio.3001016</a> Damas et al. 2020. Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates. PNAS vol. 117 no. 36:22311–22322 <a href="http://www.pnas.org/cgi/doi/10.1073/pnas.2010146117" style="color:blue; text-decoration:underline">www.pnas.org/cgi/doi/10.1073/pnas.2010146117</a>  Fu et al. 2021. SARS-CoV-2 membrane glycoprotein M antagonizes the MAVS-mediated innate antiviral response. Cell Mol Immunol 18: 613–620. https://doi.org/10.1038/s41423-020-00571-x Gordon et al. 2020. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 483:459-473. <a href="https://doi.org/10.1038/s41586-020-2286-9" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41586-020-2286-9</a> Gupta et al. 2021. CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes. bioRxiv 2021.05.10.443524; doi: https://doi.org/10.1101/2021.05.10.443524 Han et al. 2020. SARS-CoV-2 ORF9b Antagonizes Type I and III Interferons by Targeting Multiple Components of RIG-I/MDA-5-MAVS, TLR3-TRIF, and cGAS-STING Signaling Pathways. bioRX <a href="https://doi.org/10.1101/2020.08.16.252973" style="color:blue; text-decoration:underline">https://doi.org/10.1101/2020.08.16.252973</a> Hayn et al. 2021. Systematic functional analysis of SARS-CoV-2 proteins uncovers viral innate immune antagonists and remaining vulnerabilities. Cell Reports 35, 109126. <a href="https://doi.org/10.1016/j.celrep.2021.109126" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.celrep.2021.109126</a> Jiang et al. 2020. SARS-CoV-2 Orf9b suppresses type I interferon responses by targeting TOM70. Cellular & Molecular Immunology 17:998–1000; https://doi.org/10.1038/s41423-020-0514-8 Kato et al. 2021. Overexpression of SARS-CoV-2 protein ORF6 dislocates RAE1 and NUP98 from the nuclear pore complex. Biochemical and Biophysical Research Communications 536:59-66 <a href="https://doi.org/10.1016/j.bbrc.2020.11.115" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.bbrc.2020.11.115</a> Kim et al. 2019. The stress granule protein G3BP1 binds viral dsRNA and RIG-I to enhance interferon-β response. J. Biol. Chem. 294(16): 6430–6438. DOI 10.1074/jbc.RA118.005868 Kim et al. 2020. The Architecture of SARS-CoV-2 Transcriptome. Cell 181, 914–921. <a href="https://doi.org/10.1016/j.cell.2020.04.011" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.cell.2020.04.011</a> Li et al. 2020. The ORF6, ORF8 and nucleocapsid proteins of SARS-CoV-2 inhibit type I interferon signaling pathway. Virus Research vol. 286. <a href="https://doi.org/10.1016/j.virusres.2020.198074" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.virusres.2020.198074</a> Liu et al. 2021. ISG15-dependent activation of the sensor MDA5 is antagonized by the SARS-CoV-2 papain-like protease to evade host innate immunity. Nature Microbiol 6: 467–478. <a href="https://doi.org/10.1038/s41564-021-00884-1" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41564-021-00884-1</a> Moustaqil et al. 2021. SARS-CoV-2 proteases PLpro and 3CLpro cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): implications for disease presentation across species, Emerging Microbes & Infections, 10:1, 178-195. <a href="https://doi.org/10.1080/22221751.2020.1870414" style="color:blue; text-decoration:underline">https://doi.org/10.1080/22221751.2020.1870414</a> Mu et al. 2020. SARS-CoV-2 N protein antagonizes type I interferon signaling by suppressing phosphorylation and nuclear translocation of STAT1 and STAT2. Cell Discov 6, 65. <a href="https://doi.org/10.1038/s41421-020-00208-3" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41421-020-00208-3</a> O’Leary et al. 2020 Unpacking Pandora from Its Box: Deciphering the Molecular Basis of the SARS-CoV-2 Coronavirus. Int. J. Mol. Sci. 2021, 22, 386. <a href="https://doi.org/10.3390/ijms22010386" style="color:blue; text-decoration:underline">https://doi.org/10.3390/ijms22010386</a> Quarleri and Delpino, 2020. Type I and III IFN-mediated antiviral actions counteracted by SARS-CoV-2 proteins and host inherited factors. Cytokine & Growth Factor Reviews, 58: 55-65. <a href="https://doi.org/10.1016/j.cytogfr.2021.01.003" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.cytogfr.2021.01.003</a> Rashid et al. The ORF8 protein of SARS-CoV-2 induced endoplasmic reticulum stress and mediated immune evasion by antagonizing production of interferon beta. Virus Research 296, 198350. <a href="https://doi.org/10.1016/j.virusres.2021.198350" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.virusres.2021.198350</a> Ren et al. 2020. The ORF3a protein of SARS-CoV-2 induces apoptosis in cells. Cellular & Molecular Immunology 17:881–883; <a href="https://doi.org/10.1038/s41423-020-0485-9" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41423-020-0485-9</a> Rui et al. 2021. Unique and complementary suppression of cGAS-STING and RNA sensing-triggered innate immune responses by SARS-CoV-2 proteins. Sig Transduct Target Ther 6, 123. <a href="https://doi.org/10.1038/s41392-021-00515-5" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41392-021-00515-5</a> Schubert et al. 2020. SARS-CoV-2 Nsp1 binds the ribosomal mRNA channel to inhibit translation. Nature Structural & Molecular Bio. 27:959-966. <a href="https://doi.org/10.1038/s41594-020-0511-8" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41594-020-0511-8</a> Shin et al. 2020. Papain-like protease regulates SARS-CoV-2 viral spread and innate immunity. Nature 587: 657–662. <a href="https://doi.org/10.1038/s41586-020-2601-5" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41586-020-2601-5</a> Thoms et al. 2020. Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2. Science 369(6508): 1249-1255. DOI: 10.1126/science.abc8665 Wu et al. 2021. SARS-CoV-2 ORF9b inhibits RIG-I-MAVS antiviral signaling by interrupting K63-linked ubiquitination of NEMO. Cell Reports 34, 108761. <a href="https://doi.org/10.1016/j.celrep.2021.108761" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.celrep.2021.108761</a> Wu et al. 2020. Broad host range of SARS-CoV-2 and the molecular basis for SARS-CoV-2 binding to cat ACE2. Cell Discovery 6:68. <a href="https://doi.org/10.1038/s41421-020-00210-9" style="color:blue; text-decoration:underline">https://doi.org/10.1038/s41421-020-00210-9</a> Xia et al. 2020. Evasion of Type I Interferon by SARS-CoV-2. Cell Reports 33, 108234. <a href="https://doi.org/10.1016/j.celrep.2020.108234" style="color:blue; text-decoration:underline">https://doi.org/10.1016/j.celrep.2020.108234</a> Xia and Shi, 2020. Antagonism of Type I Interferon by Severe Acute Respiratory Syndrome Coronavirus 2. Journal of Interferon & Cytokine Research v.40, no. 12 DOI:10.1089/jir.2020.0214 Zhang et al. 2020. The ORF8 Protein of SARS-CoV-2 Mediates Immune Evasion through Potently Downregulating MHC-I. bioRxiv preprint doi: <a href="https://doi.org/10.1101/2020.05.24.111823" style="color:blue; text-decoration:underline">https://doi.org/10.1101/2020.05.24.111823</a> AOPWiki 2021-07-09T14:22:55

2023-04-03T15:20:42

Increased SARS-CoV-2 production

SARS-CoV-2 production

Cellular

This KE1847 "Increase coronavirus production" deals with how the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is translated, replicated, and transcribed in detail, and how the genomic RNA (gRNA) is packaged, and the virions are assembled and released from the cell.  Coronavirus is a class of viruses that have single-stranded positive-sense RNA genomes in their envelopes [D. Kim et al.]. The virus contains a 29.7 kB positive-sense RNA genome flanked by 5' and 3' untranslated regions of 265 and 342 nucleotides, respectively [E. J. Snijder et al.] that contain cis-acting secondary RNA structures essential for RNA synthesis [N. C. Huston et al.]. The genome just prior to the 5′ end contains the transcriptional regulatory sequence leader (TRS-L) [C.J. Budzilowicx et al.]. The SARS-CoV genome is polycistronic and contains 14 open reading frames (ORFs) that are expressed by poorly understood mechanisms [E. J. Snijder et al.]. Preceding each ORF there are other TRSs called the body TRS (TRS B). The 5′ two-thirds of the genome contains two large, overlapping, nonstructural ORFs and the 3′ third contains the remainder ORFs [H. Di et al.]. Genome expression starts with the translation of two large ORFs of the 5’ two-thirds: ORF1a of 4382 amino acids and ORF1ab of 7073 amino acid that occurs via a programmed (- 1) ribosomal frameshifting [E. J. Snider et al.], yielding pp1a and pp1ab. These two polyproteins are cleaved into 16 subunits by two viral proteinases encoded by ORF1a, nsp3, and nsp5 that contain a papain-like protease domain and a 3C-like protease domain [M. D. Sacco et al.]. The processing products are a group of replicative enzymes, named nsp1-nsp16, that assemble into a viral replication and transcription complex (RTC) associated with membranes of endoplasmic reticulum (ER) with the help of various membrane-associated viral proteins [S. Klein et al., E. J. Snijder et al., P. V'Kovski, et al.]. Besides replication, which yields the positive-sense gRNA, the replicase also mediates transcription leading to the synthesis of a nested set of subgenomic (sg) mRNAs to express all ORFs downstream of ORF1b that encode structural and accessory viral proteins. These localize to the 3′ one-third of the genome, as stated above, and result in a 3′ coterminal nested set of 7–9 mRNAs that share ~70–90 nucleotide (nt) in the 5′ leader and that is identical to the 5′ end of the genome [P. Liu, and J. Leibowitz]. sgRNAs encode conserved structural proteins (spike protein [S], envelope protein [E], membrane protein [M], and nucleocapsid protein [N]), and several accessory proteins. SARS-CoV-2 is known to have at least six accessory proteins (3a, 6, 7a, 7b, 8, and 10). Overall the virus is predicted to express 29 proteins [D. Kim et al.]. The gRNA is packaged by the structural proteins to assemble progeny virions. Viral translation: SARS-CoV-2 is an enveloped virus with a single-stranded RNA genome of ~30 kb, sequence orientation in a 5’ to 3’ direction typical of positive sense and reflective of the resulting mRNA [D. Kim et al.]. The SARS-CoV-2 genome contains a 5’-untranslated region (UTR; 265 bp), ORF1ab (21,289 bp) holding two overlapping open reading frames (13,217 bp and 21,289 bp, respectively) that encode two polyproteins [D. Kim et al.]. Other elements of the genome include are shown below [V. B. O'Leary et al.]. The first event upon cell entry is the primary translation of the ORF1a and ORF1b gRNA to produce non-structural proteins (nsps). This is completely dependent on the translation machinery of the host cell. Due to fewer rare “slow-codons”, SARS-CoV-2 may have a higher protein translational rate, and therefore higher infectivity compared to other coronavirus groups [V. B. O'Leary et al.]. The ORF1a produces polypeptide 1a (pp1a, 440–500 kDa) that is cleaved into nsp-1 through nsp-11. A -1 ribosome frameshift occurs immediately upstream of the ORF1a stop codon, to allow translation through ORF1b, yielding 740–810 kDa polypeptide pp1ab, which is cleaved into 15 nsps [D. Kim et al.]. Two overlapping ORFs, ORF1a and ORF1b, generate continuous polypeptides, which are cleaved into a total of 16 so-called nsps [Y Finkel et al.]. Functionally, there are five proteins from pp1ab (nsp-12 through nsp-16) as nsp-1-11 are duplications of the proteins in pp1a due to the ORF overlap. The pp1a is approximately 1.4–2.2 times more expressed than pp1ab. After translation, the polyproteins are cleaved by viral proteases nsp3 and nsp5. Nsp5 protease can be referred to as 3C-like protease (3CLpro) or as main protease (Mpro), as it cleaves the majority of the polyprotein cleavage sites. [H.A. Hussein et al.] Nsp1 cleavage is quick and nsp1 associates with host cell ribosomes and results in host cellular shutdown, suppressing host gene expression [M. Thoms et al.]. Fifteen proteins, nsp2–16 constitute the viral RTC. They are targeted to defined subcellular locations and establish a network with host cell factors. Nsp2–11 remodel host membrane architecture, mediate host immune evasion and provide cofactors for replication, whilst nsp12–16 contain the core enzymatic functions involved in RNA synthesis, modification and proofreading [P. V'Kovski et al.].  nsp-7 and nsp-8 form a complex priming the RNA-dependent RNA polymerase (RdRp or RTC) - nsp-12. nsp14 provides a 3′–5′ exonuclease activity providing RNA proofreading function. Nsp-10 composes the RNA capping machinery nsp-9. nsp13 provides the RNA 5′-triphosphatase activity. Nsp-14 is a N7-methyltransferase and nsp-16 the 2′-O-methyltransferase. Many of the nsps have multiple functions and many viral proteins are involved in innate immunity inhibition. Nsp-3 is involved in vesicle formation along with nsp-4 and nsp-6 where viral replication occurs. Interactions between SARS-CoV-2 proteins and human RNAs thwart the IFN response upon infection: nsp-16 binds to U1 and U2 splicing RNAs to suppress global mRNA splicing; nsp-1 binds to 40S ribosomal RNA in the mRNA entry channel of the ribosome to inhibit host mRNA translation; nsp-8 and nsp-9 bind to the 7SL RNA to block protein trafficking to the cell membrane [A. K. Banerjee et al.]. Xia et al. [H. Xia et al.] found that nsp-6 and nsp-13 antagonize IFN-I production via distinct mechanisms: nsp-6 binds TANK binding kinase 1 (TBK1) to suppress interferon regulatory factor 3 (IRF3) phosphorylation, and nsp-13 binds and blocks TBK1 phosphorylation.   Viral transcription and replication: Viral transcription and replication occur at the viral replication organelle (RO) [E. J. Snijder et al.]. The RO is specifically formed during infection by reshaping ER and other membranes, giving rise to small spherular invaginations, and large vesiculotubular clusters, consisting of single- and/or double-membrane vesicles (DMV), convoluted membranes (CM) and double-membrane spherules invaginating from the ER  [S. Klein et al., E. J. Snijder et al.]. There is some evidence that DMV accommodate viral replication which is based on radiolabelling viral RNA with nucleoside precursor ([5-3[H]uridine) and detection by EM autoradiography [E. J. Snijder et al.]. Viral replicative proteins and specific host factors are recruited to ROs [E. J. Snijder et al.]. RNA viral genome is transcribed into messenger RNA by the viral RTC [P. Ahlquist et al.]. Viral RTC act in combination with other viral and host factors involved in selecting template RNAs, elongating RNA synthesis, differentiating genomic RNA replication from mRNA transcription, modifying product RNAs with 5’ caps or 3’ polyadenylate [P. Ahlquist et al.]. Positive-sense (messenger-sense) RNA viruses replicate their genomes through negative-strand RNA intermediates [M. Schwartz et al.]. The intermediates comprise full-length negative-sense complementary copies of the genome, which functions as templates for the generation of new positive-sense gRNA, and a nested set of sg mRNAs that lead to the expression of proteins encoded in all ORFs downstream of ORF1b. The transcription of coronaviruses is a discontinuous process that produces nested 3′ and 5′ co-terminal sgRNAs. Of note, the synthesis of sg mRNAs is not exclusive to the order Nidovirales but a discontinuous minus-strand synthesis strategy to produce a nested set of 3′ co-terminal sg mRNAs with a common 5′ leader in infected cells are unique features of the coronaviruses and arteriviruses [W. A. Miller and G. Koev.]. Of note, the produced genomic RNA represents a small fraction of the total vRNA [N. S. Ogando et al.]. The discontinuous minus-strand synthesis of a set of nested sg mRNAs happens during the synthesis of the negative-strand RNA, by an interruption mechanism of the RTC as it reads the TRS-B preceding each gene in the 3′ one-third of the viral genome [I. Sola, F. Almazan et al., I. Sola, J. L. Moreno, et al.]. The synthesis of the negative-strand RNA stops and is re-initiated at the TRS-L of the genome sequence close from the 5′ end of the genome [H. Di et al.]. Therefore, the mechanism by which the leader sequence is added to the 5' end requires that the RTC switches template by a jumping mechanism. This interruption process involves the interaction between complementary TRSs of the nascent negative-strand RNA TRS-B and the positive-strand gRNA at the positive-sense TRS-L. The TRS-B site has a 7-8 bp conserved core sequence (CS) that facilitates RTC template switching as it hybridizes with a near complementary CS in the TRS-L [I. Sola, F. Almazan et al. I. Sola, J. L. Moreno, et al.]. Upon re-initiation of RNA synthesis at the TRS-L region, a negative-strand copy of the leader sequence is added to the nascent RNA to complete the synthesis of negative-strand sgRNAs. This means that all sg mRNAs as well as the genomic RNA share a common 5' sequence, named leader sequence [X. Zhang et al.]. This programmed template switching leads to the generation of sg mRNAs with identical 5' and 3' sequences, but alternative central regions corresponding to the beginning of each structural ORF [I. Sola et al. 2015, S. G. Sawicki et al., Y. Yang et al.]. Of note, the existence of TRSs also raises the possibility that these sites are at the highest risk of recombining through TRS-B mediated template switching [Y. Yang]. The set of sg mRNAs is then translated to yield 29 identified different proteins [F. Wu et al.], although many papers have identified additional ORFs [D. Kim et al.. Y. Finkel et al., A. Vandelli et al.]. The translation of the linear single-stranded RNA conducts to the generation of the following proteome: 4 are structural proteins, S, N, M, and E; 16 proteins nsp: the first 11 are encoded in ORF1a whereas the last 5 are encoded in ORF1ab. In addition, 9 accessory proteins named ORF3a, ORF3b, ORF6, ORF7a, ORF7b, ORF8, ORF9b, ORF9c, and ORF10 have been identified [F. Wu et al.]. At the beginning of infection, there is the predominant expression of the nsp that result from ORF1a and ORF1ab, however, at 5 hpi, the proteins encoded by the 5′ last third are found in higher amounts, and the nucleoprotein is the protein found in higher levels [Y. Finkel et al.].   Viral assembly: The final step of viral production requires virion assembly and this process is not well explored for SARS-CoV-2. For example, the role of the structural proteins of SARS-CoV-2 in virus assembly and budding in not known. In general, all beta-coronavirus structural proteins assemble at the endoplasmic reticulum (ER)-to-Golgi compartment [J. R. Cohen et al., A. Perrier et al.] and viral assembly requires two steps: Genome packaging which is a process in which the SARS-CoV-2 gRNA must be coated by the viral protein nucleoprotein (N) protein, forming viral ribonucleoprotein (vRNPs) complexes, before being selectively packaged into progeny virions [P. V'Kovski et al.], a step in which vRNPs bud into the lumen of the ER and the ER-Golgi intermediate compartment (ERGIC) [N. S. Ogando et al.]. This results in viral particles enveloped with host membranes containing viral M, E, and S transmembrane structural proteins that need to be released from the cell. SARS-CoV-2 gRNA packaging involves the N protein. The N protein of human coronaviruses is highly expressed in infected cells. It is considered a multifunctional protein, promoting efficient sub-genomic viral RNA transcription, viral replication, virion assembly, and interacting with multiple host proteins [P. V'Kovski et al., D. E. Gordon et al., R. McBride, and M. van Zyl, B. C.]. In relation to transcription and replication, the N protein could provide a cooperative mechanism to increase protein and RNA concentrations at specific localizations S. Alberti, and S. Carra, S. F. Banani et al.], and this way organize viral transcription. Five studies have shown that N protein undergoes liquid-liquid phase separation (LLPS) in vitro [A. Savastano et al., H. Chen et al., C. Iserman et al., T. M. Perdikari et al., J. Cubuk et al.], dependent on its C-terminal domain (CTD) [H. Chen et al.]. It has been hypothesised that N could be involved in replication close to the ER and in packaging of gRNA into vRNPs near the ERGIC where genome assembly is thought to take place [A. Savastano et al.], but so far this is still speculative. Phosphorylation of N could adjust the physical properties of condensates differentially in ways that could accommodate the two different functions of N: transcription and progeny genome assembly [A. Savastano et al., C. Iserman et al., C. R. Carlson et al.]. The ERGIC constitutes the main assembly site of coronaviruses [S. Klein et al., E. J. Snijder et al., L. Mendonca et al.] and budding events have been seen by EM studies. For SARS-CoV-2, virus-budding was mainly clustered in regions with a high vesicle density and close to ER- and Golgi-like membrane arrangements [S. Klein et al., E. J. Snijder et al., L. Mendonca et al.]. The ectodomain of S trimers were found facing the ERGIC lumen and not induce membrane curvature on its own, therefore proposing that vRNPs and spike trimers [S. Klein et al.]. Finally, it has been shown that SARS-CoV-2 virions de novo formed traffic to lysosomes for unconventional egress by Arl8b-dependent lysosomal exocytosis [S. Ghosh et al.]. This process results in lysosome deacidification, inactivation of lysosomal degradation enzymes, and disruption of antigen presentation [S. Ghosh et al.].

Viral translation: SARS-CoV-2 Nsp1 binds the ribosomal mRNA channel to inhibit translation [Schubert et al. 2020] <ul> <li>Sucrose pelleting binding assay to verify Nsp1–40S complex formation</li> <li>In vivo translation assay</li> <li>Transient expression of FLAG-Nsp1 in HeLa cells and puromycin incorporation assay</li> </ul> SARS-CoV-2 disrupts splicing, translation, and protein trafficking [Banerjee et al. 2020] <ul> <li>SARS-CoV-2 viral protein binding to RNA</li> <li>Interferon stimulation experiments</li> <li>Splicing assessment experiments</li> <li>IRF7-GFP splicing reporter, 5EU RNA labeling, capture of biotinylated 5EU labeled RNA</li> </ul> Membrane SUnSET assay for transport of plasma membrane proteins to the cell surface Viral transcription: The mRNA transcripts are detected by the real-time reverse transcription-PCR (RT-PCR) assay. Several methods targeting the mRNA transcripts have been developed, which includes the RT-PCR assays targeting RdRp/helicase (Hel), spike (S), and nucleocapsid (N) genes of SARS-CoV-2 [Chan et al.]. RT-PCR assays detecting SARS-CoV-2 RNA in saliva include quantitative RT-PCR (RT-qPCR), direct RT-qPCR, reverse transcription-loop-mediated isothermal amplification (RT-LAMP) [Nagura-Ikeda M, et al.]. The viral mRNAs are reverse-transcribed with RT, followed by the amplification by PCR. Viral replication: viral replication is measured by RT-qPCR in infected cells, formation of liquid organelles is assessed in vitro reconstitution systems and in infected cells. Labelling by radioactive nucleosides. Viral production: Plaque assays, infectivity assays, RT-qPCR to detect viral RNA in released virions, sequencing to detect mutations in the genome, electron microscopy.

Broad mammalian host range has been demonstrated based on spike protein tropism for and binding to ACE2 [Conceicao et al. 2020; Wu et al. 2020] and cross-species ACE2 structural analysis [Damas et al. 2020]. No literature has been found on primary translation and molecular interactions of nsps in non-human host cells, but it is assumed to occur if the virus replicates in other species. Very broad mammalian tropism: human, bat, cat, dog, civet, ferret, horse, pig, sheep, goat, water buffalo, cattle, rabbit, hamster, mouse

UBERON:0000062

UBERON organ

CL:0000000

CL cell

High Unspecific

High

All life stages

High Moderate Moderate

1.         D. Kim et al., The Architecture of SARS-CoV-2 Transcriptome. Cell 181, 914-921 e910 (2020). 2.         E. J. Snijder et al., Unique and Conserved Features of Genome and Proteome of SARS-coronavirus, an Early Split-off From the Coronavirus Group 2 Lineage. Journal of Molecular Biology 331, 991-1004 (2003). 3.         N. C. Huston et al., Comprehensive in vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms. Mol Cell 81, 584-598 e585 (2021). 4.         C. J. Budzilowicz, S. P. Wilczynski, S. R. Weiss, Three intergenic regions of coronavirus mouse hepatitis virus strain A59 genome RNA contain a common nucleotide sequence that is homologous to the 3' end of the viral mRNA leader sequence. J Virol 53, 834-840 (1985). 5.         H. Di, A. A. McIntyre, M. A. Brinton, New insights about the regulation of Nidovirus subgenomic mRNA synthesis. Virology 517, 38-43 (2018). 6.         M. D. Sacco et al., Structure and inhibition of the SARS-CoV-2 main protease reveal strategy for developing dual inhibitors against M(pro) and cathepsin L. Sci Adv 6,  (2020). 7.         S. Klein et al., SARS-CoV-2 structure and replication characterized by in situ cryo-electron tomography. BioRxiv,  (2020). 8.         E. J. Snijder et al., A unifying structural and functional model of the coronavirus replication organelle: Tracking down RNA synthesis. PLoS Biol 18, e3000715 (2020). 9.         P. V'Kovski, A. Kratzel, S. Steiner, H. Stalder, V. Thiel, Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol,  (2020). 10.       P. Liu, J. Leibowitz, in Molecular Biology of the SARS-Coronavirus. (2010),  chap. Chapter 4, pp. 47-61. 11.       V. B. O'Leary, O. J. Dolly, C. Hoschl, M. Cerna, S. V. Ovsepian, Unpacking Pandora From Its Box: Deciphering the Molecular Basis of the SARS-CoV-2 Coronavirus. Int J Mol Sci 22,  (2020). 12.       Y. Finkel et al., The coding capacity of SARS-CoV-2. Nature 589, 125-130 (2021). 13.       H. A. Hussein, R. Y. A. Hassan, M. Chino, F. Febbraio, Point-of-Care Diagnostics of COVID-19: From Current Work to Future Perspectives. Sensors (Basel) 20,  (2020). 14.       M. Thoms et al., Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2. Science 369, 1249-1255 (2020). 15.       A. K. Banerjee et al., SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses. Cell 183, 1325-1339 e1321 (2020). 16.       H. Xia et al., Evasion of Type I Interferon by SARS-CoV-2. Cell Rep 33, 108234 (2020). 17.       P. Ahlquist, RNA-dependent RNA polymerases, viruses, and RNA silencing. Science 296, 1270-1273 (2002). 18.       M. Schwartz et al., A Positive-Strand RNA Virus Replication Complex Parallels Form and Function of Retrovirus Capsids. Molecular Cell 9, 505-514 (2002). 19.       W. A. Miller, G. Koev, Synthesis of subgenomic RNAs by positive-strand RNA viruses. Virology 273, 1-8 (2000). 20.       N. S. Ogando et al., SARS-coronavirus-2 replication in Vero E6 cells: replication kinetics, rapid adaptation and cytopathology. J Gen Virol 101, 925-940 (2020). 21.       I. Sola, F. Almazan, S. Zuniga, L. Enjuanes, Continuous and Discontinuous RNA Synthesis in Coronaviruses. Annu Rev Virol 2, 265-288 (2015). 22.       I. Sola, J. L. Moreno, S. Zuniga, S. Alonso, L. Enjuanes, Role of nucleotides immediately flanking the transcription-regulating sequence core in coronavirus subgenomic mRNA synthesis. J Virol 79, 2506-2516 (2005). 23.       X. Zhang, C. L. Liao, M. M. Lai, Coronavirus leader RNA regulates and initiates subgenomic mRNA transcription both in trans and in cis. J Virol 68, 4738-4746 (1994). 24.       S. G. Sawicki, D. L. Sawicki, S. G. Siddell, A contemporary view of coronavirus transcription. J Virol 81, 20-29 (2007). 25.       Y. Yang, W. Yan, B. Hall, X. Jiang, Characterizing transcriptional regulatory sequences in coronaviruses and their role in recombination. bioRxiv,  (2020). 26.       F. Wu et al., A new coronavirus associated with human respiratory disease in China. Nature 579, 265-269 (2020). 27.       A. Vandelli et al., Structural analysis of SARS-CoV-2 genome and predictions of the human interactome. Nucleic Acids Res 48, 11270-11283 (2020). 28.       J. R. Cohen, L. D. Lin, C. E. Machamer, Identification of a Golgi complex-targeting signal in the cytoplasmic tail of the severe acute respiratory syndrome coronavirus envelope protein. J Virol 85, 5794-5803 (2011). 29.       A. Perrier et al., The C-terminal domain of the MERS coronavirus M protein contains a trans-Golgi network localization signal. J Biol Chem 294, 14406-14421 (2019). 30.       D. E. Gordon et al., A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 583, 459-468 (2020). 31.       R. McBride, M. van Zyl, B. C. Fielding, The coronavirus nucleocapsid is a multifunctional protein. Viruses 6, 2991-3018 (2014). 32.       S. Alberti, S. Carra, Quality Control of Membraneless Organelles. Journal of Molecular Biology 430, 4711-4729 (2018). 33.       S. F. Banani, H. O. Lee, A. A. Hyman, M. K. Rosen, Biomolecular condensates: organizers of cellular biochemistry. Nature Reviews Molecular Cell Biology 18, 285-298 (2017). 34.       A. Savastano, A. I. de Opakua, M. Rankovic, M. Zweckstetter, Nucleocapsid protein of SARS-CoV-2 phase separates into RNA-rich polymerase-containing condensates.  (2020). 35.       H. Chen et al., Liquid-liquid phase separation by SARS-CoV-2 nucleocapsid protein and RNA. Cell Res,  (2020). 36.       C. Iserman et al., Specific viral RNA drives the SARS CoV-2 nucleocapsid to phase separate. bioRxiv,  (2020). 37.       T. M. Perdikari et al., SARS-CoV-2 nucleocapsid protein undergoes liquid-liquid phase separation stimulated by RNA and partitions into phases of human ribonucleoproteins. bioRxiv,  (2020). 38.       J. Cubuk et al., The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA. bioRxiv,  (2020). 39.       C. Iserman et al. (Cold Spring Harbor Laboratory, 2020). 40.       C. R. Carlson et al., Phosphoregulation of phase separation by the SARS-CoV-2 N protein suggests abiophysical basis for its dual functions. Molecular Cell,  (2020). 41.       L. Mendonca et al., SARS-CoV-2 Assembly and Egress Pathway Revealed by Correlative Multi-modal Multi-scale Cryo-imaging. bioRxiv,  (2020). 42.       S. Ghosh et al., beta-Coronaviruses Use Lysosomes for Egress Instead of the Biosynthetic Secretory Pathway. Cell 183, 1520-1535 e1514 (2020). 43.       Schubert, K., Karousis, E.D., Jomaa, A. et al. SARS-CoV-2 Nsp1 binds the ribosomal mRNA channel to inhibit translation. Nat Struct Mol Biol 27, 959–966 (2020).  44.       Chan, Jasper Fuk-Woo et al. Improved Molecular Diagnosis of COVID-19 by the Novel, Highly Sensitive and Specific COVID-19-RdRp/Hel Real-Time Reverse Transcription-PCR Assay Validated In Vitro and with Clinical Specimens. J Clin Microbiol. 2020:58(5)e00310-20. doi:10.1128/JCM.00310-20 45.       Nagura-Ikeda M, Imai K, Tabata S, et al. Clinical Evaluation of Self-Collected Saliva by Quantitative Reverse Transcription-PCR (RT-qPCR), Direct RT-qPCR, Reverse Transcription-Loop-Mediated Isothermal Amplification, and a Rapid Antigen Test To Diagnose COVID-19. J Clin Microbiol. 2020;58(9):e01438-20. doi:10.1128/JCM.01438-20 46.       Conceicao C, Thakur N, Human S, Kelly JT, Logan L, Bialy D, et al. (2020) The SARS-CoV-2 Spike protein has a broad tropism for mammalian ACE2 proteins. PLoS Biol 18(12): e3001016. https://doi.org/10.1371/journal.pbio.3001016 47.       Damas J, Hughes GM, Keough KC, Painter CA, Persky NS, Corbo M, Hiller M, Koepfli KP, Pfenning AR, Zhao H, Genereux DP, Swofford R, Pollard KS, Ryder OA, Nweeia MT, Lindblad-Toh K, Teeling EC, Karlsson EK, Lewin HA. Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates. Proc Natl Acad Sci U S A. 2020 Sep 8;117(36):22311-22322. doi: 10.1073/pnas.2010146117. Epub 2020 Aug 21. PMID: 32826334; PMCID: PMC7486773. AOPWiki 2021-03-25T19:55:12

2022-06-14T08:49:57

Increase, Cell death

Cellular

Cell death is part of normal development and maturation cycle, and is the component of many response patterns of living tissues to xenobiotic agents (i.e.. micro organisms and chemicals) and to endogenous modulations, such as inflammation and disturbed blood supply (Kanduc et al., 2002). Many physiological processes require cell death for their function (e.g.., embryonal development and immune selection of B and T cells) (Bertheloot et al., 2021). Defects in cells that result in their inappropriate survival or untimely death can negatively impact development or contribute to a variety of human pathologies, including cancer, AIDS, autoimmune disorders, and chronic infection. Cell death may also occur following exposure to environmental toxins or cytotoxic chemicals. Although this is often harmful, it can be beneficial in some cases, such as in the treatment of cancer (Crowley et al., 2016). Cell death can be divided into: programmed cell death (cell death as a normal component of development) and non-programmed cell death (uncontrolled death of the cell). Although this simplistic view has blurred the intricate mechanisms separating these forms of cell death, studies have and will uncover new effectors, cell death pathways and reveal a more complex and intertwined landscape of processes involving cell death (Bertheloot et al., 2021). Programmed cell death: is a form of cell death in which the dying cell plays an active part in its own demise (Cotter & Al-Rubeai, 1995). Apoptosis At a morphological level, it is characterized by cell shrinkage rather than the swelling seen in necrotic cell death. It is characterized by a number of characteristic morphological changes in the structure of the cell, together with a number of enzyme‐dependent biochemical processes. The result of it being the clearance of cells from the body, with minimal damage to surrounding tissues. An essential feature of apoptosis is the release of cytochrome c from mitochondria, regulated by a balance between proapoptotic and antiapoptotic proteins of the BCL-2 family, initiator caspases (caspase-8, -9 and -10) and effector caspases (caspase-3, -6 and -7). Apoptosis culminates in the breakdown of the nuclear membrane by caspase-6, the cleavage of many intracellular proteins (e.g., PARP and lamin), membrane blebbing, and the breakdown of genomic DNA into nucleosomal structures (Bertheloot et al., 2021). Mechanistically, two main pathways contribute to the caspase activation cascade downstream of mitochondrial cytochrome c release: <ul> <li>Intrinsic pathway is triggered by dysregulation of or imbalance in intracellular homeostasis by toxic agents or DNA damage. It is characterized by mitochondrial outer membrane permeabilization (MOMP), which results in the release of cytochrome c into the cytosol.</li> <li>Extrinsic pathway is initiated by activation of cell surface death receptors. Proapoptotic death receptors include TNFR1/2, Fas and the TNF-related apoptosis-inducing ligand (TRAIL) receptors DR4 and DR5.</li> </ul> Other pathways of programmed cell death are called »non-apoptotic programmed cell-death« or »caspase-independent programmed cell-death« (Blank & Shiloh, 2007). Necroptosis: This type of regulated cell death, occurs following the activation of the tumor necrosis receptor (TNFR1) by TNFα. Activation of other cellular receptors triggers necroptosis. These receptors include death receptors (i.e., Fas/FasL), Toll-like receptors (TLR4 and TLR3) and cytosolic nucleic acid sensors such as RIG-I and STING, which induce type I interferon (IFN-I) and TNFα production and thus promote necroptosis in an autocrine feedback loop. Most of these pathways trigger NFκB- dependent proinflammatory and prosurvival signals. Pyroptosis is a type of cell death culminating in the loss of plasma membrane integrity and induced by activation of so-called inflammasome sensors. These include the Nod-like receptor (NLR) family, the DNA receptor Absent in Melanoma 2 (AIM2) and the Pyrin receptor. Autophagy: is a process where cellular components such as macro proteins or even whole organelles are sequestered into lysosomes for degradation (Mizushima et al., 2008; Shintani & Klionsky, 2004). The lysosomes are then able to digest these substrates, the components of which can either be recycled to create new cellular structures and/or organelles or alternatively can be further processed and used as a source of energy (D’Arcy, 2019). Anoikis is apoptosis induced by loss of attachment to substrate or to other cells (anoikis). Anoikis overlaps with apoptosis in molecular terms, but is classified as a separate entity because of its specific form od induction (Blank & Shiloh, 2007). Induction of anoikis occurs when cells lose attachment to ECM, or adhere to an inappropriate type of ECM, the latter being the more relevant in vivo (Gilmore, 2005). Cornification: is programmed cell death of keratinocytes. Cell death in the context of cornification involves distinct enzyme classes such as transglutaminases, proteases, DNases and others (Eckhart et al., 2013). Non-programmed cell death: occurs accidentally in an unplanned manner. Necrosis is generally characterized to be the uncontrolled death of the cell, usually following a severe insult, resulting in spillage of the contents of the cell into surrounding tissues and subsequent damage thereof (D’Arcy, 2019).

Assays for Quantitating Cell Death: <ul> <li>Cell death can be measured by staining a sample of cells with trypan blue, assay is described in protocol: Measuring Cell Death by Trypan Blue Uptake and Light Microscopy (Crowley, Marfell, Christensen, et al., 2015d). Or with propidium Iodide, assay is described in protocol: Measuring Cell Death by Propidium Iodide (PI) Uptake and Flow Cytometry (Crowley & Waterhouse, 2015a) </li> <li>TUNEL technique: in situ terminal deoxynucleotidyl transferase (TdT)-mediated dUTP nick-end labeling can be used to detect apoptotic cells (Bever & Fekete, 1999; Uribe et al., 2013).</li> </ul> Assays for Quantitating Cell Survival           Colony-forming assay can be used to define the number of cells in a population that are capable of proliferating and forming large groups of cells. Described in Protocol: Measuring Survival of Adherent Cells with the Colony-Forming Assay (Crowley, Christensen, & Waterhouse, 2015c); Measuring Survival of Hematopoietic Cancer Cells with the Colony-Forming Assay in Soft Agar (Crowley & Waterhouse, 2015b). ASSAYS TO DISTINGUISH APOPTOSIS FROM NECROSIS AND OTHER DEATH MODALITIES Detecting Nuclear Condensation: The nucleus is generally round in healthy cells but fragmented in apoptotic cells. Dyes such as Giemsa or hematoxylin, which are purple in color and therefore easily viewed using light microscopy, are commonly used to stain the nucleus. Other features of apoptosis and necrosis, such as plasma membrane blebbing or rupture, can be identified by staining the cytoplasm with eosin. Eosin is pinkish in color and can also be viewed using light microscopy. Hematoxylin and eosin are, therefore, commonly used together to stain cells. Assay is described in Protocol: Morphological Analysis of Cell Death by Cytospinning Followed by Rapid Staining (Crowley, Marfell, & Waterhouse, 2015c); Analyzing Cell Death by Nuclear Staining with Hoechst 33342 (Crowley, Marfell, & Waterhouse, 2015a). Detection of DNA Fragmentation: Apoptotic cells with fragmented DNA can be identified and distinguished from live cells by staining with Propidium Iodide (PI) and measuring DNA content by flow cytometry. This assay is described in Protocol: Measuring the DNA Content of Cells in Apoptosis and at Different Cell-Cycle Stages by Propidium Iodide Staining and Flow Cytometry (Crowley, Chojnowski, & Waterhouse, 2015a). TUNEL technique can also be used: in situ terminal deoxynucleotidyl transferase (TdT)-mediated dUTP nick-end labeling can be used to detect apoptotic cells (Bever & Fekete, 1999; Crowley, Marfell, & Waterhouse, 2015b; Uribe et al., 2013). Detecting Phosphatidylserine Exposure: Apoptosis is also characterized by exposure of phosphatidylserine (PS) on the outside of apoptotic cells, which acts as a signal that triggers removal of the dying cell by phagocytosis. Annexin V, can selectively bind to PS to label apoptotic cells in which PS is exposed. Purified annexin V can be conjugated to various fluorochromes, which can then be visualized by fluorescence microscopy or detected by flow cytometry. This assay is described in protocol: Quantitation of Apoptosis and Necrosis by Annexin V Binding, Propidium Iodide Uptake, and Flow Cytometry (Crowley, Marfell, Scott, et al., 2015e). Detecting Caspase Activity: antibodies that specifically recognize the cleaved fragments of caspases and their substrates can be used to specifically detect caspase activity in apoptotic cells by immunocytochemistry. Flow cytometry (using primary antibodies conjugated to fluorescent molecules, or by counter staining with fluorescently labeled antibodies against the primary antibody) can then be used to quantitate the number of apoptotic cells. This assay is described in protocol: Detecting Cleaved Caspase-3 in Apoptotic Cells by Flow Cytometry (Crowley & Waterhouse, 2015a). Detecting Mitochondrial Damage: flow cytometry can be used to quantitate the number of cells that have reduced mitochondrial transmembrane potential, which is commonly associated with cytochrome c release during apoptosis. For this assay see protocol: Measuring Mitochondrial Transmembrane Potential by TMRE Staining (Crowley, Christensen, & Waterhouse, 2015b).     Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed.     Measures of apoptotic cytomorphological alterations:   Apoptotic cells exhibit electron dense nuclei, nuclear fragmentation, intact cell membrane up to the disintegration phase, disorganized cytoplasmic organelles, large clear vacuoles, blebs at cell surface, and apoptotic bodies, which can be visualized with various methods. (Elmore, 2007; Watanabe et al., 2002)  <table border="1"> <tbody> <tr> <td> Method of Measurement  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Transmission electron microscopy (TEM) / Scanning electron microscopy (SEM)/ Fluorescence microscopy  </td> <td> Martinez, Reif, and Pappas, 2010; Watanabe et al., 2002  </td> <td> TEM and SEM can image the cytomorphological alterations caused by apoptosis.  </td> <td> No  </td> </tr> <tr> <td colspan="3"> Stains:  </td> <td>   </td> </tr> <tr> <td> Hematoxylin with eosin  </td> <td> Elmore, 2007   </td> <td> Hematoxylin stains nuclei blue and eosin stains the cytoplasm/extracellular matrix pink, allowing for the visualization of the cytomorphological alterations of cells.  </td> <td> No  </td> </tr> <tr> <td> Toluidine blue or methylene blue  </td> <td> Watanabe et al., 2002  </td> <td> Toluidine blue stains cellular nuclei, and identifies malignant tissue, which has an increased DNA content and a higher nuclear-to-cytoplasmic ratio.  Methylene blue stain applied to a healthy cell sample results in a colorless stain. This is due to the cell's enzymes, which reduce the methylene blue, thereby, reducing its color. Methylene blue stain applied to a dead cell sample turns blue.  </td> <td> No  </td> </tr> <tr> <td> DAPI  </td> <td> Crowley, Marfell, and Waterhouse, 2016  </td> <td> Binds strongly to adenine–thymine-rich regions in the DNA. DAPI can stain live and fixed cells. It passes less efficiently through the membrane in live cells.  </td> <td> Yes  </td> </tr> <tr> <td> Hoescht 33342  </td> <td> Crowley, Marfell, and Waterhouse, 2016  </td> <td> Binds to DNA in live and fixed cells, used to measure DNA condensation.  </td> <td> Yes   </td> </tr> <tr> <td> Acridine Orange (AO)  </td> <td> Watanabe et al., 2002  </td> <td> Interacts with DNA/RNA through intercalation/electrostatic interaction, is able to penetrate cell membranes. Stains live cells green and dead cells red.  </td> <td> No  </td> </tr> <tr> <td> Nile blue sulfate  </td> <td> Watanabe et al., 2002  </td> <td> Stains cell nuclei and lysosomes, indicating apoptotic bodies.  </td> <td> No  </td> </tr> <tr> <td> Neutral red  </td> <td> Watanabe et al., 2002  </td> <td> Measures lysosomal membrane integrity  </td> <td> No  </td> </tr> <tr> <td> LysoTracker Red  </td> <td> Watanabe et al., 2002  </td> <td> Measures phagolysosomal activity that occurs due to the engulfment of apoptotic bodies.  </td> <td> No   </td> </tr> </tbody> </table>   DNA damage/fragmentation assays:  <table border="1"> <tbody> <tr> <td> Assay  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) assay  </td> <td> Kressel and Groscurth, 1994  </td> <td> Apoptosis is detected with the TUNEL method to assay the endonuclease cleavage products by enzymatically end-labeling the DNA strand breaks.  </td> <td> Yes    </td> </tr> <tr> <td> Nicoletti Assay (SubG1 cell fragment measurement)  </td> <td> Nicoletti et al., 1991  </td> <td> Measures DNA content in nuclei at the pre-G1 phase of the cell cycle (apoptotic nuclei have less DNA than nuclei in healthy cells).  </td> <td> No  </td> </tr> <tr> <td> Cell Death Detection ELISA kit  </td> <td> Parajuli, 2014  </td> <td> Apoptotic nucleosomes are detected using the Cell Death Detection ELISA kit, which were calculated as absorbance subtraction at 405 nm and 490 nm.  </td> <td> No  </td> </tr> </tbody> </table>   Measurement of apoptotic markers through immunochemistry:  <table border="1"> <tbody> <tr> <td> Method of Measurement  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Western blot / immunofluorescence microscopy / immunohistochemistry  </td> <td> Elmore 2007; Martinez, Reif, and Pappas, 2010; Parajuli et al, 2014  </td> <td> Apoptosis can be detected with the expression of various apoptotic markers by western blotting using antibodies. Markers can include: cytosolic cytochrome-c; caspases 2, 3, 6, 7, 8, 9, 10; Bax; Bcl-2 (apoptosis inhibitor); BIRC2; BIRC3; GAPDH; PARP; CDK2; CDK4; cyclin D1; p53; p63; p73; cytokeratin-18  </td> <td> No   </td> </tr> </tbody> </table>   Measures of altered caspase activity:  <table border="1"> <tbody> <tr> <td> Method of Measurement  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Caspase-3 and caspase-9 activity is measured with the enzyme-catalyzed release of p-nitroanilide (pNA) and quantified at 405 nm  </td> <td>  Wu, 2016  </td> <td> Visualizes caspase-3 and caspase-9 activity  </td> <td> No  </td> </tr> <tr> <td> PhiPhiLux Assay  </td> <td> Watanabe et al., 2002  </td> <td> The PhiPhiLux molecule becomes fluorescent once it is cleaved by caspase-3, indicating caspase activity.  </td> <td> No  </td> </tr> <tr> <td> Ferrocene reporter  </td> <td> Martinez, Reif, and Pappas, 2010  </td> <td> An electrochemical method to detect apoptosis. Ferrocene is attached to a peptide. The peptide sequence is a caspase 3 cleavage site and the ferrocene acts as the electrochemical reporter. The more caspase cleavage that occurs, the more ferrocene molecules are cleaved, the stronger the signal.  </td> <td> No  </td> </tr> <tr> <td> Self-assembled monolayers for matrix assisted laser desorption ionization time-of-flight mass spectrometry (SAMDI-MS) assay  </td> <td> Martinez, Reif, and Pappas, 2010  </td> <td> This assay detects caspase activity.  </td> <td> No  </td> </tr> </tbody> </table>   Measures of altered mitochondrial physiology:  <table border="1"> <tbody> <tr> <td> Method of Measurement  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Laser scanning confocal microscopy (LSCM)  </td> <td> Watanabe et al., 2002  </td> <td> LCSM can monitor many mitochondrial events following staining of cells, such as: mitochondrial permeability transition, depolarization of the inner mitochondrial membrane, which may be indicative of apoptosis.  </td> <td> No    </td> </tr> <tr> <td> Fluorescent, cationic, lipophilic mitochondrial dyes, such as: JC-1 dye, Rhodamine, DiOC6, Mitotracker red  </td> <td> Martinez, Reif, and Pappas, 2010; Sivandzade, Bhalerao, and Cucullo, 2019  </td> <td> These mitochondrial dyes can indicate disintegration of the mitochondrial outer membrane’s electrochemical gradient, as different fluorescence is observed between healthy and apoptotic cells. In healthy cells the dye accumulates in aggregates, but in apoptotic cells missing the electrochemical membrane, the dye will spread out into the cytoplasm providing different fluorescent signals.  </td> <td> No  </td> </tr> </tbody> </table>   Other measures:  <table border="1"> <tbody> <tr> <td> Method of measurement  </td> <td> Reference  </td> <td> Description  </td> <td> OECD Approved Assay  </td> </tr> <tr> <td> Apoptosis PCR microarray  </td> <td> Elmore, 2007  </td> <td> A method to profile the gene expression of many apoptotic-related genes, for example: ligands, receptors, intracellular modulators, and transcription factors.  </td> <td> No  </td> </tr> <tr> <td> Fluorescence correlation spectroscopy (FCS) or dual-colour fluorescence cross-correlation spectroscopy (dcFCCS)   </td> <td> Martinez, Reif, and Pappas, 2010  </td> <td> Used to measure protease activity.  </td> <td> No  </td> </tr> <tr> <td> Apoptosis is measured with Annexin V-FITC probes  </td> <td> Elmore, 2007; Wu et al., 2016  </td> <td> A measure of apoptotic membrane alterations. Annexin-V detects externalized phosphatidylserine residues, a result of apoptosis. Can be conducted in conjunction with propidium iodide (PI) staining. The relative percentage of Annexin V-FITC-positive/PI-negative cells is analyzed by flow cytometry.  </td> <td> Yes    </td> </tr> </tbody> </table>

The process of cell death is highly conserved within multi‐cellular organisms. (Lockshin & Zakeri, 2004).   Taxonomic applicability: Increased cell death is applicable to all animals. This includes vertebrates such as humans, mice and rats (Alberts et al., 2002).   Life stage applicability: There is insufficient data on life stage applicability of this KE.  Sex applicability: This key event is not sex specific (Forger and de Vries, 2010; Ortona Matarrese, and Malorni, 2014).   Evidence for perturbation by a stressor: Multiple studies show that cell death can be increased or disrupted by many types of stressors including ionizing radiation and altered gravity (Zhu et al., 2016).

UBERON:0000062

UBERON organ

CL:0000000

CL cell

High Unspecific

High

All life stages

High High High High Alberts, B. et al. (2002), “Programmed Cell Death (Apoptosis)”, in Molecular Biology of the Cell. 4th edition, Garland Science, New York, https://www.ncbi.nlm.nih.gov/books/NBK26873/   Bertheloot, D., Latz, E., & Franklin, B. S. (2021). Necroptosis, pyroptosis and apoptosis: an intricate game of cell death. Cellular & Molecular Immunology, 18, 1106–1121. https://doi.org/10.1038/s41423-020-00630-3 Bever, M. M., & Fekete, D. M. (1999). Ventromedial focus of cell death is absent during development of Xenopus and zebrafish inner ears. Journal of Neurocytology, 28(10–11), 781–793. https://doi.org/10.1023/a:1007005702187 Blank, M., & Shiloh, Y. (2007). Cell Cycle Programs for Cell Death: Apoptosis is Only One Way to Go. Cell Cycle, 6(6), 686–695. https://doi.org/10.4161/cc.6.6.3990 Cotter, T. G., & Al-Rubeai, M. (1995). Cell death (apoptosis) in cell culture systems. Trends in Biotechnology, 13(4), 150–155. https://doi.org/10.1016/S0167-7799(00)88926-X Crowley, L. C., Chojnowski, G., & Waterhouse, N. J. (2015a). Measuring the DNA content of cells in apoptosis and at different cell-cycle stages by propidium iodide staining and flow cytometry. Cold Spring Harbor Protocols, 10, 905–910. https://doi.org/10.1101/pdb.prot087247 Crowley, L. C., Christensen, M. E., & Waterhouse, N. J. (2015b). Measuring mitochondrial transmembrane potential by TMRE staining. Cold Spring Harbor Protocols, 12, 1092–1096. https://doi.org/10.1101/pdb.prot087361 Crowley, L. C., Christensen, M. E., & Waterhouse, N. J. (2015c). Measuring survival of adherent cells with the Colony-forming assay. Cold Spring Harbor Protocols, 8, 721–724. https://doi.org/10.1101/pdb.prot087171 Crowley, L. C., Marfell, B. J., Christensen, M. E., & Waterhouse, N. J. (2015d). Measuring cell death by trypan blue uptake and light microscopy. Cold Spring Harbor Protocols, 7, 643–646. https://doi.org/10.1101/pdb.prot087155 Crowley, L. C., Marfell, B. J., Scott, A. P., Boughaba, J. A., Chojnowski, G., Christensen, M. E., & Waterhouse, N. J. (2016). Dead cert: Measuring cell death. Cold Spring Harbor Protocols, 2016(12), 1064–1072. https://doi.org/10.1101/pdb.top070318 Crowley, L. C., Marfell, B. J., Scott, A. P., & Waterhouse, N. J. (2015e). Quantitation of apoptosis and necrosis by annexin V binding, propidium iodide uptake, and flow cytometry. Cold Spring Harbor Protocols, 11, 953–957. https://doi.org/10.1101/pdb.prot087288 Crowley, L. C., Marfell, B. J., & Waterhouse, N. J. (2015a). Analyzing cell death by nuclear staining with Hoechst 33342. Cold Spring Harbor Protocols, 9, 778–781. https://doi.org/10.1101/pdb.prot087205 Crowley, L. C., Marfell, B. J., & Waterhouse, N. J. (2015b). Detection of DNA fragmentation in apoptotic cells by TUNEL. Cold Spring Harbor Protocols, 10, 900–905. https://doi.org/10.1101/pdb.prot087221 Crowley, L. C., Marfell, B. J., & Waterhouse, N. J. (2015c). Morphological analysis of cell death by cytospinning followed by rapid staining. Cold Spring Harbor Protocols, 9, 773–777. https://doi.org/10.1101/pdb.prot087197 Crowley, L. C., & Waterhouse, N. J. (2015a). Detecting cleaved caspase-3 in apoptotic cells by flow cytometry. Cold Spring Harbor Protocols, 11, 958–962. https://doi.org/10.1101/pdb.prot087312 Crowley, L. C., & Waterhouse, N. J. (2015b). Measuring survival of hematopoietic cancer cells with the Colony-forming assay in soft agar. Cold Spring Harbor Protocols, 8, 725. https://doi.org/10.1101/pdb.prot087189 D’Arcy, M. S. (2019). Cell death: a review of the major forms of apoptosis, necrosis and autophagy. Cell Biology International, 43(6), 582–592. https://doi.org/10.1002/cbin.11137 Eckhart, L., Lippens, S., Tschachler, E., & Declercq, W. (2013). Cell death by cornification. Biochimica et Biophysica Acta - Molecular Cell Research, 1833(12), 3471–3480. https://doi.org/10.1016/j.bbamcr.2013.06.010 Elmore, S. (2007), “Apoptosis: A Review of Programmed Cell Death”, Toxical Pathology, Vol. 35/4, SAGE, <a href="https://doi.org/10.1080%2F01926230701320337" rel="noreferrer noopener" target="_blank">https://doi.org/10.1080/01926230701320337</a>.  Forger, N. G. and G. J. de Vries (2010), “Cell death and sexual differentiation of behavior: worms, flies, and mammals”, Current opinion in neurobiology, Vol. 20/6, Elsevier, Amsterdam, <a href="https://doi.org/10.1016/j.conb.2010.09.006" rel="noreferrer noopener" target="_blank">https://doi.org/10.1016/j.conb.2010.09.006</a>   Gilmore, A. P. (2005). Anoikis. Cell Death and Differentiation, 12, 1473–1477. https://doi.org/10.1038/sj.cdd.4401723 Kanduc, D., Mittelman, A., Serpico, R., Sinigaglia, E., Sinha, A. A., Natale, C., Santacroce, R., Di Corcia, M. G., Lucchese, A., Dini, L., Pani, P., Santacroce, S., Simone, S., Bucci, R., & Farber, E. (2002). Cell death: apoptosis versus necrosis (review). International Journal of Oncology, 21(1), 165–170. https://doi.org/10.3892/ijo.21.1.165 Kressel, M. and P. Groscurth (1994), "Distinction of apoptotic and necrotic cell death by in situ labelling of fragmented DNA", Cell and tissue research, Vol. 278/3, Nature, <a href="https://doi.org/10.1007/BF00331373" rel="noreferrer noopener" target="_blank">https://doi.org/10.1007/BF00331373</a>.  Lockshin, R. A., & Zakeri, Z. (2004). Apoptosis, autophagy, and more. International Journal of Biochemistry and Cell Biology, 36(12), 2405–2419. https://doi.org/10.1016/j.biocel.2004.04.011 Martinez, M. M., R. D. Reif, and D. Pappas (2010), “Detection of apoptosis: A review of conventional and novel techniques”, Analytical Methods, Vol. 2/8, Royal Society of Chemistry, <a href="https://doi.org/10.1039/C0AY00247J" rel="noreferrer noopener" target="_blank">https://doi.org/10.1039/C0AY00247J</a>  Mizushima, N., Levine, B., Cuervo, A. M., & Klionsky, D. J. (2008). Autophagy fights disease through cellular self-digestion. Nature, 451(7182), 1069–1075. https://doi.org/10.1038/nature06639 Nicoletti I. et al. (1991), “A rapid and simple method for measuring thymocyte apoptosis by propidium iodide staining and flow cytometry”, Journal of Immunological Methods, Vol. 139/2, Elsevier, Amsterdam, https://doi.org/10.1016/0022-1759(91)90198-O Ortona, E., P. Matarrese, and W. Malorni (2014), “Taking into account the gender issue in cell death studies”, Cell Death & Disease, Vol. 5, Nature, <a href="https://doi.org/10.1038/cddis.2014.73" rel="noreferrer noopener" target="_blank">https://doi.org/10.1038/cddis.2014.73</a>.   Parajuli, K. R. et al. (2014), "Methoxyacetic acid suppresses prostate cancer cell growth by inducing growth arrest and apoptosis", American journal of clinical and experimental urology, Vol. 2/4, pp. 300-312.  Shintani, T., & Klionsky, D. J. (2004). Autophagy in health and disease: A double-edged sword. Science, 306(5698), 990–995. https://doi.org/10.1126/science.1099993 Sivandzade, F., A. Bhalerao and L. Cucullo (2019), “Analysis of the Mitochondrial Membrane Potential Using Cationic JC-1 Dye as a Sensitive Fluorescent Probe”, Bio Protocol, Vol. 9/1, <a href="https://doi.org/10.21769/BioProtoc.3128" rel="noreferrer noopener" target="_blank">https://doi.org/10.21769/BioProtoc.3128</a>.  Uribe, P. M., Sun, H., Wang, K., Asuncion, J. D., & Wang, Q. (2013). Aminoglycoside-Induced Hair Cell Death of Inner Ear Organs Causes Functional Deficits in Adult Zebrafish (Danio rerio). PLoS ONE, 8(3), 58755. https://doi.org/10.1371/journal.pone.0058755 Wade, M. G. et al. (2008), "Methoxyacetic acid-induced spermatocyte death is associated with histone hyperacetylation in rats", Biology of Reproduction, Vol. 78/5, Oxford University Press, Oxford, <a href="https://doi.org/10.1095/biolreprod.107.065151" rel="noreferrer noopener" target="_blank">https://doi.org/10.1095/biolreprod.107.065151</a>  Watanabe, M., et al. (2002), “The pros and cons of apoptosis assays for use in the study of cells, tissues, and organs”, Microscopy and microanalysis, Vol. 8/5, Cambridge University Press, Cambridge, <a href="https://doi.org/10.1017/S1431927602010346" rel="noreferrer noopener" target="_blank">https://doi.org/10.1017/S1431927602010346</a>.  Wu, R. et al. (2016), "microRNA-497 induces apoptosis and suppressed proliferation via the Bcl-2/Bax-caspase9-caspase 3 pathway and cyclin D2 protein in HUVECs", PLoS One, Vol. 11/12, PLOS, San Francisco, <a href="https://doi.org/10.1371/journal.pone.0167052" rel="noreferrer noopener" target="_blank">https://doi.org/10.1371/journal.pone.0167052</a>.  Zhu, M., et al. (2021), “Immunogenic Cell Death Induction by Ionizing Radiation”, Frontiers in Immunology, Vol. 12, <a href="https://doi.org/10.3389/FIMMU.2021.705361" rel="noreferrer noopener" target="_blank">https://doi.org/10.3389/FIMMU.2021.705361</a>.  AOPWiki 2020-12-04T15:13:07

2023-03-22T11:07:45

Increased, secretion of proinflammatory mediators

Increased proinflammatory mediators

Cellular

Pro-inflammatory mediators are the chemical and biological molecules that initiate and regulate inflammatory reactions. Pro-inflammatory mediators are secreted following exposure to an inflammogen in a gender/sex or developmental stage independent manner. They are secreted during inflammation in all species. Different types of pro-inflammatory mediators are secreted during innate or adaptive immune responses across various species (Mestas and Hughes, 2004). Cell-derived pro-inflammatory mediators include cytokines, chemokines, and growth factors. Blood derived pro-inflammatory mediators include vasoactive amines, complement activation products and others. These modulators can be grouped based on the cell type that secrete them, their cellular localisation and also based on the type of immune response they trigger. For example, members of the interleukin (IL) family including <a href="https://bioregistry.io/genecards:IL2">IL-2</a>, <a href="https://bioregistry.io/genecards:IL4">IL-4</a>, <a href="https://bioregistry.io/genecards:IL7">IL-7</a>, <a href="https://bioregistry.io/genecards:IL9">IL-9</a>, <a href="https://bioregistry.io/genecards:IL15">IL-15</a>, <a href="https://bioregistry.io/genecards:IL21">IL-21</a>, <a href="https://bioregistry.io/genecards:IL3">IL-3</a>, <a href="https://bioregistry.io/genecards:IL5">IL-5</a> and Granulocyte-macrophage colony stimulating factor (<a href="https://bioregistry.io/genecards:CSF2">GM-CSF</a>) are involved in the adaptive immune responses. The pro-inflammatory cytokines include IL-1 family (<a href="https://bioregistry.io/genecards:IL1a">IL-1</a>α , <a href="https://bioregistry.io/genecards:IL1b">IL-1</a>β, <a href="https://bioregistry.io/genecards:IL1ra">IL-1r</a>α, <a href="https://bioregistry.io/genecards:IL18">IL-18</a>, <a href="https://bioregistry.io/genecards:IL36a">IL-36</a>α, <a href="https://bioregistry.io/genecards:IL36b">IL-36</a>β, <a href="https://bioregistry.io/genecards:IL36g">IL-36</a>γ, <a href="https://bioregistry.io/genecards:IL36Ra">IL-36R</a>α, <a href="https://bioregistry.io/genecards:IL37">IL-37</a>), <a href="https://bioregistry.io/genecards:IL6">IL-6 </a>family, Tumor necrosis factor (<a href="https://bioregistry.io/genecards:TNF">TNF</a>) family, <a href="https://bioregistry.io/genecards:IL17">IL-17</a>, and Interferon gamma (<a href="https://bioregistry.io/genecards:IFNg">IFN</a>-γ) (Turner et al., 2014). While <a href="https://bioregistry.io/genecards:IL4">IL-4</a> and <a href="https://bioregistry.io/genecards:IL5">IL-5</a> are considered T helper (Th) cell type 2 response, <a href="https://bioregistry.io/genecards:IFNg">IFN</a>-γ is suggested to be Th1 type response. Different types of pro-inflammatory mediators are secreted during innate or adaptive immune responses across various species (Mestas and Hughes, 2004). However, <a href="https://bioregistry.io/genecards:IL1">IL-1</a> family cytokines, <a href="https://bioregistry.io/genecards:IL4">IL-4</a>, <a href="https://bioregistry.io/genecards:IL5">IL-5</a>, <a href="https://bioregistry.io/genecards:IL6">IL-6</a>, <a href="https://bioregistry.io/genecards:TNFa">TNF</a>-α, IFN-γ are the commonly measured mediators in experimental animals and in humans. Similar gene expression patterns involving inflammation and matrix remodelling are observed in human patients of pulmonary fibrosis and mouse lungs exposed to bleomycin (Kaminski, 2002). Literature evidence for its perturbation: Several studies show increased proinflammatory mediators in rodent lungs and bronchoalveolar lavage fluid, and in cell culture supernatants following exposure to a variety of carbon nanotube (CNT) types and other materials. Poland et al., 2008 showed that long and thin CNTs (>5 µm) can elicit asbestos-like pathogenicity through the continual release of pro-inflammatory cytokines and reactive oxygen species. Exposure to crystalline silica induces release of inflammatory cytokines (TNF-α, IL-1, IL-6), transcription factors (Nuclear factor kappa B [NF-κB], Activator protein-1 [AP-1]) and kinase signalling pathways in mice that contain NF-κB luciferase reporter (Hubbard et al., 2002). Boyles et al., 2015 found that lung responses to long multi-walled carbon nanotubes (MWCNTs) included high expression levels of pro-inflammatory mediators Monocyte chemoattractant protein 1 (MCP-1), Transforming growth factor beta 1 (TGF-β1), and TNF-α (Boyles et al., 2015). Bleomycin administration in rodents induces lung inflammation and increased expression of pro-inflammatory mediators (Park et al., 2019). Inflammation induced by bleomycin, paraquat and CNTs is characterised by the altered expression of pro-inflammatory mediators. A large number of nanomaterials induce expression of cytokines and chemokines in lungs of rodents exposed via inhalation (Halappanavar et al., 2011; Husain et al., 2015a). Similarities are observed in gene programs involving pro-inflammatory event is observed in both humans and experimental mice (Zuo et al., 2002).

The selection of pro-inflammatory mediators for investigation varies based on the expertise of the lab, cell types studied and the availability of the specific antibodies. Real-time reverse transcription-polymerase chain reaction (qRT-PCR) – will measure the abundance of cytokine mRNA in a given sample. The method involves three steps: conversion of RNA into cDNA by reverse transcription method, amplification of cDNA using the PCR, and the real-time detection and quantification of amplified products (amplicons) (Nolan et al., 2006). Amplicons are detected using fluorescence, increase in which is directly proportional to the amplified PCR product. The number of cycles required per sample to reach a certain threshold of fluorescence (set by the user – usually set in the linear phase of the amplification, and the observed difference in samples to cross the set threshold reflects the initial amount available for amplification) is used to quantify the relative amount in the samples. The amplified products are detected by the DNA intercalating minor groove-binding fluorophore SYBR green, which produces a signal when incorporated into double-stranded amplicons. Since the cDNA is single stranded, the dye does not bind enhancing the specificity of the results. There are other methods such as nested fluorescent probes for detection, but SYBR green is widely used. RT-PCR primers specific to several pro-inflammatory mediators in several species including mouse, rat and humans, are readily available commercially. Enzyme-linked immunosorbent assays (ELISA) – permit quantitative measurement of antigens in biological samples. The method is the same as described for the MIE. Both ELISA and qRT-PCR assays are used in vivo and are readily applicable to in vitro cell culture models, where cell culture supernatants or whole cell homogenates are used for ELISA or mRNA assays. Both assays are straight forward, quantitative and require relatively a small amount of input sample. Apart from assaying single protein or gene at a time, cytokine bead arrays or cytokine PCR arrays can also be used to detect a whole panel of inflammatory mediators in a multiplex method (Husain et al., 2015b). This method is quantitative and especially advantageous when the sample amount available for testing is scarce. Lastly, immunohistochemistry can also be used to detect specific immune cell types producing the pro-inflammatory mediators and its downstream effectors in any given tissue (Costa et al., 2017). Immunohistochemistry results can be used as weight of evidence; however, the technique is not quantitative and depending on the specific antibodies used, the assay sensitivity may also become an issue (Amsen and De Visser, 2009). Cell models - of varying complexity have been used to assess the expression of pro-inflammatory mediators. Two dimensional submerged monocultures of the main fibrotic effector cells – lung epithelial cells, macrophages, and fibroblasts – have routinely been used in vitro due to the large literature base, and ease of use, but do not adequately mimic the in vivo condition (Sharma et al., 2016; Sundarakrishnan et al., 2018). Recently, the EpiAlveolar in vitro lung model (containing epithelial cells, endothelial cells, and fibroblasts) was used to predict the fibrotic potential of MWCNTs, and researchers noted increases in the pro-inflammatory molecules TNF-α, IL-1β, and the pro-fibrotic TGF-β using ELISA (Barasova et al., 2020). A similar, but less complicated co-culture model of immortalized human alveolar epithelial cells and idiopathic pulmonary fibrosis patient derived fibroblasts was used to assess pro-fibrotic signalling, and noted enhanced secretion of Platelet derived growth factor (PDGF) and Basic fibroblast growth factor (bFGF), as well as evidence for epithelial to mesenchymal transition of epithelial cells in this system (Prasad et al., 2014). Models such as these better capitulate the in vivo pulmonary alveolar capillary, but have lower reproducibility as compared to traditional submerged mono-culture experiments.

Human, mouse, rat Cytokines are the common pro-inflammatory mediators secreted following inflammogenic stimuli. Cytokines can be defined as a diverse group of signaling protein molecules. They are secreted by different cell types in different tissues and in all mammalian species, irrespective of gender, age or sex. A lot of literature is available to support cross species, gender and developmental stage application for this KE. The challenge is the specificity; most cytokines exhibit redundant functions and many are pleotropic.

CL:0000255

CL eukaryotic cell

High Male High Female

High

Adults

High High High

1. Amsen D, de Visser KE, Town T. Approaches to determine expression of inflammatory cytokines. Methods Mol Biol. 2009;511:107-42. doi: 10.1007/978-1-59745-447-6_5.  2. Barosova H, Maione AG, Septiadi D, Sharma M, Haeni L, Balog S, O'Connell O, Jackson GR, Brown D, Clippinger AJ, Hayden P, Petri-Fink A, Stone V, Rothen-Rutishauser B. Use of EpiAlveolar Lung Model to Predict Fibrotic Potential of Multiwalled Carbon Nanotubes. ACS Nano. 2020 Apr 28;14(4):3941-3956. doi: 10.1021/acsnano.9b06860.  3. Boyles MS, Young L, Brown DM, MacCalman L, Cowie H, Moisala A, Smail F, Smith PJ, Proudfoot L, Windle AH, Stone V. Multi-walled carbon nanotube induced frustrated phagocytosis, cytotoxicity and pro-inflammatory conditions in macrophages are length dependent and greater than that of asbestos. Toxicol In Vitro. 2015 Oct;29(7):1513-28. doi: 10.1016/j.tiv.2015.06.012.  4. Costa PM, Gosens I, Williams A, Farcal L, Pantano D, Brown DM, Stone V, Cassee FR, Halappanavar S, Fadeel B. Transcriptional profiling reveals gene expression changes associated with inflammation and cell proliferation following short-term inhalation exposure to copper oxide nanoparticles. J Appl Toxicol. 2018 Mar;38(3):385-397. doi: 10.1002/jat.3548. 5. Halappanavar S, Jackson P, Williams A, Jensen KA, Hougaard KS, Vogel U, Yauk CL, Wallin H. Pulmonary response to surface-coated nanotitanium dioxide particles includes induction of acute phase response genes, inflammatory cascades, and changes in microRNAs: a toxicogenomic study. Environ Mol Mutagen. 2011 Jul;52(6):425-39. doi: 10.1002/em.20639.  6. Hubbard AK, Timblin CR, Shukla A, Rincón M, Mossman BT. Activation of NF-kappaB-dependent gene expression by silica in lungs of luciferase reporter mice. Am J Physiol Lung Cell Mol Physiol. 2002 May;282(5):L968-75. doi: 10.1152/ajplung.00327.2001. 7. Husain M, Kyjovska ZO, Bourdon-Lacombe J, Saber AT, Jensen KA, Jacobsen NR, Williams A, Wallin H, Halappanavar S, Vogel U, Yauk CL. Carbon black nanoparticles induce biphasic gene expression changes associated with inflammatory responses in the lungs of C57BL/6 mice following a single intratracheal instillation. Toxicol Appl Pharmacol. 2015a Dec 15;289(3):573-88. doi: 10.1016/j.taap.2015.11.003. 8. Husain M, Wu D, Saber AT, Decan N, Jacobsen NR, Williams A, Yauk CL, Wallin H, Vogel U, Halappanavar S. Intratracheally instilled titanium dioxide nanoparticles translocate to heart and liver and activate complement cascade in the heart of C57BL/6 mice. Nanotoxicology. 2015b;9(8):1013-22. doi: 10.3109/17435390.2014.996192. 9. Kaminski N. Microarray analysis of idiopathic pulmonary fibrosis. Am J Respir Cell Mol Biol. 2003 Sep;29(3 Suppl):S32-6. 10. Mestas J, Hughes CC. Of mice and not men: differences between mouse and human immunology. J Immunol. 2004 Mar 1;172(5):2731-8. doi: 10.4049/jimmunol.172.5.2731. 11. Nolan T, Hands RE, Bustin SA. Quantification of mRNA using real-time RT-PCR. Nat Protoc. 2006;1(3):1559-82. doi: 10.1038/nprot.2006.236. 12. Park SJ, Im DS. Deficiency of Sphingosine-1-Phosphate Receptor 2 (S1P2) Attenuates Bleomycin-Induced Pulmonary Fibrosis. Biomol Ther (Seoul). 2019 May 1;27(3):318-326. doi: 10.4062/biomolther.2018.131. 13. Poland CA, Duffin R, Kinloch I, Maynard A, Wallace WA, Seaton A, Stone V, Brown S, Macnee W, Donaldson K. Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study. Nat Nanotechnol. 2008 Jul;3(7):423-8. doi: 10.1038/nnano.2008.111. 14. Prasad S, Hogaboam CM, Jarai G. Deficient repair response of IPF fibroblasts in a co-culture model of epithelial injury and repair. Fibrogenesis Tissue Repair. 2014 Apr 29;7:7. doi: 10.1186/1755-1536-7-7.  15. Sharma M, Nikota J, Halappanavar S, Castranova V, Rothen-Rutishauser B, Clippinger AJ. Predicting pulmonary fibrosis in humans after exposure to multi-walled carbon nanotubes (MWCNTs). Arch Toxicol. 2016 Jul;90(7):1605-22. doi: 10.1007/s00204-016-1742-7.  16. Sundarakrishnan A, Chen Y, Black LD, Aldridge BB, Kaplan DL. Engineered cell and tissue models of pulmonary fibrosis. Adv Drug Deliv Rev. 2018 Apr;129:78-94. doi: 10.1016/j.addr.2017.12.013. 17. Turner MD, Nedjai B, Hurst T, Pennington DJ. Cytokines and chemokines: At the crossroads of cell signalling and inflammatory disease. Biochim Biophys Acta. 2014 Nov;1843(11):2563-2582. doi: 10.1016/j.bbamcr.2014.05.014.  18. Zuo F, Kaminski N, Eugui E, Allard J, Yakhini Z, Ben-Dor A, Lollini L, Morris D, Kim Y, DeLustro B, Sheppard D, Pardo A, Selman M, Heller RA. Gene expression analysis reveals matrilysin as a key regulator of pulmonary fibrosis in mice and humans. Proc Natl Acad Sci U S A. 2002 Apr 30;99(9):6292-7. doi: 10.1073/pnas.092134099. AOPWiki 2018-01-02T13:12:11

2023-05-17T15:18:03

Increased, recruitment of inflammatory cells

Recruitment of inflammatory cells

Tissue

Pro-inflammatory cells originate in bone marrow and are recruited to the site of infection or injury via circulation following specific pro-inflammatory mediator (cytokine and chemokine) signalling. Pro-inflammatory cells are recruited to lungs to clear the invading pathogen or the toxic substance. Monocytes (dendritic cells, macrophages, and neutrophils) are subsets of circulating white blood cells that are involved in the immune responses to pathogen or toxicant stimuli (Kolaczkowska and Kubes, 2013; Kopf et al., 2015). They are derived from the bone marrow. They can differentiate into different macrophage types and dendritic cells. They can be categorised based on their size, the type of cell surface receptors and their ability to differentiate following external or internal stimulus such as increased expression of cytokines. Monocytes participate in tissue healing, clearance of toxic substance or pathogens, and in the initiation of adaptive immunity. Recruited monocytes can also influence pathogenesis (Ingersoll et al., 2011). Sensing or recognition of pathogens and harmful substances results in the recruitment of monocytes to lungs (Shi and Pamer, 2011). Activated immune cells secrete a variety of pro-inflammatory mediators, the purpose of which is to propagate the immune signalling and response, which when not controlled, leads to chronic inflammation, cell death and tissue injury. Thus, Event 1496 and Event 1497 act in a positive feedback loop mechanism and propagate the proinflammatory environment. Literature evidence for its perturbation: Macrophages accumulate in bronchoalveolar fluid (BALF) post-exposure to bleomycin (Phan et al., 1980; Smith et al., 1995). Nanomaterial (NM)-induced inflammation is predominantly neutrophilic (Poulsen et al., 2015; Rahman L et al., 2017a; Rahman et al., 2017b; Shvedova et al., 2005). An increased number of neutrophils (Reynolds et al., 1977) is observed in the BALF of patients with idiopathic pulmonary fibrosis. Eosinophils are a type of white blood cells and a type of granulocytes (contain granules and enzymes) that are recruited following exposure to allergens, during allergic reactions such as asthma or during fibrosis (Reynolds et al., 1977). Multi-walled carbon nanotubes (MWCNTs) induce increased eosinophil count in lungs (Købler C et al., 2015). MWCNTs act as allergens and induce lung infiltration of eosinophils and cause airway hypersensitivity (Beamer et al., 2013). It is important to note that the stressor-induced Event 1495, Event 1496, and Event 1497 are part of the functional changes that we collectively consider as inflammation, and together, they mark the initiation of acute inflammatory phase. Event 1495 and Event 1496 occur at the cellular level. Event 1497 occurs at the tissue level.

In vivo, recruitment of pro-inflammatory cells is measured using BALF cellularity assay. The fluid lining the lung epithelium is lavaged (BALF) and its composition is assessed as marker of lung immune response to the toxic substances or pathogens. BALF is assessed quantitatively for types of infiltrating cells, levels and types of cytokines and chemokines. Thus, BALF assessment can aid in developing dose-response of a substance, to rank a substances’ potency and to set up no effect level of exposure for the regulatory decision making. For NMs, in vivo BALF assessment is recommended as a mandatory test (discussed in ENV/JM/MONO(2012)40 and also in OECD inhalation test guideline for NMs). Temporal changes in the BALF composition can be prognostic of initiation and progression of lung immune disease (Cho et al., 2010). In vitro, it is difficult to assess the recruitment of pro-inflammatory cells. Thus, a suit of pro-inflammatory mediators specific to cell types are assessed using the same techniques mentioned above (real-time reverse transcription-polymerase chain reaction [qRT-PCR], enzyme-linked immunosorbent assays [ELISA], immunohistochemistry) in cell culture models, as indicative of recruitment of cells into the lungs. Alternatively, the use of precision cut lung slices can allow for limited assessment of recruitment of tissue resident inflammatory cells, based on the repertoire of cells remaining in the specific slice following harvesting. This method was used to show that there is a histological increase in inflammatory foci following treatment with bleomycin and MWCNTs (Rahman et al., 2020). Finally, more complicated microfluidic lung-on-a-chip devices can be used to assess the migration of select immune cells and fibroblasts toward a simulated epithelium following treatment with a pro-fibrotic compound (He et al., 2017). However, this method is limited to two cell types, and it lacks the reservoirs of immune cells present in the body in vivo.

Human, mouse, rat

High Mixed

High

All life stages

High High High

1. Beamer CA, Girtsman TA, Seaver BP, Finsaas KJ, Migliaccio CT, Perry VK, Rottman JB, Smith DE, Holian A. IL-33 mediates multi-walled carbon nanotube (MWCNT)-induced airway hyper-reactivity via the mobilization of innate helper cells in the lung. Nanotoxicology. 2013 Sep;7(6):1070-81. doi: 10.3109/17435390.2012.702230. 2. Cho WS, Duffin R, Poland CA, Howie SE, MacNee W, Bradley M, Megson IL, Donaldson K. Metal oxide nanoparticles induce unique inflammatory footprints in the lung: important implications for nanoparticle testing. Environ Health Perspect. 2010 Dec;118(12):1699-706. doi: 10.1289/ehp.1002201.  3. He J, Chen W, Deng S, Xie L, Feng J, Geng J, et al. Modeling alveolar injury using microfluidic co-cultures for monitoring bleomycin-induced epithelial/fibroblastic cross-talk disorder. RSC Advances. 2017 7(68):42738-49. doi: 10.1039/C7RA06752F. 4. Ingersoll MA, Platt AM, Potteaux S, Randolph GJ. Monocyte trafficking in acute and chronic inflammation. Trends Immunol. 2011 Oct;32(10):470-7. doi: 10.1016/j.it.2011.05.001. 5. Købler C, Poulsen SS, Saber AT, Jacobsen NR, Wallin H, Yauk CL, Halappanavar S, Vogel U, Qvortrup K, Mølhave K. Time-dependent subcellular distribution and effects of carbon nanotubes in lungs of mice. PLoS One. 2015 Jan 23;10(1):e0116481. doi: 10.1371/journal.pone.0116481.  6. Kolaczkowska E, Kubes P. Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol. 2013 Mar;13(3):159-75. doi: 10.1038/nri3399.  7. Kopf M, Schneider C, Nobs SP. The development and function of lung-resident macrophages and dendritic cells. Nat Immunol. 2015 Jan;16(1):36-44. doi: 10.1038/ni.3052. 8. Phan SH, Thrall RS, Ward PA. Bleomycin-induced pulmonary fibrosis in rats: biochemical demonstration of increased rate of collagen synthesis. Am Rev Respir Dis. 1980 Mar;121(3):501-6. doi: 10.1164/arrd.1980.121.3.501.  9. Poulsen SS, Saber AT, Williams A, Andersen O, Købler C, Atluri R, Pozzebon ME, Mucelli SP, Simion M, Rickerby D, Mortensen A, Jackson P, Kyjovska ZO, Mølhave K, Jacobsen NR, Jensen KA, Yauk CL, Wallin H, Halappanavar S, Vogel U. MWCNTs of different physicochemical properties cause similar inflammatory responses, but differences in transcriptional and histological markers of fibrosis in mouse lungs. Toxicol Appl Pharmacol. 2015 Apr 1;284(1):16-32. doi: 10.1016/j.taap.2014.12.011.  10. Rahman L, Wu D, Johnston M, William A, Halappanavar S. Toxicogenomics analysis of mouse lung responses following exposure to titanium dioxide nanomaterials reveal their disease potential at high doses. Mutagenesis. 2017a Jan;32(1):59-76. doi: 10.1093/mutage/gew048.  11. Rahman L, Jacobsen NR, Aziz SA, Wu D, Williams A, Yauk CL, White P, Wallin H, Vogel U, Halappanavar S. Multi-walled carbon nanotube-induced genotoxic, inflammatory and pro-fibrotic responses in mice: Investigating the mechanisms of pulmonary carcinogenesis. Mutat Res Genet Toxicol Environ Mutagen. 2017b Nov;823:28-44. doi: 10.1016/j.mrgentox.2017.08.005.  12. Rahman L, Williams A, Gelda K, Nikota J, Wu D, Vogel U, Halappanavar S. 21st Century Tools for Nanotoxicology: Transcriptomic Biomarker Panel and Precision-Cut Lung Slice Organ Mimic System for the Assessment of Nanomaterial-Induced Lung Fibrosis. Small. 2020 Sep;16(36):e2000272. doi: 10.1002/smll.202000272.  13. Reynolds HY, Fulmer JD, Kazmierowski JA, Roberts WC, Frank MM, Crystal RG. Analysis of cellular and protein content of broncho-alveolar lavage fluid from patients with idiopathic pulmonary fibrosis and chronic hypersensitivity pneumonitis. J Clin Invest. 1977 Jan;59(1):165-75. doi: 10.1172/JCI108615. 14. Shi C, Pamer EG. Monocyte recruitment during infection and inflammation. Nat Rev Immunol. 2011 Oct 10;11(11):762-74. doi: 10.1038/nri3070.  15. Shvedova AA, Kisin ER, Mercer R, Murray AR, Johnson VJ, Potapovich AI, Tyurina YY, Gorelik O, Arepalli S, Schwegler-Berry D, Hubbs AF, Antonini J, Evans DE, Ku BK, Ramsey D, Maynard A, Kagan VE, Castranova V, Baron P. Unusual inflammatory and fibrogenic pulmonary responses to single-walled carbon nanotubes in mice. Am J Physiol Lung Cell Mol Physiol. 2005 Nov;289(5):L698-708. doi: 10.1152/ajplung.00084.2005.   16. Smith RE, Strieter RM, Zhang K, Phan SH, Standiford TJ, Lukacs NW, Kunkel SL. A role for C-C chemokines in fibrotic lung disease. J Leukoc Biol. 1995 May;57(5):782-7. doi: 10.1002/jlb.57.5.782.  AOPWiki 2018-01-03T09:31:07

2023-05-12T17:03:00

Hyperinflammation

Tissue

Hyperinflammation can be defined as an uncontrolled and self-perpetuating inflammatory process that results in tissue damage. The state of hyperinflammation is also observed in cytokine storm syndrome, cytokine release syndrome, haemophagocytic lymphohistiocytosis, macrophage activation syndrome and in conditions of sepsis; however, it is not a frequent observation. For example, in COVID-19 infection, hyperinflammation plays a critical role in driving the disease severity. Although high viral titre initiates the cascade, the disease severity itself is dependent on the severity of the inflammatory state. Clinically, the hallmarks of hyperinflammation state include excessive serum levels of pro-inflammatory mediator C-reactive protein (<a href="http://bioregistry.io/genecards:CRP">CRP</a>), reduced or absence of lymphocytes (lymphopenia), high levels of ferritin and D-dimer, and increased lactate dehydrogenase. Higher neutrophil to lymphocyte ratio is another clinical marker. Some research studies have also associated high serum levels of<a href="https://bioregistry.io/genecards:IL6"> IL6</a> protein and accumulation of neutrophils to be causal and indicative of hyperinflammation. Other molecular markers associated with hyperinflammation include <a href="http://bioregistry.io/genecards:IL1B">IL1ꞵ</a> and <a href="http://bioregistry.io/genecards:TNFA">TNFɑ</a> and have together with IL6 and a multitude of other cytokines, chemokines and other proinflammatory factors been identified as potential therapeutic targets (<a href="https://doi.org/10.1371/journal.pone.0254374">Desvaux et al. 2021</a>). While the total serum levels of these markers is important, more critically, how fast the levels increase in serum is taken into consideration in judging the severity (<a href="http://doi.org/10.1101/2021.01.11.20248765">Bergamaschi et al. 2021</a>). The number of studies that have reported on the various markers of hyperinflammation is listed in Table-1.   Although the initiation and promotion of inflammation involves several cell types including epithelial cells, alveolar macrophages, type I and II pneumocytes and dendritic cells, the cell types that play role on inducing hyperinflammatory state may include macrophages, dendritic cells and neutrophils. Lack of neutrophil plays an important role in slowing the viral clearance and thus perpetuating the condition. Hyperferritinaemia is associated with high macrophage activation. Weight of evidence KE Hyperinflammation <table border="1" bordercolor="#ccc" cellpadding="5" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse"> <tbody> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:110px"> References </td> <td colspan="6" style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:396px"> Markers </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:127px"> Comments </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Research </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> Clinical </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Clinical </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Clinical </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Clinical </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Research </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> IL6, TNFa </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> CRP </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Lymphopenia </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Ferritin </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Lactate dehydrogenase </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Impaired IFN 1 type response </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Lazear H.M et al., Immunity. 2019;50:907–923.  </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased protein levels, NFkB pathway activation </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Reduced IFN stimulated genes </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Zhang B, Zhou X, Qiu Y, et al. Clinical characteristics of 82 death cases with COVID‐19. medRxiv. 2020. </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Present, also thrombocytopenia </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> IncreasedIncreased D-dimer </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> J Clin.  Invest. 2020;<a href="http://www.jci.org/130/5" style="color:blue; text-decoration:underline">130(5)</a>:2620-2629. <a href="https://doi.org/10.1172/JCI137244" style="color:blue; text-decoration:underline">https://doi.org/10.1172/JCI137244</a> </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Present </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Increased D-dimer </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Hadjadj et al., Science doi: <a href="http://dx.doi.org/10.1126/science.abc6027" style="color:blue; text-decoration:underline" target="_blank">10.1126/science.abc6027</a> </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increasedprotein </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Impaired </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Del Valle DM et al., Medrxiv : the Preprint Server for Health Sciences. 2020 May.  </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased protein </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Impaired </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Chen G ei al., J Clin Invest. 2020;130(5):2620-2629 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased IL-6 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Present </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Increased ferritin and D-dimer </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Marginal reduction </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Cheng L et al., Journal of Clinical Laboratory Analysis <a href="https://onlinelibrary.wiley.com/toc/10982825/2020/34/10" style="color:blue; text-decoration:underline" title="View Volume 34, Issue 10">Volume34, Issue10</a> October 2020 e23618 <a href="https://doi.org/10.1002/jcla.23618" style="color:blue; text-decoration:underline">https://doi.org/10.1002/jcla.23618</a>   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> IL-6 increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Increased ferritin levels </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Review – meta analysis of 52 studies that have data for ferritin levels. Showing severity can be predicted by ferritin levels. Connections with inflammation state. </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Manson JJ et al., <a href="https://www.sciencedirect.com/science/journal/26659913" style="color:blue; text-decoration:underline" title="Go to The Lancet Rheumatology on ScienceDirect">The Lancet Rheumatology</a> <a href="https://www.sciencedirect.com/science/journal/26659913/2/10" style="color:blue; text-decoration:underline" title="Go to table of contents for this volume/issue">Volume 2, Issue 10</a>, October 2020, Pages e594-e602   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px"> Increased Ferritin levels </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Logitudinal cohort study showing association of hyperinflammation with prognosis. Only CRP and Ferritin levels considered. </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Caricchio R, et al.,  Ann Rheum Dis doi:10.1136/ annrheumdis-2020-218323 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Recommended criteria for assessing hyperinflammation </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Mojtabavi, H., et al., Eur Cytokine Netw 31, 44–49 (2020). https://doi.org/10.1684/ecn.2020.0448 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Review- meta-analysis of available data. 11 studies included. </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Henry B et al.,  Acta Biomed. 2020;91(3):e2020008. doi:10.23750/abm.v91i3.10217 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px"> Lymphopenia and neutrophilia </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Meta-analysis study – 22 studies included. Correlation between lymphopenia and neutrophilia at admission with severity of disease. </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Human </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Jin J-M et al., Front. Public Health, 29 April 2020 | <a href="https://doi.org/10.3389/fpubh.2020.00152" style="color:blue; text-decoration:underline">https://doi.org/10.3389/fpubh.2020.00152</a> </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> Gender differences </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Ex vivo, human lung tissue </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Chu H, et al., Clin Infect Dis. 2020;71(6):1400-1409. </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Increased IL-6 </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Impaired IFN I, II, III signalling </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px">   </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:56px"> Mouse </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:110px"> Channappanavar et al.,  Cell Host Microbe 19 (2) (2016) 181–193, </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:56px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:60px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:94px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:57px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:69px">   </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:59px"> Reduced IFN I response </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:127px"> SARS-COV </td> </tr> </tbody> </table>

Hyperinflammation is observed in all age groups with high rates of infection and mortality observed in aged population. In children, although the rate of infection is low, hyperinflammatory syndrome is observed leading to long term disabilities. However, mortality rate in young children and adults below 40 years of age is less pronounced. Data in other developmental stages is lacking. Prevalence of hyperinflammation is same in men and women; however, studies have found that men develop more severe symptoms than women.

Not Specified Mixed High Moderate

1. Caricchio R, et al.,  Ann Rheum Dis doi:10.1136/ annrheumdis-2020-218323 2. Channappanavar et al.,  Cell Host Microbe 19 (2) (2016) 181–193, 3. Chen G ei al., J Clin Invest. 2020;130(5):2620-2629 4. Cheng L et al.,Journal of Clinical Laboratory Analysis<a href="https://onlinelibrary.wiley.com/toc/10982825/2020/34/10"> Volume34, Issue10</a>, October 2020 e23618, <a href="https://doi.org/10.1002/jcla.23618">https://doi.org/10.1002/jcla.23618</a> 5. Chu H, et al., Clin Infect Dis. 2020;71(6):1400-1409. 6. Del Valle DM et al., Medrxiv : the Preprint Server for Health Sciences. 2020 May. 7. J Clin.  Invest. 2020;<a href="http://www.jci.org/130/5">130(5)</a>:2620-2629. <a href="https://doi.org/10.1172/JCI137244">https://doi.org/10.1172/JCI137244</a> 8. Jin J-M et al., Front. Public Health, 29 April 2020 | <a href="https://doi.org/10.3389/fpubh.2020.00152">https://doi.org/10.3389/fpubh.2020.00152</a> 9. Hadjadj et al., Science doi: <a href="http://dx.doi.org/10.1126/science.abc6027">10.1126/science.abc6027</a> 10. Henry B et al.,  Acta Biomed. 2020;91(3):e2020008. doi:10.23750/abm.v91i3.10217 11. Lazear H.M et al., Immunity. 2019;50:907–923. 12. Manson JJ et al.,<a href="https://www.sciencedirect.com/science/journal/26659913"> The Lancet Rheumatology</a> <a href="https://www.sciencedirect.com/science/journal/26659913/2/10">Volume 2, Issue 10</a>, October 2020, Pages e594-e602 13. Mojtabavi, H., et al., Eur Cytokine Netw 31, 44–49 (2020). https://doi.org/10.1684/ecn.2020.0448 14. Zhang B, Zhou X, Qiu Y, et al. Clinical characteristics of 82 death cases with COVID‐19. medRxiv. 2020. AOPWiki 2021-04-20T02:44:25

2021-12-29T02:29:24

<upstream-id>0db7ffb8-739c-4bb7-9e6b-fc06aef35e1e</upstream-id> <downstream-id>ac09bd0d-b6ad-4f19-8747-d162397280c4</downstream-id> This KER deals with the evidence supporting the individual weight that the surface protein of SARS-CoV-2 spike needs to bind:ACE2, and of being cleaved in two different sites, for viral entry to occur. Viral entry is essential for initiating a cascade of events leading to COVID19.

To develop this KER, the authors have gone through the literature that came out especially since SARS-CoV-2 was detected in humans up to July 2022 to find supporting evidence linking: 1) ACE2 essentiality for viral infection 2) Mechanisms that support viral entry 2.1) involvement of host proteases 2.2) viral proteins that interact with host components to promote viral entry Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is initiated by virus binding to the ACE2 cell-surface receptor (Nature 579, 270–273, 2020 ; J. Virol. 94, e00127-20; Nature 588, 327–330). The SARS-CoV-2 surface spike (S) protein mediates the binding to the receptor and requires 2 cleavage steps for viral entry to occur, as follows. The spike protein contains 1273 aminoacids divided into two subunits, S1 and S2. The subunits are cleaved by furin-like enzymes, as spike of sars-cov-2 contains an insertion 680SPRRAR↓SV687 forming a cleavage motif RxxR for furin-like enzymes at the boundary of S1/S2 subunits. In addition, there is a second cleavage site 808PSKPSKR|SFIEDL822 just before the fusion peptide that needs to occur for viral entry. The S1 subunit contains a receptor-binding domain (RBD) encompassing the receptor-binding motif (RBM) that binds ACE2. The S2 contains a fusion peptide (FP), that penetrates into cell membranes and mediates fusion between the viral and host membranes to release viral proteins and genome. When TMPRSS2 is not available, spike it is hypothethised that the virus may use alternative proteases to get in the cells either by fusion with the plasma membrane or entry via endosomes and fusion with endocytic membranes at low pH, when proteases for priming become active, but evidence is less robust. 3) The initial delivery of SARS-CoV2 proteins and genome to the cells.

Binding of SARS-CoV-2 S protein to ACE2 receptors present in the brain (endothelial, neuronal and glial cells) : The highest ACE2 expression level in the brain was found in the pons and medulla oblongata in the human brainstem, containing the medullary respiratory centers, and this may in part explain the susceptibility of many COVID-19 patients to severe respiratory distress (Lukiw et al., 2020). High ACE2 receptor expression was also found in the amygdala, cerebral cortex and in the regions involved in cardiovascular function and central regulation of blood pressure including the sub-fornical organ, nucleus of the tractus solitarius, paraventricular nucleus, and rostral ventrolateral medulla (Gowrisankar and Clark 2016; Xia and Lazartigues 2010). The neurons and glial cells, like astrocytes and microglia also express ACE-2, thus highlighting the vulnerability of the nervous system to SARS-CoV-2 infection. Additionally, they also express transmembrane serine protease 2 (TMPRSS2) and furin, which facilitate virus entry into the host (Jakhmola et al. 2020). Once inside the brain, the virus can infect the neural cells, astrocytes, and microglia. These cells express ACE-2, thus initiating the viral budding cycle followed by neuronal damage and inflammation (Jakhmola et al. 2020). Specifically in the brain, ACE2 is expressed in endothelium and vascular smooth muscle cells (Hamming et al., 2004), as well as in neurons and glia (Gallagher et al., 2006; Matsushita et al., 2010; Gowrisankar and Clark, 2016; Xu et al., 2017; de Morais et al., 2018) (from Murta et al., 2020). Astrocytes are the main source of angiotensinogen and express ATR1 and MasR; neurons express ATR1, ACE2, and MasR, and microglia respond to ATR1 activation (Shi et al., 2014; de Morais et al., 2018). Binding of S protein to ACE2 receptors present in the intestines

<div> <table border="1" bordercolor="#ccc" cellpadding="5" cellspacing="0" class="table table-bordered table-fullwidth" style="border-collapse:collapse"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>MF Specification</th> <th>Effect(s) on the KER</th> <th>Reference(s)</th> </tr> </thead> <tbody> <tr> <td> Chemicals (weak evidence) </td> <td> PFAS (PFOS, PFOA, PFNA, PFHxS, and GenX) </td> <td> Short-term (10 days), high dose (20 mg/kg/day) exposure to PFOA leads to about 1.6 fold upregulation of the pulmonary mRNA level of Ace2 and to about 1.5 upregulation of the pulmonary mRNA level of Tmprss2 in CD1 mice. [1] Long-term (12 weeks) of an environmentally relevant PFAS mixture (PFOS, PFOA, PFNA, PFHxS, and GenX; each in 2 mg/l concentration) exposure leads to downregulation of pulmonary mRNA expression of Ace2 2.5-fold in C57BL/6 J male mice. A similar decreasing trend was observed in PFAS-exposed male mice for Tmprss2. [2] </td> <td> 1. doi: <a href="http://10.1016/j.toxrep.2021.11.014">10.1016/j.toxrep.2021.11.014</a> 2.  doi: <a href="http://10.1016/j.taap.2022.116284">10.1016/j.taap.2022.116284</a> </td> </tr> <tr> <td colspan="1" rowspan="2"> Sex (strong evidence) </td> <td>female sex (XX chromosomes)</td> <td> ACE2 localizes to the X sex chromosome and displays a sex-dependent expression profile with higher expression in female than in male tissues [1,2]. Estradiol inhibits TMPRSS2, needed to facilitate SARS-CoV-2 entry into the cell [3]. Estrogen therapy has been shown to mitigate endoplasmic reticulum stress induced by SARS-CoV-2 invasion through activation of cellular unfold protein response and regulation of inositol triphosphate (IP3) and phospholipase C [4]. Different studies have also illustrated that estradiol increases the expression of ADAM17, leading to high-circulating soluble ACE2 potentially neutralizing SARS-CoV-2 and preventing its binding to mACE2. [5] Thus, Estradiol might reduce SARS-CoV-2 infectivity through modulation of cellular ACE2/TMPRSS2/ADAM17 axis expression. </td> <td> 1. doi:<a href="http://10.1177/1933719115597760"> 10.1177/1933719115597760</a> 2. doi:<a href="http://10.1016/j.mce.2015.11.004"> 10.1016/j.mce.2015.11.004</a> 3. doi: <a href="http://10.1007/s11033-021-06390-1">10.1007/s11033-021-06390-1</a> 4.doi: <a href="http://10.1016/j.mehy.2020.110148">10.1016/j.mehy.2020.110148</a> 5. doi: <a href="http://10.2217/pgs-2020-0092">10.2217/pgs-2020-0092</a> </td> </tr> <tr> <td> Male sex (XY chromosomes) </td> <td> Androgen receptors (ARs) play a key role in increasing transcription of TMPRSS2. This may explain the predominance of males to COVID-19 fatality and severity. [6] </td> <td> 6. doi: <a href="http://10.1073/pnas.2021450118">10.1073/pnas.2021450118 </a> </td> </tr> <tr> <td>Age</td> <td>Young/old people</td> <td>ACE2 protein expression is increased with aging in several tissues [1], including lungs and particularly in patients requiring mechanical ventilation [2]. During aging, telomere dysfunction activates a DNA damage response leading to higher ACE2 expression. Thus, telomere shortening could contribute to make elderly more susceptible to SARS-CoV-2 infection [3].</td> <td> 1. doi: <a href="https://doi.org/10.1016/j.exger.2021.111507" style="color:blue; text-decoration:underline">10.1016/j.exger.2021.111507</a> 2. doi: <a href="https://doi.org/10.1371/journal.pone.0247060" style="color:blue; text-decoration:underline">10.1371/journal.pone.0247060</a> 3. doi: <a href="https://doi.org/10.15252/embr.202153658" style="color: blue; text-decoration-line: underline;">10.15252/embr.202153658</a> </td> </tr> <tr> <td rowspan="2">Lipids</td> <td>Atherogenic dyslipidemia</td> <td> Lipids, as important structural components of cellular and sub-cellular membranes, are crucial in the infection process [1]. Changes in intracellular cholesterol alter cell membrane composition, impacting structures such as lipid rafts, which accommodate many cell-surface receptors [2], including ACE2 and TMPRSS2 [3, 4]. In COVID-19. In an in vitro study, the depletion of membrane-bound cholesterol in ACE2-expressing cells led to a reduced infectivity of SARS-CoV [3]. In vitro, higher cellular cholesterol increased uptake of SARS-CoV-2 S protein; this effect was decreased with Methyl-beta-cyclodextrin, a compound which extracts cholesterol from cell membranes [5]. HDL scavenger receptor B type 1 (SR-B1), a receptor found in pulmonary and many other cells, could facilitate ACE2-dependent entry of SARS-CoV-2 [6]. </td> <td rowspan="2"> 1. doi: 10.1001/jama.2020.12839 2. doi: <a href="https://doi.org/10.3389/fcell.2020.618296" style="color:blue; text-decoration:underline">10.3389/fcell.2020.618296</a> 3. doi: <a href="https://doi.org/10.1016/j.bbrc.2008.02.023" style="color:blue; text-decoration:underline" target="_blank" title="Persistent link using digital object identifier">10.1016/j.bbrc.2008.02.023</a> 4. doi: <a href="https://doi.org/10.1096/fj.202000654R" style="color:blue; text-decoration:underline">10.1096/fj.202000654R</a> 5. doi: 10.1101/2020.05.09.086249 6.doi: 10.1038/s42255-020-00324-0 7.doi: <a href="https://doi.org/10.1016/j.bbalip.2020.158849" style="color:blue; text-decoration:underline" target="_blank" title="Persistent link using digital object identifier">10.1016/j.bbalip.2020.158849</a> 8.doi: <a href="https://doi.org/10.1016/j.obmed.2020.100283" style="color:blue; text-decoration:underline" target="_blank" title="Persistent link using digital object identifier">10.1016/j.obmed.2020.100283</a> 9. doi: <a href="https://doi.org/10.3390/ijms21103544" style="color:blue; text-decoration:underline">10.3390/ijms21103544</a> 10.doi: <a href="http://10.1101/2020.04.16.20068528">10.1101/2020.04.16.20068528</a> </td> </tr> <tr> <td>Obesity</td> <td> In COVID-19. ACE2 is highly expressed in adipose tissue, thus excess adiposity may drive more infection (8). Obese patients have more adipose tissue and therefore more ACE2-expressing cells [9]. SARS-CoV-2 dysregulates lipid metabolism in the host and the effect of such dysregulated lipogenesis on the regulation of ACE2, specifically in obesity [10]. Lung epithelial cells infected with SARS-CoV-2 showed upregulation of genes associated with lipid metabolism [11], including the SOC3 gene. A mouse model of diet-induced obesity showed higher Ace2 expression in the lungs, which negatively correlated with the expression sterol response element binding proteins 1 and 2 (SREBP) genes. Suppression of Srebp1 showed a significant increase in Ace2 expression in the lung. Lipids, including fatty acids, could interact directly with SARS-CoV-2 influencing spike configuration and modifying the affinity for ACE2 and thus its infectivity [12]. The dysregulated lipogenesis and the subsequently high ACE2 expression in obese patients might be one mechanism underlying the increased risk for severe complications [10]. </td> </tr> <tr> <td> Vitamin D (moderate evidence) </td> <td> Vitamin D deficiency   </td> <td> Vitamin D administration enhanced mRNA expression of VDR and ACE2 in a rat model of acute lung injury [1]. In particular, vitamin D upregulates the soluble ACE2 form [2]. Thus, low vitamin D status may impair the trapping protective mechanism of soluble ACE2 [3]. Furthermore, vitamin D deficiency has been shown to reduce the expression of antimicrobial peptides (-defensin, cathelicidin), which act against enveloped viruses [4,5]. In COVID-19. Decreased sACE2 and cellular viral defense might be some mechanisms explaining how low vitamin D modulate SARS-CoV-2 infectibility. </td> <td>   1. doi: <a href="http://10.1016/j.injury.2016.09.025">10.1016/j.injury.2016.09.025</a> 2. doi: <a href="http://10.1152/ajplung.00071.2009">10.1152/ajplung.00071.2009</a> 3. doi: <a href="http://10.3390/ijms22105251">10.3390/ijms22105251</a> 4. doi:<a href="http://10.1007/s11154-021-09679-5"> 10.1007/s11154-021-09679-5</a> 5. doi: <a href="http://10.1080/14787210.2021.1941871">10.1080/14787210.2021.1941871</a> </td> </tr> <tr> <td> Gut microbiota </td> <td> Gut dysbiosis (alteration of gut microbiota) </td> <td> <div> <div> <div> Some evidence shows that gut microbiota influences Ace2 expression in the gut. Colonic Ace2 expression decreased significantly upon microbial colonization in mice and rats [1,2]. Coprobacillus enrichment was associated with severe COVID-19 in patients [3] and was shown to upregulate colonic ACE2 in mice [4]. The abundance of Bacteroides species was associated with reduced ACE2 expression in the murine gut [4] and negatively correlated with fecal SARS-CoV-2 load [3,5]. Thus, gut dysbiosis might lead to higher levels of ACE2 in the gut, potentially increasing the ability of SARS-CoV-2 to enter enterocytes. </div> </div> </div> </td> <td> 1. doi: <a href="http://10.1080/19490976.2021.1984105">10.1080/19490976.2021.1984105</a> 2. doi: <a href="http://10.1161/HYPERTENSIONAHA.120.15360">10.1161/HYPERTENSIONAHA.120.15360</a> 3.doi: <a href="http://10.1053/j.gastro.2020.05.048">10.1053/j.gastro.2020.05.048</a> 4.doi: <a href="http://10.1016/j.cell.2017.01.022">10.1016/j.cell.2017.01.022</a> 5. doi: <a href="http://10.1016/j.tifs.2020.12.009">10.1016/j.tifs.2020.12.009</a> </td> </tr> <tr> <td>Genetic factors</td> <td> </td> <td> Polymorphisms inducing amino acid residue changes of ACE2 in the binding interface would influence affinity for the viral S protein. Evidence exists that K353 and K31 in hACE2, the main hotspots that form hydrogen bonds with the main chain of N501 and Q493 in receptor-binding motif respectively, play a role in tightly binding to the S protein of SARS-CoV-2 [1]. Around the twenty natural ACE2 variants, three alleles of 17 variants were found to affect the attachment stability [2]. Thus, the ACE2 variants modulating the interaction between the virus and the host have been reported to be rare, consistently with the overall low appearance of ACE2 polymorphisms. In this context, it is key to approach both the ACE2 genotypes and the clinical descriptions of the phenotypes in a population-wide manner, in order to better understand how ACE2 variations are relevant in the susceptibility for SARS-CoV-2 infection [3]. In addition, since ACE2 is X-linked, the rare variants that enhance SARS-CoV-2 binding are expected to increase susceptibility to COVID-19 in males [4]. On the other hand, the X-chromosome inactivation of the female causes a “mosaic pattern”, which might be an advantage for females in terms of reduced viral binding [5]. TMPRSS2 single-nucleotide polymorphisms (SNPs) were associated with a frequent “European haplotype” [6], which not observed in Asians, is suggested to upregulate TMPRSS2 gene expression in an androgen-specific way. Thus, there is a need for in vitro validation studies to assess the involvements of population-specific SNPs of both ACE2 and TMPRSS2 in susceptibility toward SARS-CoV-2 infection. The occurrence of a pandemic is related to the genetics of the infecting agent. In the case of SARS-CoV-2, through genomic surveillance it is possible to track the spread of SARS-CoV-2 lineages and variants, and to monitor changes to its genetic code that can influence viral entry and production. Consequently, genomic surveillance is crucial to understand how mutations occurring on SARS-CoV-2 genome influence and drive the pandemic [7]. For example, a recent study [8] highlights that through genomic surveillance it is possible to trace co-infections by distinct SARS-CoV-2 genotypes, which are expected to have a different impact on factors modulating COVID-19. Genomic surveillance of SARS-CoV-2 is able to reveal tremendous genomic diversity [9], and coupled with language models and machine learning approaches, contributes to predicting the impact of mutations (such as those occurring in the spike protein), and thus can better address challenging aspects, like an estimation of the efficacy of therapeutic treatments [10].   </td> <td> [1] doi: 10.1080/07391102.2020.1796809 [2] doi: 10.1002/jmv.26126 [3] doi: 10.1038/s42003-021-02030-3 [4] doi: 10.1101/2020.04.05.026633 [5] doi: 10.3390/ijms21103474 [6] doi: 10.18632/aging.103415 [7] doi: 10.1038/s41588-022-01033-y [8] doi: 10.1038/s41598-022-13113-4 [9] doi:10.1371/journal.pone.0262573 [10] doi: 10.3389/fgene.2022.858252 </td> </tr> <tr> <td>Therapeutic intervention against COVID-19</td> <td> Casirivimab, Imdevimab and Sotrivimab</td> <td> Are monoclonal antibodies designed to recognize and attach to two different sites of the Receptor-Binding Domain (RBD) of the S protein of SARS-CoV-2, blocking the virus to enter cells [1,2,3].</td> <td> 1) 10.1056/NEJMoa2035002   2) EMA Starts Rolling Review of REGN-COV2 Antibody Combination (Casirivimab / Imdevimab). EMA 2021. Available online: https://www.ema.europa.eu/en/news/ema-starts-rolling-review-regn-cov2-antibody-combination-casirivimab-imdevimab (accessed on 12 May 2022)   3) EMA Starts Rolling Review of Sotrovimab (VIR-7831) for COVID-19. EMA 2021. Available online: https://www.ema.europa.eu/en/news/ema-starts-rolling-review-sotrovimab-vir-7831-covid-19 (accessed on 12 May 2022)</td> </tr> <tr> <td> </td> <td>Heparin</td> <td> Interacts directly with viral particles and has been shown to bind to the SARS-CoV-2 S1 Spike RBD, causing significant protein architecture alteration, impacting infectivity [1,2].</td> <td> 1) 10.3389/fmed.2021.615333   2) 10.1055/s-0040-1721319 </td> </tr> <tr> <td>Air pollution</td> <td> </td> <td> Air pollution induces Increased expression of ACE2 which may result in increased viral entry and coronavirus production.  Increased ACE2 expression has been reported in the respiratory system in response to air pollution exposure (1-4). Increased expression may affect susceptibility to SARS-CoV-2 infection. Similarly, some constituents of air pollution (PM, ozone) have been reported to increase the expression of TMPRSS2 (3, 5-6).   </td> <td> 1) https://doi.org/10.1186/s12989-015-0094-4 2) 10.1016/j.burns.2015.04.010 3) 10.1016/j.envres.2021.110722 4) 10.3390/ijerph17155573 5) 10.1186/s12989-021-00404-3 6) https://doi.org/10.1038/s41598-022-04906-8 </td> </tr> <tr> <td>Pre-existing heart failure</td> <td> </td> <td> ACE2 mRNA and protein levels, as well as enzymatic activity, were shown to be upregulated in explanted hearts from patients with end-stage HF, as well as in the HF rat model [1-3]. Myocytes, fibroblasts, vascular smooth muscle cells, pericytes [4] and endothelial cells of the coronaries [5] express ACE2, while myocytes in patients suffering from heart disease exhibit higher ACE2 expression [6]. Pericytes - the mural cells lining microvasculature, interacting with endothelial cells notably to maintain microvascular stability - exhibited the strongest ACE2 expression in HF patients [7], rendering these cells involved in the coronary vasculature of the myocardium, more susceptible to infection. Furthermore, SARS-CoV-2 infects and replicates in pericytes, and a decrease in their numbers follows [8]. Patients with pre-existing HF showed increased ACE2 levels in myocytes and pericytes, having thereby higher risk of heart injury [7, 9]. In addition, sACE2 levels are higher in HF patients [10, 11] and sACE2 activity is increased in HF [12]. In contrast to a protective role of sACE2, it has been proposed that viral binding to circulating sACE2 forms SARS-CoV-2/sACE2 complexes, which might mediate infection of cells in distal tissues [13]; hence, pre-existing HF might disseminate SARS-CoV-2 infection. Interestingly, the increase in sACE2 activity is associated with HF with reduced ejection fraction (HFrEF) but not with HF with preserved ejection fraction (HFpEF), suggesting (i) a rather complex role of HF in regulating ACE2-mediated infection by SARS-CoV-2 [10] and (ii) the potential of sACE2 activity to be used as a biomarker to distinguish between the two HF types. Lastly, it is noteworthy that Khoury et al. provided evidence in a different direction, by showing that ADAM17 and TMPRSS2 [14] expression levels are downregulated in a HF rat model, thus potentially conferring a protective role against infection by SARS-CoV-2 in HF [3]. </td> <td> 1: <a href="https://doi.org/10.1186/1741-7015-2-19" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1186/1741-7015-2-19</a>   2: <a href="https://doi.org/10.1161/01.CIR.0000094734.67990.99" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1161/01.CIR.0000094734.67990.99</a>       3: <a href="https://onlinelibrary.wiley.com/doi/10.1111/jcmm.16310#:~:text=https%3A//doi.org/10.1111/jcmm.16310" style="color:#0563c1; text-decoration:underline">https://onlinelibrary.wiley.com/doi/10.1111/jcmm.16310#:~:text=https%3A//doi.org/10.1111/jcmm.16310</a> 4: <a href="https://doi.org/10.1161/CIRCULATIONAHA.120.047911" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1161/CIRCULATIONAHA.120.047911</a> 5: <a href="https://doi.org/10.1152/ajpheart.00331.2008" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1152/ajpheart.00331.2008</a> 6: <a href="https://doi.org/10.1093/eurheartj/ehaa311" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1093/eurheartj/ehaa311</a> 7: <a href="https://doi.org/10.1093/cvr/cvaa078" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1093/cvr/cvaa078</a> 8: <a href="https://doi.org/10.21203/rs.3.rs-105963/v1" style="color:#0563c1; text-decoration:underline">https://doi.org/10.21203/rs.3.rs-105963/v1</a> 9: <a href="https://doi.org/10.1016/j.jacbts.2020.06.007" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1016/j.jacbts.2020.06.007</a> 10: <a href="https://doi.org/10.1177/1470320316668435" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1177/1470320316668435</a> 11: <a href="https://doi.org/10.1093/eurheartj/ehaa697" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1093/eurheartj/ehaa697</a> 12: <a href="https://doi.org/10.1002/jmv.27144" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1002/jmv.27144</a> 13: <a href="https://doi.org/10.1002/rmv.2213" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1002/rmv.2213</a> 14: <a href="https://doi.org/10.1016/j.cell.2020.02.052" style="color:#0563c1; text-decoration:underline">https://doi.org/10.1016/j.cell.2020.02.052</a>     </td> </tr> <tr> <td>Diet</td> <td>Chemicals in foods affect ACE3 expression</td> <td> <ul> <li>Geranium and lemon oils were found to reduce in vitro ACE2 activity and expression, as well as ACE2 and TMPRSS2 mRNA levels [207].</li> <li>Several molecular modelling and docking studies indicate the potential for compounds found in garlic [208], turmeric (curcumin) [209], thyme and oregano (carvacrol) [210], green tea [211] and other plant foods (quercetin) [212] to inhibit binding of SARS-CoV-2.</li> <li>Pelargonidin, found in red and black berries, was shown to dose-dependently block SARS-CoV-2 binding to ACE2, reduce SARS-CoV-2 replication in vitro and reduce ACE2 expression [213].</li> <li>Quercetin and related compounds inhibit recombinant human ACE2 activity [214] at physiologically relevant concentrations in vitro.</li> <li>In a human crossover study, 30-day supplementation with resveratrol decreased ACE2 in adipose tissue [216], potentially attenuating an increased risk for infection and viral replication in humans with obesity. In vitro, resveratrol inhibited the replication of SARS-CoV-2 [217].</li> </ul> </td> <td> <ul> <li>207: <a href="http://doi.org/10.3390/plants9060770">http://doi.org/10.3390/plants9060770</a> </li> <li>208: <a href="http://doi.org/10.1021/acsomega.0c00772">http://doi.org/10.1021/acsomega.0c00772</a></li> <li>209: <a href="http://doi.org/10.1007/s13337-020-00598-8">http://doi.org/10.1007/s13337-020-00598-8</a></li> <li>210:<a href="http:// http://doi.org/10.1080/07391102.2020.1772112"> http://doi.org/10.1080/07391102.2020.1772112</a></li> <li>211: <a href="http://doi.org/10.1080/07391102.2020.1779818">http://doi.org/10.1080/07391102.2020.1779818</a></li> <li>212: <a href="http://doi.org/10.18632/aging.103001">http://doi.org/10.18632/aging.103001</a></li> <li>213: <a href="http://doi.org/10.1016/j.bcp.2021.114564">http://doi.org/10.1016/j.bcp.2021.114564</a></li> <li>214: <a href="http://doi.org/10.1021/acs.jafc.0c05064">http://doi.org/10.1021/acs.jafc.0c05064</a></li> <li>216: <a href="http://doi.org/10.1080/21623945.2021.1965315">http://doi.org/10.1080/21623945.2021.1965315</a></li> <li>217: <a href="http://doi.org/10.1002/ptr.6916">http://doi.org/10.1002/ptr.6916</a></li> </ul> </td> </tr> </tbody> </table> </div>

High Unspecific

High

All life stages

High

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9a87f30> AOPWiki 2020-03-02T03:19:15

2023-02-07T23:24:14

<upstream-id>4a7e7a88-27e9-480b-8c6d-a29c4494e85e</upstream-id> <downstream-id>da4116ea-e1e0-404d-bf1e-dd8584dd491e</downstream-id>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9a9d830> AOPWiki 2022-09-01T03:51:09

2022-09-01T03:51:09

<upstream-id>ac09bd0d-b6ad-4f19-8747-d162397280c4</upstream-id> <downstream-id>45eb9feb-ceb0-4174-81c4-bd05e95cb682</downstream-id> Upon entry of a virus into the host cell (KE1738), the virus is unpackaged from the structural nucleocapsid (N), envelope (E), and membrane (M) proteins. The viral RNA is detected by Pattern Recognition Receptor (PRR) proteins including RIG-I and MDA5 but the M proteins can interact with these PRRs directly, and block this initial host reaction (Fu et al., 2021). The viral genomic RNA can then be translated directly at the host ribosomes. The viral proteins are processed through cleavage by viral protease enzymes. This releases a repertoire of non-structural proteins (NSPs) and accessory open reading frame (ORF) proteins that has evolved, for example in the SARS-CoV-2 virus, to bind and block the proteins in the interferon I (IFN-I) antiviral cascade (KE1901). The normal function of the host’s IFN-I response to other viruses is the expression of IFN-I which in turn stimulates the expression of many interferon-stimulated gene (ISG) proteins with antiviral functions. The SARS-CoV-2 antagonism of the IFN-I pathway delays or curtails the expression of IFN-I and ISG proteins.

The COVID-19 pandemic began in early 2020, after the cause of a respiratory illness first seen in Wuhan, China in December 2019 was identified as a severe acute respiratory syndrome-related coronavirus and the viral genome was sequenced in January 2020 (Zhu et al., February 2020; Gorbalenya et al., March 2020). Early literature characterizing the transcripts and proteins from SARS-CoV-2 started to become available soon after (e.g., Dongwan Kim et al., April 2020). Of two other papers published in April 2020, one indicated the angiotensin converting enzyme 2 (ACE2) cell entry receptor and the TMPRSS2 enzyme priming mechanism for the virus to enter the host cell (Hoffmann et al.), and another provided a map of protein-protein interactions of the host with the translated viral genome proteins after entry (Gordon et al.). These sources established a course that led to literature indicating the specific effects of protein-protein interactions between viral and host proteins. Other sources made comparisons with data from previous studies of the SARS and MERS coronaviruses (Channappanavar et al., 2019). Many of the host proteins engaged by the viral non-structural proteins (NSPs) and accessory open reading frame (ORF) proteins were part of the IFN-I antiviral response pathway (Xia et al., 2020; Xia and Shi, 2020). Therefore, IFN-I response antagonism was considered a key event and literature search strings targeted the specific NSPs and ORFs with IFN-I pathway proteins (e.g., SARS-CoV-2 NSP3 + interferon regulatory factor 3 [IRF3]). Literature searches utilized the large established digital libraries including NCBI, Google and Google Scholar. Database resources for 3D molecular structures and viral-host protein binding information include Aquaria-COVID Structural Models of COVID-19 Proteins at <a href="https://aquaria.ws/covid#Map" style="color:blue; text-decoration:underline">https://aquaria.ws/covid#Map</a>, the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB) at <a href="https://www.rcsb.org/" style="color:blue; text-decoration:underline">https://www.rcsb.org/</a> and Alphafold Protein Structure Database at <a href="https://alphafold.ebi.ac.uk/" style="color:blue; text-decoration:underline">https://alphafold.ebi.ac.uk/</a>. General IFN and innate immune antiviral response literature was reviewed, and primary literature cited in review articles was also investigated.

Empirical evidence supporting this relationship is described below.

This relationship is concerned with how entry of the virus into the host cell and subsequent release and transcription of viral proteins affects the downstream innate immune response. In particular, literature suggests the main pathway antagonized is the expression of type I interferons (IFN-I), consisting primarily of IFNα and IFNβ, and IFN-I stimulated genes (ISGs) (Banerjee et al., 2020; Blanco-Melo et al., 2020; Cheemarla et al., 2021; Xia et al., 2020; Sharif-Askari et al., 2022). Although there are few studies with evidence for cell entry leading directly to reduced IFN expression (Xia et al., 2020; Hatton et al. 2021), several studies demonstrate individual viral protein interactions with and blocking of host proteins in the IFN-I pathway or ISG proteins (Schubert et al. 2020; Thoms et al. 2020; Rui et al. 2021; Shin et al. 2020; Liu et al. 2021; Mostaqil et al., 2021; Xia et al. 2020; Quarleri and Delpino, 2021; Xia and Shi, 2020; Miorin et al. 2020; Kato et al. 2020; Fu et al. 2020; Chen et al. 2020; Han et al. 2020; Jiang et al. 2020; Wu et al. 2021; Gordon et al 2020; see below and also key event 1901). These studies provide the biological rationale that SARS-CoV-2 entry into the host cell causes interactions between viral proteins and known protein components of the host IFN-I antiviral response, resulting in inhibition of IFN-I and ISG expression.

Empirical evidence in support of temporal concordance comes from patient reports, showing that interferon expression is delayed by SARS-CoV-2 compared to other viruses like influenza, which is also described as an untuned or imbalanced response between interferons being initially low in moderate to severe cases (Banco-Melo et al. 2020; Galani et al., 2021; Hadjadj et al., 2020; Hatton et al., 2021; Rouchka et al., 2021). This indicates that SARS-CoV-2 stressors are suppressing the interferon response and highlights an important point regarding the difference between SARS-CoV-2 and other viruses in the stressors produced upon viral entry. Other viruses, as well as non-viral compounds used in research (e.g., polyinosinic:polycytidylic acid or poly[I:C]) enter the cell and stimulate the normal functional operation of the immune response, while SARS-CoV-2 blocks the response at multiple points, acting as a true prototypical stressor. Hatton et al. (2021) used human nasal epithelium differentiated at the air-liquid interface (ALI) cultures (organoids) with several cell types. Secretory cells were the cell type with the highest expression of viral transcripts, with ciliated and deuterosomal cells also showing expression. The SARS-CoV-2-infected secretory and ciliated cells also had many downregulated ISGs. Compared to SARS-CoV-2, influenza A virus induced significantly higher levels of IFN-I (IFNβ) and IFN-III (IFNλ1) at 6 and 24 hours post infection, as well as ISGs Ubiquitin specific peptidase 18 (USP18), radical s-adenosyl methionine domain containing 2 (RSAD2), and ubiquitin-like protein ISG15 at 24 hours post infection (Hatton et al., 2021). Individual stressors from the virus were investigated by Xia et al. (2020) using an IFN-β promoter luciferase assay. HEK293T cells were co-transfected with luciferase reporter plasmids, the specific viral protein expressing plasmid, and stimulator plasmid RIG-I (2CARD). Of the viral proteins tested (NSPs 1, 2, 4-16, S, N, E, M, and ORFs 3a, 3b, 6, 7a, 7b, 8, and 10), four proteins (NSPs 1, 6, and 13 and ORF6) significantly reduced INF-β induction compared to the control (empty vector). A similarly conducted ISRE-promoter luciferase assay showed significant inhibition of the IFN-I signaling pathway (normally resulting in induction of ISGs) by NSPs 1, 6, 7, 13 and 14, ORFs 3a, 6, 7a and 7b, and M protein (Xia et al., 2020). See Xia et al. (2020) and Xia and Shi (2020) for schematics depicting the actions of the SARS-CoV-2 proteins on the protein components of the IFN-I antiviral response pathway. SARS-CoV-2 stressor proteins and the IFN-I pathway responses were investigated individually in the following studies: <table border="1" class="Table" style="border:solid windowtext 1px"> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> Viral protein stressor </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> Host protein </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> Crystal Structure PDB </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> KER findings: Binding, Stressor/IFN-I or ISG expression </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> N (nucleocapsid) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> RIG-I: Retinoic acid-inducible gene I </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> Not available (NA) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Significant reductions in IFNβ mRNA induction were seen when SARS-CoV-2 N protein was co-transfected into A549 cells with RIG-I, MAVS, or TBK1, and similar transfections resulted in IFNβ promoter activity reduction in poly(I:C)-stimulated HEK293T cells (Chen et al., 2020). </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP3 Papain-like protease (Plpro) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> MDA5: Melanoma differentiation-associated gene 5 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Sun et al. (2022) determined that SARS-CoV-2 and avian coronavirus infectious bronchitis virus (IBV) NSP3 PLpro N-terminal domain directly interacts with MDA5 to inhibit IFNβ expression when co-transfected in HEK293T cells. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> M (membrane) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> MAVS: Mitochondiral antiviral signaling protein </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Fu et al. (2020) found M interaction with MAVS (as determined by coimmunoprecipitation and in vitro pull-down assay) interferes with recruitment of downstream pathway proteins TRAF, TBK1, and IRF3, inhibiting IFNβ1 promoter, IFN-stimulated response element (ISRE), and NFκB promoter activity in a dose-dependent manner. The M protein inhibited the transcription of ISGs (ISG56, CXCL10, and TNF) based on mRNA levels, and inhibited IFNβ and TNFα secretion based on measures of these proteins in HEK293 cell culture. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP3 Papain-like protease (Plpro) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> ISG15: Ubiquitin-like interferon stimulated gene 15 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/6YVA" style="color:blue; text-decoration:underline">6YVA</a> </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Shin et al. (2020) generated a crystal structure and found that SARS-CoV-2 Plpro preferentially cleaves ISG15. ISG15 functions in antiviral immunity to directly inhibit viral replication (Perng and Lenschow, 2018). </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> ORF9b </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> TOMM70: Translocase of outer mitochondrial membrane </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/7KDT" style="color:blue; text-decoration:underline">7KDT</a> </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Gordon et al. (2020) showed interaction between TOMM70 and ORF9b via affinity purification-mass spectrometry (AP-MS). TOMM70-ORF9b interaction is supported by several studies (Gao et al., 2021; Brandherm et al., 2021; Ayinde et al., 2022). Jiang et al. (2020) used a dual luciferase reporter assay to show human IFN-β promoter activity was significantly reduced in the presence SARS-CoV-2 Orf9b compared to controls. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> ORF6 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> Nup98-RAE1: Nuclear pore complex 98-ribonucleic acid export 1 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/7VPG" style="color:blue; text-decoration:underline">7VPG</a>, <a href="https://www.rcsb.org/structure/7VPH" style="color:blue; text-decoration:underline">7VPH</a>  </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:318px"> Gordon et al. (2020) showed interaction between ORF6 and the host Nup98-RAE1 protein pair via AP-MS. The interaction was confirmed by Miorin et al., 2020 and Li et al., 2021 (see crystal structures). Miorin et al. (2020) also demonstrate that upon treatment with recombinant IFN-I in HEK293T cells, Nup98 binding to SARS-CoV-2 Orf6 blocks translocation of STAT1 into the nucleus, resulting in suppression of ISRE-dependent gene expression. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> ORF6 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> KPNA2: Karyopherin subunit alpha 1 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Using co-immunoprecipitation, Xia et al. (2020) showed that ORF6 selectively bound with KPNA2. Expression of ORF6 blocked nuclear translocation of IRF3, suggesting that ORF6 inhibited IFN-β production by binding to KPNA2 to block IRF3 nuclear translocation. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> N (nucleocapsid) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> G3BP1/2: GTPase-activating protein SH3 domain–binding protein </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/7SUO" style="color:blue; text-decoration:underline">7SUO</a> </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Biswal et al. (2022) solved the X-ray crystal structure of the G3BP1 N-terminal nuclear transport factor 2-like domain bound to the first intrinsically disordered region of SARS-CoV-2 N protein. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> ORF9b </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> NEMO: Nuclear factor kappa-B (NF-κB) essential modulator </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> The interaction of the N-terminus of ORF9b with NEMO upon viral infection interrupts its K63-linked polyubiquitination, thereby inhibiting viral-RNA-induced IFNβ1 activation in HEK293T cells in an ORF9b-dose-dependent manner (Wu et al., 2021) </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP5 (3CLpro) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> NEMO </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/7T2U" style="color:blue; text-decoration:underline">7T2U</a> </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Hameedi et al. (2022) solved the X-ray crystal structure of 3CLpro bound to NEMO and characterized 3CLpro cleavage of NEMO. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP1 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> POLA1: DNA polymerase alpha 1, catalytic subunit 40S ribosomal subunit </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> <a href="https://www.rcsb.org/structure/7OPL" style="color:blue; text-decoration:underline">7OPL</a>   <a href="https://www.rcsb.org/structure/6ZOJ" style="color:blue; text-decoration:underline">6ZOJ</a>, <a href="https://www.rcsb.org/structure/6zok" style="color:blue; text-decoration:underline">6ZOK</a>, <a href="https://www.rcsb.org/structure/6zol" style="color:blue; text-decoration:underline">6ZOL</a> </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Kilkenny et al., 2021 demonstrate that components of the host DNA polymerase α (Pol α)–primase complex or primosome directly bind with SARS-CoV-2 NSP1. They also provide a cryo-electron microscopy structure of NSP1 bound to the primosome. Schubert et al. (2020) provide cryo-EM structures of NSP1 bound to the 40S ribosome subunit, inhibiting translation of host proteins. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP6, NSP13 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> TBK1: TANK-binding kinase 1 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Sui et al. (2022) show that NSP13 recruits TBK1 to an aggregation of ubiquitinated proteins (p62) for autophagic degradation, resulting in inhibition of IFNβ production, and that NSP13 impaired IRF3 luciferase reporter activity induced by TBK1 in a dose-dependent manner. Xia et al. (2020) co-transfected HEK293T cells with plasmids containing TBK1 and either nsp6 or nsp13. Only NSP13 inhibited TBK1 phosphorylation, and did so in a dose-dependent manner, but both NSP6 and NSP13 suppressed IRF3 phosphorylation. Both NSP6 and NSP13 bind TBK1, as shown by co-immunoprecipitation. NSP6 binds to TBK1 without affecting TBK1 phosphorylation but this decreases IRF3 phosphorylation, while NSP13/TBK1 binding inhibits TBK1 phosphorylation. In both cases, IFN-β production is reduced (Xia et al., 2020). </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP5 (3CLpro), ORF3a </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> STING: Stimulator of interferon genes </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Rui et al. (2021) SARS-CoV-2 ORF3a and 3CLpro inhibited IFNβ promoter activity through cyclic GMP-AMP synthase (cGAS)-STING pathways, specifically through interaction with STING, as indicated by co-immunoprecipitation. 3CLpro also bound to STING and specifically inhibited K63-ubiquitin-mediated modification of STING, which is required for signaling and downstream expression of IFN-I. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> NSP3 Papain-like protease (Plpro) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> IRF3: Interferon regulatory factor 3 </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Mostaquil et al. (2020) showed with a fluorescent-based cleavage assay that NSP3 (Plpro) cleaves IRF-3, and thereby reduces IRF-3 available for induction of IFN-I expression. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:103px"> N (nucleocapsid) </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:94px"> STAT1/STAT2: Signal transducer and activator of transcription </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:60px"> NA </td> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:318px"> Mu et al. (2020) used Sendai virus (SeV)-induced ISRE-promoter activation via the luciferase reporter assay to determine that SARS-CoV-2 N protein can inhibit the phosphorylation of STAT1 and STAT2 resulting in decrease in ISG production. They also showed through co-immunoprecipitation that N interacts with both STAT1 and STAT2, and that N inhibits STAT1/2 phosphorylation by blocking interactions with kinases including JAK1. </td> </tr> </tbody> </table>

There are uncertainties based on differing disease outcomes, especially associated with timing of IFN increase or suppression under different cell culture circumstances and in different people infected with SARS-CoV-2. Effectiveness of IFN treatment is still uncertain due to some studies evaluating IFN along with other drugs (Sodeifian et al., 2021). Interferon-induced transmembrane proteins (IFITMs 1, 2 and 3) are ISGs that have been implicated in SARS-CoV-2 entry as well as antiviral activity (Prelli Bozzo et al., 2021), in addition to the fact that the SARS-CoV-2 entry receptor ACE2 is an IFN-I stimulated gene (Ziegler et al., 2020). These are some of the paradoxes that confound transcriptomic studies that determine up- or downregulation of IFNs and ISGs in response to infection, and responses are highly dependent on the time points sampled. Efforts to address uncertainties around when and under what circumstances IFNs and ISGs either promote or supress the virus are ongoing.

<div>Genetic mutations. Autoimmunity to IFNs has been found in some COVID-19 patients. These individuals produce autoantibodies that attack IFN (Bastard et al., 2021 and 2022), which may be associated with human leukocyte antigen (HLA) gene mutations (Ku et al., 2016; Chi et al., 2013). Zhang et al., 2020 note inborn errors (genetic mutations) in IFN-I immunity that result in severe COVID-19, but some are also genes for proteins involved in the initial response (TBK1, IRF3, NEMO, IFNAR1, IFNAR2, STAT1, and STAT2). Zhang et al. (2022) also found similar mutations (STAT2 and IFNAR1) in children with COVID-19 pneumonia.</div> Pollutant exposures. Most studies have been conducted with the endpoints to determine whether prior or concurrent exposure to chemical or air particulate pollutants exacerbates COVID-19 symptoms resulting in more severe disease or higher mortality rates. This would point to effects downstream of viral replication usually relating to antibody suppression, inflammation and organ/tissue damage. Fewer studies can be found that study pollutant effects on susceptibility to infection, which are relevant to this KER, specifically cell entry or interferon response antagonism. Marques et al., (2022) reviews associations between COVID-19 and outdoor air pollutants including PM2.5, PM10, O3, NO2, SO2 and CO, reporting that environmental air pollution increases both disease incidence and severity. Physiological mechanism is not investigated for most studies. One relevant study estimated significant odds ratios for increased risk of severe COVID-19 and gene transcriptional analysis showing downregulation of genes associated with the IFN-I pathway in patients with high short-term NO2 exposure (Feng et al., 2023). Per- and polyfluoroalkyl substances (PFAS) are a large group of contaminants of current concern, due to their potential for toxicity, ubiquitous presence in the environment and consumer products, as well as their resistance to degradation. Although most community exposure to PFAS is through diet and drinking water, airborne and dermal exposures may also occur, especially in the workplace (CDC/NIOSH 2022). Statistical links between high measured serum or urine concentrations of specific PFAS compounds or mixtures and higher rates of COVID-19-positive cases have been found. One study in Sweden calculated a sex- and age-Standardized Incidence Ratio (SIR) for the town of Ronneby that had highly PFAS-contaminated drinking water compared to a demographically matched town with background PFAS levels (Nielsen et al. 2021). Serum PFAS concentrations were previously measured in 2014-15 for 3507 participants (Xu et al. 2021), after the Ronneby drinking water contamination issue was identified in 2013. Ronneby residents had higher infection risk, with a SIR of 1.19 [95% CI: 1.12-1.27]. Ji et al. (2021) measured urine and serum in a smaller study in China with 160 subjects. They reported statistically significant odds ratios for infection of 1.94 [95% CI: 1.39–2.96] for perfluorooctane sulfonate (PFOS), 2.73 [1.71–4.55] for perfluorooctanoic acid (PFOA), and 2.82 [1.97–3.51] for Σ (12) PFASs, after controlling for age, sex, body mass index (BMI), comorbidities, and urine albumin-to-creatinine ratio (UACR). These odds of infection were clearly higher even though the PFAS-exposed subjects in China had serum concentrations lower than in the Ronneby study participants. Additionally, the risk of infection was similar for residents in a significantly more contaminated section of Ronneby compared with a less contaminated section, so there was no dose-response relationship (Nielsen et al. 2021). However, these associations warrant more study to determine causality. Ji et al. (2021) also found elevated PFAS to be associated with altered mitochondrial metabolism. A potential consideration is that inhibition of mitochondrial oxidative phosphorylation impairs MAVS-mediated induction of IFNs, indicating the coordination between antiviral response and mitochondrial metabolism (Yoshizumi et al., 2017). Another study proposes modulation of ACE2 and TMPRSS2 expression in the lungs of PFAS-exposed mice may play a role in PFAS-associated immune suppression (Yang et al. 2022). Houck et al., (2022) report testing 147 PFAS substances in screening platforms including the BioMAP® Diversity PLUS panel, which is used to model complex tissue adverse effects of pharmaceuticals and environmental chemicals. Toxicity Signatures within the BioMAP profile indicated the Skin Rash (MEK-Associated) Signature for PFOA, with IFNα/β as one of the target mechanisms. While not specific to COVID-19, one study found that exposure to aryl hydrocarbons and dioxins may block IFN production (Franchini and Lawrence, 2018).

The current quantitative understanding of this relationship is described below.

A specific titer of virus can be used for infection, but as shown by Hatton et al. (2021), different cell types may express different levels of the actual stressors (viral protein transcripts). Because there are many stressors from each viral particle, which might be differentially expressed and also differentially inhibit each of their targets, a consistent whole viral entry dose leading to IFN-I or ISG response is difficult to measure. However, Chen et al. (2020), Xia et al. (2020), Fu et al. (2021), Wu et al. (2021) and Sui et al., (2022) all showed that individual protein stressor components of SARS-CoV-2 reduced IFN-I expression in a dose-dependent manner.

The viral entry MIE and early KEs coincide with the time from exposure to symptoms, within which are the latent period, or time from exposure to infectiousness, and the serial interval, or the time interval between the onset of symptoms in the primary (infector) and secondary case (infectee). Viral entry leading to antagonism of the IFN response occurs during the latent period of the disease prior to symptom onset.  Latent period calculation is based on serial interval and median pre-symptomatic infectious period: Serial interval 5.2 days (Rai et al. 2021) – 2.5 days pre-symptom infectious period (Byrne et al. 2020) equals approximately 2.7 days. The latent period was longer in asymptomatic cases (4-9 days); pre-symptomatic transmission occurs from about 3 days after exposure to symptom onset at about day 5-7, viral load peaks from about day 5-7 to day 9-11, and the host can remain infectious to symptom clearance or death (Byrne et al. 2020). As noted, IFN administered prior to exposure or within the latent period window can stop replication. However, IFN administered too late, in the inflammatory stage (post-symptom onset), led to long-lasting harm and worsened disease outcome (Sodeifian et al., 2022). In a study using a primary nasal cell model (differentiated at air-liquid interface), the virus did not proliferate beyond the limit of assay detection if treated with IFN beta or lambda 16 hours prior to infection, and virus was significantly reduced in cultures treated 6h post-infection compared to untreated cultures. Treatments 24h post infection were not significantly different from untreated controls for either type of IFN (Hatton et al., 2021).

SARS-CoV-2 uses the host ACE2-receptor for entry, upon which the host IFN response could upregulate ACE2 to enhance infection (Ziegler et al., 2020), a positive feedback loop for viral entry, while the IFN response also induces antiviral protein expression to help restore homeostasis as a positive feedback loop to KE 1901.

High Unspecific

High

All life stages

High

Sex and age applicability It has been shown that in human populations males are more likely to suffer severe infections and deaths due to COVID-19 than females. However, in the viral entry and infection phase, one study found that women of working age had higher infection rates than men, but the suggested cause was higher contact rates among women (Doerre and Doblhammer, 2022). Contact rate increase is an important transmission factor but would not constitute a gender-based biological difference in viral entry or IFN-I pathway antagonism. A biological basis for females having higher levels of Type I IFN has been proposed concerning Toll-like receptor (TLR) 7. TLR7 is expressed in plasmacytoid dendritic cells (pDCs), an immune cell type that on infection with SARS-CoV-2 migrates from peripheral blood into the respiratory tract epithelium. TLR7 stimulates higher IFN-I production in pDCs in women than in men (Van der Sluis et al. 2022). It is proposed that this is due to the TLR7 gene being on the X chromosome, and that X inactivation in males is incomplete regarding the TLR7 gene, creating a double gene-dose effect in females (Spiering and de Vries, 2021). In a mouse SARS-CoV model, XY males had more adverse outcomes than XX females and XXY males (Gadi et al. 2020). Additionally, loss-of-function TLR7 mutations have been identified that are associated with increased COVID-19 severity (Szeto et al. 2021). However, these results focus on disease outcome as the endpoint, where factors beyond the initial antiviral response could be involved. Also note that the nasal and upper respiratory tract (URT) epithelial cells express ACE2 receptors for SARS-CoV-2 entry while the pDCs do not, relying on viral endocytosis (Van der Sluis et al. 2022). There is not a clear picture in the literature of the timing of pDC arrival in the epithelium after exposure, and the role of TLR7 in sex differences is currently hypothetical (Spiering and de Vries, 2021). In a large study modelling URT viral load dynamics drawn from measurements in 605 human subjects, variations over 5 orders of magnitude in URT viral load from the time of symptom onset was not explained by age, sex, or severity of illness. Additionally, these variables did not explain modelling results concerning control of viral load by immune responses in the early (innate) or late (adaptive) phases (Challenger et al. 2022). Other sources also support that rate of infection and measured viral load does not differ by gender (e.g., Arnold et al. 2022; Qi et al. 2021; Cheemarla et al. 2021). Therefore, evidence exists that the components of cell entry and the early antiviral response are not influenced by gender specific differences such as sex hormone levels or sex chromosomes to the extent of affecting viral load. Elderly people are more susceptible to severe disease than children and young adults, but Challenger et al. (2022) found no evidence indicating that life stage increases infectability or early viral load generation. However, Sharif-Askari et al. (2022) reported that children had higher expression of IFN-I and associated ISGs than adults. Taxonomic applicability Generally, most mammals are likely susceptible to the SARS-CoV-2 virus based on reports of naturally and experimentally infected animals (See AO 1939). No infections have been reported in other classes of vertebrates. Other than bioinformatic studies on the ACE2 sequence across vertebrates however, there have been few studies on the mechanisms of susceptibility to infection of non-human hosts. Three studies were found on protein targets in the IFN-I innate immune response pathway that included other vertebrates. Rui et al. (2021) showed that SARS-CoV-2 3CLpro and ORF3a inhibit vertebrate (human, mouse, and chicken) STING ability to induce IFNβ promoter activity in a dose-dependent manner in HEK293T cells transfected with IFNβ-luciferase reporter plasmid vectors, together with tagged STING and cGAS vectors and increasing amounts of the SARS-CoV-2 3CLpro or ORF3a expression vectors. This study shows that the vulnerability of the host IFN-I pathway protein components to inhibition by SARS-CoV-2 protein stressors is not limited to humans, however Rui et al. (2021) did not determine the specific amino acids involved in the STING-ORF3a or STING-3CLpro interactions. Mostaquil et al. (2020) studied the cleavage site of IRF3 by PLpro (SARS-CoV-2 NSP3) and compared sequences across mammals. They determined that the IRF3 cleavage site in mammalian species in the taxonomic orders of primates, carnivora, artiodactyla, chiroptera (bats) and a few other mammals was conserved and would generally be susceptible to cleavage, and therefore IFN-I antagonism, but rodentia IRF3 would likely not be susceptible. Hameedi et al. (2022) compared molecular dynamic simulations of 3CLpro cleavage of NEMO in humans and mice showing a decrease in the average number of contacts between mNEMO and 3CLpro compared to hNEMO. Also, hNEMO may be more strongly bound to the catalytic site, and the mNEMO/3CLpro interaction appears more prone to destabilization (Hameedi et al., 2022).

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9aea338> AOPWiki 2021-10-24T17:10:38

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#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9b0b768> AOPWiki 2021-10-24T17:11:37

2021-10-24T17:11:37

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#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9b151a0> AOPWiki 2021-10-19T13:39:43

2021-10-19T13:39:43

<upstream-id>d7112d1d-4dea-4deb-81a6-6b43f033b3af</upstream-id> <downstream-id>da4116ea-e1e0-404d-bf1e-dd8584dd491e</downstream-id>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9b32c50> AOPWiki 2022-09-01T03:49:30

2022-09-01T03:49:30

<upstream-id>da4116ea-e1e0-404d-bf1e-dd8584dd491e</upstream-id> <downstream-id>4a7e7a88-27e9-480b-8c6d-a29c4494e85e</downstream-id> Pro-inflammatory mediators are the chemical and biological molecules that initiate and regulate inflammatory reactions. They are secreted following inflammation or exposure to an inflammogen. Commonly measured pro-inflammatory mediators include Interleukin (IL)-1 family cytokines, <a href="https://bioregistry.io/genecards:IL4">IL-4</a>,<a href="https://bioregistry.io/genecards:IL5"> IL-5</a>, <a href="https://bioregistry.io/genecards:IL6">IL-6</a>, Tumor necrosis factor alpha (<a href="https://bioregistry.io/genecards:TNFa">TNF</a>-α), Interferon gamma (<a href="https://bioregistry.io/genecards:IFNg">IFN</a>-γ) (<a href="https://aopwiki.org/events/1496">KE1496</a>) Proinflammatory mediator increase is caused when there’s increased inflammation. This can be found in many ways, including bradykinin system activation or hypofibrinolysis (Hofman et al., 2016). With more proinflammatory mediators, this causes increased signaling from proinflammatory cytokines, which promotes leukocyte recruitment, which will differentiate into proinflammatory cells (Villeneuve et al., 2018). Increased proinflammatory mediators means this process happens more, which means increase recruitment of inflammatory cells.

The biological plausibility of this KER is high. There are very well established functional relationships between the secreted signalling molecules and the chemotactic effects on pro-inflammatory cells (Harris, 1954; Petri and Sanz 2018). Increased proinflammatory mediators means more pro-inflammatory cytokines, chemokines, vasoactive amines, and lipid mediators (Villeneuve et al., 2018). Increased signaling from these Cytokines and Chemokines promote leukocyte recruitment to areas of infection, including monocytes and neutrophils (Khatri et al., 2017; Leick et al., 2014; Marchini et al., 2016). The leukocytes will differentiate into mature pro-inflammatory cells, in response to mediators they encounter in the local tissue microenvironment (Villeneuve et al., 2018). With higher levels of leukocytes from increased pro-inflammatory mediators, it causes an increase in pro-inflammatory cells (Libby, 2015).

The empirical support for this KER is moderate. There are many studies which show temporal and dose-dependent recruitment of immune cells following increases in pro-inflammatory mediators. However, these mediators exhibit pleiotropy, and knockdown or knockout of a single pathway or mediator can result in compensation and recruitment of immune cells at a later time, as is seen in Nikota et al.,. 2017. (Chen et al., 2016; Nikota et al., 2017; Schremmer et al., 2016) (Additional studies available in <a href="https://aopwiki.org/system/dragonfly/production/2023/05/15/352dxc9mru_KE1_KE2_Table_1.pdf">Table 1</a>). Dose-Response Evidence: Many studies provide dose-response evidence of this KER. For example, in vitro and in vivo studies testing stressors at different doses/concentrations have demonstrated a dose-response relationship; at the higher dose of the stressor, the pro-inflammatory mediators increased, leading to an increase of pro-inflammatory cell recruitment.  Ma et al. (2016) studied inflammatory responses in male BALB/c mice exposed to multi-walled carbon nanotubes (MWCNTs) administered intravenously at different doses (0.5-4 mg/kg) for 2 days. A dose-dependent relationship was found between the levels of the inflammatory mediators IL-6 and TNF-α and the MWCNT dose. At the highest dose, 4 mg/Kg, white blood cells, lymphocytes, and neutrophils levels increased. Porter et al. (2020) have demonstrated that MWCNTs caused dose-dependent and time-dependent pulmonary inflammation in male C57BL/6J mice. Animals received a single dose of 2.5, 10, or 40 µg/mouse. At 40 µg/mouse, IL-1β and IL-18 increased at one day post-exposure. Moreover, polymorphonuclear leukocytes increased on day 1, and after 7 days the number of inflammatory cells was higher. Zinc oxide (ZnO) nanoparticles (NPs) can induce metal fume fever and acute inflammation. Female C57BL/6J mice were intratracheally instilled once at 11, 33, and 100 µg/kg with coated ZnO NPs. Inflammatory responses were evaluated after 1, 3, and 28 days of exposure. An increase in Serum Amyloid A3 (Saa3) mRNA in lung tissue was observed at 33 and 100 µg/kg. Neutrophils accumulated in bronchoalveolar lavage fluid (BALF) after 28 days of exposure in a dose-dependent manner (Hadrup et al., 2019). Polyhexamethylene guanidine phosphate (PHMG-P) is used as a disinfectant. PHMG-P at 0.3, 0.9, and 1.5 mg/kg was instilled into the lungs of mice. At 7- and 14-days post-exposure an increase in the levels of pro-inflammatory markers (IL-1β, IL-6, and C-X-C motif chemokine ligand [CXCL]1) and an increase in mRNA levels of Monocyte chemoattractant protein (MCP)1, Matrix metalloproteinase (MMP)2, and MMP12 was seen. Moreover, on day 7, neutrophils were recruited to the inflamed site. These changes were observed in a dose-response manner (Song et al., 2014). Bourdon et al. 2012 evaluated the toxicity of carbon black nanoparticles (CBNPs) in mouse lung and liver. C57BL/6 mice were exposed to Printex 90 CBNPs with 0.018, 0.054, or 0.162 mg, and after 1, 3, and 28 days of the single instillation, BALF was analyzed. Polymorphonuclear cell counts in BALF increased in a dose-dependent manner with the strongest recruitment 1- and 3-days post-exposure and remained elevated at day 28. CBNPs also increased the expression of Saa3 mRNA levels in lung tissue on days 1, 3, and 28 in a dose-dependent manner. Although this response decreased over time, the expression of Saa3 mRNA increased at all time points, which indicates a persistent acute phase response. A study evaluated the mechanisms of toxicity after exposure to particulate matter (PM2.5) in a tri-culture system: A549 cells (alveolar epithelial cells) and THP-1 differentiated macrophages in the apical chamber; meanwhile, EA.hy926 endothelial cells were cultured in the basolateral chamber. The system was exposed to PM2.5 at three different concentrations 20, 60, and 180 µg/ml for 24 h. An increase in the pro-inflammatory mediators IL-6, IL-8, and TNF-α was observed, as well an increase in mRNA expression of MMP9, Intercellular adhesion molecule 1 (ICAM-1), and caveolin 1 (CAV-1). These genes are involved in the movement and recruitment of leukocytes in sites of inflammation. Changes were observed in a concentration-dependent manner (Wang et al., 2019). In another study, female C57BL/6 mice were exposed to 18, 54, or 162 µg of MWCNT/mouse via single intratracheal instillation. An increased gene expression of Cxcl1, IL-6, Metallothionein-2 (Mt2), Saa1, and Saa2 was observed in a dose-dependent manner at 24 h post-exposure. Moreover, an increase in the recruitment of pro-inflammatory cells was observed in a dose-dependent manner (Poulsen et al., 2013). Temporal Evidence: There is significant evidence of the temporal relationship between the two KES.  In vitro and in vivo studies have demonstrated that pro-inflammatory mediators (Event 1496) increased prior to the recruitment of pro-inflammatory cells (Event 1497). Female C57BL/6J mice were exposed to carbon NPs at 20 µg/mouse via intratracheal instillation. An increase in the levels of cytokines CXCL1, CXCL2, and CXCL5 at 3 h post-exposure was observed, with peaks after 12 and 18 h post-exposure. These pro-inflammatory mediators preceded neutrophil recruitment (12 and 24 h post-exposure) (Chen et al., 2016). Alveolar macrophages (AM) were isolated from lungs 3 to 12 h after instillation, but they did not show a pro-inflammatory response. The authors suggest that AM are not involved in the initiation of the inflammatory response. Meanwhile, alveolar epithelial type II cells induced the highest CXCL levels and acute neutrophilic inflammation. Nickel oxide (NiO) NPs intratracheally instilled at one single dose 200 cm2/rat into female Wistar rats induced an increase of pro-inflammatory cytokines in BALF, at 24 and 74 h for Cytokine-Induced neutrophil chemoattractant 3 (CINC-3) and eotaxin, respectively. At 24 h and 48 h, neutrophils were observed, and after 72 h, the levels of neutrophils, eosinophils, and macrophages increased (Lee et al., 2016). Porter et al. (2002) have shown pulmonary inflammation in rats exposed to crystalline silica aerosol at a concentration of 15 mg/m3 (6h/day, 5 days/week) for 116 days.  Lung disease was linked to TNF-α and IL-10 production in a timely response (10-116 days). The number of polymorphonuclear cells in the BALF increased progressively from day 41 - 116. One study has demonstrated a dose-response and temporal relationship for these two KEs (Patowary et al., 2020). Female Wistar rats were exposed to oleoresin capsicum sprays at 2, 6, and 10%, and after 1, 3, and 24 h post-exposure, blood cell and BALF cytokines were evaluated. The pro-inflammatory cytokine TNF-α increased in a dose-dependent manner, and polymorphonuclear cells increased in a time-dependent manner. Schremmer et al. (2016) have reported the time course of chemotaxis in vitro in response to the challenge of biopersistent particles and their relation to inflammatory mediators.  NR8383 rat alveolar macrophages were challenged with different types of particles for 1, 4, and 16 h. The cell supernatants obtained from different time points were used to evaluate the chemotaxis of unexposed NR8383 macrophages. They found that nanosized silica at 16 µg/cm2 induced an elevated transcription of C-C motif chemokine ligand (CCL)4, CXCL1, CXCL3, and TNF-α in a time-dependent manner. The pro-inflammatory cytokines present in the supernatants induced chemotaxis of unexposed macrophages at 4 and 16 h post-exposure. Husain et al. (2015) found increased expression of genes related to chemotactic recruitment of pro-inflammatory cells at 3 h and 1 day after exposure to 162 µg/mouse CBNPs in female C57BL/6 mice. They observed an increase in the gene expression of pro-inflammatory mediators at day 1 (CXCL2, Ccl2), day 3 (IL-17, IL-33), day 14 (Cd2), and day 42 (Cxcl) post-exposure. The KE2 (Event 1497) increased over time with the maximum levels of neutrophils, macrophages, eosinophils, and lymphocytes at 4- and 5-days post-exposure. This response suggests chronic inflammation occurs because of an incomplete resolution of acute inflammation. Rahman et al. (2017) evaluated whether different titanium dioxide (TiO2) NPs induce lung inflammation. C57BL/6 mice were exposed to 18, 54, 162, or 486 µg/mouse of TiO2 NPs via single intratracheal instillation. At 1-day post-exposure, gene expression analysis showed more changes in genes associated with inflammation and fibrosis. Moreover, after 1- and 28 days post-exposure, an increase in cell counts in BALF was observed in a dose-dependent manner. Ho et al. (2013) evaluated the inflammatory response in mice exposed to coated quantum dots, cadmium-based NPs, (QD705-poly(ethylene glycol[PEG], QD705-COOH) at 12 or 60 µg/mouse. At 2-, 17- and 90-days post-exposure, an increase in the level of TNF-α, IL-1b, IL-6, CXCL1, CCL2, CCL1, CCL17, and CXCL13 mRNA levels in lungs was observed and the amount of polymorphonuclear cells in BALF increased in a dose-dependent manner at day 7 post-exposure. The inflammatory response increased on days 2 and 17, but on day 90 decreased. QD705-COOH induced granulomas persistently presented from 2 to 90 days. Morimoto et al. (2010) examined the different kinds of cytokines related to lung inflammation by NiO exposure. Rats were intratracheally exposed to 0.33 mg/Kg and 0.66 mg/kg NiO NPs and were sacrificed at day 3, after 1 week, 1, 3, and 6 months post-exposure. Infiltration of alveolar macrophages in lung tissue and BALF was observed from day 3 to 3 months post-exposure, with higher levels after 1 and 3 months. Before the recruitment of inflammatory cells, an increase in the level of pro-inflammatory cells such as MCP-1 and IL-1β in BALF was observed. NiO NPs induced a persistent inflammatory effect. Kamata et al. (2011) studied the impact of CBNPs on susceptible subjects with predisposing lung disease and the effects of nanoparticles on inflammation and fibrotic changes. To achieve this goal, female C57BL/6J mice were intratracheally administered with bleomycin 20 µg/mouse and CBNPs 10 µg/mouse. Evaluations were performed post-exposure at different time points. An increase of IL-6 and CCL2 in BALF was observed at days 2 and 7. After 7- and 14 days, a recruitment of pro-inflammatory cells was observed. Oxidant injury (evaluated as nitrotyrosine expression) was observed after 7 days and 14 days. The levels of Transforming growth factor beta (TGF-β) increased over time with the highest level at day 14. Finally, they observed an increase in lung collagen deposition and a decrease in lung compliance at day 21.

Attenuation or complete abrogation of KE1 (<a href="https://aopwiki.org/events/1496">KE1496</a>) and KE2 (<a href="https://aopwiki.org/events/1497">KE1497</a>) following inflammogenic stimuli is observed in rodents lacking functional Interleukin 1 receptor type 1 (IL-1R1) or other cell surface receptors that engage innate immune response upon stimulation (Gasse et al., 2007; Halappanavar et al., 2013). However, following exposure to MWCNTs, it has been shown that absence of IL-1R1 signalling is compensated for eventually and neutrophil influx is observed at a later post-exposure time point (Nikota et al., 2017). In another study, acute neutrophilic inflammation induced by MWCNTs was suppressed at 24 h in mice deficient in IL-1R1 signalling; however, these mice showed exacerbated neutrophilic influx and fibrotic response at 28 days post-exposure (Girtsman et al., 2014). The early defence mechanisms involving damage-associated molecular patterns is fundamental for survival, which may necessitate activation of compensatory signalling pathways. As a result, inhibition of a single biological pathway mediated by an individual cell surface receptor may not be sufficient to completely abrogate the lung inflammatory response. Forced suppression of pro-inflammatory and immune responses early after exposure to substances that cannot be effectively cleared from lungs, may enhance the injury and initiate other pathways leading to exacerbated response. Most of the studies evaluate one dose at different time points or one-time point at different concentrations. Moreover, some studies have demonstrated that a stressor can lead to the recruitment of pro-inflammatory cells, but the presence of pro-inflammatory mediators was not determined (Westphal et al., 2015). Recruitment of pro-inflammatory cells is a key event that is complicated to replicate in vitro conditions as cell migration is induced by cooperative chemotactic mediators (Gouwy et al., 2015) which are produced and released from different cells. Therefore, more kinetics studies in co-culture techniques are needed to fill this gap.

<table border="1" bordercolor="#ccc" cellpadding="5" cellspacing="0" class="table table-bordered table-fullwidth" style="border-collapse:collapse"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>MF Specification</th> <th>Effect(s) on the KER</th> <th>Reference(s)</th> </tr> <tr> <th> </th> <th> </th> <th> </th> <th> </th> </tr> <tr> <th> Air pollution </th> <th> </th> <th> Air pollution primes immunity; increases the levels of circulating IL-1β, IL-6 and TNF-α; impairs the normal functions of macrophages and alveolar cells. Exposure to particulate air pollution, such as PM2.5, is associated with pulmonary inflammation [1,2]. Both short term and chronic exposures to fine particulate matter (PM) have been shown to increase levels of circulating IL-1β, IL-6 and TNF-α [3-5]. Air pollution works as a priming factor that exacerbates the inflammatory phenotype of COVID-19 and further dysregulates immune cell activity. Dysregulation of the immune cell functions, on the other hand, plays a role in tissue damage and the ability of the immune system to fight pathogens, which increases the susceptibility to concomitant bacterial superinfection, for instance [6-9]. </th> <th style="text-align:justify"> [1] Zhao et al., 2013 [2] Jia et al., 2021 [3] Tsai et al., 2012 [4] Ljungman et al., 2009 [5] Kido et al., 2011 [6] Knoll et al., 2021 [7] Glencross et al., 2020 [8] Yamasaki and Eeden, 2018 9) Signorini et al., 2018 </th> </tr> </thead> <tbody> <tr> <td> Chemicals (weak evidence) </td> <td> Per- and polyfluoroalkyl substances (PFAS) (Perfluorooctane sulfonate [PFOS], perfluorooctanoic acid [PFOA], perfluorobutane sulfonic acid [PFBS], perfluorooctane sulfonamide [PFOSA], and perfluorodecanoic acid [PFDA]) </td> <td> Several in vitro studies in human-derived cells have shown that PFAS can modify the secretion of pro-inflammatory mediators in a dose-dependent manner [1].  PFOS exposure significantly induced IL-1 IL-4, IL-6, and IL-8 in human lymphocytes and reduced chemokines CXCL8 and CXCL10 secretion in human bronchial epithelial cells while increasing of IL-1α release [2]; both PFOS and PFOA enhanced IL-1β release in response to Poly I:C [3]; PFOS, PFOA, PFBS, PFOSA, and PFDA exposure decreased PHA-induced release of IL-4, IL-10, and IL-6 and PFOS, PFOSA, and PFDA decreased IFN-γ release in human leukocytes with PFOS as a more potent inhibitor of cytokine production than other PFAS, and leukocytes obtained from female donors appeared to be more sensitive to the in vitro immunomodulating effects of PFAS, compared to leukocytes from male donors [4]. In a rat study exposed to PFOS, increased serum levels of TNF-α and IL-6 were observed. Kupffer cells exposed to PFOS showed cell activation, which was mostly inhibited by anti-TNF-α or anti-IL-6 treatment. Moreover, NF-κB inhibitor and JNK inhibitor significantly inhibited the production of IL-6 [5,6]. </td> <td> [1] Tian et al., 2021 [2] Li et al., 2020 [3] Sørli et al., 2020 [4] Corsini et al., 2012 [5] Han et al., 2018 [6] EFSA CONTAM Panel, 2020 </td> <td> </td> </tr> <tr> <td colspan="1" rowspan="2">Sex</td> <td>Female sex (XX chromosomes)</td> <td> Females produce higher amounts of the antiviral infection cytokine IFN-α than men [1].  Estrogens are critical regulators of gene expression and functions in innate immune cells, including monocytes, macrophages, and dendritic cells, as well as lymphocytes such as T helper 1/2 (TH1/2) cells, regulatory T-cells (Treg cells), and B cells. One of the major forms of estrogen, estradiol, has been shown to dampen the production of excessive innate inflammatory cytokines by monocytes and macrophages [2]. In the presence of progesterone, CD4+ Th cells skew from Th-1 to Th-2 in the production of anti-inflammatory cytokines, specifically IL-4 and IL-10 [3]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct and immune response in females is enriched with activated T-cells [1]. In lactating women, higher SARS-CoV-2 reactive memory B-cells and antibody titers have been associated with the hormone prolactin [4]. Poor T-cell response to SARS-CoV-2 correlates with worse disease progression in female patients. </td> <td> [1] Takahashi et al., 2020 [2] Scully et al., 2020 [3] Mauvais-Jarvis et al., 2020 [4] Gonçalves et al., 2021 </td> </tr> <tr> <td>Male sex (XY chromosomes)</td> <td> Males display a higher innate immune response to SARS-CoV-2 than females, which conditions their cytokine profile. Men have higher levels of the innate immune cytokines IL-8 and IL-18 in circulation  [1]. Moreover, elderly men in particular display autoantibodies against IFN-α more frequently [5]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct. Men display higher circulating levels of non-classical monocytes [1]. Higher innate immune activation in men leads to higher plasma levels of the inflammatory cytokines IFN-α [6], IL-8 and IL-18 [1], driving hyperinflammation and more pronounced lymphopenia in males. </td> <td> [5] Bastard et al., 2020 [6] Agrawal et al., 2021 </td> </tr> <tr> <td> Age </td> <td>Old people</td> <td>During aging, a subclinical chronic inflammatory response develops leading to an immune senescent state, where pathogen protective immune responses are impaired, but the production of inflammatory cytokines, such as <a href="http://bioregistry.io/genecards:IL6">IL-6</a>, is increased. This process is called inflammaging. The persistent <a href="http://bioregistry.io/genecards:IL6">IL-6</a> elevation can induce lung tissue inflammation and mortality. The rate of inflammaging is higher in men and accelerated inflammaging is believed to worsen COVID-19 outcomes [1]. The chronic inflammatory status is associated with a dramatic depletion of B lymphocyte-driven acquired immunity. Aging also attenuates the upregulation of co-stimulatory molecules critical for T-cell priming and reduces antiviral IFN production by alveolar macrophages and dendritic cells in response to infection with the influenza virus [2].</td> <td> [1] Bonafè et al., 2020 [2] Kovacs et al., 2017</td> </tr> <tr> <td rowspan="2">Lipids</td> <td> Atherogenic dyslipidemia </td> <td> Lipids impact innate and adaptive immune responses [1,2]. In COVID-19. The atherogenic dyslipidemia associated with COVID-19 severity (high tryglycerides and low total, low density lipoprotein and high density lipoprotein cholesterol) was inversely correlated with inflammatory biomarkers such as increased levels of serum C-reactive protein (CRP), <a href="http://bioregistry.io/genecards:IL6">IL-6</a>, IL-8, and IL-10 [3,4]. </td> <td rowspan="2"> [1] Hubler and Kennedy, 2016 [2] Bernardi et al., 2018 [3] Henry et al., 2021 [4] Caterino et al., 2021 [5] Hubler and Kennedy, 2016 [6] Winer et al., 2009 [7] Im et al., 2011 [8] Muscogiuri et al., 2020 </td> </tr> <tr> <td> Obesity </td> <td> In obesity, immune cells interact with various classes of lipids, which can control the plasticity of macrophages and T lymphocytes. In COVID-19. Altered lipid homeostasis is associated with severe COVID-19 outcomes and, at the same time, with chronic inflammation and inflammatory polarization of macrophages and T lymphocytes [5]. Th1 lymphocytes are more prevalent in adipose tissue of obese patients [6]. In the same way, Th1 lymphocytes are elevated in visceral fat [6]. Both macrophages and T lymphocytes interact with lipids that influence their proliferation, differentiation, polarization [7] and transcriptional regulation, which is tightly controlled by Sterol regulatory element-binding protein (SREBP) and Liver X receptors (LXRs), expressed in macrophages and known regulators of cytokine release. Adipose tissue produces many pro-inflammatory adipokines and cytokines, which lead to low-grade inflammation and the recruitment of immune cells which may clarify the connection between obesity and COVID-19 severity [8]. </td> </tr> <tr> <td>Gut microbiota</td> <td>Gut dysbiosis (alteration of gut microbiota)</td> <td> The gut microbiota is increasingly acknowledged to play a central role in human health and disease, notably by shaping the immune response. Notably some bacteria living in the gut produce short-chain fatty acids (SCFA), recognized as mediators of the intestinal inflammatory response [1]. SCFAs modulate inflammation by regulating immune cell cytokine production such as TNF-α, IL-12, IL-6 [2]. For example, butyrate decreased the lipopolysaccharide (LPS)-induced TNF-α expression in monocytes [4] and activated Treg cells, blocking an excessive inflammatory response [1,3]. In COVID-19. In a COVID-19 cohort, the depletion of several bacterial species (B. adolescentis, E. rectale and F. prausnitzii, known to play immunomodulatory roles in the human gastrointestinal system) was linked to increased plasma concentrations of TNF-α, CXCL10, CCL2 and IL-10 [4]. Conversely, two species enriched in the COVID-19 cohort, B. dorei and Akkermansia muciniphila, were positively correlated with IL-1β, IL-6 and CXCL8. Using a machine learning model [5], it was reported that the disruption of gut microbiota significantly correlated with pro-inflammatory cytokines and may predispose normal individuals to severe COVID-19. Decreases in the abundance of butyrate-producing bacteria and a decline in SCFA were observed in severe COVID-19 [4,6,7,8]. Reduced relative proportion of bacteria producing SCFA was observed in Syrian hamsters infected with SARS-CoV-2, compared to non-infected controls, with a transient decrease in systemic SCFA amounts [9]. However, SCFA supplementation in hamsters during infection had no effect on inflammatory parameters. Targeted analysis of fecal metabolites showed significantly lower fecal concentrations of SCFAs in COVID-19 patients, which correlated with disease severity and increased plasma concentrations of CXCL-10 and CRP [10]. </td> <td> [1] Yoo et al., 2020 [2] Vinolo et al., 2011 [3] Atarashi et al., 2013 [4] Yeo et al., 2021 [5] Gou et al., 2021 [6] Zuo et al., 2020 [7] Gu et al., 2020 [8] Grenga et al., 2022 [9] Sencio et al., 2022 [10] Zhang et al., 2022 </td> </tr> <tr> <td>Vitamin D (low evidence)</td> <td>Vitamin D deficiency</td> <td> There is a complex interplay between vitamin D and the immune response to viral infections. Low vitamin D status is proposed to induce upregulation of the TNF-α and downstream of Nuclear Factor Kappa B Subunit 1 (NF–κB1) signaling pathway, which regulates inflammatory reactions toward viral infection in macrophages [1,2]. Vitamin D was shown as a potent suppressor of IFN-γ mediated macrophages response, preventing the release of inflammatory cytokines and chemokines [3]. Thus, release of pro-inflammatory cytokines might be exacerbated in COVID-19 patients with vitamin D deficiency [4]. </td> <td> [1] Hassan et al., 2022 [2] Książek et al., 2021 [3] Helming et al., 2005 [4] Munshi et al., 2021 </td> </tr> <tr> <td> Genetic factors </td> <td> </td> <td> The inflammatory response manifested by increased cytokine levels results in inhibition of heme oxygenase (HO-1), with a subsequent loss of cytoprotection. In the 50-non-coding regions of the HO-1 gene, there are two polymorphic sites, namely the (GT)n dinucleotide and T (-413) A sites, which regulate the transcriptional activity of HO-1. These polymorphisms have been shown to be associated with the occurrence and progression of numerous diseases, including COVID-19 [1]. The timing of the IFN response to SARS-CoV-2 infection can vary with viral load and genetic differences in host response. When the viral load is low, IFN responses are engaged and contribute to viral clearance, resulting in mild infection. When viral load is high and/or genetic factors slow antiviral responses, virus replication can delay the IFN response and cytokine storm can occur before adaptive responses clear the virus, resulting in severe disease including multisystem inflammatory syndrome in Children (MIS-C) [2]. </td> <td> [1] Singh et al., 2020 [2] Rowley, 2020 </td> </tr> <tr> <td colspan="1" rowspan="3"> Therapeutic intervention against COVID-19 </td> <td> Tocilizumab and Sarilumab </td> <td> Are anti-IL-6 receptor monoclonal antibodies, which reduce inflammation [1] by attaching to the IL-6 receptor (as IL-6 receptor inhibitors) [2]. Tocilizumab, a biological drug approved for rheumatoid arthritis, is currently being evaluated for its efficacy against the effects of systemic IL-6 elevation (ClinicalTrial.gov accessed on March 2022, NCT04317092, NCT04320615, NCT04306705) [3]. </td> <td> [1] WHO, 2021. [2] European Medicines Agency, 2021 [3] Bonafè et al., 2020 </td> </tr> <tr> <td> Baricitinib </td> <td> Is an immunosuppressant that blocks the action of enzymes known as Janus kinases (JK), which play an important role in inflammatory processes (JAK inhibitor) [1–4]. </td> <td> [1] Jorgensen et al., 2020 [2] Bekerman et al., 2017 [3] Neveu et al., 2015 [4] Richardson et al., 2020 </td> </tr> <tr> <td> Low molecular weight heparins (LMWHs) </td> <td> Have anti-inflammatory effects by blocking pro-inflammatory mediators (TNF-α, IL-6 and Leukotriene [LTB4]) [1]. </td> <td> [1] Buijsers et al., 2020 </td> </tr> <tr> <td colspan="1"> Pre-existing heart failure </td> <td> </td> <td> Dysregulation of renin angiotensin system due to pre-existing heart failure can have detrimental inflammatory effects both locally (in the heart) and systematically. The Angiotensin converting enzyme 2 (ACE2)/Angiotensin (Ang) (1-7) pathway is associated with the attenuation of a wide range of pro-inflammatory cytokines and chemokines, such as IL-1, IL-5, IL-6, IL-12, CCL2, TNF-α and MCP-1 [1]. </td> <td> [1] Rodrigues Prestes et al., 2017.                      </td> </tr> <tr> <td colspan="1"> Diet </td> <td> Dietary elements linked to pro-inflammatorymediators </td> <td> High-fat diets have been linked—in multiple studies—to promote an “inflammatory status” in the gut and subsequently other organs [1]. Compounds found in many plant foods may affect COVID-19 prognosis by blocking inflammatory mediators and pathways. Bousquet et al. [2,3] identified bioactive compounds contained in spices and fermented vegetables, including capsaicin, cinnamaldehyde, curcumin, genistein, gingerol, mustard oil, piperine, wasabi, and sulforaphane, that upregulate the signaling of nuclear factor (erythroid-derived 2)-like 2 (Nrf2), a potent endogenous antioxidant which blocks oxidative stress from the Angiotensin type I receptor (AT1R) axis, inhibits overproduction of proinflammatory cytokines and chemokines (including IL-6), and limits the activation of NF-κB. There is some in vitro evidence that Lactobacillus, found in many fermented foods, works through the same mechanism [4]. Finally, naringin, a compound found in citrus fruits, reduced LPS-induced IL-6 expression levels in vitro [5]. </td> <td> [1] Duan et al., 2018 [2] Bousquet et al., 2021a [3] Bousquet et al., 2020 [4] Bousquet et al., 2021b [5] Liu et al., 2022 </td> </tr> </tbody> </table>

A majority of the in vivo studies are conducted with only one dose and thus, it is difficult to derive quantitative dose-response relationships based on the existing data. However, it is clear from the studies referenced above that greater concentrations or doses of pro-fibrotic substances results in higher release of alarmins, and consequently, higher pro-inflammatory signalling. The above studies also demonstrate strong temporal relationships between the individual KEs.

Activated pro-inflammatory cells secrete pro-inflammatory mediators, and those mediators' goal is to cause signalling and response, which can lead to chronic inflammation (<a href="https://aopwiki.org/events/1497">KE1497</a>). Chronic inflammation means proinflammatory mediators increase and increased recruitment of inflammatory cells acts in a positive feedback loop, which continues a pro-inflammatory environment.

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9bd7a48> AOPWiki 2018-01-05T13:18:46

2023-05-18T12:46:20

<upstream-id>4a7e7a88-27e9-480b-8c6d-a29c4494e85e</upstream-id> <downstream-id>3d85f8fb-ab2c-4509-87d8-7eb871a1f7a0</downstream-id> The recruitment of proinflammatory cells occurs as a result of proinflammatory mediator signaling, recruiting the cells, such as monocytes which can differentiate into different macrophage types, to clear out invading toxic pathogens. However, when invading toxic pathogens are not properly cleared out and pro-inflammatory mediators are not controlled, the proinflammatory cells persist, causing a positive feedback loop leading to a dysregulated para-inflammation, which is responsible for chronic inflammation conditions (Medzhitov et al). This persistence causes over-activated proinflammatory macrophages, recruitment of neutrophils, and mass levels of proinflammatory cytokines (Medzhitov et al). Hyperinflammation properties include higher levels of inflammatory markers in blood (CRP, ferritin, and D- dimers), increased neutrophil to lymphocyte ratio, and increased proinflammatory cytokines.    In COVID-19 patients, monocytes are derived into pro-inflammatory macrophages as a result of SARS-COV-2 infection (Merad et al).  Pro-inflammatory macrophages along with neutrophils and T-cells are recruited into the lung epithelium and exacerbate inflammation by establishing the proinflammatory feedback loop that persists and causes the hyperinflammatory state (Gustine et al).  Hyperinflammation in COVID-19 is also triggered by pyroptosis and tissue damage (reviewed in Tan et al. 2021 <a href="https://doi.org/10.3389/fimmu.2021.742941">https://doi.org/10.3389/fimmu.2021.742941</a>). SARS-COV-2 activates Gasdermin D (GSDMD), a key trigger of pyroptosis in pro-inflammatory macrophages. When pyroptosis causes cell death in these macrophages, it releases mass amounts of pro-inflammatory cytokines, ROS, and LDH, leading to hyperinflammation (Zhang et al). A number of so called alarmins have been associated with the evolution towards hyperinflammation. Alarmins are a family of immunomodulatory proteins that act as damage-associated molecular patterns (DAMPs) and recruit and activate various immune cells such as monocytes, macrophages, lymphoid cells and myeloid dendritic cells. Multiple proteins from this family, including especially IL33 and S100 family proteins (S100A4, S100A7, S100A9, S100A12, S100B, and S100P) have been identified to be associated with the later stages of inflammation culminating in hyperinflammation in the lungs (Desvaux et al. 2021 <a href="https://doi.org/10.1371/journal.pone.0254374">https://doi.org/10.1371/journal.pone.0254374</a>). IL33 and the S100 family proteins can stimulate production of IL1B, IL6 and TNFA, some of the hallmark molecules associated with hyperinflammation (reviewed in Desvaux et al. 2021).

<div> <table class="table table-bordered table-fullwidth"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>MF Specification</th> <th>Effect(s) on the KER</th> <th>Reference(s)</th> </tr> </thead> <tbody> <tr> <td colspan="1" rowspan="2">SEX</td> <td> <table class="table table-bordered table-fullwidth"> <tbody> <tr> <td colspan="1" rowspan="2"> </td> <td>female sex (XX chromosomes)</td> </tr> </tbody> </table> </td> <td>Females produce higher amounts of the antiviral infection cytokine IFN- a than men [1].  Estrogens are critical regulators of gene expression and functions in innate immune cells, including monocytes, macrophages, and dendritic cells, as well as lymphocytes such as T-helper 1/2 (TH1/2) cells, regulatory T-cells (Tregs), and B cells. One of the major forms of estrogen, estradiol, has been shown to dampen the production of excessive innate inflammatory cytokines by monocytes and macrophages [2]. In the presence of progesterone, CD4+ T-helper cells skew from Th-1 to Th-2 in the production of anti-inflammatory cytokines, specifically IL-4 and IL-10 [3]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct and immune response in females is enriched with activated T-cells [1]. In lactating women, higher SARS-CoV-2 reactive memory B-cells and antibody titers have been associated with the hormone prolactin [4]. Poor T-cell response to SARS-CoV-2 correlates with worse disease progression in female patients.</td> <td> 1.) DOI: 10.1038/s41586-020-2700-3 2.) DOI: 10.1038/s41577-020-0348-8 3.) DOI: 10.1016/S0140-6736(20)31561-0 4.) DOI: 10.1016/j.xcrm.2021.100468 </td> </tr> <tr> <td>male sex (XY chromosomes)</td> <td> Males display a higher innate immune response to SARS-CoV-2 than females,which conditions their cytokine profile. Men have higher levels of the innate immune cytokines IL-8 and IL-18 in circulation  [1]. Moreover, elderly men in particular display autoantibodies against IFN-a more frequently [5]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct. Men display higher circulating levels of non-classical monocytes [1]. Higher innate immune activation in men leads to higher plasma levels of the inflammatory cytokines IFN-a [6], IL-8 and IL-18 [1], driving hyperinflammation and more pronounced lymphopenia in males. </td> <td> 5.) DOI: 10.1126/science.abd4585 6.) DOI: 10.3389/fimmu.2021.739757 </td> </tr> <tr> <td colspan="1">Age</td> <td>Young/old people</td> <td>During aging, a subclinical chronic inflammatory response develops leading to an immune senescent state, where pathogen protective immune responses are impaired, but the production of inflammatory cytokines, such as IL-6, is increased. This process is called inflammaging. The persistent IL-6 elevation can induce lung tissue inflammation and mortality. The rate of inflammaging is higher in men and accelerated inflammaging is believed to worsen COVID-19 outcomes [1]. The chronic inflammatory status is associated with a dramatic depletion of B lymphocyte-driven acquired immunity. Aging also attenuates the upregulation of co-stimulatory molecules critical for T-cell priming and reduces antiviral IFN production by alveolar macrophages and dendritic cells (DCs) in response to infection with the influenza virus [2].</td> <td> 1) 10.1016/j.cytogfr.2020.04.005 2) 10.1016/j.cger.2017.06.002 </td> </tr> <tr> <td colspan="1">Vitamin D (low evidence)</td> <td>Vitamin D deficiency </td> <td> Vitamin D deficiency was shown to promote intestinal mucosal barrier dysfunction with higher permeability in infection-induced or TNF-treated cells and in in vivo colitis models [1,2]. An association between increased markers of intestinal permeability and vitamin D deficiency has been observed in critically ill subjects from ICU [3]. </td> <td> [1] doi: 10.1093/infdis/jiu235 [2] doi: 10.1097/MIB.0000000000000526 [3] doi: 10.1136/jim-2019-001132 </td> </tr> <tr> <td colspan="1">Genetic factors</td> <td> </td> <td>The inflammatory response manifested by increased cytokine levels results in inhibition of heme oxygenase (HO-1), with a subsequent loss of cytoprotection. In the 50-non-coding regions of the HO-1 gene, there are two polymorphic sites, namely the (GT)n dinucleotide and T (-413) A sites, which regulate the transcriptional activity of HO-1. These polymorphisms have been shown to be associated with the occurrence and progression of numerous diseases, including COVID-19 [1]. The timing of the IFN response to SARS-CoV-2 infection can vary with viral load and genetic differences in host response. When the viral load is low, IFN responses are engaged and contribute to viral clearance, resulting in mild infection. When viral load is high and/or genetic factors slow antiviral responses, virus replication can delay the IFN response and cytokine storm can occur before adaptive responses clear the virus, resulting in severe disease including MIS-C [2].</td> <td> [1] doi: 10.1016/j.freeradbiomed.2020.10.016 [2] doi: 10.1038/s41577-020-0367-5 </td> </tr> <tr> <td colspan="1">Air pollution</td> <td>Air pollution, particularly PM2.5</td> <td> Air pollution and PM2.5 induce detrimental recruitment of cytotoxic effectors that contribute to tissue damage and sustained hyperinflammation. Pulmonary macrophages have been shown to be hyper-activated in the lungs of COVID-19 patients. This, in turn, can result in detrimental recruitment of cytotoxic effectors that affect tissue damage and hyperinflmmation [1]. Furthermore, air pollution induces imbalanced activation of cytotoxic and protective immune effectors [2]. </td> <td> [1] https://doi.org/10.3389/fimmu.2021.720109 [2] https://doi.org/10.3389/fncel.2021.647643 </td> </tr> <tr> <td colspan="1">Pre-existing heart failure</td> <td> </td> <td> Hyperinflammation is one of the hallmarks of HF and counteracting the inflammatory response has been for years a target for various experimental therapies [1]. Crucial pro-inflammatory mediators such as TNF-α, IL-1 and IL-6 have been shown to affect endothelial inflammation, leading to the recruitment of monocytes, themselves secreting cytokines, thus contributing to the cytokine storm [2]. ACE2 downregulation leads to a shift towards the Ang II/AT1R pathway, and a proinflammatory response leading to the recruitment of inflammatory cells, such as monocytes and macrophages in the heart [3,4]. In addition, ADAM17 is implicated in a wide range of cardiovascular pathologies [5] and its expression is increased in HF [6,7]. ADAM17 is known as a sheddase of ACE2, but also as the TNF-α converting enzyme (TACE) [8]. According to Palacios et al. [382], increased levels of ADAM17 are correlated not only with mortality, but also with increased circulation of soluble forms of TNF-α and its corresponding receptors (soluble TNFR1/2)—key mediators of the COVID-19-associated cytokine storm [383,384] and the activation of inflammatory cells like macrophages and neutrophils [385]. Thus, pre-existing HF and associated enhanced ADAM17 expression might predispose an organism to enhanced pro-inflammatory cell activation. </td> <td> 1: https://www.nature.com/articles/nrcardio.2014.28 2: https://doi.org/10.1016/j.jacc.2020.01.014 3: https://doi.org/10.1016/j.stemcr.2021.07.012 4: https://doi.org/10.1161/CIRCRESAHA.121.319060 5: https://link.springer.com/article/10.1007/s00018-021-03779-w 6: https://doi.org/10.1016/j.ejheart.2004.02.007 7: https://doi.org/10.1161/01.CIR.99.25.3260 8: https://doi.org/10.3390/ijms22168423 9: https://doi.org/10.1016/j.hsr.2021.100011 10: https://doi.org/10.3389/fimmu.2020.01446 11: https://doi.org/10.1016/j.cell.2020.11.025 </td> </tr> <tr> <td colspan="1">Diet</td> <td>Compounds found in foods may be able to affect hyperinflammation via inflammatory mediators </td> <td> <ul> <li>Piperine (found in black pepper), inhibits the production of IFN- and IL-2 in human peripheral blood mononuclear cells [399] and neutralizes free radicals and ROS [400]. </li> <li>Linoin, a compound found in lemon, has been found to inhibit CD4+ T-cell proliferation by inhibition of NF-�B translocation in human cells [401]. The isoflavone Biochanin-A similarly prevents cell proliferation and LPS-induced inflammatory mediator release in vitro [402]. </li> <li>Increased fiber intake in humans is shown to reduce Creactive protein [403]. </li> <li>Parthenolide, a potent phenolic compound, inhibited inflammatory mediators in vitro in microglia, monocytes, macrophages, and neutrophils, including IL-6, NF–kB, and TNF- [404,405]. </li> <li>Arachidonic acid, a fatty acid found in numerous foods, enhances the function of -amino butyric acid (GABA) receptors, which attenuates severe inflammatory illness in coronavirus-infected mice. This contrasts with other dietary fatty acids, which induce systemic inflammation [406].</li> </ul> </td> <td> <ul> <li>399: <a href="http://doi.org/10.4238/2012.March.14.5">http://doi.org/10.4238/2012.March.14.5</a></li> <li>400: <a href="http://doi.org/10.1358/mf.2000.22.5.796644">http://doi.org/10.1358/mf.2000.22.5.796644</a></li> <li>401: <a href="http://doi.org/10.1016/j.ejphar.2011.08.035">http://doi.org/10.1016/j.ejphar.2011.08.035</a></li> <li>402: <a href="http://doi.org/10.1016/j.ejphar.2010.11.026">http://doi.org/10.1016/j.ejphar.2010.11.026</a></li> <li>403: <a href="http://doi.org/10.1038/ejcn.2009.8">http://doi.org/10.1038/ejcn.2009.8</a></li> <li>404: <a href="http://doi.org/10.1002/ptr.3732">http://doi.org/10.1002/ptr.3732</a></li> <li>405: <a href="http://doi.org/10.1002/ptr.6776">http://doi.org/10.1002/ptr.6776</a></li> <li>406: <a href="http://doi.org/10.1186/s40246-020-00297-x">http://doi.org/10.1186/s40246-020-00297-x</a></li> </ul> </td> </tr> </tbody> </table> </div>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42e9c1de08> AOPWiki 2021-04-20T02:46:22

2023-02-08T09:25:40

Binding of SARS-CoV-2 to ACE2 leads to hyperinflammation (via cell death)

Cytopathic SARS-CoV-2 leads to hyperinflammation

Allie Always

Laure-Alix Clerbaux, Penny Nymark, Sabina Halappanavar, Sally Mayasich

BY-SA

2.5

In lungs, SARS-CoV-2 Spike (S) proteins bind to the Angiotensin 2 Converting Enzyme (<a href="https://www.genecards.org/cgi-bin/carddisp.pl?gene=ACE2">ACE-2)</a> receptor (<a href="https://aopwiki.org/events/1739">KE1739</a>, Binding to ACE2), expressed at high levels on airway epithelial cells, alveolar epithelial cells, vascular endothelial cells and macrophages. Upon binding, the S protein subunits undergo sequential cleavage mediated by proteases and conformational changes that results in virus and host cell membrane fusion and viral entry into the cells (<a href="https://aopwiki.org/events/1738">KE1738</a>, SARS-CoV-2 cellular entry). Following cellular entry, the SARS-CoV-2 virus has evolved a repertoire of proteins that block the interferon cascade so the host antiviral proteins are not expressed, and the virus is free to replicate. If the<a href="https://www.wikipathways.org/index.php/Pathway:WP4868"> type I interferon antiviral response</a> is antagonized (<a href="https://aopwiki.org/events/1901">KE1901</a>, Interferon-I antiviral response antagonized by SARS-CoV-2), the viral RNA can be translated, replicated, transcribed and the genomic RNA packaged before the new SARS-CoV-2 virions are assembled (<a href="https://aopwiki.org/events/1847">KE1847</a>, SARS-CoV-2 production). SARS-COV-2 is a cytopathic virus and causes massive cell death in lungs (<a href="https://aopwiki.org/events/1825">KE1825,</a> Increased cell death). Cell death triggers immune response. Activated local innate immune response includes secretion of soluble factors such as cytokines (<a href="https://bioregistry.io/genecards:IL6">IL-6</a>, <a href="https://bioregistry.io/genecards:TNF">TNF</a>), chemokines (<a href="https://bioregistry.io/genecards:CXCL8">CXCL8</a>), growth factors, hormones and several types of metabolites (<a href="https://aopwiki.org/events/1496">KE1496</a>, Increased secretion of pro-inflammatory mediators). This KE is the most common/central node common of the network. The soluble factors recruit immune cells including macrophages, monocytes and lymphocytes to the sites of infection (<a href="https://aopwiki.org/events/1497">KE1497,</a> Recruitment of immune cells), which further amplify secretion of cytokines and chemokines, creating a pro-inflammatory environment. Prolonged and self-perpetuating inflammatory response referred to as hyperinflammation (<a href="https://aopwiki.org/events/1868">KE1866,</a> Hyperinflammation) exhibiting notably excessive serum levels of pro-inflammatory mediator C-reactive protein (<a href="http://bioregistry.io/genecards:CRP">CRP</a>). A vicious cycle of hyperinflammatory response initiated by SARS-CoV-2 leads to tissue injury, pulmonary dysfunction and organ failure. <div> <div> This AOP is developed within the <a href="https://www.ciao-covid.net/">CIAO project</a>, "Modelling the Pathogenesis of COVID-19 Using the Adverse Outcome Pathway (AOP)". The overall goal is to organize and understand the vast amount of data that is constantly evolving as a result of the COVID-19 pandemic. This AOP-aligned systematic organisation of the knowledge allows to identify uncertainties and knowledge gaps. Many AOPs were developed in the CIAO project, each AOP focusing on a specific element of the SARS-COV-2 virus responses in humans. This AOP focuses on the acute respiratory distress associated mortality following viral infection of pulmonary cells by SARS-CoV-2 leading to cell death and excessive inflammatory repsonse. </div> </div>

Receptor recognition is an essential determinant of molecular level in this AOP. ACE2 was reported as an entry receptor for SARS-CoV-2. The viral entry process is mediated by the envelope-embedded surface-located spike (S) glycoprotein.  Jun Lan and Walls, A.C et al (Nature 581, 215–220; Cell 180, 281–292) demonstrated a critical initial step of infection at the molecular level from the interaction of ACE2 and S protein. ACE2 has shown that receptor binding affinity to S protein is nM range. To elucidate the interaction between the SARS-CoV-2 RBD and ACE2 at a higher resolution, they also determined the structure of the SARS-CoV-2 RBD–ACE2 complex using X-ray crystallography. The expression and distribution of the ACE2 in human body may indicate the potential infection of SARS-CoV-2. Through the developed single-cell RNA sequencing (scRNA-Seq) technique and single-cell transcriptomes based on the public database, researchers analyzed the ACE2 RNA expression profile at single-cell resolution. High ACE2 expression was identified in type II alveolar cells (Zou, X. et al. Front. Med.2020) SARS-CoV-2 belongs to the Coronaviridae family, which includes evolutionary related enveloped (+) strand RNA viruses of vertebrates, such as seasonal common coronaviruses, SARS-CoV and CoV-NL63, SARS-CoV (Kim Young Jun et al) <table cellspacing="0" class="Table" style="border-collapse:collapse; width:1248px"> <tbody> <tr> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:206px"> Human viruses strains </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:172px"> Genus </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:172px"> Major cell receptor </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:172px"> First report </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:172px"> Animal reservoir </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:204px"> Intermediate host </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:340px"> Pathology </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:252px"> Diagnostic test </td> <td style="background-color:#a5a5a5; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; height:19px; vertical-align:bottom; width:182px"> Evidence </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:206px"> HCoV-NL63 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Alphacoronavirus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> ACE2 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> 2004 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Bat </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:204px"> Unknown </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:340px"> Mild respiratory tract illness </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:252px"> RT-PCR, IF, ELISA, WB </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:182px"> Strong </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:206px"> SARS-CoV </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Betacoronavirus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> ACE2 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> 2003 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Bat </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:204px"> Pangolin </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:340px"> Severe acute respiratory syndrome </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:252px"> RT-PCR, IF, ELISA, WB </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:182px"> Strong </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:206px"> SARS-CoV-2 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Betacoronavirus </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> ACE2 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> 2020 </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:172px"> Bat </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:204px"> Pangolin </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:340px"> Severe acute respiratory syndrome </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:252px"> RT-PCR, IF, ELISA, WB </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; height:19px; vertical-align:bottom; width:182px"> Strong </td> </tr> </tbody> </table>

adjacent

High

High adjacent

Moderate

High adjacent

Moderate

High adjacent

Moderate

High adjacent

Not Specified

Not Specified adjacent

High

High adjacent

Not Specified

Not Specified non-adjacent

Not Specified

<div> <table class="table table-bordered table-fullwidth"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>Influence or Outcome</th> <th>KER(s) involved</th> </tr> </thead> <tbody> <tr> <td> Sex</td> <td> Higher risk for severe AO for males </td> <td>2056, 1703, 2354</td> </tr> <tr> <td>Age</td> <td> risk for more severe AO increases with age </td> <td>2056, 1703, 2354</td> </tr> <tr> <td>Obesity</td> <td>risk for more severe AO increases linearly with BMI increase, already starting at BMI >23 kg/m2</td> <td>2056, 1703, 2354</td> </tr> <tr> <td>Vit D deficiency</td> <td>Low vitamin D status prior to infection increases risk of higher AO severity </td> <td>2056 , 1703, 2354 </td> </tr> <tr> <td>Chemicals (PFAS, PFOS, PFOA, PFNA, PFHxS, and GenX)</td> <td>chemical exposure correlates with higher risk for AO severity</td> <td>2056, 1703, 2354</td> </tr> </tbody> </table> </div>

AOPWiki 2022-09-01T03:39:14

2023-09-25T16:27:12