Frontline Research

The novel pneumonia (COVID-19) was first reported in Wuhan city, Hubei province, China in December 2019. Next generation sequencing of an early patient on January 5th 2020 provided us the first complete viral genome (GenBank accession MN908947). Around 40,000 SARS-CoV-2 viral genomes from different countries are publicly available till now on GISAID ( These sequence data assisted the development of diagnostic tests and shortened our race to effective vaccine (

Human Biomarkers for COVID-19 treatment 

The rapid rise of SARS-CoV-2 infections has elicited different strategies for treating people suffering from COVID-19. The strategies depend also on the stage of infection defined by biomarkers. Of high interest are biomarkers found in the hyperinflammatory response because abnormal biomarker concentrations are found in patients suffering acute respiratory distress syndrome (ARDS) resulting more likely in death. 

Figure 1: Simplified view of viral infection, disease progression and proteins related to SARS-CoV-2. While the virus attacks intracellular mechanisms in the early phase (viral response phase), the second phase is marked by extracellular signaling response (hyperinflammatory response). Proteins within the viral response phase can be found in the interactome section. ARDS: Acute respiratory distress syndrome. 

The most specific treatment against SARS-CoV-2 is the human body’s own specific immune response. So, those who recovered from COVID-19, may donate their own polyclonal antibodies for neutralizing the viral infection in individuals experiencing symptoms. The availability of such donor samples, however, is limited. Other treatment strategies are either weakening the virus life cycle in the host (e.g. by antivirals) or dampening the misaligned immune response such as cytokine storms. Immune responses to COVID-19 are measured through various biomarkers (listed in the table below). They may be grouped in cytokines (7 types), receptors (3 types) and acute phase proteins (1 type). In addition to the biomarkers listed in the table, their targeting antibodies currently in clinical trials are also listed. The top biomarker, such as IL6, IL1 and IFNB1, has more than 5 clinical trial studies ongoing. 

Targets/Biomarker Family Group Mechanism of action Reaction to COVID  Drug/API NCT Refs 
Interleukin-6 (IL6) Cytokine Pleiotropic, i.e. different stimulating effects Increased concentrationKevzara/Sarilumab; 
16 Studies
58 Studies
3 Studies 
Interleukin-1 (IL1B) Cytokine Triggers proinflammation  Increased concentration Ilaris/Canakinumab; 
3 Studies
20 Studies
No Studies 
Interferon Beta 1 (IFNB1) Cytokine Promotes interfering with viral replication Suppressed in early phase, increased in mid/later stage Interferon Beta-1A; 
Interferon Beta-1B 
7 Studies
3 Studies 
VEGFA Cytokine Angiogenesis Increased concentration Avastin/Bevacizumab 
3 Studies (4) 
Chemotactic cytokine ligand 5 (CCL5) Cytokine Triggers inflammation  Increased concentration PRO140/Leronlimab 2 Studies (5) 
Granulocyte-macrophage colony-stimulating factor (CSF2) Cytokine Stimulates immune response Increased concentration Leukine/Sargramostim
3 Studies
3 Studies
1 Study 
Interferon Gamma 1 (IFNG) Cytokine Promotes antiviral and immunoregulatory responses Increased concentration Gamifant/ Emapalumab 1 Study (7) 
Basigin (CD-147, BSG) Receptor Receptor for ligand CyPA for triggering inflammatory chemotaxis Receptor for Spike protein Nucala/Meplazumab 1 Study (8) 
Complement protein C5 Acute phase protein Is cleaved into C5a and C5b resulting in cell lysis Increased cleaved C5b Soliris/Eculizumab 
4 Studies; 
2 Studies 
Programmed cell death protein 1 (PD-1) Receptor Suppress immune response Hyperactivated PD-1 on CD4- and CD8-T-cells Opdivo/Nivolumab 4 Studies (10) 
CD14 Receptor Receptor for binding lipopolysaccharide Triggers inflammatory response IC14 2 Studies (11) 

The current study indicates that upon SARS-CoV-2 infection, a cytokine storm happens thus causes acute respiratory distress syndrome (ARDS). In this situation, large amounts of pro-inflammatory cytokines (IFNα, IFNγ, IL-1β, IL-6, IL-12, IL-18, IL-33, TNFα, TGFβ) and chemokines (CXCL10, CXCL8 (IL-8), CXCL9, CCL2, CCL3, CCL5) are released (12), which in turn will cause ARDS and multiple organ failure. Going forward, we will see new antibody drugs to be developed targeting those biomarkers to treat COVID-19 patients.


1. Wan, Suxin, et al. Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID‐19) infected patients. British Journal of Haematology. Apr 2020. 

2. Ong, Eugenia Ziying, et al. A Dynamic Immune Response Shapes COVID-19 Progression. Cell Host & Microbe. Apr 2020. 

3. Sallard, Erwan, et al. Type 1 interferons as a potential treatment against COVID-19. Antiviral Research. Jun 2020. 

4. Huang, Chaolin, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. Feb 2020. 

5. Patterson, Bruce K, et al. Disruption of the CCL5/RANTES-CCR5 Pathway Restores Immune Homeostasis and Reduces Plasma Viral Load in Critical COVID-19. Medrxiv. May 2020. 

6. Schett, Georg, Sticherling, Michael and Neurath, Markus F. COVID-19: risk for cytokine targeting in chronic inflammatory diseases? Nature Reviews Immunology. Apr 2020. 

7. Pedersen, SF and Ho, YC. SARS-CoV-2: a storm is raging. The journal of Clinical Investigation. Mar, 2020. 

8. Bian, Huijie, et al. Meplazumab treats COVID-19 pneumonia: an open-labelled, concurrent controlled add-on clinical trial. medrxiv. Mar 2020. 

9. Diurno, F, et al. Eculizumab treatment in patients with COVID-19: preliminary results from real life ASL Napoli 2 Nord experience. European Review for Medical and Pharmacological Sciences. Apr 2020. 

10. Diao, Bo, et al. Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19). Frontiers in Immunology. May 2020. 

11. J.Giamarellos-Bourboulis, Evangelos, et al. Complex Immune Dysregulation in COVID-19 Patients with Severe Respiratory Failure. Cell & Host Microbe. Apr 2020. 

12. Coperchini, et al. The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. Cytokine Growth Factor Rev . 2020 May 11

SARS-CoV-2 exploits biomarker IL1B

In patients severely suffering from SARS-CoV-2 infection, IL1B has been reported to be abnormally elevated. The major driver of upregulating IL1B is a multiprotein complex of the innate immune system, the NLRP3/ASC/CASP1 inflammasome. It is a protein multimer formed by Nod-like receptor (NLR) family pyrin domain containing family (NLRP3), a member of the caspase-recruitment domain-containing proteins (PYCARD/ASC) and the caspase CASP1. The gene expression of NLRP3, inactivated precursor pro-caspase-1 and also pro-IL1B is upregulated by viral detection mechanisms similar to IL6 (1) or through IL-6 in neutrophils (2). Then the assembly process towards forming the inflammasome is initiated through sensing events owing to viral infection. One protein class sensing viral RNA is DExD/H-box helicase, a recognizing pathogen-associated molecular patterns (PAMP) (3, 4). Other sensors monitor damage-associated molecular patterns (DAMPs); include cellular concentration imbalances (such as K+-efflux and raised levels of reactive oxygen species), DNA from dysfunctional mitochondria and SARS-CoV viroporins which is relevant for viruses to initiate cell lysis to spread the viral particles (5, 6). Such protein domains as sensors then trigger the downstream signaling towards activating the caspases through caspase-recruitment domain-containing proteins (7). The activated cysteine protease CASP1 cleaves amino acids of the inactivated precursors especially rendering IL1B active.

Figure 1: NLRP3, PYCARD and CASP1 inflammasome pathway for producing IL1B. Inflammasome-activating stimuli are AIM2, DHX33, NEK7, NOD1 and TXNIP. AIM2 senses cytosolic DNA (8); DHX33 is a member of DExH-box helicases sensing viral RNA; NEK7 reacts to K+ efflux (9); NOD1 senses viral RNA (10); and TXNIP is induced by ROS as to counteract these (11).  Interacting with the caspase-recruitment domain-containing proteins such as PYCARD, CARD8, NLRC4 and NLRP1 finally activates the caspases such as CASP1, CASP5 and CASP8.

Cells produce IL1B either through membrane pores (12), lysosomes (13) or cell lysis through apoptosis (14). Secreted IL-1B interacts with interleukin-1 receptor type 1 or 2 (IL1R1 or IL1R2) that are soluble or membrane-bound. While soluble receptor inhibits the effect of IL1B (15), membrane-bound IL1R1 found on monocytes, macrophages or dendritic cells, upon binding to IL1B, attract interleukin-1 receptor-associated kinases resulting in NF-κB kinase signaling pathway (16, 17) and stimulating gene expression of cytokines and interferons (18, 19). In addition, the receptor IL1R2 is known to counteract the aforementioned signaling pathway (20, 21), to partake in regulating STAT3 signaling (22) and to regulate the exocyst complex that has a role in viral defense mechanism (18).

Figure 2: Signaling pathways elicited by IL1B. Together with other interleukins, IL1B triggers gene expression of other cytokines through adaptor proteins (MYD88, TICAM2), signaling proteins (TOLLIP, TRAF6) and IL1-receptor associated kinases (IRAK1, IRAK2, IRAK4) resulting in upregulation of other cytokines (23). This is inhibited by the signaling pathways through binding of IL1B to IL1R2. The interleukin-1 receptor antagonist IL1RN inhibits the activities by IL1B (and IL1A).

Allelic variation of Ticam2 in mice, an adaptor protein interacting with IL1R1, has been reported to contribute to SARS-CoV infection (24). In addition, SARS-CoV-2 spike protein boosts secretion of IL1B in macrophages, thus antagonists against IL1B are considered for treatment (25). Finally, the interleukins IL37 and IL38, both suppressing IL1B activity, have been highlighted for treating COVID-19 patients as well (26). The active pharmaceutical ingredient Anakrina, an antagonist for IL1B for inhibiting tumour growth in breast cancer and bone metastasis (27), Canakinumab and Rilonacept, blocking IL1B for treating diseases such as arthritis are of interest for treating COVID-19 patients.


1. Swanson, Karen V., et al. A noncanonical function of cGAMP in inflammasome priming and activation. Journal of Experimental Medicine. Dec 2017.

2. Dinarello, Charles A. Overview of the IL-1 family in innate inflammation and acquired immunity. Immunological Reviews. Dec 2017.

3. Mitoma, Hiroki, et al. The DHX33 RNA Helicase Senses Cytosolic RNA and Activates the NLRP3 Inflammasome. Immunity. July 2013.

4. Cheng, Wenyu, et al. DDX5 RNA Helicases: Emerging Roles in Viral Infection. International Journal of Molecular Sciences. April 2018.

5. Zhao, Chunyuan Zhao and Wei. NLRP3 Inflammasome—A Key Player. Frontiers in Immunology. Feb 2020.

6. Castaño-Rodriguez, Carlos, et al. Role of Severe Acute Respiratory Syndrome Coronavirus Viroporins E, 3a, and 8a in Replication and Pathogenesis. American Society for Microbiology. May 2018.

7. Broz, Petr and Dixit, Vishva M. Inflammasomes: mechanism of assembly, regulation and signalling. Nature Reviews Immunology. Jun 2016.

8. Rathinam, Vijay A K, et al. The AIM2 inflammasome is essential for host defense against cytosolic bacteria and DNA viruses. Nature Immunology. Mar 2010.

9. He, Yuan, et al. NEK7 Is an Essential Mediator of NLRP3 Activation Downstream of Potassium Efflux. Nature. Jan 2016.

10. MarijkeKeestra-Gounder, A. and M.Tsolis, Renée. NOD1 and NOD2: Beyond Peptidoglycan Sensing. Trends in Immunology. Oct 2017.

11. Muri, Jonathan, et al. Thioredoxin-1 distinctly promotes NF-κB target DNA binding and NLRP3 inflammasome activation independently of Txnip. Elife. Feb 2020.

12. Ding, Jingjin, et al. Pore-forming activity and structural autoinhibition of the gasdermin family. Nature. Jun 2016.

13. Vince, James E. and Silke, John. The intersection of cell death and inflammasome activation. Apr 2016.

14. Shi, Jianjin, Gao, Wenqing and Shao, Feng. Pyroptosis: Gasdermin-Mediated Programmed Necrotic Cell Death. Trends in Biochemical Sciences. Apr 2017.

15. Smith, Dirk E, et al. The Soluble Form of IL-1 Receptor Accessory Protein Enhances the Ability of Soluble Type II IL-1 Receptor to Inhibit IL-1 Action. Immunity. Jan 2003.

16. Romay, Milagros C., et al. Regulation of NF-kB signaling by oxidized glycerophospholipid and IL-1b induced miRs-21-3p and -27a-5p in human aortic endothelial cells. Journal of Lipid research. Oct 2014.

17. Taniguchi, Koji and Karin, Michael. NF-κB, inflammation, immunity and cancer: coming of age. Nature review immunology. Jan 2018.

18. Takeuchi, Osamu and Akira, Shizuo. Pattern Recognition Receptors and Inflammation. Cell. Mar 2010.

19. Whitley, Sarah K., et al. IL-1R signaling promotes STAT3 and NF-κB factor recruitment to distal cis-regulatory elements that regulate Il17a/f transcription. Journal of Biological Chemistry. Aug 2018.

20. Garlanda, Cecilia, Dinarello, Charles A. and Mantovani, Alberto. The Interleukin-1 Family: Back to the Future. Immunity. Dec 2013.

21. Schlüter, Thomas, et al. Regulation of IL-1 signaling by the decoy receptor IL-1R2. Journal of Molecular Medicine. Aug 2018.

22. Kuchipudi, Suresh V. The Complex Role of STAT3 in Viral Infections. Journal of Immunology Research. Jun 2015.

23. Muroi, Masashi and Tanamoto, Ken-ichi. TRAF6 Distinctively Mediates MyD88- And IRAK-1-induced Activation of NF-kappaB. The Journal of Leukocyte Biology. Mar 2008.

24. Gralinski, Lisa E., et al. Allelic Variation in the Toll-Like Receptor Adaptor Protein Ticam2 Contributes to SARS-Coronavirus Pathogenesis in Mice. Genes, Genomes and Genetics. Jun 2017.

25. SJ, Theobald, et al. The SARS-CoV-2 spike protein primes inflammasome-mediated interleukin-1- beta secretion in COVID-19 patient-derived macrophages. Research Square (Preprint). May 2020.

26. Conti, P., et al. Induction of Pro-Inflammatory Cytokines (IL-1 and IL-6) and Lung Inflammation by Coronavirus-19 (COVI-19 or SARS-CoV-2): Anti-Inflammatory Strategies. Journal of biological regulators and homeostatic agents. Mar 2020.

27. Tulotta, Claudia and Ottewell, Penelope. The role of IL-1B in breast cancer bone metastasis. Endocrine-Related Cancer. Jul 2018.

Interleukin-6 in COVID: The misaligned signaling in immunity 

Recent clinical trials have investigated the effectiveness of IL6 antibodies (siltuximab) or IL6-receptor antagonists (sarilumab, tocilizumab) for treating COVID-19 patients. IL6 level is significantly elevated in COVID-19 patients with severe condition compared to those having non-severe condition (1, 2). Clinical studies on COVID-19 with tocilizumab indicated beneficial outcomes while the suppression of IL6 levels may promote bacterial and viral infections so that its usage was not suggested for routine usage (3). This review describes the pathway around IL6 during coronavirus infection suggesting why related antibodies may offer entry points for COVID-19. 

Cells in the host innate immune system such as dendritic and lung epithelial cells detect viral infections by recognizing viral dsRNA through pattern recognition receptor (PRR) such as Toll-like receptor (TLRs such as TLR3 and TLR7) and RIG-1-like receptors (RLRs such as IFIH1 and DDX58). This recognition triggers signaling pathways like NF-κB kinase (IKBKB, IKBKE), interferon regulatory transcription factor (IRF3, IRF7), tumor necrosis factor (TNF), c-Jun-N-terminal kinase (JNK), and JNK-mitogen activated protein kinase (MAPK), which results in upregulation of IL6 gene expression – a cytokine that subsequently activates the immune response to counteract the viral infection, produced 24h earlier than interferons (IFNs) (4).

Coronaviruses, however, leverage their own molecular mechanisms to impede the recognition patterns. For example, the cell’s RLRs (IFIH1 and DDX58) and TLRs (TLR3 and TLR7) are suppressed; in addition, the cell’s signaling downstream pathway through molecules (IRF3 and NF-κB) triggered by PRR is weakened by coronavirus’ papain-like protease (PLpro). It has been reported that coronavirus dampens the kinetic response of the cell’s immune system towards boosting its own viral replication, resulting in a delayed response, in an uncontrolled expression of IL6 and in a cytokine storm (5).  

IL6, a member of the interleukin-6 family, binds to a non-signaling cognate receptor (IL6R) which is present in membrane-bound and soluble form. This IL6/IL6R complex in turn interacts with the IL6 signal transducer (IL6ST; alias name gp130) that is present in either membrane-bound or soluble form as well. Membrane-bound IL6ST activated by IL6/IL6R initiates signaling pathways mainly through JAK-STAT  (6). The soluble IL6ST, which is present in later stages of a normal inflammation response, acts as an antagonist against triggering cellular signaling through membrane-bound IL6ST (7). The resulting effect of IL6 signals depends on cell type and other signaling molecules. The cytokine IL6 is known to be pleiotropic, i.e. it has different stimulating effects (8). In particular, IL6 takes an important role in transitioning from innate to acquired immune response (9).

The table lists a few leukocytes that react to IL6:  

Leukocyte Stimulating Cytokine Effect 
B-cell IL6 Initiates Transition from B-cells into plasma cells (10).
Neutrophils IL6 Regulates neutrophils (11).  
(transitioning from innate to adaptive immune response) 
Neutrophils IL6, IL23 Neutrophils start production of IL17 (12). 
Naïve CD4+ IL6, IL17 Promotes differentiation into Th17 (targets pathogens at mucosal sites) while repressing differentiation into regulatory T-cells (13). 
Naïve CD4+ IL6, IL21 Promotes differentiation into follicular helper T-cell (TFH) that drives B-cell immune response; also repressing regulatory T-cells that suppress B-cell response (14).
CD8 IL6, IL7, IL15 Promotes CD8 proliferation and increases cytolytic activity. It has been reported that CD8 T cells undergo different phases against viral infection (15). 

Overexpression of IL6 during viral infection, however, is correlated with viral persistence (16). In addition, abnormal raised Th17 cell levels are known for damaging tissue as occurring in autoimmune diseases (17). Inhibitors against IL-6, IL-6R and JAK have therapeutic effects on these autoimmune diseases (18).  Compared to mildly suffering patients from SARS-CoV-1 or MERS-CoV infection, patients severely suffering have elevated levels of cytokines including IL6 and neutrophils while CD8 T-cell counts is decreased (19). Recent findings on SARS-CoV-2 conclude similar result arguing these viruses may deploy strategies to distort the natural immune response elicited by IL6 and triggered by IL6R (2, 20, 21, 22, 23).


1. Ulhaq, Zulvikar Syambani and Soraya, Gita Vita. Interleukin-6 as a potential biomarker of COVID-19 progression. Médecine et Maladies Infectieuses. April 2020. 

2. Wan, Suxin, et al. Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID‐19) infected patients. British Journal of Haematology. Apr 2020. 

3. Kimmig, Lucas M. et al. IL6 inhibition in critically ill COVID-19 patients is associated with increased secondary infections. medRxiv. Jul 2020.

4. Yoshikawa, Tomoki, et al. Dynamic Innate Immune Responses of Human Bronchial Epithelial Cells to Severe Acute Respiratory Syndrome-Associated Coronavirus Infection. Plos One. Jan 2010. 

5. Liu, Bingwen, et al. Can we use interleukin-6 (IL-6) blockade for coronavirus disease 2019 (COVID-19)-induced cytokine release syndrome (CRS)? Journal of Autoimmunity. Apr 2020. 

6. Rose-John, Stefan. Interleukin-6 Family Cytokines. Cold Spring Harbor Perspectives in Biology. Feb 2018. 

7. Hurst, Suzanne M, et al. IL-6 and Its Soluble Receptor Orchestrate a Temporal Switch in the Pattern of Leukocyte Recruitment Seen during Acute Inflammation. Immunity. Jun 2001. 

8. Tanaka, Toshio, Narazaki, Masashi and Kishimoto, Tadamitsu. IL-6 in Inflammation, Immunity, and Disease. Cold Spring Harbor Perspectives in Biology. Sep 2014. 

9. Jones, Simon A. Directing Transition from Innate to Acquired Immunity: Defining a Role for IL-6. The Journal of Immunology. Sep 2005. 

10. Muraguchi, A, et al. The essential role of B cell stimulatory factor 2 (BSF-2/IL-6) for the terminal differentiation of B cells. Journal of Experimental Medicine. Feb 1988. 

11. Fielding, Ceri A., et al. IL-6 Regulates Neutrophil Trafficking during Acute Inflammation via STAT3. The Journal of Immunology. Aug 2008. 

12. Taylor, Patricia R, et al. Activation of neutrophils by autocrine IL-17A–IL-17RC interactions during fungal infection is regulated by IL-6, IL-23, RORγt and dectin-2. Nature Immunology. Dec 2013. 

13. Guglani, Lokesh and Khader, Shabaana A. Th17 cytokines in mucosal immunity and inflammation. Current Opinion in HIV and AIDS. Mar 2010. 

14. Deng, Jun, et al. T follicular helper cells and T follicular regulatory cells in rheumatic diseases. Nature Reviews Rheumatology. Jul 2019. 

15. A.Cox, Maureen, M.Kahan, Shannon and J.Zajac, Allan. Anti-viral CD8 T cells and the cytokines that they love. Virology. Jan 2013. 

16. Velazquez-Salinas, Lauro, et al. The Role of Interleukin 6 During Viral Infections. Frontiers in Microbiology. May 2019. 

17. Kimura, Akihiro and Kishimoto, Tadamitsu. IL‐6: Regulator of Treg/Th17 balance. European Journal of Immunology. Jun 2010. 

18. Jones, Britta E, Maerz, Megan D and Buckner, Jane H. IL-6: a cytokine at the crossroads of autoimmunity. Current Opinion in Immunology. Dec 2018. 

19. Channappanavar, Rudragouda and Perlman, Stanley. Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Seminars in Immunopathology. May 2017. 

20. Li, Xiaowei, et al. Molecular immune pathogenesis and diagnosis of COVID-19. Journal of Pharmaceutical Analysis. Apr 2020. 

21. Zheng, Meijuan, et al. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Nature Cellular & Molecular Immunology. Mar 2020. 

22. Diao, Bo, et al. Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19). Frontiers in Immunology. May 2020. 

23. Zhang, Chi, et al. The cytokine release syndrome (CRS) of severe COVID-19 and Interleukin-6 receptor (IL-6R) antagonist Tocilizumab may be the key to reduce the mortality. International Journal of Antimicrobial Agents. Mar 2020. 

IFNB1 signaling distorted by SARS-CoV-2

Interferon β-1 (IFNB1) is a member of the interferon family that interferes with lifecycle of pathogens such as viruses. The immune response to pathogens, similar to the cases of IL6 and IL1, is orchestrated by detecting distinctive structures on pathogens (pathogen-associated molecular patterns (PAMP)) and by danger-associated molecular patterns (DAMPs) and then by relaying the signaling cascades to interferon regulatory factors (IRF). Upon PAMP and/or DAMP involvments, members of the IRF family bind specifically to interferon stimulated response element (ISRE), a conserved regulatory element of DNA sequences, that ultimately trigger gene expression of interferons, including IFNB11,2. Clinical studies that investigate the effect of IFBN1 on COVID-19 treatment are ongoing, therefore, this summary sheds light on the inflammatory impact of IFBN1 on SARS-CoV-2 lifecycle and how the virus subvert host defenses elicited by interferon inflammatory signaling.

Figure 1: IFNB1 and IRFs within cellular signaling against viral pathogens. Detecting viral components by proteins of genes such as DDX58, IFIH1 and OASL activate downstream signaling molecules (TRAF3, TBK1, TANK, IKBKE, MAVS, JUN, RELA). In response to interferons and interferon regulatory factors (IRF), counteracting viral replication (by ISG15, CIITA, IFIT1, MX1 and RSAD2 proteins) and gene expression regulation (by MYD88, STAT1, STAT2, CREBBP and IRF2BP1 proteins) are promoted. Cytokines like IFNγ and IL1B also indirectly activate upregulation of IFNB1 through e.g. autocrine or paracrine signaling while inhibitory proteins such as SOCS1 control this upregulation. 

Interferon IFNB1 belongs to a class of interleukins known for binding to the receptors IFNAR1 and IFNAR2, which activate the JAK-STAT pathway resulting in upregulating interferon simulating genes (ISG)3. ISGs include other cytokines resulting in upregulation of molecular machineries that divert and eradicate viral infection by activating leukocytes and triggering adaptive immune response4,5. Specifically in SARS-CoV-2 infection, 83 ISGs were upregulated indicating a robust IFN response and ultimately potentiating IFN signaling by an increased expression of some ISGs6

However, cellular regulation of IFNB1 expression was of importance because abnormal elevated levels of IFNs were found to induce tissue damage or immunosuppression – depending on the cellular and pathogen context that is driven by IFNB17. In cases of SARS-CoV infection, a delayed IFN response has been correlated with severe pneumonia; only early administration of IFNB1 has been reported to be beneficial in mice models8. In contrast to SARS-CoV, it has been reported that SARS-CoV-2 increased viral load before symptom onset9. SARS-CoV-2’s non-structural protien 1 (nsp1) distorted IFNB1 signaling and anti-viral ISG expression10. A phase 2 clinical study indicated that IFNB1 impeded viral replication in patients with SARS-CoV-2 and subsequently improved lung disease progression11. In conclusion, the immune response relies heavily on IFNB1 signaling that needs to be monitored closely in COVID patients.


1. The IRF Family Transcription Factors in Immunity and Oncogenesis, Tamura et al., Annual Review of Immunology (2008): 

2. DNA-binding landscape of IRF3, IRF5 and IRF7 dimers: implications for dimer-specific gene regulation, K. K. Andrilenas, Nucleic Acids Research (2018):

3. Advances in anti-viral immune defence: revealing the importance of the IFN JAK/STAT pathway, N. Raftery and N.J. Stevenson, Cellular and Molecular Life Sciences (2017):  

4. Regulation of type I interferon responses, Ivashkiv et al., Nature Reviews Immunology (2013): 

5. IFNβ‐dependent increases in STAT1, STAT2, and IRF9 mediate resistance to viruses and DNA damage, Cheon et al., The EMBO Journal (2013):  

6. Heightened Innate Immune Responses in the Respiratory Tract of COVID-19 Patients, Zhou et al., Cell Host & Microbe (2020):  

7. Type I interferons in infectious disease, F. McNab et al., Nature Reviews Immunology (2015):  

8. Dysregulated Type I Interferon and Inflammatory Monocyte-Macrophage Responses Cause Lethal Pneumonia in SARS-CoV-Infected Mice, Channappanavar et al., Cell Host & Microbe (2016):  

9. SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients, Zou et al., The New England Journal of Medicine (2020):  

10. Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2, Thoms et al., bioRxiv preprint (2020):  

11. Triple combination of interferon beta-1b, lopinavir–ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial, Hung et al., The Lancet (2020):   

Microbiome effect on human health and disease 

The human microbiome is the collection of all the microorganisms living within the human body. They can be found in and on nearly every part of the body, including the gut, skin, respiratory, urinary and vaginal tracts. The human microbiota, estimated as ∼1013–1014 microbial cells, is made up of bacteria, archaea, viruses (bacteriophages) and eukaryotic microbes. Ever-growing evidence has demonstrated that changes in the compositions of the human gut microbiome are correlated with numerous disease states, including inflammatory bowel disease (IBD), obesity, diabetes, cancer, heart disease, autoimmune diseases, and emerging infectious diseases (Brody 2020, Shreiner et al., 2015).

Examples of disease associated with human intestine microbiome

Detection of COVID-19 in human intestines and feces and public health concern over fecal viral transmission

Although respiratory tract manifestations are the most commonly reported symptoms in COVID -19, the growing data suggest that the gastrointestinal tract is also affected by COVID-19. Based on their meta-analysis of the data from 35 studies, including 6686 patients with COVID-19, Ren Mao and colleagues (2020) recently reported that COVID-19 patients in 29 studies (6064 cases) were found to have gastrointestinal symptoms. In comparison to patients with non-severe disease, patients with severe COVID-19 had a higher risk of developing gastrointestinal symptoms (Mao et al, 2020). 

A dozen groups have detected COVID-19 in feces in their individual labs. Through intracellular staining of viral nucleocapsid protein in duodenal and rectal epithelia, Xiao et al. confirmed detection of COVID-19 in human duodenal, and rectum glandular epithelial cells. Prolonged presence of COVID-19 viral RNA has been documented in fecal samples. For example, 23.29% of 78 patients in the study continued to have positive stool results even after showing negative results in respiratory samples (Xiao et al., 2020). This raised public health concerns over fecal-oral transmissions of COVID-19 in addition to respiratory transmission.

Interactions between COVID-19 and the human gut and microbiome; can the microbiome predict COVID-19 disease severity and treatment response?

Entry of COVID-19 into human cells is dependent on angiotensin converting enzyme 2 (ACE2). The ACE2 receptor is expressed in many tissues throughout the body, especially lung tissue. The human ileum and colon express high levels of ACE2, but its expression is reduced in the gut of Crohn’s disease patients (Potdar et al.,2020). An early study with principal coordinate analysis plots has demonstrated that mutations of the ACE2 receptor gene in mice could directly lead to the gut microbiome composition variations and intestinal inflammation.

A small case study showed that some patients have an altered gut microbiota composition, with depleted Lactobacillus and Bifidobacterium (Mak et al., 2020). Recently, Guo et al. (2020) examined the fecal microbiome using 16s RNA sequencing technology from 31 COVID-19 patients (13 severe disease and 18 non-severe). Though Guo et al. (2020) did not perform further analysis to characterize changes of bacterial composition and abundance between healthy controls and COVID-19 patients, they attempted to utilize the microbiome to predict COVID-19 disease severity through their proteomic risk score (PRS). Though their work could be expanded, they developed the first model to predict COVID-19 disease progression from the fecal microbiome.

Overall our current understanding is still quite limited in following areas, 1) how COVID-19 impacts the human gut and disease, 2) how the microbiome impacts COVID-19 infection and disease progression, and 3) how the interaction between COVID-19 and the microbiome impacts public health. We will keep updating exciting discoveries in this field.   


  1. Herb Brody, The Gut Microbiome, Nature, 2020.
  2. Andrew B. Shreiner, John Y. Kao, and Vincent B. Young, The gut microbiome in health and in disease, Curr Opin Gastroenterol. 2015
  3. Mao et al., Manifestations and prognosis of gastrointestinal and liver involvement in patients with COVID-19: a systematic review and meta-analysis, Lancet Gastroenterol Hepatol. 2020
  4. Gou, Wanglong, Yuanqing Fu, Liang Yue, Geng-dong Chen, Xue Cai, Menglei Shuai, Fengzhe Xu, et al. “Gut Microbiome May Underlie the Predisposition of Healthy Individuals to COVID-19.” MedRxiv, April 25, 2020, 2020.04.22.20076091.
  5. F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for Gastrointestinal Infection of SARS-CoV-2. Gastroenterology. 2020 May;158(6):1831
  6. ., Reduced expression of COVID-19 host receptor, ACE2 is associated with small bowel inflammation, more severe disease, and response to anti-TNF therapy in Crohn’s disease, MedRxiv, April 23, 2020
  7. Joyce W Y Mak, Francis K L Chan, and Siew C Ng, Probiotics and COVID-19: one size does not fit all, Lancet Gastroenterol Hepatol. 2020 Apr 25

Can human gut microbiome predict COVID-19 disease severity?

The recent publication entitled with “Gut microbiota may underlie the predisposition of healthy individuals to COVID-19” in MedRxiv was widely reported by a collection of social media. In this paper, the authors demonstrated that gut microbiota could predict severity of COVID-19. Its research workflow is shown below,     

Main findings in this work:

1. With 20 proteomic biomarkers, Guo et al. (2020) developed a COVID-19-related proteomic risk score (PRS) system allowing to associate COVID-19 disease severity.

2. They next assessed the validity of PRS – values on prediction of COVID-19 severity using 31 COVD-19 patient data including disease severity and 20 proteomic biomarkers. Poisson regression analysis indicated that risk ratio (RR) is 1.57, suggesting that per 10% increment in the PRS, there was associated a 57% higher risk of progressing to clinically severe phase.

3. Using the gut bacterial16s rRNA sequencing results and blood proteomics data from 301 participants, the authors further investigated relationship between the gut microbiota and the PRS scores using light GBM machine learning algorithm.

  • First, they identified top 20 predictive operational taxonomic units (OTUs). The results showed that the subset of core OTUs explained an average 21.5% of the PRS variation (mean out-of-sample R2=0.215 across ten cross-validations).
  • Next, Pearson correlation analysis indicated that the correlation coefficient between the core OTUs-predicted PRS and actual PRS for their cross-sectional dataset (n=132) reached to 0.59 (p<0.001), while this number was 0.18 for their independent prospective subset of the individuals (n=169).

4.The top OTUs associated with PRS identified in this study include Bacteroides genus, Streptococcus genus, Lactobacillus genus, Ruminococcaceae   family, Lachnospiraceae family and Clostridiales order


  • Success for prediction of COVID-19 disease severity with patients’ microbiome data was largely dependent on how well the proteomic risk score (PRS) in its prediction of COVID-19 diseases progression. Given the fact that the same 31 COVID-19 patients that were used to construct PRS score system were also used to assess the PRS score prediction performance, current validation test was insufficient. It is suggested that additional tests using data set from a collection of independent CORVID-19 patients were needed.
  • In addition, correlation was moderate (0.58) between predicted PRS scores based on microbiome data with measured PRS scores in non-COVID19 cross-sectional cohort study, and this correlation became 0.18 in non-COVID-19 prospective cohort study. Note that further tests with COVID-19 patients are needed to verify such findings.
  • It should also be noted that approximately 58 to 71% of COVID-19 patients in China took antibiotics that likely impacted patients’ microbiome compositions and abundance. Taking antibiotics may in turn affect on the accurate prediction of COVID-19 disease severity from patients’ microbiome data. 


Gou, Wanglong, Yuanqing Fu, Liang Yue, Geng-dong Chen, Xue Cai, Menglei Shuai, Fengzhe Xu, et al. “Gut Microbiome May Underlie the Predisposition of Healthy Individuals to COVID-19.” MedRxiv, April 25, 2020, 2020.04.22.20076091.

Covid-19 detected in patient’s intestine and feces, and concerns over Covid-19 fecal-oral rout transmission

The infection of COVID-19 is typically characterized by respiratory symptoms (Mao et al., 2020). However, a few studies reported that a fraction of COVID-19 patients also experienced some gastrointestinal (GI) symptoms. In a recent paper published in Gastroenterology, Xiao et al. (2020) examined COVID-19 RNA from 73 Covid-19 patients’ feces during their hospitalizations. To confirm whether COVID-19 can be detected in human intestine, they further conducted intracellular staining of viral nucleocapsid protein in duodenal and rectal epithelia. Finally, they attempted to explore potential mechanisms by which CORVID-19 interacts with the gastrointestinal tract through examination of gene expressions of human intestine angiotensin converting enzyme 2 (ACE2), as it was shown that CORVID-19 uses ACE2 as a viral receptor in respiratory system (Potdar et al 2020). A few important findings include:

  1. Using China Disease Control and Prevention–standardized quantitative polymerase chain reaction assay, Xiao et al. revealed that 53.42% (39 patients) of 73 patients had COVID-19 in their feces, in which patients’ ages ranged from 10 months to 78 years old. Interestingly, 17 patients (23.29%) continued to have positive results in stool even after showing negative results in their respiratory samples.
  2. The immunofluorescent data showed that ACE2 protein, a cell receptor for SARS-CoV-2, was abundantly expressed in the glandular cells of gastric, duodenal, and rectal epithelia, supporting the entry of SARS-CoV-2 into the host cells. ACE2 staining was rarely seen in esophageal mucosa, probably because the esophageal epithelium is mainly composed of squamous epithelial cells, which express less ACE2 than glandular epithelial cells.
  3. Staining of viral nucleocapsid protein was visualized in the cytoplasm of gastric, duodenal, and rectum glandular epithelial cell.
  4. Gastrointestinal endoscopy test indicated that the mucous epithelium of esophagus, stomach, duodenum, and rectum showed no significant damage with haematoxylin and eosin (H&E) staining. But in lamina propria of the stomach, duodenum, and rectum, numerous infiltrating plasma cells and lymphocytes with interstitial edema were seen.


  1. Detection of COVID-19 in patients’ feces raised concern over potential fecal–oral transmission. However, current knowledge on fecal is still limited, and additional studies are needed to clarify and assess the potential for fecal–oral transmission.
  2. Though COVID-19 was found in intestine and feces, the mechanisms by which COVID-19 interacts with the gastrointestinal tract remain unknown.


Xiao F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for Gastrointestinal Infection of SARS-CoV-2.Gastroenterology. 2020 May;158(6):1831

Potdar et al., Reduced expression of COVID-19 host receptor, ACE2 is associated with small bowel inflammation, more severe disease, and response to anti-TNF therapy in Crohn’s disease, MedRxiv, April 23, 2020

CRISPR was initially discovered as a part of bacterial immune systems for responding to viruses and was modified to allow gene editing (1). The CRISPR system has been modified beyond gene editing to allow for gene regulation, imaging, chromatin engineering, and epigenetic editing (1). Because of their versatility, CRISPR-based methods have been studied for the diagnosis and treatment of COVID-19.

Multiple methods using CRISPR/Cas have been developed and implemented for viral detection to provide reliable, rapid, and portable detection techniques for COVID-19. For example, a CRISPR/Cas13-based assay named the SHERLOCK technique (Specific High sensitivity Enzymatic Reporter unLOCKing) was developed by Kellner et al. (2020) for the detection of COVID-19 and was approved by FDA for emergency use to screen clinical samples (2, 3).  This method employed synthetic SARS-CoV-2 RNA fragments to detect target COVID-19 sequences in less than an hour without relying on thermal cyclers, and the current COVID-19 screening standard (2). Additionally, CRISPR/Cas12a-NER was developed by Wang et al. (2020); this fluorescence-based technology was readable by the naked eye and can detect as few as 10 viral RNA copies in 45 minutes without using thermal cycler (4). Meanwhile, CRISPR-Cas12 DETECTOR assay was developed as a lateral flow-based assay to detect SARS-CoV-2 in less than 40 minutes with high sensitivity and specificity (5). Likewise, other detection assays were developed to screen multiple viruses in parallel. CARMEN-Cas13, a Multiplexed Microwell Array platform, was able to detect 169 different human associated viruses, including SARS-CoV-2 simultaneously (6).

        Not only have CRISPR-based methods been developed for diagnosis, CRISPR-based technologies have also been investigated for potential treatments of COVID-19. For example, prophylactic antiviral CRISPR in human cells (PAC-MAN), another CRISPR/Cas13 based technology, was shown to degrade SARS-CoV-2 in human lung epithelial cells and resulted in the reduction of viral load in these cells (7). Similarly, a CRISPR/Cas13d system was used to cleave the SARS-CoV-2 viral RNA in a study under review; this system allows for flexibility in gRNA design for targeting different viral strains (8).


  1. Adli M. 2018. The CRISPR tool kit for genome editing and beyond. Nature Communications. 9: 1911.
  2. Kellner M.J., J.G. Koob, J.S. Gootenberg , O.O. Abudayyeh , Zhang F. 2019. SHERLOCK: nucleic acid detection with CRISPR nucleases. Nature Protocols. 14: 2986–3012.
  3. Hinton, D.M. 2020. Sherlock CRISPR SARS-CoV-2 Kit Emergency Use Approval. (
  4. Wang X., M. Zhong, Y. Liu, P. Ma, L. Dang, Q. Meng, W. Wan, X. Ma, J Liu, G. Yang,  Z. Yang,  X. Huang, and M. Liu. 2020. Rapid and Sensitive Detection of COVID-19 Using CRISPR/Cas12a-based Detection with Naked Eye Readout, CRISPR/Cas12a-NER. Sci Bull (Beijing).
  5. Broughton J.P., X. Deng, G. Yu, C.L. Fasching, V. Servellita, J. Singh, X. Miao, J.A. Striethorst, A. Granados, A. Sotomayor-Gonzalez, K. Zorn, A. Gopez, E. Hsu, W. Gu, S. Miller, C.Y. Pan, H. Guevara, D.A. Wadford, J.S. Chen, C.Y. Chiu. 2020. CRISPR-Cas12-based detection of SARS-CoV-2. Nat Biotechnol. doi: 10.1038/s41587-020-0513-4.
  6. Ackerman C.M., C. Myhrvold, S.G. Thakku, C.A. Freije, H.C. Metsky, D.K. Yang, S.H. Ye, C.K. Boehm, T.F. Kosoko-Thoroddsen, J. Kehe, T.G. Nguyen, A. Carter, A. Kulesa, J.R. Barnes, V.G. Dugan, D.T. Hung, P.C. Blainey, P.C. Sabeti. 2020. Massively multiplexed nucleic acid detection using Cas13. Nature. doi: 10.1038/s41586-020-2279-8.
  7. Abbott T.R., G. Dhamdhere, Y. Liu, X. Lin, L. Goudy, L. Zeng, A. Chemparathy, S. Chmura, N.S. Heaton, R. Debs, T. Pande, D. Endy, M.F. La Russa, D.B. Lewis, L.S. Qiu. 2020. Development of CRISPR as an Antiviral Strategy to Combat SARS-CoV-2 and Influenza. Cell. doi: 10.1016/j.cell.2020.04.020.
  8. Nguyen T.M., Y. Zhang, P.P. Pandolfi. 2020. Virus against virus: a potential treatment for 2019-nCov (SARS-CoV-2) and other RNA viruses. Cell Research. 30: 189–190.
  • On May 6, 2020, the FDA issued an Emergency Use Authorization (EUA) to Sherlock BioSciences, Inc.’s Sherlock CRISPR SARS-CoV-2 Kit. This test is the first authorized use of CRISPR technology for an infectious disease test. The Sherlock CRISPR SARS-CoV-2 Kit is a CRISPR-based SHERLOCK (Specific High sensitivity Enzymatic Reporter unLOCKing) diagnostic test that looks for the specific target RNA or DNA sequences of the SARS-CoV-2 virus in upper respiratory specimens, such as nasal swabs, and bronchoalveolar lavage specimens, such as from fluid in the lungs, from individuals suspected of COVID-19 by their healthcare provider. Use of the test is limited to laboratories certified under CLIA to perform high-complexity tests. (
  • A review proposed that CRISPR can be used to modify B cells into antigen specific antibody producing cells that are long lasting and perpetually viable to serve as a vaccine for COVID-19 as well as other viruses. With traditional vaccines V(D)J recombination may not occur, may not occur rapidly enough, or may be transient. CRISPR may be used to perform this recombination so that desired antibodies are produced. A library or B cells engineered with different antibodies can be constructed to overcome the issue of rapid virus mutation, although it must be ensured that engineered B cells are not oncogenic. This paper provides an interesting hypothesis, but further work must be done to validate the usage of a B cell vaccine for COVID-19. (Faiq M.A. 2020. “B-Cell Engineering: A promising approach towards vaccine development for COVID-19”. Med Hypothesis. 109948.)
  • In a letter to the editor, Niu et al. describe using CRISPR to detect COVID-19 in allogenic stem cell transplant patients (ASCT), where initial RT-PCR results for COVID-19 were negative. One patient with B-cell acute lymphoblastic leukemia tested negative for COVID-19 with RT-PCR testing after ASCT, but CRISPR based testing was able to detect the virus. The patient was treated with COVID-19 convalescent plasma (CCP), and symptoms improved allowing the patient to be released from the hospital on day 15. Another patient with high-risk acute myeloid lymphoma repeatedly tested negative for COVID-19 with RT-PCR and died of organ failure; COVID-19 was confirmed via a CRISPR assay in the autopsy. (Niu A., A. McDougal, B. Ning, F. Safa, A. Luk, D.M. Mushatt, A. Nachabe, K.J. Zwezdaryk, J. Robinson, T. Peterson, F. Socola, H. Safah, N.S. Saba. 2020. “COVID-19 in allogeneic stem cell transplant: high false-negative probability and role of CRISPR and convalescent plasma”. Bone Marrow Transplantation.

Genome Structure

SARS-Cov-2 belongs to the Coronaviridae family. Severe acute respiratory syndrome coronavirus (SARS-CoV), Middle-East respiratory syndrome coronavirus (MERS-CoV) and SARS-Cov-2 are all betacoronaviruses. The genome of coronaviruses is approximately between 26,000 and 32,000 bases. The first open reading frame (ORF) represents around two thirds of the entire genome and encodes 15 non-structural proteins (nsp), while the other third encodes for structural and accessory proteins1. Upon fusing the viral particle with host cell, cellular machineries translate this two thirds ORFs into two large polypeptides (pp1a and pp1ab) that are cleaved into the 15 nsps by viral protease domains encoded within the nsp3 and nsp5 sequence2. Cleaved nsps rearrange into an RNA-dependent RNA polymerase that generates multiple copies of the viral RNA (‘negative strand’) encoding structural and accessory proteins necessary for the creation of structurally complete viral particles3. The four major structural proteins are the spike surface glycoprotein (S), small envelope protein (E), matrix protein (M), and nucleocapsid protein (N). The transmembrane spike glycoprotein S mediates the binding of the virus to receptors on the host cell surface. SARS-CoV S protein uses angiotensin-converting enzyme 2 (ACE2) as one of the main receptors for virus entry while MERS-CoV interacts with dipeptidyl peptidase 4 (DPP4 or CD26)1. SARS-like bat coronaviruses and SARS-CoV-2 share a close genetic relationship as identified by Zhou et al.2. Through in-depth genome annotation of the SARS-CoV-2, Aiping Wu et al. compared the first three determined genomes of SARS-CoV-2 (GISAID accession ID: EPI_ISL_402119, EPI_ISL_402120, EPI_ ISL_402121) with related coronaviruses (SARS-CoV, bat SARS-like CoV, MERS-CoV) and they found 380 amino acid substitutions from them1. These differences may contribute to functional and pathogenic changes of SARS-CoV-2. 

Figure 1. Proteins encoded by the SARS-CoV-2 genome (courtesy of National Library of Medicine)

Mutation dynamics

To explore the genetic diversity profile of SARS-CoV-2, Yong Jia et al. calculated pairwise genetic distance for each nucleotide site for 106 complete or near complete SARS-CoV-2 genome sequences that were retrieved from NCBI3. No mutation was found in ORF6 and ORF7ab. In this study, 12 genomes were identified to have single amino acid substitution for the S glycoprotein. One of these mutations was R408I that is located in the receptor binding domain (RBD). 408R (Arginine at position 408) is strictly conserved in SARS-CoV-2, SARS-CoV and bat SARS-like CoV. 408R was shown to form a hydrogen bond with the glycan on ACE2 90N. This hydrogen bond may contribute to the high ACE2 binding affinity. This R408I mutation changed the hydrophilic arginine to hydrophobic isoleucine which has no potential to form hydrogen-bond. ACE2 binding affinity of this mutant strain is likely to decrease due to this change which in turn would affect virus transmission rate3. Since current SARS-CoV-2 vaccine and drug development is focusing on S protein and ACE2, this single mutation in RBD may raise concerns that current vaccine development may lose its target if SARS-CoV-2 epitopes undergo multiple mutations in RBD region during viral replications. One possible therapeutic alternative is to identify potential ACE2 blocker as recommended by Yong Jia et al.3.

Phylogeny clustering analyses were also performed to trace SARS-CoV-2 spread history3. Two major clusters were found from the unrooted Minimum Evolution (ME) tree suggesting that two major spread sources for SARS-CoV-2 potentially exist. Although sequences from China were widespread in the ME tree, there was one clade that contained sequences from the US, Italy, Australia, Brazil, Sweden and South Korea but no one was correlated to sequences from China3.

Phylogenetic network analysis of SARS-CoV-2 genomes

A phylogenetic network analysis of 160 complete human SARS-CoV-2 genomes was published on April 8th, 20204. To understand the SARS-CoV-2 evolution in humans, Peter et al. used the bat coronavirus sequence (BatCoVRaTG13) as an outgroup and found three central variants which they labelled as A, B and C clusters. Cluster A had the ancestral genome and its subclusters linked out to infected patients from United States, East Asia, and Australia. Cluster B derives from cluster A by two mutations (T8782C, C28144T). Evolved mutations were found in every genome outside of Asia in cluster B which indicated a need to mutate in order to overcome immunological or environmental barriers for SARS-CoV-2 to spread outside of East Asia. Cluster C is the major European type. It was distinguished from cluster B by a nonsynonymous mutation G26144T which was absent in the mainland Chinese samples. Such phylogenetic network analysis helped in tracing the infection pathways. This analysis supported the fact that the Mexican virus was transmitted from Italy in which originally came from the first documented German infection that in turn was traced back to a Shanghai patient whose parents visited her from Wuhan4.

Nucleotide substitution

Nucleotide substitution is an important mechanism of virus molecular evolution. With rapid spread of SARS-CoV-2, Tung Phan et al. investigated the evolution of SARS-CoV-2 mutations through pairwise nucleotide sequence alignment5. They collected 86 SARS-CoV-2 genomes from GISAID to check the genetic variation. These SARS-CoV-2 strains were identified in infected patients from 12 different countries. As the reference genome, the strain EPI_ISL_406716 was chosen. In this study, 93 mutations were found over the entire SARS-CoV-2 genomes. Mutations in the S protein deserved more attention since they might induce conformational changes which can lead to substantial variations in the viral antigenicity5.


1. Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China, A. Wu et al., Cell Host & Microbe 27 (2020);

2. Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin, P. Zhou et al., bioRxiv (2020);

3. Analysis of the mutation dynamics of SARS-CoV-2 reveals the spread history and emergence of RBD mutant with lower ACE2 binding affinity. Yong J., et al., bioRxiv (2020);

4. Phylogenetic network analysis of SARS-CoV-2 genomes, f. Peter et al., PNAS (2020);

5. Genetic diversity and evolution of SARS-CoV-2, T. Phan, Infection, Genetics and Evolution (2020);

A brief interactome between SARS-CoV genome and Human genome

Across the lifecycle of SARS-Cov-2, the virus’ biomolecules interact with various components of the host cell. This indicates that human genome becomes more susceptible to the virus and human cells have evolved an immune response to multiple viral components. The underlying biomolecular interactions among human and CoV-2 genes were listed in the Table below. References can be found at the very bottom of this tab.

Human Gene CoV gene Type of CoV’s MoA MoA (Mechanism of Action)
ACE2S-proteinHost cell entryS-protein binds to ACE2 receptor
TMPRESS2S-proteinHost cell entry TMPRSS2 primes endocytosis
IFIH1, DDX58 nsp15, nsp16 Immune suppression nsp15 cleaves poly(U) sequences in viral RNA relevant for pattern recognition by IFIH1 (MDA5). IFIH1 and DDX58 (RIG-I,RIG-like receptors) is suppressed by 2′O-MTase/nsp16 (RNA capping enzyme), thereby escaping viral dsRNA recognition in cytoplasm.
Immune suppression IRF3 and NF-κB (NFKB1, NFKB2, RELA, RELB, REL) are inhibited by papain-like protease (PLpro)
TLR3, TLR7 nsp10, nsp13,
nsp14, nsp16
Immune suppression The toll-like receptors (TLRs) sensing dsRNA/ssRNA do not recognize viral RNAs because capping enzymes in RTC (RNA-triphosphatase/nsp13, N7-Methyltransferase/nsp14, 2′O-MTase/nsp16) make the viral RNA immune to these receptors. Also the 3’-5’ exoribonuclease/nsp10&nsp14 removes RNA-PAMPs relevant for TLRs.
TRAF3, TBK1, IKBKE M-proteinImmune suppression The protein complex TRAF3, TANK, TBK1, IKBKE relevant for innate immune system is distorted by CoV’s M-protein (inhibition of IKK family)
40S subunit nsp1Ribosome inhibition40S subunit (ribosome containing RPSA, RPS2,…,RPS30,RACK1) is deactivated while viral ribosome is not influenced by nsp1
RCHY1, TP53 nsp3 Immune suppression E3 ligase activity of RCHY1 is enhanced by SUD/nsp3
resulting in degrading cellular p53 (TP53) that is supposed to inhibit viral replication

An interactome analysis revealed that eight relevant proteins expressed from human genes TRAF3, TBK1, IKBKE, IRF3, IFIH1, DDX58, TLR3 and TLR7 were interacting in a network of immune responses against foreign agents. For each of these eight human genes highlighted in red, the most significant ten interacting proteins were shown below. While only TLR7 showed indirect relation to the other proteins, the other seven proteins were found to be directly related.

See Reference

SARS-CoV-2 transcriptome

Kim et al. (2020) identified discontinuous transcription by investigating the transcriptome of experimental kidney cell lines (Vero) infected with SARS-CoV-2.1 The coronavirus RNA harbors transcription-regulatory sequences (TRS) in front of each sequence that give rise to functional products such as spike, envelope, membrane and nucleocapsid protein. While such TRS are labelled as TRS-body, another very important TRS is at the 5’ beginning of the whole viral sequence, the so called TRS-leader. For most transcripts, the RNA-dependent RNA polymerase stalls at TRS-leader sequences and switches to one of these TRS-body sequences resulting in a large sequence gap between the TRS leader and one of the TRS-bodies. These shortened RNA sequences serve as a template further RNA replication. In addition to this TRS-mediated RNA polymerase jumping, few RNA sequences were independent of TRS joining – this finding questioned the biological function of these uncommon jumps. Finally, the same researches identified modification of RNA bases that correlated with length of RNA sequence and of poly(A) tail indicating that the coronavirus life cycle was also governed by RNA regulation.1

Transcriptome from bronchoalveolar lavage fluid samples

Zhou et al. (2020) found a unique effect of SARS-CoV-2 on patients compared to other viruses in “community-acquired pneumonia” patients by analyzing the RNA transcriptome derived from bronchoalveolar lung liquid sample and then by mapping it to human genes.2 Compared to a control sample from healthy persons, 457 gene expressions were upregulated; 366 downregulated – hundreds more than infection from other viruses (60 up- and 114 downregulated). SARS-CoV-2 also distinguishes from other virus by elevating more host’s transcripts related to mRNA processing and inflammatory response (chemokine, cytokine, interleukin, TNF and NF-κB signaling) while suppressing transcripts for neuronal function (CREB, synaptogenesis and endocannabinoid neural signaling). In addition, the antiviral response is also marked by 83 upregulated interferon stimulating genes (ISGs including IFIT and JAK-STAT family genes), more than immune response from SARS-CoV reaches (only 2). The pattern from these 83 upregulated also differ to upregulated ISGs from other viruses such as Yellow Fever virus, HCV, EBV and Dengue virus. Finally, immune cell composition analysis revealed a shifted pattern favoring rather innate than adaptive immune response – the neutrophil proportions were increased while lymphocyte proportions were decreased.2

Transcriptome changes owing to SARS-CoV-2 and hydroxychloroquine

Corley et al. (2020) investigated the effect of hydroxychloroquine (HCQ) on cells related to SARS-CoV-2 infection by analyzing the transcriptome of various cells.3 Transcription changes were investigated for in-vitro epithelial cell models (A549 and NHBE) infected with SARS-CoV-2, primary peripheral blood mononuclear cells (PBMC) treated with HCQ, PBMC from COVID-19 patients, monocyte-derived macrophages treated with HCQ, biopsy samples (bronchoalveolar lavage and post-mortem lung tissue biopsy) from COVID-19 patients; each transcriptional change is compared to its own respective control. More than 5000 significant transcriptional changes have been identified in bronchoalveolar lavage samples from COVID-19 compared to healthy individuals; more than 2000 transcriptional changes in PBMC from COVID-19 patients compared to healthy individuals; more than 600 in in-vitro cell models compared to non-infected SARS-CoV-2 cells; more than 250 in lung tissue biopsy compared to healthy individuals; more than 150 in macrophage samples treated with HCQ; and finally 16 transcriptional changes in PBMC treated with HCQ. Comparing SARS-CoV-2 impacted with HCQ treated cells, less than 0.5% of all altered gene expressions in COVID-19 patients correlated with these models treated with HCQ. In human primary macrophages, HCQ influenced gene expression for cholesterol biosynthesis process (LDLR) and chemokine activity (CXCL and CCL family). Based on this finding, the authors suggested that HCQ minimally influenced transcriptional changes elicited by SARS-CoV-2.3

1. The Architecture of SARS-CoV-2 Transcriptome, Kim et al., Cell (2020):
2. Heightened Innate Immune Responses in the Respiratory Tract of COVID-19 Patients, Zhou et al., Cell Host & Microbe (2020):
3. Comparative in vitro transcriptomic analyses of COVID-19 candidate therapy hydroxychloroquine suggest limited immunomodulatory evidence of SARS-CoV-2 host response genes, Corley et al., Preprint (2020):

An arginine-rich cleavage site in the S protein plays an important role for infecting human lung cells

S protein has been identified to facilitate host cell entry for coronaviruses. During attachment of receptor binding domain (RBD) of the S protein at the ACE2 receptor, the subunit S1 is responsible for binding to cellular receptor while the subunit S2 mediates the fusion of virus and host cell membrane.1 Host cell proteases started the fusion process by cleaving the S1/S2 and the S2′ site and, therefore, they became potential antiviral therapeutic targets (Figure 1). The S1/S2 site in SARS-CoV-2 uniquely contains multiple arginine residues which are absent in SARS-CoV.2 Removal of this arginine-rich site in SARS-CoV-2 resulted in an abortion of the cleavage process and thereby dampened the viral entry into Calu-3 cells. Insertion of this arginine-rich sequence into SARS-CoV, however, induced S protein cleavage while cleavage was not seen in wild type SARS-CoV. In addition, Walls et al. (2020) found out that arginine-rich residues in SARS-CoV-2 influenced the viral transmissibility in BHK cells while these were not infected by SARS-CoV.3 These findings suggested the importance of this arginine-rich residues within S protein region for efficient cleavage, host cell entry and viral tropism.

Figure 1. A coronavirus spike glycoprotein is depicted. The S1/S2 cleavage site of SARS-2-S is unique among group 2b betacoronaviruses.

Furthermore, Izaguirre (2019) revealed that S1/S2 cleavage was essential for host entry in TMPRSS2+ human lung cells but not in cathepsin B/L-dependent TMPRSS2 Vero cells. Such cleavage was processed by furin, a class of proprotein convertase.4 This study indicated that viruses exploited host protein furin in order to regulate its cell entry mechanism and infectivity. Izaguirre (2019) showed that furin inhibitor, decanoyl-RVKR-CMK, was able to block S1/S2 cleavage and resulted in inhibition of host cell entry.  Similarly, Hoffmann et al. (2020) also revealed that furin, used for mediating S1/S2 cleavage in SARS-CoV-2, was required for S protein activation by TMPRSS2 in lung cells2. Therefore, these studies suggested that inhibitors, developed to target and block furin, proprotein convertases, and/or TMPRSS2, could have potential therapeutic outcomes on COVID-19.

Kim et al. (2020) also identified the same arginine-rich residue as the role player in SARS-CoV-2 spike protein binding to heparan sulfate5. Using surface plasmon resonance binding assays, they revealed that monomeric and natural trimeric spike protein showed high binding affinity to heparin and heparan sulfate – the latter was present as heparan sulfate proteoglycan (HSPG) that acted as a cell-surface receptor for endocytosis6. In the meantime, computational ligand docking assays were used to identify that arginine-rich residue as the decisive binding domain for heparan sulfate. The authors suggested that SARS-CoV-2 cell entry was facilitated by HSPG prior to cleavage of S1/S2 by proteases such as furin, cathepsin or TMPRSS2 and then endocytosis. Hence substances that weaken the SARS-CoV-2 binding to HSPG on host cell surfaces were recommended as a potential strategy for anti-SARS-CoV-2 activity.


1. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor, M. Hoffmann et al., Cell (2020):

2. A multibasic cleavage site in the spike protein of SARS-CoV-2 is essential for infection of human lung cells, M. Hoffmann et al., Molecular Cell (2020):

3. Structure, function and antigenicity of the SARS-CoV-2 spike glycoprotein, A.C. Walls et al., bioRxiv preprint (2020):

4. The Proteolytic Regulation of Virus Cell Entry by Furin and Other Proprotein Convertases, G. Izaguirre, Viruses (2019):

5. Glycosaminoglycan binding motif at S1/S2 proteolytic cleavage site on spike glycoprotein may facilitate novel coronavirus (SARS-CoV-2) host cell entry. So Young K. et al., bioRxiv preprint (2020):

6. Heparan sulfate proteoglycan as a cell-surface endocytosis receptor, Christianson et al., Matrix Biology (2014):

Molecular Differences in the ACE2 Receptor between Human and Animal Species

A set of amino acids in the angiotensin-converting enzyme 2 (ACE2) receptor was susceptible for the spike glycoprotein within the receptor binding domain (RBD) of SARS-CoV-2 that eventually mediated the viral entry into the host cell. Sun et al. (2020) and Liu et al. (2020) compared the amino acids residues in ACE2 receptor among animals to answer whether the virus can infect other species1,2. To address this question, Sun et al. (2020) investigated 19 amino acids that played a primarily role in the interaction between ACE2 receptor and S protein while Liu et al. (2020) examined only 13 amino acids from the same RBD sequence.

In Sun’s study, 19 residues of macaques and chimpanzees were identical to those of human ACE2 (100%). Meanwhile, ACE2 from other species revealed 84%, 74%, and 42% amino acid similarities in cat, horses, and chicken, respectively, when they were compared to human ACE2 (Table 1)1.

(source: Table 1 from Reference [1],

Likewise, Liu et al. (2020) found that gorillas and macaques shared identical amino acid residues with human counterparts (100%). Amino acid sequences of ACE2 for hamsters/cats, pangolins, dogs/bats, mice, and snakes/turtles were approximately estimated 77%, 69%, 62%, 54%, and 38% similarity to human ACE2 sequence, respectively2.

Such findings assert the importance of monitoring farm animals (cattle, sheeps, pigs, horses) and pet cats for infection with SARS-CoV-2. Since these intermediate hosts may open new ways for viral transmission to humans, it was recommended that continued surveillance of SARS-CoV-2 in other species was essential and may help prevent the viral spread among animal species that were in direct contact with humans3,4. Therefore, a global surveillance network involving public health personnel, veterinarians, and animal biologists is urgently needed to monitor, and possibly to predict, potential sources for the emergence of another wave of 2019-nCoV.


1. COVID-19: Epidemiology, Evolution, and Cross-Disciplinary Perspectives, Sun J et al., Trends Mol Med. 2020 May;26(5):483-495

2. Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS‐CoV‐2, Z. Liu et al., Journal of Medical Virology (2020):

3. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak, H. A. Rothan et al., Journal of Autoimmunity (2020):

4. A decade after SARS: strategies for controlling emerging coronaviruses, R. L. Graham et al., Nature Reviews Microbiology (2013):

Vaccine design by Immunodominance mapping of S Protein

Developing a successful vaccine against SARS-CoV-2 is challenged by viral evolution and vaccine design. Either the virus evolved to distort the immune response elicited by the vaccine or the vaccine candidate may uncover an epitope that does not trigger a neutralizing immune response at all.1 Kennedy and Read (2017) indicated that viral resistance was occurring at a much slower rate than antibiotic resistance.2 Therefore, knowledge about viral epitopes has been of prime interest for vaccine design.

Zhang et al. (2020) identified four linear sites of S-protein in the receptor-binding domain (RBD) that were dominated in the immune response marked by anti-RBD antibodies from sera samples of recovered SARS-CoV-2 patients (Figure 1) – other sites contributed to personalized immune responses3. Their mice vaccination experiment against SARS-CoV-2 also revealed that antiviral activity was equal for targeting epitopes within S-protein or entire RBD fragments. Nevertheless, the two glycosylation sites (N331 and N343) observed in RBD showed no influence on the immune response. This mapping of the immunodominance regions in the virus was of immediate relevance for the design of promising vaccine candidates in which immune responses were mounted against only a few of the antigenic peptides out of multiple peptides presented. Therefore, Zhang et al. recommended specific linear antigenic epitopes of S protein instead of the entire S protein for vaccine development against SARS-CoV-23.

Figure 1. Structural representation of immunodominant (ID) and potential neutralizing sites in SARS-CoV-2 Receptor Binding domain. SARS-CoV-2 S ID Sites are indicated in blue; SARS-CoV S ID sites are indicated in yellow. Multiple Sequence Alignment was performed using CLUSTAL O. Extracted from

The transmembrane spike glycoprotein (S-protein) in coronavirus had multiple N-linked glycosylation sites that influenced S folding and may also regulate antibody recognition5. In this study, 16 out of the 22 N-linked glycosylation sites in SARS-CoV-2 were found to be glycosylated from the cryo-EM map. By comparison, at least 19 out of the 23 N-linked glycosylation sites in SARS-CoV were glycosylated. As seen in Table 1, twenty N-glycosylation sites were seen to be conserved in both SARS-CoV and SARS-CoV-25. In addition, Kumar et al. (2020) identified an epitope within the spike glycoprotein of SARS-CoV-2 that was known to interact with cytotoxic T cells as discovered in SARS-CoV6. This may suggest a comparable accessibility of immune response antibodies and T-cells among these viruses.

Table 1. Conservation of N-Linked Glycosylation Sequons in SARS-CoV-2 S and SARS-CoV S.5 “Italic” are indicated the absence of a glycosylation sequon; “periods” are indicated for deletions. Glycans observed in the SARS-CoV-2 S cryo- EM map were bold and underlined.5

However, Ju et al. (2020) introduced 206 different neutralizing antibodies without any identification of antibody families among recovered patients7. Compared to previous coronaviruses such as SARS-CoV and MERS, the identified neutralizing antibodies showed a distinct immunological response indicating a high specificity of antibodies against SARS-CoV-2 even though these coronaviruses belong to one family. Three of the most potent neutralizing antibodies were identified by neutralization tests on pseudoviruses expressing the S-protein; subsequently, crystal structure analysis revealed that one of these three neutralizing antibodies interfered with critical contact residues between RBD and ACE2 by binding simultaneously to both ACE2 receptor’s epitope and the epitope of S-protein of SARS-CoV-2. In conclusion, the variety of antibodies response shows that there are plenty approaches to neutralize viral infection where targeting the most efficient viral epitopes is the challenge for both host’s immune response and human vaccine developers.


1. Introduction of neutralizing immunogenicity index to the rational design of MERS coronavirus subunit vaccines, L. Du et al., Nature Communications (2016):
2. Why does drug resistance readily evolve but vaccine resistance does not?, D.A. Kennedy and A.F. Read, Proceedings. Biological sciences (2017):
3. Mining of epitopes on spike protein of SARS-CoV-2 from COVID-19 patients, B. Zhang et al., Cell Research (2020):
4. Immunodominance: a pivotal principle in host response to viral infections, A. Akram and R.D. Inman, Clinical Immunology (2012):
5. Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein, Walls et al., Cell (2020),
6. Structural, glycosylation and antigenic variation between 2019 novel coronavirus (2019-nCoV) and SARS coronavirus (SARS-CoV), Kumar et al., Virus Disease (2020):
7. Human neutralizing antibodies elicited by SARS-CoV-2 infection, B. Ju et al., Nature (2020):

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