In silico and in vitro studies reveal complement system drives coagulation cascade in SARS-CoV-2 pathogenesis

Abstract

The emergence and continued spread of SARS-CoV-2 have resulted in a public health emergency across the globe. The lack of knowledge on the precise mechanism of viral pathogenesis is impeding medical intervention. In this study, we have taken both in silico and in vitro experimental approaches to unravel the mechanism of viral pathogenesis associated with complement and coagulation pathways. Based on the structural similarities of viral and host proteins, we initially generated a protein-protein interactome profile. Further computational analysis combined with Gene Ontology (GO) analysis and KEGG pathway analysis predicted key annotated pathways associated with viral pathogenesis. These include MAPK signaling, complement, and coagulation cascades, endocytosis, PD-L1 expression, PD-1 checkpoint pathway in cancer and C-type lectin receptor signaling pathways. Degree centrality analysis pinned down to MAPK1, MAPK3, AKT1, and SRC are crucial drivers of signaling pathways and often overlap with the associated pathways. Most strikingly, the complement and coagulation cascade and platelet activation pathways are interconnected, presumably directing thrombotic activity observed in severe or critical cases of COVID-19. This is complemented by in vitro studies of Huh7 cell infection and analysis of the transcriptome and proteomic profile of gene candidates during viral infection. The most known candidates associated with complement and coagulation cascade signaling by KEGG pathway analysis showed significant up-regulated fold change during viral infection. Collectively both in silico and in vitro studies suggest complement and coagulation cascade signaling are a mechanism for intravascular coagulation, thrombotic changes, and associated complications in severe COVID-19 patients.

Keywords: ARDS; Cytokines storm; MAPK1/MAPK3; Neutrophil degranulation; SARS-CoV-2; Thrombosis.

Graphical abstract

Fig. 1

GOSt multi-query Manhattan plot and Degree centrality analysis of overlapping proteins in the profoundly enriched pathways. (a) g: GOSt multi-query Manhattan plot shows significantly enriched GO: BP, KEGG terms, and Reactome enhanced data for SARS CoV-2 interacting proteins. (b) Network analysis based on the input pathways, showing overlapping proteins between 6 highly enriched pathways. Of these, the subnetwork shows MAPK1, MAPK3, AKT1, and SRC proteins are connected maximally. Abbreviations: M1: MAPK signaling pathway, M2: C-type lectin receptor signaling pathway, M3: Platelet activation, M4: PD-L1 expression, and PD-1 checkpoint pathway in cancer, M5: Innate Immune System, M6: Cytokine Signaling in Immune system.

Fig. 2

Type I interferon induction and signaling during SARS-CoV-2 infection and virus-mediated inhibition of IFNI and ISGs. The schematic diagram represents key players of INF-I pathways associated with SARS-CoV-2 infection. After entering the cells, the innate sensors such as MDA5, RIG1, and PAMS recognize the viral proteins and nucleic acids, which then activate IFN-I and proinflammatory cytokines production. Subsequently, INF-I enhances the production of ISGs and sets the stage for the potent antiviral immune response. Simultaneously, the SARS CoV-2 proteins interact with the MAVS, TRAF6, IRAK1 and negatively regulate IFN-I signaling and dampen host immune response. Abbreviations: TyK2: Tyrosine kinase 2, JAK1: Janus kinase 1, MK2: MAPK-activated protein kinase 2, MKK1/2/3/4/6/7: Mitogen-activated protein kinase, ERK1/2: extracellular signal-regulated kinases, JNK1/2: c-Jun N-terminal kinases, TAB2/3: TGF-Beta Activated Kinase Binding Protein, TAK1: TGF-beta-activated kinase, ABIN2: TNFAIP3 interacting protein 3, IRF 3/9: Interferon regulatory factor 3/ 9, STAT1/2: Signal Transducer and Activator Of Transcription, IKKα: IκB Kinase α, IKKβ: IκB Kinase β, NEMO: NF-Kappa-B essential modulator, RIGI: retinoic acid-inducible gene I, MDA5: melanoma differentiation-associated protein 5, MAVS: Mitochondrial antiviral-signaling protein, TBK1: TANK Binding Kinase 1, TRAF3: TNF Receptor Associated Factor 3, TRAF6: TNF Receptor Associated Factor 6, TRIF: TIR domain-containing adapter molecule 1, MYD88: Myeloid differentiation primary response protein MyD88,IRAK1/2/4: Interleukin-1 receptor-associated kinase, PAMP: Pathogen-associated molecular pattern, TLR: Toll-like receptors, TLP2: Thioredoxin, ISG: Interferon-stimulated gene, AP1: Activator protein 1, ISRE: Interferon-Stimulated Response Element, IFN-1: Type I Interferon, RIP1: Receptor Interacting Serine/Threonine Kinase 1. The figure was created with Biorender.com.

Fig. 3

A predicted interaction map of SARS-CoV-2 proteins and top 20 host proteins associated with cytokine signaling pathway and Neutrophils degranulation. Blue color represents the virus proteins, and brown color represents the human interactor proteins. (a) Sixteen SARS-CoV-2 proteins interact with human proteins associated with cytokine pathway. TP53, TNF, and MAPK3 (represent in green color) are highly weighted proteins and may regulate the cytokine production. (b) Thirteen SARS-CoV-2 proteins interact with human proteins associated with Neutrophils degranulation. Degree centrality analysis reveals that VAMP8, ITGAM, and STOM (represented in green color) are the key players in neutrophils degranulation process. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4

A predicted interaction map of SARS-CoV-2 proteins and the top 20 host proteins associated with complement and coagulation cascade. Blue color represents the virus proteins, and brown color represents the human interactor proteins. Four SARS-CoV-2 proteins interact with human proteins associated with complementing and coagulation cascade. Most of the proteins interact with spike protein. Degree centrality analysis reveals that KNG1, C3, and FGG (represented in green color) are the key players in complement and coagulation cascade. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

Schematic representation of the mechanism of complement system-mediated thrombosis. SARS-CoV-2- Spike (S) protein interacts with C3 and activates proteolytic processing of C3, C3 hydrolysiszes in C3a and C3b, and further C3b cleaves C5 into C5a and C5b. C3a and C5a induce inflammatory cytokine production. Further, C3a, C5a, and C5b9 activate the coagulation pathway. C5a also activates IL6 and TNF alpha production, which magnifies the coagulation pathway.

Fig. 6

In vitro validation of the complement and coagulation cascade in Huh7 cells. (a) Heatmap of 59 genes associated with the KEGG pathway “Complement and coagulation cascades” that were detected in the transcriptomics over the indicated time of infection. (b) Heatmap of 36 proteins associated with KEGG pathway “Complement and coagulation cascades” that were detected in the proteomics data over the indicated time of infection. Data were quantile normalized, and Z-score transformed. Lower values are represented in yellow and higher values in red. (c) Cytoscape network of KEGG pathway “Complement and coagulation cascades” labeled with transcriptomics results. 59 transcripts were detected and 44 have differential expression over time. (d) Cytoscape network of KEGG pathway “Complement and coagulation cascades” labeled with proteomics results. 36 proteins were detected and 28 have differential abundance over time . Genes or proteins are represented as circles. Gradient color was applied to proteins depending on temporal fold change calculated by LIMMA (low = green to high = red). Nonsignificant proteins or transcripts are represented with transparency. Non detected proteins are represented grey. The size of the significant protein is proportional to the fold change. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)