A proteome-scale map of the SARS-CoV-2-human contactome

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.

The NSP3 protein of SARS-CoV-2 binds fragile X mental retardation proteins to disrupt UBAP2L interactions

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1, FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and reduced levels of viral antigen in lungs during the early stages of infection. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins and provides molecular insight into the possible underlying molecular defects in fragile X syndrome.

SARS-CoV-2 NSP14 MTase activity is critical for inducing canonical NF-κB activation

Upon SARS-CoV-2 infection, patients with severe forms of COVID-19 often suffer from a dysregulated immune response and hyperinflammation. Aberrant expression of cytokines and chemokines is associated with strong activation of the immunoregulatory transcription factor NF-κB, which can be directly induced by the SARS-CoV-2 protein NSP14. Here, we use NSP14 mutants and generated cells with host factor knockouts (KOs) in the NF-κB signaling pathways to characterize the molecular mechanism of NSP14-induced NF-κB activation. We demonstrate that full-length NSP14 requires methyltransferase (MTase) activity to drive NF-κB induction. NSP14 WT, but not an MTase-defective mutant, is poorly expressed and inherent post-translational instability is mediated by proteasomal degradation. Binding of SARS-CoV-2 NSP10 or addition of the co-factor S-adenosylmethionine (SAM) stabilizes NSP14 and augments its potential to activate NF-κB. Using CRISPR/Cas9-engineered KO cells, we demonstrate that NSP14 stimulation of canonical NF-κB activation relies on NF-κB factor p65/RELA downstream of the NEMO/IKK complex, while c-Rel or non-canonical RelB are not required to induce NF-κB transcriptional activity. However, NSP14 overexpression is unable to induce canonical IκB kinase β (IKKβ)/NF-κB signaling and in co-immunoprecipitation assays we do not detect stable associations between NSP14 and NEMO or p65, suggesting that NSP14 activates NF-κB indirectly through its methyltransferase activity. Taken together, our data provide a framework how NSP14 can augment basal NF-κB activation, which may enhance cytokine expression in SARS-CoV-2 infected cells.

Aminoacyl-tRNA synthetase interactions in SARS-CoV-2 infection

Aminoacyl-tRNA synthetases (aaRSs) are ancient enzymes that serve a foundational role in the efficient and accurate translation of genetic information from messenger RNA to proteins. These proteins play critical, non-canonical functions in a multitude of cellular processes. Multiple viruses are known to hijack the functions of aaRSs for proviral outcomes, while cells modify antiviral responses through non-canonical functions of certain synthetases. Recent findings have revealed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronaviral disease 19 (COVID-19), utilizes canonical and non-canonical functions of aaRSs, establishing a complex interplay of viral proteins, cellular factors and host aaRSs. In a striking example, an unconventional multi-aaRS complex consisting of glutamyl-prolyl-, lysyl-, arginyl- and methionyl-tRNA synthetases interact with a previously unknown RNA-element in the 3'-end of SARS-CoV-2 genomic and subgenomic RNAs. This review aims to highlight the aaRS-SARS-CoV-2 interactions identified to date, with possible implications for the biology of host aaRSs in SARS-CoV-2 infection.

Single-cell transcriptomic atlas of distinct early immune responses induced by SARS-CoV-2 Proto or its variants in rhesus monkey

Immune responses induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection play a critical role in the pathogenesis and outcome of coronavirus disease 2019 (COVID-19). However, the dynamic profile of immune responses postinfection by SARS-CoV-2 variants of concern (VOC) is not fully understood. In this study, peripheral blood mononuclear cells single-cell sequencing was performed to determine dynamic profiles of immune response to Prototype, Alpha, Beta, and Delta in a rhesus monkey model. Overall, all strains induced dramatic changes in both cellular subpopulations and gene expression levels at 1 day postinfection (dpi), which associated function including adaptive immune response, innate immunity, and IFN response. COVID-19-related genes revealed different gene profiles at 1 dpi among the four SARS-CoV-2 strains, including genes reported in COVID-19 patients with increased risk of autoimmune disease and rheumatic diseases. Delta-infected animal showed inhibition of translation pathway. B cells, T cells, and monocytes showed much commonality rather than specificity among the four strains. Monocytes were the major responders to SARS-CoV-2 infection, and the response lasted longer in Alpha than the other strains. Thus, this study reveals the early immune responses induced by SARS-CoV-2 Proto or its variants in nonhuman primates, which is important information for controlling rapidly evolving viruses.

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets.

SARS-CoV-2 and the DNA damage response

The recent coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is characterized by respiratory distress, multiorgan dysfunction and, in some cases, death. The virus is also responsible for post-COVID-19 condition (commonly referred to as 'long COVID'). SARS-CoV-2 is a single-stranded, positive-sense RNA virus with a genome of approximately 30 kb, which encodes 26 proteins. It has been reported to affect multiple pathways in infected cells, resulting, in many cases, in the induction of a 'cytokine storm' and cellular senescence. Perhaps because it is an RNA virus, replicating largely in the cytoplasm, the effect of SARS-Cov-2 on genome stability and DNA damage responses (DDRs) has received relatively little attention. However, it is now becoming clear that the virus causes damage to cellular DNA, as shown by the presence of micronuclei, DNA repair foci and increased comet tails in infected cells. This review considers recent evidence indicating how SARS-CoV-2 causes genome instability, deregulates the cell cycle and targets specific components of DDR pathways. The significance of the virus's ability to cause cellular senescence is also considered, as are the implications of genome instability for patients suffering from long COVID.

A robust platform for integrative spatial multi-omics analysis to map immune responses to SARS-CoV-2 infection in lung tissues

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid and similar, but a robust platform for deep tissue characterization of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues. Five tissue-profiling technologies were combined by a novel computational mapping methodology to comprehensively characterize and compare the transcriptome and targeted proteome of virus infected and uninfected tissues. By integrating spatial transcriptomics data (Visium, GeoMx and RNAScope) and proteomics data (CODEX and PhenoImager HT) at different cellular resolutions across lung tissues, we found strong evidence for macrophage infiltration and defined the broader microenvironment surrounding these cells. By comparing infected and uninfected samples, we found an increase in cytokine signalling and interferon responses at different sites in the lung and showed spatial heterogeneity in the expression level of these pathways. These data demonstrate that integrative spatial multi-omics platforms can be broadly applied to gain a deeper understanding of viral effects on cellular environments at the site of infection and to increase our understanding of the impact of SARS-CoV-2 on the lungs.

SARS-CoV-2 hijacks fragile X mental retardation proteins for efficient infection

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1 and FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and have delayed disease onset in vivo. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins for efficient infection and provides molecular insight to the possible underlying molecular defects in fragile X syndrome.

Coronaviral Main Protease Induces LPCAT3 Cleavage and Endoplasmic Reticulum (ER) Stress

Zoonotic coronaviruses infect mammals and birds, causing pulmonary and gastrointestinal infections. Some animal coronaviruses, such as the porcine epidemic diarrhea virus (PEDV) and transmissible gastroenteritis virus (TGEV), lead to severe diarrhea and animal deaths. Gastrointestinal symptoms were also found in COVID-19 and SARS patients. However, the pathogenesis of gastrointestinal symptoms in coronavirus diseases remains elusive. In this study, the main protease-induced LPCAT3 cleavage was monitored by exogenous gene expression and protease inhibitors, and the related regulation of gene expression was confirmed by qRT-PCR and gene knockdown. Interestingly, LPCAT3 plays an important role in lipid absorption in the intestines. The Mpro of coronaviruses causing diarrhea, such as PEDV and MERS-CoV, but not the Mpro of HCoV-OC43 and HCoV-HKU1, which could induce LPCAT3 cleavage. Mutagenesis analysis and inhibitor experiments indicated that LPCAT3 cleavage was independent of the catalytic activity of Mpro. Moreover, LPCAT3 cleavage in cells boosted CHOP and GRP78 expression, which were biomarkers of ER stress. Since LPCAT3 is critical for lipid absorption in the intestines and malabsorption may lead to diarrhea in coronavirus diseases, Mpro-induced LPCAT3 cleavage might trigger gastrointestinal symptoms during coronavirus infection.

Neuroinvasion and anosmia are independent phenomena upon infection with SARS-CoV-2 and its variants

Anosmia was identified as a hallmark of COVID-19 early in the pandemic, however, with the emergence of variants of concern, the clinical profile induced by SARS-CoV-2 infection has changed, with anosmia being less frequent. Here, we assessed the clinical, olfactory and neuroinflammatory conditions of golden hamsters infected with the original Wuhan SARS-CoV-2 strain, its isogenic ORF7-deletion mutant and three variants: Gamma, Delta, and Omicron/BA.1. We show that infected animals develop a variant-dependent clinical disease including anosmia, and that the ORF7 of SARS-CoV-2 contributes to the induction of olfactory dysfunction. Conversely, all SARS-CoV-2 variants are neuroinvasive, regardless of the clinical presentation they induce. Taken together, this confirms that neuroinvasion and anosmia are independent phenomena upon SARS-CoV-2 infection. Using newly generated nanoluciferase-expressing SARS-CoV-2, we validate the olfactory pathway as a major entry point into the brain in vivo and demonstrate in vitro that SARS-CoV-2 travels retrogradely and anterogradely along axons in microfluidic neuron-epithelial networks.

In Vitro Reconstitution and Analysis of SARS-CoV-2/Host Protein-Protein Interactions

The emergence of viral threats such as Ebola, ZIKA, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requires a rapid and efficient approach for elucidating mechanisms of pathogenesis and development of therapeutics. In this context, cell-free protein synthesis (CFPS) holds a promise to resolve the bottlenecks of multiplexed protein production and interaction analysis among host and pathogen proteins. Here, we applied a eukaryotic CFPS system based on Leishmania tarentolae extract (LTE) protein expression in combination with AlphaLISA proximity-based protein interaction technology to identify intraviral and viral-human protein interactions of SARS-CoV-2 virus that can potentially be targeted by the existing or novel antiviral therapeutics. We produced and tested 54 putative human-viral protein pairs in vitro and identified 45 direct binary protein interactions. As a casing example of the assay's suitability for drug development applications, we analyzed the effect of a putative biologic on the human angiotensin-converting enzyme 2/receptor-binding domain (hACE2/RBD) interaction. This suggests that the presented pathogen characterization platform can facilitate the development of new therapeutic agents.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Role of E3 ubiquitin ligases and deubiquitinating enzymes in SARS-CoV-2 infection

Ever since its emergence in 2019, COVID-19 has rapidly disseminated worldwide, engendering a pervasive pandemic that has profoundly impacted healthcare systems and the socio-economic milieu. A plethora of studies has been conducted targeting its pathogenic virus, SARS-CoV-2, to find ways to combat COVID-19. The ubiquitin-proteasome system (UPS) is widely recognized as a crucial mechanism that regulates human biological activities by maintaining protein homeostasis. Within the UPS, the ubiquitination and deubiquitination, two reversible modifications, of substrate proteins have been extensively studied and implicated in the pathogenesis of SARS-CoV-2. The regulation of E3 ubiquitin ligases and DUBs(Deubiquitinating enzymes), which are key enzymes involved in the two modification processes, determines the fate of substrate proteins. Proteins associated with the pathogenesis of SARS-CoV-2 may be retained, degraded, or even activated, thus affecting the ultimate outcome of the confrontation between SARS-CoV-2 and the host. In other words, the clash between SARS-CoV-2 and the host can be viewed as a battle for dominance over E3 ubiquitin ligases and DUBs, from the standpoint of ubiquitin modification regulation. This review primarily aims to clarify the mechanisms by which the virus utilizes host E3 ubiquitin ligases and DUBs, along with its own viral proteins that have similar enzyme activities, to facilitate invasion, replication, escape, and inflammation. We believe that gaining a better understanding of the role of E3 ubiquitin ligases and DUBs in COVID-19 can offer novel and valuable insights for developing antiviral therapies.

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

Repurposing Drugs for the Treatment of COVID-19 and Its Cardiovascular Manifestations

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

SARS-COV-2 Coronavirus Papain-like Protease PLpro as an Antiviral Target for Inhibitors of Active Site and Protein-Protein Interactions

The papain-like protease PLpro of the SARS-CoV-2 coronavirus is a multifunctional enzyme that catalyzes the proteolytic processing of two viral polyproteins, pp1a and pp1ab. PLpro also cleaves peptide bonds between host cell proteins and ubiquitin (or ubiquitin-like proteins), which is associated with a violation of immune processes. Nine structures of the most effective inhibitors of the PLpro active center were prioritized according to the parameters of biochemical (IC 50) and cellular tests to assess the suppression of viral replication (EC 50) and cytotoxicity (CC 50). A literature search has shown that PLpro can interact with at least 60 potential protein partners in cells, 23 of which are targets for other viral proteins (human papillomavirus and Epstein-Barr virus). The analysis of protein-protein interactions showed that the proteins USP3, UBE2J1, RCHY1, and FAF2 involved in deubiquitinylation and ubiquitinylation processes contain the largest number of bonds with other proteins; the interaction of viral proteins with them can affect the architecture of the entire network of protein-protein interactions. Using the example of a spatial model of the PLpro/ubiquitin complex and a set of 154 naturally occurring compounds with known antiviral activity, 13 compounds (molecular masses in the range of 454-954 Da) were predicted as potential PLpro inhibitors. These compounds bind to the "hot" amino acid residues of the protease at the positions Gly163, Asp164, Arg166, Glu167, and Tyr264 involved in the interaction with ubiquitin. Thus, pharmacological effects on peripheral PLpro sites, which play important roles in binding protein substrates, may be an additional target-oriented antiviral strategy.

A computational map of the human-SARS-CoV-2 protein-RNA interactome predicted at single-nucleotide resolution

RNA-binding proteins (RBPs) are critical host factors for viral infection, however, large scale experimental investigation of the binding landscape of human RBPs to viral RNAs is costly and further complicated due to sequence variation between viral strains. To fill this gap, we investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP-viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments on more than 100 human RBPs. We evaluated conservation of RBP binding between six other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of mutations from 11 variants of concern on protein-RNA interaction, identifying a set of gain- and loss-of-binding events, as well as predicted the regulatory impact of putative future mutations. Lastly, we linked RBPs to functional, OMICs and COVID-19 patient data from other studies, and identified MBNL1, FTO and FXR2 RBPs as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and open new avenues for therapeutic intervention.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.