SARS-CoV-2 infected cells present HLA-I peptides from canonical and out-of-frame ORFs

Deciphering the similarities and disparities of molecular mechanisms behind respiratory epithelium response to HCoV-229E and SARS-CoV-2 and drug repurposing, a systems biology approach

PURPOSE

Identifying the molecular mechanisms behind SARS-CoV-2 disparities and similarities will help find new treatments. The present study determines networks' shared and non-shared (specific) crucial elements in response to HCoV-229E and SARS-CoV-2 viruses to recommend candidate medications.

METHODS

We retrieved the omics data on respiratory cells infected with HCoV-229E and SARS-CoV-2, constructed PPIN and GRN, and detected clusters and motifs. Using a drug-gene interaction network, we determined the similarities and disparities of mechanisms behind their host response and drug-repurposed.

RESULTS

CXCL1, KLHL21, SMAD3, HIF1A, and STAT1 were the shared DEGs between both viruses' protein-protein interaction network (PPIN) and gene regulatory network (GRN). The NPM1 was a specific critical node for HCoV-229E and was a Hub-Bottleneck shared between PPI and GRN in HCoV-229E. The HLA-F, ADCY5, TRIM14, RPF1, and FGA were the seed proteins in subnetworks of the SARS-CoV-2 PPI network, and HSPA1A and RPL26 proteins were the seed in subnetworks of the PPI network of HCOV-229E. TRIM14, STAT2, and HLA-F played the same role for SARS-CoV-2. Top enriched KEGG pathways included cell cycle and proteasome in HCoV-229E and RIG-I-like receptor, Chemokine, Cytokine-cytokine, NOD-like receptor, and TNF signaling pathways in SARS-CoV-2. We suggest some candidate medications for COVID-19 patient lungs, including Noscapine, Isoetharine mesylate, Cycloserine, Ethamsylate, Cetylpyridinium, Tretinoin, Ixazomib, Vorinostat, Venetoclax, Vorinostat, Ixazomib, Venetoclax, and epoetin alfa for further in-vitro and in-vivo investigations.

CONCLUSION

We suggested CXCL1, KLHL21, SMAD3, HIF1A, and STAT1, ADCY5, TRIM14, RPF1, and FGA, STAT2, and HLA-F as critical genes and Cetylpyridinium, Cycloserine, Noscapine, Ethamsylate, Epoetin alfa, Isoetharine mesylate, Ribavirin, and Tretinoin drugs to study further their importance in treating COVID-19 lung complications.

FASTMAP-a flexible and scalable immunopeptidomics pipeline for HLA- and antigen-specific T-cell epitope mapping based on artificial antigen-presenting cells

The study of peptide repertoires presented by major histocompatibility complex (MHC) molecules and the identification of potential T-cell epitopes contribute to a multitude of immunopeptidome-based treatment approaches. Epitope mapping is essential for the development of promising epitope-based approaches in vaccination as well as for innovative therapeutics for autoimmune diseases, infectious diseases, and cancer. It also plays a critical role in the immunogenicity assessment of protein therapeutics with regard to safety and efficacy concerns. The main challenge emerges from the highly polymorphic nature of the human leukocyte antigen (HLA) molecules leading to the requirement of a peptide mapping strategy for a single HLA allele. As many autoimmune diseases are linked to at least one specific antigen, we established FASTMAP, an innovative strategy to transiently co-transfect a single HLA allele combined with a disease-specific antigen into a human cell line. This approach allows the specific identification of HLA-bound peptides using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Using FASTMAP, we found a comparable spectrum of endogenous peptides presented by the most frequently expressed HLA alleles in the world's population compared to what has been described in literature. To ensure a reliable peptide mapping workflow, we combined the HLA alleles with well-known human model antigens like coagulation factor VIII, acetylcholine receptor subunit alpha, protein structures of the SARS-CoV-2 virus, and myelin basic protein. Using these model antigens, we have been able to identify a broad range of peptides that are in line with already published and in silico predicted T-cell epitopes of the specific HLA/model antigen combination. The transient co-expression of a single affinity-tagged MHC molecule combined with a disease-specific antigen in a human cell line in our FASTMAP pipeline provides the opportunity to identify potential T-cell epitopes/endogenously processed MHC-bound peptides in a very cost-effective, fast, and customizable system with high-throughput potential.

Functional and structural segregation of overlapping helices in HIV-1

Overlapping coding regions balance selective forces between multiple genes. One possible division of nucleotide sequence is that the predominant selective force on a particular nucleotide can be attributed to just one gene. While this arrangement has been observed in regions in which one gene is structured and the other is disordered, we sought to explore how overlapping genes balance constraints when both protein products are structured over the same sequence. We use a combination of sequence analysis, functional assays, and selection experiments to examine an overlapped region in HIV-1 that encodes helical regions in both Env and Rev. We find that functional segregation occurs even in this overlap, with each protein spacing its functional residues in a manner that allows a mutable non-binding face of one helix to encode important functional residues on a charged face in the other helix. Additionally, our experiments reveal novel and critical functional residues in Env and have implications for the therapeutic targeting of HIV-1.

Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein

Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a nonstructural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation levels. We discover that a functionally coherent subset of human genes is preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5' UTRs from TOP transcripts can drive preferential expression in the presence of Nsp1. Finally, we found that LARP1, a key effector protein in the mTOR pathway, may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine-tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.

Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection

The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug-target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.

Host-Virus Chimeric Events in SARS-CoV-2-Infected Cells Are Infrequent and Artifactual

The pathogenic mechanisms underlying severe SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection remain largely unelucidated. High-throughput sequencing technologies that capture genome and transcriptome information are key approaches to gain detailed mechanistic insights from infected cells. These techniques readily detect both pathogen- and host-derived sequences, providing a means of studying host-pathogen interactions. Recent studies have reported the presence of host-virus chimeric (HVC) RNA in transcriptome sequencing (RNA-seq) data from SARS-CoV-2-infected cells and interpreted these findings as evidence of viral integration in the human genome as a potential pathogenic mechanism. Since SARS-CoV-2 is a positive-sense RNA virus that replicates in the cytoplasm, it does not have a nuclear phase in its life cycle. Thus, it is biologically unlikely to be in a location where splicing events could result in genome integration. Therefore, we investigated the biological authenticity of HVC events. In contrast to true biological events like mRNA splicing and genome rearrangement events, which generate reproducible chimeric sequencing fragments across different biological isolates, we found that HVC events across >100 RNA-seq libraries from patients with coronavirus disease 2019 (COVID-19) and infected cell lines were highly irreproducible. RNA-seq library preparation is inherently error prone due to random template switching during reverse transcription of RNA to cDNA. By counting chimeric events observed when constructing an RNA-seq library from human RNA and spiked-in RNA from an unrelated species, such as the fruit fly, we estimated that ∼1% of RNA-seq reads are artifactually chimeric. In SARS-CoV-2 RNA-seq, we found that the frequency of HVC events was, in fact, not greater than this background "noise." Finally, we developed a novel experimental approach to enrich SARS-CoV-2 sequences from bulk RNA of infected cells. This method enriched viral sequences but did not enrich HVC events, suggesting that the majority of HVC events are, in all likelihood, artifacts of library construction. In conclusion, our findings indicate that HVC events observed in RNA-sequencing libraries from SARS-CoV-2-infected cells are extremely rare and are likely artifacts arising from random template switching of reverse transcriptase and/or sequence alignment errors. Therefore, the observed HVC events do not support SARS-CoV-2 fusion to cellular genes and/or integration into human genomes. IMPORTANCE The pathogenic mechanisms underlying SARS-CoV-2, the virus responsible for COVID-19, are not fully understood. In particular, relatively little is known about the reasons some individuals develop life-threatening or persistent COVID-19. Recent studies identified host-virus chimeric (HVC) reads in RNA-sequencing data from SARS-CoV-2-infected cells and suggested that HVC events support potential "human genome invasion" and "integration" by SARS-CoV-2. This suggestion has fueled concerns about the long-term effects of current mRNA vaccines that incorporate elements of the viral genome. SARS-CoV-2 is a positive-sense, single-stranded RNA virus that does not encode a reverse transcriptase and does not include a nuclear phase in its life cycle, so some doubts have rightfully been expressed regarding the authenticity of HVCs and the role played by endogenous retrotransposons in this phenomenon. Thus, it is important to independently authenticate these HVC events. Here, we provide several lines of evidence suggesting that the observed HVC events are likely artifactual.

Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein

Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a non-structural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-Seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation level. We discover a functionally-coherent subset of human genes are preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5' UTRs from TOP transcripts can drive preferential expression in the presence of NSP1. Finally, we found that LARP1, a key effector protein in the mTOR pathway may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.

SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

Despite its clinical importance, the SARS-CoV-2 gene set remains unresolved, hindering dissection of COVID-19 biology. We use comparative genomics to provide a high-confidence protein-coding gene set, characterize evolutionary constraint, and prioritize functional mutations. We select 44 Sarbecovirus genomes at ideally-suited evolutionary distances, and quantify protein-coding evolutionary signatures and overlapping constraint. We find strong protein-coding signatures for ORFs 3a, 6, 7a, 7b, 8, 9b, and a novel alternate-frame gene, ORF3c, whereas ORFs 2b, 3d/3d-2, 3b, 9c, and 10 lack protein-coding signatures or convincing experimental evidence of protein-coding function. Furthermore, we show no other conserved protein-coding genes remain to be discovered. Mutation analysis suggests ORF8 contributes to within-individual fitness but not person-to-person transmission. Cross-strain and within-strain evolutionary pressures agree, except for fewer-than-expected within-strain mutations in nsp3 and S1, and more-than-expected in nucleocapsid, which shows a cluster of mutations in a predicted B-cell epitope, suggesting immune-avoidance selection. Evolutionary histories of residues disrupted by spike-protein substitutions D614G, N501Y, E484K, and K417N/T provide clues about their biology, and we catalog likely-functional co-inherited mutations. Previously reported RNA-modification sites show no enrichment for conservation. Here we report a high-confidence gene set and evolutionary-history annotations providing valuable resources and insights on SARS-CoV-2 biology, mutations, and evolution.

Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning

A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, multiplexing and sequencing technologies have accelerated engineering of improved capsid properties such as production yield, packaging efficiency, biodistribution and transduction efficiency. Here we outline how machine learning, advances in viral immunology, and high-throughput measurements can enable engineering of a new generation of de-immunized capsids beyond the antigenic landscape of natural AAVs, towards expanding the therapeutic reach of gene therapy.

Coronavirus biology and replication: implications for SARS-CoV-2

The SARS-CoV-2 pandemic and its unprecedented global societal and economic disruptive impact has marked the third zoonotic introduction of a highly pathogenic coronavirus into the human population. Although the previous coronavirus SARS-CoV and MERS-CoV epidemics raised awareness of the need for clinically available therapeutic or preventive interventions, to date, no treatments with proven efficacy are available. The development of effective intervention strategies relies on the knowledge of molecular and cellular mechanisms of coronavirus infections, which highlights the significance of studying virus-host interactions at the molecular level to identify targets for antiviral intervention and to elucidate critical viral and host determinants that are decisive for the development of severe disease. In this Review, we summarize the first discoveries that shape our current understanding of SARS-CoV-2 infection throughout the intracellular viral life cycle and relate that to our knowledge of coronavirus biology. The elucidation of similarities and differences between SARS-CoV-2 and other coronaviruses will support future preparedness and strategies to combat coronavirus infections.

Open Science Resources for the Mass Spectrometry-Based Analysis of SARS-CoV-2

The SARS-CoV-2 virus is the causative agent of the 2020 pandemic leading to the COVID-19 respiratory disease. With many scientific and humanitarian efforts ongoing to develop diagnostic tests, vaccines, and treatments for COVID-19, and to prevent the spread of SARS-CoV-2, mass spectrometry research, including proteomics, is playing a role in determining the biology of this viral infection. Proteomics studies are starting to lead to an understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein-protein interactions, and post-translational modifications. This is beginning to provide insights into potential therapeutic targets or diagnostic strategies that can be used to reduce the long-term burden of the pandemic. However, the extraordinary situation caused by the global pandemic is also highlighting the need to improve mass spectrometry data and workflow sharing. We therefore describe freely available data and computational resources that can facilitate and assist the mass spectrometry-based analysis of SARS-CoV-2. We exemplify this by reanalyzing a virus-host interactome data set to detect protein-protein interactions and identify host proteins that could potentially be used as targets for drug repurposing.