SARS-CoV-2 VOCs, Mutational diversity and clinical outcome: Are they modulating drug efficacy by altered binding strength?

The global COVID-19 pandemic continues due to emerging Severe Acute Respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC). Here, we performed comprehensive analysis of in-house sequenced SARS-CoV-2 genome mutations dynamics in the patients infected with the VOCs - Delta and Omicron, within Recovered and Mortality patients. Statistical analysis highlighted significant mutations - T4685A, N4992N, and G5063S in RdRp; T19R in NTD spike; K444N and N532H in RBD spike, associated with Delta mortality. Mutations, T19I in NTD spike, Q493R and N440K in the RBD spike were significantly associated with Omicron mortality. We performed molecular docking for possible effect of significant mutations on the binding of Remdesivir. We found that Remdesivir showed less binding efficacy with the mutant Spike protein of both Delta and Omicron mortality compared to recovered patients. This indicates that mortality associated mutations could have a modulatory effect on drug binding which could be associated with disease outcome.

SARS-CoV-2 infection severity and mortality is modulated by repeat-mediated regulation of alternative splicing.

Like single-stranded RNA viruses, SARS-CoV-2 hijacks the host transcriptional machinery for its own replication. Numerous traditional differential gene expression-based investigations have examined the diverse clinical symptoms caused by SARS-CoV-2 infection. The virus, on the other hand, also affects the host splicing machinery, causing host transcriptional dysregulation, which can lead to diverse clinical outcomes. Hence, in this study, we performed host transcriptome sequencing of 125 hospital-admitted COVID-19 patients to understand the transcriptomic differences between the severity sub-phenotypes of mild, moderate, severe, and mortality. We performed transcript-level differential expression analysis, investigated differential isoform usage, looked at the splicing patterns within the differentially expressed transcripts (DET), and elucidated the possible genome regulatory features. Our DTE analysis showed evidence of diminished transcript length and diversity as well as altered promoter site usage in the differentially expressed protein-coding transcripts in the COVID-19 mortality patients. We also investigated the potential mechanisms driving the alternate splicing and discovered a compelling differential enrichment of repeats in the promoter region and a specific enrichment of SINE (Alu) near the splicing sites of differentially expressed transcripts. These findings suggested a repeat-mediated plausible regulation of alternative splicing as a potential modulator of COVID-19 disease severity. In this work, we emphasize the role of scarcely elucidated functional role of alternative splicing in influencing COVID-19 disease severity sub-phenotypes, clinical outcomes, and its putative mechanism. IMPORTANCE The wide range of clinical symptoms reported during the COVID-19 pandemic inherently highlights the numerous factors that influence the progression and prognosis of SARS-CoV-2 infection. While several studies have investigated the host response and discovered immunological dysregulation during severe infection, most of them have the common theme of focusing only up to the gene level. Viruses, especially RNA viruses, are renowned for hijacking the host splicing machinery for their own proliferation, which inadvertently puts pressure on the host transcriptome, exposing another side of the host response to the pathogen challenge. Therefore, in this study, we examine host response at the transcript-level to discover a transcriptional difference that culminates in differential gene-level expression. Importantly, this study highlights diminished transcript diversity and possible regulation of transcription by differentially abundant repeat elements near the promoter region and splicing sites in COVID-19 mortality patients, which together with differentially expressed isoforms hold the potential to elaborate disease severity and outcome.

Co-evolution of SARS-CoV-2 variants and host immune response trajectories underlie COVID-19 pandemic to epidemic transition.

COVID-19 pandemic saw emergence of multiple SAR-CoV-2 variants. Exacerbated risk of severe outcome and hospital admissions led us to comprehend differential host-immune kinetics associated with SARS-CoV-2 variants. Longitudinal investigation was conducted through different time periods of Pre-VOC and VOCs (Delta & Omicron) mapping host transcriptome features. Robust antiviral type-1 interferon response marked Omicron infection, which was largely missing during Pre-VOC and Delta waves. SARS-CoV-2-host protein-protein interactions and docking complexes highlighted N protein to interact with HNRNPA1 in Pre-VOC, demonstrating its functional role for enhanced viral replication. Omicron revealed enhanced binding efficiency of LARP1 to N protein, probably potentiating antiviral effects of LARP1. Differential expression of zinc finger protein genes, especially in Omicron, mechanistically support induction of strong IFN (Interferon) response, thereby strengthening early viral clearance. Study highlights eventual adaptation of host to immune activation patterns that interrupt virus evolution with enhanced immune-evasion mutations and counteraction mechanisms, delimiting the next phase of COVID-19 pandemic.

Early transcriptomic host response signatures in the serum of dengue patients provides insights into clinical pathogenesis and disease severity.

Dengue virus (DENV), known to cause viral infection, belongs to the family Flaviviridae, having four serotypes (DENV1-4) that spreads by the bite of the Aedes aegypti mosquito. India has been suffering from dengue outbreaks annually with widespread epidemics by prevalence of all the four DENV serotypes. The diverse spectrum of clinical manifestations in dengue infection, mild to severe forms, makes the need of timely diagnosis and prompt treatment an essence. The identification of a dengue host response signature in serum can increase the understanding of dengue pathogenesis since most dengue NS1 Ag tests have been developed and evaluated in serum samples. Here, to understand the same, we undertook a dual RNA-sequencing (RNA-Seq) based approach from the serum samples of dengue-infected patients. The results thus yield the early transcriptional signatures that discriminated the high viral reads patients from patients who had low dengue viral reads. We identified a significant upregulation of two sets of genes, key antiviral (IFIT3, RSAD2, SAT1) and vascular dysfunction (TNFS10, CXCL8) related genes in the high viral reads group. Deeper delving of this gene profile revealed a unique two-way response, where the antiviral genes can mediate the disease course to mild, contrarily the increased expression of the other gene set might act as pointers of severe disease course. Further, we explored the hematologic parameters from the complete blood count (CBC), which suggests that lymphocytes (low) and neutrophils (high) might serve as an early predictor of prognosis in dengue infection. Collectively, our findings give insights into the foundation for further investigation of the early host response using the RNA isolated from dengue patients' serum samples and opens the door for careful monitoring of the early clinical and transcriptome profiles for management of the dengue patients.

Unraveling the genetic evolution of SARS-CoV-2 Recombinants using mutational dynamics across the different lineages.

Introduction: Recombination serves as a common strategy employed by RNA viruses for their genetic evolution. Extensive genomic surveillance during the COVID-19 pandemic has reported SARS-CoV-2 Recombinant strains indicating recombination events during the viral evolution. This study introspects the phenomenon of genome recombination by tracing the footprint of prominent lineages of SARS-CoV-2 at different time points in the context of on-going evolution and emergence of Recombinants. Method: Whole genome sequencing was carried out for 2,516 SARS-CoV-2 (discovery cohort) and 1,126 (validation cohort) using nasopharyngeal samples collected between the time period of March 2020 to August 2022, as part of the genomic surveillance program. The sequences were classified according to the different lineages of SARS-CoV-2 prevailing in India at respective time points. Results: Mutational diversity and abundance evaluation across the 12 lineages identified 58 Recombinant sequences as harboring the least number of mutations (n = 111), with 14 low-frequency unique mutations with major chunk of mutations coming from the BA.2. The spontaneously/dynamically increasing and decreasing trends of mutations highlight the loss of mutations in the Recombinants that were associated with the SARS-CoV-2 replication efficiency, infectivity, and disease severity, rendering them functionally with low infectivity and pathogenicity. Linkage disequilibrium (LD) analysis revealed that mutations comprising the LD blocks of BA.1, BA.2, and Recombinants were found as minor alleles or as low-frequency alleles in the LD blocks from the previous SARS-CoV-2 variant samples, especially Pre-VOC. Moreover, a dissipation in the size of LD blocks as well as LD decay along with a high negative regression coefficient (R squared) value was demonstrated in the Omicron and BA.1 and BA.2 lineages, which corroborated with the breakpoint analysis. Conclusion: Together, the findings help to understand the evolution and emergence of Recombinants after the Omicron lineages, for sustenance and adaptability, to maintain the epidemic spread of SARS-CoV-2 in the host population already high in immunity levels.

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.

Mutational dynamics across VOCs in International travellers and Community transmission underscores importance of Spike-ACE2 interaction.

BACKGROUND: Emergence of SARS-CoV-2 VOCs at different time points through COVID-19 pandemic raised concern for increased transmissibility, infectivity and vaccination breakthroughs. METHODS: 1567 international travellers plus community transmission COVID-19 cases were analysed for mutational profile of VOCS, that led to notable waves in India, namely Alpha, Delta, and Omicron. Spike mutations in Linkage Disequilibrium were investigated for potential impact on structural and functional changes of Spike-ACE2. RESULTS: ORF1ab and spike harboured diverse mutational signatures for each lineage. B.1.617.2 and AY. * demonstrated comparable profile, yet non-clade defining mutations were majorly unique between international vs community samples. Contrarily, Omicron lineages showed substantial overlap in non-clade defining mutations, signifying early phase of transmission and evolution within Indian community. Mutations in LD for Alpha [N501Y, A570D, D1118H, S982A], Delta [P681R, L452R, EFR:156-158 G, D950N, G142D] and Omicron [P681H, D796Y, N764K, N969K, N501Y, S375F] resulted in decreased binding affinity of Spike-ACE2 for Alpha and BA.1 whereas Delta, Omicron and BA.2 demonstrated strong binding. CONCLUSION: Genomic surveillance tracked spread of VOCs in international travellers' vs community transmission. Behavioural transmission patterns of variants, based on selective advantage incurred by spike mutations, led us to predict sudden takeover of Delta over Alpha and BA.2 over BA.1 in India.

SARS-CoV-2 Mutations and COVID-19 Clinical Outcome: Mutation Global Frequency Dynamics and Structural Modulation Hold the Key.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an enormous burden on the healthcare system worldwide as a consequence of its new emerging variants of concern (VOCs) since late 2019. Elucidating viral genome characteristics and its influence on disease severity and clinical outcome has been one of the crucial aspects toward pandemic management. Genomic surveillance holds the key to identify the spectrum of mutations vis-à-vis disease outcome. Here, in our study, we performed a comprehensive analysis of the mutation distribution among the coronavirus disease 2019 (COVID-19) recovered and mortality patients. In addition to the clinical data analysis, the significant mutations within the two groups were analyzed for their global presence in an effort to understand the temporal dynamics of the mutations globally in comparison with our cohort. Interestingly, we found that all the mutations within the recovered patients showed significantly low global presence, indicating the possibility of regional pool of mutations and the absence of preferential selection by the virus during the course of the pandemic. In addition, we found the mutation S194L to have the most significant occurrence in the mortality group, suggesting its role toward a severe disease progression. Also, we discovered three mutations within the mortality patients with a high cohort and global distribution, which later became a part of variants of interest (VOIs)/VOCs, suggesting its significant role in enhancing viral characteristics. To understand the possible mechanism, we performed molecular dynamics (MD) simulations of nucleocapsid mutations, S194L and S194*, from the mortality and recovered patients, respectively, to examine its impacts on protein structure and stability. Importantly, we observed the mutation S194* within the recovered to be comparatively unstable, hence showing a low global frequency, as we observed. Thus, our study provides integrative insights about the clinical features, mutations significantly associated with the two different clinical outcomes, its global presence, and its possible effects at the structural level to understand the role of mutations in driving the COVID-19 pandemic.