The UCSC SARS-CoV-2 Genome Browser

"Outlaw" mutations in quasispecies of SARS-CoV-2 inhibit replication

The evolution of SARS-CoV-2, the agent of COVID-19, has been remarkable for its high mutation potential, leading to the appearance of variants. Some mutations have never appeared in the published genomes, which represent consensus, or bona fide genomes. Here we tested the hypothesis that mutations that did not appear in consensus genomes were, in fact, as frequent as the mutations that appeared during the various epidemic episodes, but were not expressed because lethal. To identify these mutations, we analysed the genomes of 90 nasopharyngeal samples and the quasispecies determined by next-generation sequencing. Mutations observed in the quasispecies and not in the consensus genomes were considered to be lethal, what we called "outlaw" mutations. Among these mutations, we analysed the 21 most frequent. Eight of these "outlaws" were in the RNA polymerase and we were able to use a structural biology model and molecular dynamics simulations to demonstrate the functional incapacity of these mutated RNA polymerases. Three other mutations affected the spike, a major protein involved in the pathogenesis of COVID-19. Overall, by analysing the SARS-CoV-2 quasispecies obtained during sequencing, this method made it possible to identify "outlaws," showing areas that could potentially become the target of treatments.

Rapid detection of SARS-CoV-2 variants by molecular-clamping technology-based RT-qPCR

Given the challenges that SARS-CoV-2 variants have caused in terms of rapid spread and reduced vaccine efficacy, a rapid and cost-effective assay that can detect new and emerging variants is greatly needed worldwide. We have successfully applied the xenonucleic acid-based molecular-clamping technology to develop a multiplex reverse-transcription quantitative real-time PCR assay for SARS-CoV-2 multivariant detection. The assay was used to test 649 nasopharyngeal swab samples that were collected for clinical diagnosis or surveillance. The assay was able to correctly identify all 36 Delta variant samples as it accurately detected the D614G, T478K, and L452R mutations. In addition, the assay was able to correctly identify all 34 Omicron samples by detecting the K417N, T478K, N501Y, and D614G mutations. This technique reliably detects a variety of variants and has an analytical sensitivity of 100 copies/mL. In conclusion, this novel assay can serve as a rapid and cost-effective tool to facilitate large-scale detection of SARS-CoV-2 variants.

IMPORTANCE

We have developed a multiplex reverse-transcription quantitative real-time PCR (RT-qPCR) testing platform for the rapid detection of SARS-CoV-2 variants using the xenonucleic acid (XNA)-based molecular-clamping technology. The XNA-based RT-qPCR assay can achieve high sensitivity with a limit of detection of about 100 copies/mL for variant detection which is much better than the next-generation sequencing (NGS) assay. Its turnaround time is about 4 hours with lower cost and a lot of Clinical Laboratory Improvement Amendments (CLIA) labs own the instrument and meet skillset requirements. This assay provides a rapid, reliable, and cost-effective testing platform for rapid detection and monitoring of known and emerging SARS-CoV-2 variants. This testing platform can be adopted by laboratories that perform routine SARS-CoV-2 PCR testing, providing a rapid and cost-effective method in lieu of NGS-based assays, for detecting, differentiating, and monitoring SARS-CoV-2 variants. This assay is easily scalable to any new variant(s) should it emerge.

Genetic diversity and genomic epidemiology of SARS-CoV-2 during the first 3 years of the pandemic in Morocco: comprehensive sequence analysis, including the unique lineage B.1.528 in Morocco

During the 3 years following the emergence of the COVID-19 pandemic, the African continent, like other regions of the world, was substantially impacted by COVID-19. In Morocco, the COVID-19 pandemic has been marked by the emergence and spread of several SARS-CoV-2 variants, leading to a substantial increase in the incidence of infections and deaths. Nevertheless, the comprehensive understanding of the genetic diversity, evolution, and epidemiology of several viral lineages remained limited in Morocco. This study sought to deepen the understanding of the genomic epidemiology of SARS-CoV-2 through a retrospective analysis. The main objective of this study was to analyse the genetic diversity of SARS-CoV-2 and identify distinct lineages, as well as assess their evolution during the pandemic in Morocco, using genomic epidemiology approaches. Furthermore, several key mutations in the functional proteins across different viral lineages were highlighted along with an analysis of the genetic relationships amongst these strains to better understand their evolutionary pathways. A total of 2274 genomic sequences of SARS-CoV-2 isolated in Morocco during the period of 2020 to 2023, were extracted from the GISAID EpiCoV database and subjected to analysis. Lineages and clades were classified according to the nomenclature of GISAID, Nextstrain, and Pangolin. The study was conducted and reported in accordance with STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. An exhaustive analysis of 2274 genomic sequences led to the identification of 157 PANGO lineages, including notable lineages such as B.1, B.1.1, B.1.528, and B.1.177, as well as variants such as B.1.1.7, B.1.621, B.1.525, B.1.351, B.1.617.1, B.1.617.2, and its notable sublineages AY.33, AY.72, AY.112, AY.121 that evolved over time before being supplanted by Omicron in December 2021. Among the 2274 sequences analysed, Omicron and its subvariants had a prevalence of 59.5%. The most predominant clades were 21K, 21L, and 22B, which are respectively related phylogenetically to BA.1, BA.2, and BA.5. In June 2022, Morocco rapidly observed a recrudescence of cases of infection, with the emergence and concurrent coexistence of subvariants from clade 22B such as BA.5.2.20, BA.5, BA.5.1, BA.5.2.1, and BF.5, supplanting the subvariants BA.1 (clade display 21K) and BA.2 (clade display 21L), which became marginal. However, XBB (clade 22F) and its progeny such XBB.1.5(23A), XBB.1.16(23B), CH.1.1(23C), XBB.1.9(23D), XBB.2.3(23E), EG.5.1(23F), and XBB.1.5.70(23G) have evolved sporadically. Furthermore, several notable mutations, such as H69del/V70del, G142D, K417N, T478K, E484K, E484A, L452R, F486P, N501Y, Q613H, D614G, and P681H/R, have been identified. Some of these SARS-CoV-2 mutations are known to be involved in increasing transmissibility, virulence, and antibody escape. This study has identified several distinct lineages and mutations involved in the genetic diversity of Moroccan isolates, as well as the analysis of their evolutionary trends. These findings provide a robust basis for better understanding the distinct mutations and their roles in the variation of transmissibility, pathogenicity, and antigenicity (immune evasion/reinfection). Furthermore, the noteworthy number of distinct lineages identified in Morocco highlights the importance of maintaining continuous surveillance of COVID-19. Moreover, expanding vaccination coverage would also help protect patients against more severe clinical disease.

Real-time PCR assays that detect genes for botulinum neurotoxin A-G subtypes

The role of Real-Time PCR assays for surveillance and rapid screening for pathogens is garnering more and more attention because of its versatility and ease of adoption. The goal of this study was to design, test, and evaluate Real-Time TaqMan PCR assays for the detection of botulinum neurotoxin (bont/A-G) genes from currently recognized BoNT subtypes. Assays were computationally designed and then laboratory tested for sensitivity and specificity using DNA preparations containing bont genes from 82 target toxin subtypes, including nine bivalent toxin types; 31 strains representing other clostridial species; and an extensive panel that consisted of DNA from a diverse set of prokaryotic (bacterial) and eukaryotic (fungal, protozoan, plant, and animal) species. In addition to laboratory testing, the assays were computationally evaluated using in silico analysis for their ability to detect bont gene sequences from recently identified toxin subtypes. Seventeen specific assays (two for each of the bont/C, bont/D, bont/E, and bont/G subtypes and three for each of the bont/A, bont/B, and bont/F subtypes) were designed and evaluated for their ability to detect bont genes encoding multiple subtypes from all seven serotypes. These assays could provide an additional tool for the detection of botulinum neurotoxins in clinical, environmental and food samples that can complement other existing methods used in clinical diagnostics, regulatory, public health, and research laboratories.

Role of SARS-CoV-2 mutations in the evolution of the COVID-19 pandemic

OBJECTIVES

The SARS-CoV-2 pandemic and large-scale genomic surveillance provided an exceptional opportunity to analyze mutations that appeared over three years in viral genomes. Here we studied mutations and their epidemic consequences for SARS-CoV-2 genomes from our center.

METHODS

We analyzed 61,397 SARS-CoV-2 genomes we sequenced from respiratory samples for genomic surveillance. Mutations frequencies were calculated using Nextclade, Microsoft Excel, and an in-house Python script.

RESULTS

A total of 22,225 nucleotide mutations were identified, 220 (1.0%) being each at the root of ≥836 genomes, classifying mutations as 'hyperfertile'. Two seeded the European pandemic: P323L in RNA polymerase, associated with an increased mutation rate, and D614G in spike that improved fitness. Most 'hyperfertile' mutations occurred in areas not predicted with increased virulence. Their mean number was 8±6 (0-22) per 1000 nucleotides per gene. They were 3.7-times more frequent in accessory than informational genes (13.8 versus 3.7/1000 nucleotides). Particularly, they were 4.1-times more frequent in ORF8 than in the RNA polymerase gene. Interestingly, stop codons were present in 97 positions, almost only in accessory genes, including ORF8 (21/100 codons).

CONCLUSIONS

most 'hyperfertile' mutations did not predict emergence of a new epidemic, and some were stop codons indicating the existence of so-named 'non-virulence' genes.

SARS-CoV-2 rapidly evolves lineage-specific phenotypic differences when passaged repeatedly in immune-naïve mice

The persistence of SARS-CoV-2 despite the development of vaccines and a degree of herd immunity is partly due to viral evolution reducing vaccine and treatment efficacy. Serial infections of wild-type (WT) SARS-CoV-2 in Balb/c mice yield mouse-adapted strains with greater infectivity and mortality. We investigate if passaging unmodified B.1.351 (Beta) and B.1.617.2 (Delta) 20 times in K18-ACE2 mice, expressing the human ACE2 receptor, in a BSL-3 laboratory without selective pressures, drives human health-relevant evolution and if evolution is lineage-dependent. Late-passage virus causes more severe disease, at organism and lung tissue scales, with late-passage Delta demonstrating antibody resistance and interferon suppression. This resistance co-occurs with a de novo spike S371F mutation, linked with both traits. S371F, an Omicron-characteristic mutation, is co-inherited at times with spike E1182G per Nanopore sequencing, existing in different within-sample viral variants at others. Both S371F and E1182G are linked to mammalian GOLGA7 and ZDHHC5 interactions, which mediate viral-cell entry and antiviral response. This study demonstrates SARS-CoV-2's tendency to evolve with phenotypic consequences, its evolution varying by lineage, and suggests non-dominant quasi-species contribution.

Camptothecin structure simplification elaborated new imidazo[2,1-b]quinazoline derivative as a human topoisomerase I inhibitor with efficacy against bone cancer cells and colon adenocarcinoma

Camptothecin is a pentacyclic natural alkaloid that inhibits the hTop1 enzyme involved in DNA transcription and cancer cell growth. Camptothecin structure pitfalls prompted us to design new congeners using a structure simplification strategy to reduce the ring extension number from pentacyclic to tetracyclic while maintaining potential stacking of the new compounds with the DNA base pairs at the Top1-mediated cleavage complex and aqueous solubility, as well as minimizing compound-liver toxicity. The principal axis of this study was the verification of hTop1 inhibiting activity as a possible mechanism of action and the elaboration of new simplified inhibitors with improved pharmacodynamic and pharmacokinetic profiling using three structure panels (A-C) of (isoquinolinoimidazoquinazoline), (imidazoquinazoline), and (imidazoisoquinoline), respectively. DNA relaxation assay identified five compounds as hTop1 inhibitors belonging to the imidazoisoquinolines 3a,b, the imidazoquinazolines 12, and the isoquinolinoimidazoquinazolines 7a,b. In an MTT cytotoxicity assay against different cancer cell lines, compound 12 was the most potent against HOS bone cancer cells (IC50 = 1.47 μM). At the same time, the other inhibitors had no detectable activity against any cancer cell type. Compound (12) demonstrated great penetrating power in the HOS cancer cells' 3D-multicellular tumor spheroid model. Bioinformatics research of the hTop1 gene revealed that the TP53 cell proliferative gene is in the network of hTop1. The finding is confirmed empirically using the gene expression assay that proved the increase in p53 expression. The impact of structure simplification on compound 12 profile, characterized by the absence of acute oral liver toxicity when compared to Doxorubicin as a standard inhibitor, the lethal dose measured on Swiss Albino female mice and reported at LD50 = 250 mg/kg, and therapeutic significance in reducing colon adenocarcinoma tumor volume by 75.36 % after five weeks of treatment with compound 12. The molecular docking solutions of the active CPT-based derivative 12 and the inactive congener 14 into the active site of hTop1 and the activity cliffing of such MMP directed us to recommend the addition of HBD and HBA variables to compound 12 imidazoquinazoline core scaffold to enhance the potency via hydrogen bond formation with the major groove amino acids (Asp533, Lys532) as well as maintaining the hydrogen bond with the minor groove amino acid Arg364.

The return of the "Mistigri" (virus adaptative gain by gene loss) through the SARS-CoV-2 XBB.1.5 chimera that predominated in 2023

Severe acute respiratory syndrome coronavirus 2 XBB.1.5 is the first recombinant lineage to predominate at the country and global scales. Very interestingly, like the Marseille-4B subvariant (or B.1.160) and the pandemic variant B.1.1.7 (or Alpha) previously, it has its ORF8 gene inactivated by a stop codon. We aimed here to study the distribution of stop codons in ORF8 of XBB.1.5 and non-XBB.1.5 genomes. We identified that a stop codon was present at 89 (74%) ORF8 codons in ≥1 of 15 222 404 genomes available in GISAID. The mean proportion of genomes with a stop codon per codon was 0.11% (range, 0%-7.8%). In addition, a stop codon was detected at 15 (12%) codons in at least 1000 genomes. These 15 codons are notably located on seven stem-loop hairpin regions and in the signal peptide region for the case of the XBB.1.5 lineage (codon 8). Thus, it is very likely that stop codons in ORF8 gene contributed on at least three occasions and independently during the pandemic to the evolutionary success of a lineage that became transiently predominant. Such association of gene loss with evolutionary success, which suits the recently described Mistigri rule, is an important biological phenomenon very unknown in virology while largely described in cellular organisms.

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://cgc.sbgenomics.com) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://github.com/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly; it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic.

Unambiguous detection of SARS-CoV-2 subgenomic mRNAs with single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-Seq) studies have provided critical insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). scRNA-Seq library preparation methods and data processing workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq library preparation methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We show that compared to 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') libraries or 10X Genomics Chromium Next GEM Single Cell V(D)J (10X 5') libraries sequenced with standard read configurations, 10X 5' libraries sequenced with an extended length read 1 (R1) that covers both cell barcode and transcript sequence (termed "10X 5' with extended R1") increase the number of unambiguous reads spanning leader-sgmRNA junction sites. We further present a data processing workflow, single-cell coronavirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to viral sgmRNAs or viral genomic RNA (gRNA). We find that combining 10X 5' with extended R1 library preparation/sequencing and scCoVseq data processing maximizes the number of viral UMIs per cell quantified by scRNA-Seq. Corresponding sgmRNA expression levels are highly correlated with expression in matched bulk RNA-Seq data sets quantified with established tools for SARS-CoV-2 analysis. Using this scRNA-Seq approach, we find that SARS-CoV-2 gene expression is highly correlated across individual infected cells, which suggests that the proportion of viral sgmRNAs remains generally consistent throughout infection. Taken together, these results and corresponding data processing workflow enable robust quantification of coronavirus sgmRNA expression at single-cell resolution, thereby supporting high-resolution studies of viral RNA processes in individual cells. IMPORTANCE Single-cell RNA sequencing (scRNA-Seq) has emerged as a valuable tool to study host-virus interactions, especially for coronavirus disease 2019 (COVID-19). Here we compare the performance of different scRNA-Seq library preparation methods and sequencing strategies to detect SARS-CoV-2 RNAs and develop a data processing workflow to quantify unambiguous sequence reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. After establishing a workflow that maximizes the detection of SARS-CoV-2 subgenomic mRNAs, we explore patterns of SARS-CoV-2 gene expression across cells with variable levels of total viral RNA, assess host gene expression differences between infected and bystander cells, and identify non-canonical and lowly abundant SARS-CoV-2 RNAs. The sequencing and data processing strategies developed here can enhance studies of coronavirus RNA biology at single-cell resolution and thereby contribute to our understanding of viral pathogenesis.

Multidimensional futuristic approaches to address the pandemics beyond COVID-19

Globally, the impact of the coronavirus disease 2019 (COVID-19) pandemic has been enormous and unrelenting with ∼6.9 million deaths and ∼765 million infections. This review mainly focuses on the recent advances and potentially novel molecular tools for viral diagnostics and therapeutics with far-reaching implications in managing the future pandemics. In addition to briefly highlighting the existing and recent methods of viral diagnostics, we propose a couple of potentially novel non-PCR-based methods for rapid, cost-effective, and single-step detection of nucleic acids of viruses using RNA mimics of green fluorescent protein (GFP) and nuclease-based approaches. We also highlight key innovations in miniaturized Lab-on-Chip (LoC) devices, which in combination with cyber-physical systems, could serve as ideal futuristic platforms for viral diagnosis and disease management. We also discuss underexplored and underutilized antiviral strategies, including ribozyme-mediated RNA-cleaving tools for targeting viral RNA, and recent advances in plant-based platforms for rapid, low-cost, and large-scale production and oral delivery of antiviral agents/vaccines. Lastly, we propose repurposing of the existing vaccines for newer applications with a major emphasis on Bacillus Calmette-Guérin (BCG)-based vaccine engineering.

A microRNA Arising from the Negative Strand of SARS-CoV-2 Genome Targets FOS to Reduce AP-1 Activity

Virus-encoded microRNAs were first reported in the Epstein-Barr virus in 2004. Subsequently, a few hundred viral miRNAs have been identified, mainly in DNA viruses belonging to the herpesviridae family. To date, only 30 viral miRNAs encoded by RNA viruses are reported by miRBase. Since the outbreak of the SARS-CoV-2 pandemic, several studies have predicted and, in some cases, experimentally validated miRNAs originating from the positive strand of the SARS-CoV-2 genome. By integrating NGS data analysis and qRT-PCR approaches, we found that SARS-CoV-2 also encodes for a viral miRNA arising from the minus (antisense) strand of the viral genome, in the region encoding for ORF1ab, herein referred to as SARS-CoV-2-miR-AS1. Our data show that the expression of this microRNA increases in a time course analysis of SARS-CoV-2 infected cells. Furthermore, enoxacin treatment enhances the accumulation of the mature SARS-CoV-2-miR-AS1 in SARS-CoV-2 infected cells, arguing for a Dicer-dependent processing of this small RNA. In silico analysis suggests that SARS-CoV-2-miR-AS1 targets a set of genes which are translationally repressed during SARS-CoV-2 infection. We experimentally validated that SARS-CoV-2-miR-AS1 targets FOS, thus repressing the AP-1 transcription factor activity in human cells.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

New trends in synthetic drugs and natural products targeting 20S proteasomes in cancers

Cancer is a global health challenge that remains to be a field of extensive research aiming to find new anticancer therapeutics. The 20S proteasome complex is one of the targets of anticancerdrugs, as it is correlated with several cancer types. Herein, we aim to discuss the 20S proteasome subunits and investigatethe currently studied proteasome inhibitors targeting the catalytically active proteasome subunits. In this review, we summarize the proteindegradation mechanism of the 20S proteasome complex and compareit with the 26S proteasome complex. Afterwards, the localization of the 20S proteasome is summarized as well as its use as a diagnosticandprognostic marker. The FDA-approved proteasome inhibitors (PIs) under clinical trials are summarized and their current limited use in solid tumors is also reviewed in addition to the expression of theβ5 subunit in differentcell lines. The review discusses in-silico analysis of the active subunit of the 20S proteasome complex. For development of new proteasome inhibitor drugs, the natural products inhibiting the 20S proteasome are summarized, as well as novel methodologies and challenges for the natural product discovery and current information about the biosynthetic gene clusters encoding them. We herein briefly summarize some resistancemechanismsto the proteasomeinhibitors. Additionally, we focus on the three main classes of proteasome inhibitors: 1] boronic acid, 2] beta-lactone and 3] epoxide inhibitor classes, as well as other PI classes, and their IC₅₀ values and their structure-activity relationship (SAR). Lastly,we summarize several future prospects of developing new proteasome inhibitors towards the treatment of tumors, especially solid tumors.

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.

Diagnostic Significance of hsa-miR-21-5p, hsa-miR-192-5p, hsa-miR-155-5p, hsa-miR-199a-5p Panel and Ratios in Hepatocellular Carcinoma on Top of Liver Cirrhosis in HCV-Infected Patients

Early hepatocellular carcinoma (HCC) diagnosis is challenging. Moreover, for patients with alpha-fetoprotein (AFP)-negative HCC, this challenge is augmented. MicroRNAs (miRs) profiles may serve as potential HCC molecular markers. We aimed to assess plasma homo sapiens-(hsa)-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p-expression levels as a panel of biomarkers for HCC in chronic hepatitis C virus (CHCV) patients with liver cirrhosis (LC), especially AFP-negative HCC cases, as a step toward non-protein coding (nc) RNA precision medicine.

SUBJECTS AND METHODS

79 patients enrolled with CHCV infection with LC, subclassified into an LC group without HCC (n = 40) and LC with HCC (n = 39). Real-time quantitative PCR was used to measure plasma hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p.

RESULTS

Plasma hsa-miR-21-5p and hsa-miR-155-5p demonstrated significant upregulation, while hsa-miR-199a-5p demonstrated significant downregulation in the HCC group (n = 39) when compared to the LC group (n = 40). hsa-miR-21-5p expression was positively correlated with serum AFP, insulin, and insulin resistance (r = 0.5, p < 0.001, r = 0.334, p = 0.01, and r = 0.303, p = 0.02, respectively). According to the ROC curves, for differentiating HCC from LC, combining AFP with each of hsa-miR-21-5p, hsa-miR-155-5p, and miR199a-5p improved the diagnostic sensitivity to 87%, 82%, and 84%, respectively, vs. 69% for AFP alone, with acceptable specificities of 77.5%, 77.5%, and 80%, respectively, and AUC = 0.89, 0.85, and 0.90, respectively vs. 0.85 for AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios discriminated HCC from LC at AUC = 0.76 and 0.71, respectively, with sensitivities = 94% and 92% and specificities = 48% and 53%, respectively. Upregulation of plasma hsa-miR-21-5p was considered as an independent risk factor for HCC development [OR = 1.198(1.063-1.329), p = 0.002].

CONCLUSIONS

Combining each of hsa-miR-21-5p, hsa-miR-155-5p, and hsa-miR-199a-5p with AFP made it possible to identify HCC development in the LC patients' cohort with higher sensitivity than using AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios are potential HCC molecular markers for AFP-negative HCC patients. hsa-miR-21-5p was linked, clinically and via in silico proof, to insulin metabolism, inflammation, dyslipidemia, and tumorigenesis in the HCC patients' group as well as for an upregulated independent risk factor for the emergence of HCC from LC in the CHCV patients.

Translation landscape of SARS-CoV-2 noncanonical subgenomic RNAs

The ongoing COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with a positive-stranded RNA genome. Current proteomic studies of SARS-CoV-2 mainly focus on the proteins encoded by its genomic RNA (gRNA) or canonical subgenomic RNAs (sgRNAs). Here, we systematically investigated the translation landscape of SARS-CoV-2, especially its noncanonical sgRNAs. We first constructed a strict pipeline, named vipep, for identifying reliable peptides derived from RNA viruses using RNA-seq and mass spectrometry data. We applied vipep to analyze 24 sets of mass spectrometry data related to SARS-CoV-2 infection. In addition to known canonical proteins, we identified many noncanonical sgRNA-derived peptides, which stably increase after viral infection. Furthermore, we explored the potential functions of those proteins encoded by noncanonical sgRNAs and found that they can bind to viral RNAs and may have immunogenic activity. The generalized vipep pipeline is applicable to any RNA viruses and these results have expanded the SARS-CoV-2 translation map, providing new insights for understanding the functions of SARS-CoV-2 sgRNAs.

Molecular Virology of SARS-CoV-2 and Related Coronaviruses

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The global COVID-19 pandemic continues to threaten the lives of hundreds of millions of people, with a severe negative impact on the global economy. Although several COVID-19 vaccines are currently being administered, none of them is 100% effective. Moreover, SARS-CoV-2 variants remain an important worldwide public health issue. Hence, the accelerated development of efficacious antiviral agents is urgently needed. Coronavirus depends on various host cell factors for replication. An ongoing research objective is the identification of host factors that could be exploited as targets for drugs and compounds effective against SARS-CoV-2. In the present review, we discuss the molecular mechanisms of SARS-CoV-2 and related coronaviruses, focusing on the host factors or pathways involved in SARS-CoV-2 replication that have been identified by genome-wide CRISPR screening.

Human Identical Sequences, hyaluronan, and hymecromone ─ the new mechanism and management of COVID-19

COVID-19 caused by SARS-CoV-2 has created formidable damage to public health and market economy. Currently, SARS-CoV-2 variants has exacerbated the transmission from person-to-person. Even after a great deal of investigation on COVID-19, SARS-CoV-2 is still rampaging globally, emphasizing the urgent need to reformulate effective prevention and treatment strategies. Here, we review the latest research progress of COVID-19 and provide distinct perspectives on the mechanism and management of COVID-19. Specially, we highlight the significance of Human Identical Sequences (HIS), hyaluronan, and hymecromone ("Three-H") for the understanding and intervention of COVID-19. Firstly, HIS activate inflammation-related genes to influence COVID-19 progress through NamiRNA-Enhancer network. Accumulation of hyaluronan induced by HIS-mediated HAS2 upregulation is a substantial basis for clinical manifestations of COVID-19, especially in lymphocytopenia and pulmonary ground-glass opacity. Secondly, detection of plasma hyaluronan can be effective for evaluating the progression and severity of COVID-19. Thirdly, spike glycoprotein of SARS-CoV-2 may bind to hyaluronan and further serve as an allergen to stimulate allergic reaction, causing sudden adverse effects after vaccination or the aggravation of COVID-19. Finally, antisense oligonucleotides of HIS or inhibitors of hyaluronan synthesis (hymecromone) or antiallergic agents could be promising therapeutic agents for COVID-19. Collectively, Three-H could hold the key to understand the pathogenic mechanism and create effective therapeutic strategies for COVID-19.

Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Tracing the SARS-CoV-2 infection on the ocular surface: Overview and preliminary corneoscleral transcriptome sequencing

COVID-19's impact on the ocular surface has already been recognized, however the molecular mechanisms induced by the infection on the ocular surface are still unclear. The aim of this paper is to provide a first overview of the transcriptional perturbations caused by SARS-CoV-2 on the ocular surface by analyzing gene expression profile of corneoscleral ring samples from post-mortem SARS-CoV-2 positive donors (PD). The presence of SARS-CoV-2 on the ocular surface, in tears and corneal tissues has rarely been detected in infected individuals in both the presence and the absence of ocular manifestations. In this preliminary study, 6 human corneoscleral tissues of 3 PD and two tissues from a negative donor (CTRL) were obtained at the local eye bank. The presence of genomic and sub-genomic SARS-CoV-2 RNAs was assessed by qRT-PCR, while transcriptome analysis (RNA-sequencing) was performed by Illumina. Principal Component Analysis (PCA), search for differentially expressed genes (DEGs) and Gene Ontology (GO)-enrichment analysis were performed. Three samples from PD were found positive for SARS-CoV-2 genomic RNA, although the absence of sub-genomic RNAs indicated an inactive virus. PCA analysis grouped 3 different clusters, one including CTRL, and the other two including, respectively, PD with undetected SARS-CoV-2 (PD-SARS-neg) and PD with detected SARS-CoV-2 (PD-SARS-pos). The DEGs in common with the 2 PD clusters included several genes associable to the interferon pathway, such as ADAMTS4, RSAD2, MMP1, IL6, ISG15 and proinflammatory cytokines. Among the down-regulated genes we found AQP5. GO analysis revealed 77 GO terms over-represented in PD-SARS-neg vs. CTRL, and 17 GO terms in PD-SARS-pos vs. CTRL. The presence of SARS-CoV-2 RNA and RNA-sequencing reads in ocular surface tissues supports the possibility that the eye acts as an entry route. The modulation of early responsive genes, together with several ISGs suggests a potential protective responsiveness of the ocular tissues to SARS-CoV-2.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Limited extent and consequences of pancreatic SARS-CoV-2 infection

Concerns that infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), may cause new-onset diabetes persist in an evolving research landscape, and precise risk assessment is hampered by, at times, conflicting evidence. Here, leveraging comprehensive single-cell analyses of in vitro SARS-CoV-2-infected human pancreatic islets, we demonstrate that productive infection is strictly dependent on the SARS-CoV-2 entry receptor ACE2 and targets practically all pancreatic cell types. Importantly, the infection remains highly circumscribed and largely non-cytopathic and, despite a high viral burden in infected subsets, promotes only modest cellular perturbations and inflammatory responses. Similar experimental outcomes are also observed after islet infection with endemic coronaviruses. Thus, the limits of pancreatic SARS-CoV-2 infection, even under in vitro conditions of enhanced virus exposure, challenge the proposition that in vivo targeting of β cells by SARS-CoV-2 precipitates new-onset diabetes. Whether restricted pancreatic damage and immunological alterations accrued by COVID-19 increase cumulative diabetes risk, however, remains to be evaluated.

Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

Coordinated regulation of interferon and inflammasome signaling pathways by SARS-CoV-2 proteins

Type I and III interferons (IFNs) and the nucleotide-binding domain (NBD) leucine-rich repeat (LRR)-containing receptor (NLR) family pyrin domain containing 3 (NLRP3) inflammasome play pivotal roles in the pathogenesis of SARS-CoV-2. While optimal IFN and inflammasome responses are essential for limiting SARS-CoV-2 infection, aberrant activation of these innate immune responses is associated with COVID-19 pathogenesis. In this review, we focus our discussion on recent findings on SARS-CoV-2-induced type I and III IFNs and NLRP3 inflammasome responses and the viral proteins regulating these mechanisms.

The UCSC Genome Browser database: 2022 update

The UCSC Genome Browser, https://genome.ucsc.edu, is a graphical viewer for exploring genome annotations. The website provides integrated tools for visualizing, comparing, analyzing, and sharing both publicly available and user-generated genomic datasets. Data highlights this year include a collection of easily accessible public hub assemblies on new organisms, now featuring BLAT alignment and PCR capabilities, and new and updated clinical tracks (gnomAD, DECIPHER, CADD, REVEL). We introduced a new Track Sets feature and enhanced variant displays to aid in the interpretation of clinical data. We also added a tool to rapidly place new SARS-CoV-2 genomes in a global phylogenetic tree enabling researchers to view the context of emerging mutations in our SARS-CoV-2 Genome Browser. Other new software focuses on usability features, including more informative mouseover displays and new fonts.

The Ensembl COVID-19 resource: ongoing integration of public SARS-CoV-2 data

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser; the first virus to be encompassed within the Ensembl platform. This resource incorporates a new Ensembl gene set, multiple variant sets, and annotation from several relevant resources aligned to the reference SARS-CoV-2 assembly. Since the first release in May 2020, the content has been regularly updated using our new rapid release workflow, and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

Obatoclax inhibits SARS-CoV-2 entry by altered endosomal acidification and impaired cathepsin and furin activity in vitro

Coronavirus disease 2019 (COVID-19) caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has set off a global pandemic. There is an urgent unmet need for safe, affordable, and effective therapeutics against COVID-19. In this regard, drug repurposing is considered as a promising approach. We assessed the compounds that affect the endosomal acidic environment by applying human angiotensin-converting enzyme 2 (hACE2)- expressing cells infected with a SARS-CoV-2 spike (S) protein-pseudotyped HIV reporter virus and identified that obatoclax resulted in the strongest inhibition of S protein-mediated virus entry. The potent antiviral activity of obatoclax at nanomolar concentrations was confirmed in different human lung and intestinal cells infected with the SARS-CoV-2 pseudotype system as well as clinical virus isolates. Furthermore, we uncovered that obatoclax executes a double-strike against SARS-CoV-2. It prevented SARS-CoV-2 entry by blocking endocytosis of virions through diminished endosomal acidification and the corresponding inhibition of the enzymatic activity of the endosomal cysteine protease cathepsin L. Additionally, obatoclax impaired the SARS-CoV-2 S-mediated membrane fusion by targeting the MCL-1 protein and reducing furin protease activity. In accordance with these overarching mechanisms, obatoclax blocked the virus entry mediated by different S proteins derived from several SARS-CoV-2 variants of concern such as, Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.2). Taken together, our results identified obatoclax as a novel effective antiviral compound that keeps SARS-CoV-2 at bay by blocking both endocytosis and membrane fusion. Our data suggested that obatoclax should be further explored as a clinical drug for the treatment of COVID-19.

A Daily-Updated Database and Tools for Comprehensive SARS-CoV-2 Mutation-Annotated Trees

The vast scale of SARS-CoV-2 sequencing data has made it increasingly challenging to comprehensively analyze all available data using existing tools and file formats. To address this, we present a database of SARS-CoV-2 phylogenetic trees inferred with unrestricted public sequences, which we update daily to incorporate new sequences. Our database uses the recently proposed mutation-annotated tree (MAT) format to efficiently encode the tree with branches labeled with parsimony-inferred mutations, as well as Nextstrain clade and Pango lineage labels at clade roots. As of June 9, 2021, our SARS-CoV-2 MAT consists of 834,521 sequences and provides a comprehensive view of the virus' evolutionary history using public data. We also present matUtils-a command-line utility for rapidly querying, interpreting, and manipulating the MATs. Our daily-updated SARS-CoV-2 MAT database and matUtils software are available at http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/ and https://github.com/yatisht/usher, respectively.

Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes

SARS-CoV-2 genomic sequencing efforts have scaled dramatically to address the current global pandemic and aid public health. However, autonomous genome annotation of SARS-CoV-2 genes, proteins, and domains is not readily accomplished by existing methods and results in missing or incorrect sequences. To overcome this limitation, we developed a novel semi-supervised pipeline for automated gene, protein, and functional domain annotation of SARS-CoV-2 genomes that differentiates itself by not relying on the use of a single reference genome and by overcoming atypical genomic traits that challenge traditional bioinformatic methods. We analyzed an initial corpus of 66,000 SARS-CoV-2 genome sequences collected from labs across the world using our method and identified the comprehensive set of known proteins with 98.5% set membership accuracy and 99.1% accuracy in length prediction, compared to proteome references, including Replicase polyprotein 1ab (with its transcriptional slippage site). Compared to other published tools, such as Prokka (base) and VAPiD, we yielded a 6.4- and 1.8-fold increase in protein annotations. Our method generated 13,000,000 gene, protein, and domain sequences-some conserved across time and geography and others representing emerging variants. We observed 3362 non-redundant sequences per protein on average within this corpus and described key D614G and N501Y variants spatiotemporally in the initial genome corpus. For spike glycoprotein domains, we achieved greater than 97.9% sequence identity to references and characterized receptor binding domain variants. We further demonstrated the robustness and extensibility of our method on an additional 4000 variant diverse genomes containing all named variants of concern and interest as of August 2021. In this cohort, we successfully identified all keystone spike glycoprotein mutations in our predicted protein sequences with greater than 99% accuracy as well as demonstrating high accuracy of the protein and domain annotations. This work comprehensively presents the molecular targets to refine biomedical interventions for SARS-CoV-2 with a scalable, high-accuracy method to analyze newly sequenced infections as they arise.

AIDS patient with severe T cell depletion achieved control but not clearance of SARS-CoV-2 infection

A late presenter AIDS patient with severe T cell depletion presented non-severe COVID-19 symptoms, with prolonged viral shedding. Our case report supports the hypothesis that an effective T cell response may be dispensable for the control of COVID-19 progression to severe forms, while it may be necessary for SARS-CoV-2 clearance.

Reductionism Ad Absurdum: The Misadventures of Structural Biology in the Time of Coronavirus

The tragic consequences of the COVID-19 pandemic have led to admirable responses by the global scientific community, including a profound acceleration in the pace of research and exchange of findings. However, this has had considerable costs of its own, as erroneous conclusions have propagated faster than researchers have been able to detect and correct them. We illustrate the specific misunderstandings that have resulted from reductionist approaches to the study of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp), which are but one instance of a regrettably growing trend in structural biology. Far from merely being cautionary tales about the conduct of scientific research, these errors have had significant practical impact, by hampering a correct understanding of RdRp structure and mechanism, its inhibition by nucleoside analogues such as remdesivir, and the discovery and characterization of such analogues. After correcting these misunderstandings, we close with several recommendations for a broader correction of the course of scientific research.

A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

RNA-Binding Proteins in the Post-transcriptional Control of Skeletal Muscle Development, Regeneration and Disease

Embryonic myogenesis is a temporally and spatially regulated process that generates skeletal muscle of the trunk and limbs. During this process, mononucleated myoblasts derived from myogenic progenitor cells within the somites undergo proliferation, migration and differentiation to elongate and fuse into multinucleated functional myofibers. Skeletal muscle is the most abundant tissue of the body and has the remarkable ability to self-repair by re-activating the myogenic program in muscle stem cells, known as satellite cells. Post-transcriptional regulation of gene expression mediated by RNA-binding proteins is critically required for muscle development during embryogenesis and for muscle homeostasis in the adult. Differential subcellular localization and activity of RNA-binding proteins orchestrates target gene expression at multiple levels to regulate different steps of myogenesis. Dysfunctions of these post-transcriptional regulators impair muscle development and homeostasis, but also cause defects in motor neurons or the neuromuscular junction, resulting in muscle degeneration and neuromuscular disease. Many RNA-binding proteins, such as members of the muscle blind-like (MBNL) and CUG-BP and ETR-3-like factors (CELF) families, display both overlapping and distinct targets in muscle cells. Thus they function either cooperatively or antagonistically to coordinate myoblast proliferation and differentiation. Evidence is accumulating that the dynamic interplay of their regulatory activity may control the progression of myogenic program as well as stem cell quiescence and activation. Moreover, the role of RNA-binding proteins that regulate post-transcriptional modification in the myogenic program is far less understood as compared with transcription factors involved in myogenic specification and differentiation. Here we review past achievements and recent advances in understanding the functions of RNA-binding proteins during skeletal muscle development, regeneration and disease, with the aim to identify the fundamental questions that are still open for further investigations.

CoVrimer: A tool for aligning SARS-CoV-2 primer sequences and selection of conserved/degenerate primers

As mutations in SARS-CoV-2 virus accumulate rapidly, novel primers that amplify this virus sensitively and specifically are in demand. We have developed a webserver named CoVrimer by which users can search for and align existing or newly designed conserved/degenerate primer pair sequences against the viral genome and assess the mutation load of both primers and amplicons. CoVrimer uses mutation data obtained from an online platform established by NGDC-CNCB (12 May 2021) to identify genomic regions, either conserved or with low levels of mutations, from which potential primer pairs are designed and provided to the user for filtering based on generalized and SARS-CoV-2 specific parameters. Alignments of primers and probes can be visualized with respect to the reference genome, indicating variant details and the level of conservation. Consequently, CoVrimer is likely to help researchers with the challenges posed by viral evolution and is freely available at http://konulabapps.bilkent.edu.tr:3838/CoVrimer/.

A comparative recombination analysis of human coronaviruses and implications for the SARS-CoV-2 pandemic

The SARS-CoV-2 pandemic prompts evaluation of recombination in human coronavirus (hCoV) evolution. We undertook recombination analyses of 158,118 public seasonal hCoV, SARS-CoV-1, SARS-CoV-2 and MERS-CoV genome sequences using the RDP4 software. We found moderate evidence for 8 SARS-CoV-2 recombination events, two of which involved the spike gene, and low evidence for one SARS-CoV-1 recombination event. Within MERS-CoV, 229E, OC43, NL63 and HKU1 datasets, we noted 7, 1, 9, 14, and 1 high-confidence recombination events, respectively. There was propensity for recombination breakpoints in the non-ORF1 region of the genome containing structural genes, and recombination severely skewed the temporal structure of these data, especially for NL63 and OC43. Bayesian time-scaled analyses on recombinant-free data indicated the sampled diversity of seasonal CoVs emerged in the last 70 years, with 229E displaying continuous lineage replacements. These findings emphasize the importance of genomic based surveillance to detect recombination in SARS-CoV-2, particularly if recombination may lead to immune evasion.

Science at Its Best in the Time of the COVID-19 Pandemic

The COVID-19 (coronavirus disease 2019) pandemic has spread worldwide, leading to the deaths of millions and changing the way we live; we all hope to see the end of the pandemic soon. Nonetheless, an urgent need for medical interventions led to unprecedented and focused research efforts to translate scientific knowledge to new therapeutic and preventative interventions. Procedures were simplified, and new norms were established to expedite high-quality scientific output. We do hope that these changes will be adopted and streamlined to advance science in the future.

Contribution of SARS-CoV-2 Accessory Proteins to Viral Pathogenicity in K18 Human ACE2 Transgenic Mice

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the viral pathogen responsible for the current coronavirus disease 2019 (COVID-19) pandemic. As of 19 May 2021, John Hopkins University’s COVID-19 tracking platform reported 3.3 million deaths associated with SARS-CoV-2 infection. Currently, the World Health Organization has granted emergency use listing (EUL) to six COVID-19 vaccine candidates. However, much of the pathogenesis observed during SARS-CoV-2 infection remains elusive. To gain insight into the contribution of individual accessory open reading frame (ORF) proteins in SARS-CoV-2 pathogenesis, we used our recently described reverse-genetics system approach to successfully engineer recombinant SARS-CoV-2 (rSARS-CoV-2) constructs; we removed individual viral ORF3a, −6, −7a, −7b, and −8 proteins from them, and we characterized the resulting recombinant viruses in vitro and in vivo. Our results indicate differences in plaque morphology, with ORF-deficient (ΔORF) viruses producing smaller plaques than those of the wild type (rSARS-CoV-2/WT). However, growth kinetics of ΔORF viruses were like those of rSARS-CoV-2/WT. Interestingly, infection of K18 human angiotensin-converting enzyme 2 (hACE2) transgenic mice with the ΔORF rSARS-CoV-2s identified ORF3a and ORF6 as the major contributors of viral pathogenesis, while ΔORF7a, ΔORF7b, and ΔORF8 rSARS-CoV-2s induced pathology comparable to that of rSARS-CoV-2/WT. This study demonstrates the robustness of our reverse-genetics system to generate rSARS-CoV-2 constructs and the major role for ORF3a and ORF6 in viral pathogenesis, providing important information for the generation of attenuated forms of SARS-CoV-2 for their implementation as live attenuated vaccines for the treatment of SARS-CoV-2 infection and associated COVID-19.

IMPORTANCE Despite great efforts put forward worldwide to combat the current coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be a human health and socioeconomic threat. Insights into the pathogenesis of SARS-CoV-2 and the contribution of viral proteins to disease outcome remain elusive. Our study aims (i) to determine the contribution of SARS-CoV-2 accessory open reading frame (ORF) proteins to viral pathogenesis and disease outcome and (ii) to develop a synergistic platform combining our robust reverse-genetics system to generate recombinant SARS-CoV-2 constructs with a validated rodent model of infection and disease. We demonstrate that SARS-CoV-2 ORF3a and ORF6 contribute to lung pathology and ultimately disease outcome in K18 hACE2 transgenic mice, while ORF7a, ORF7b, and ORF8 have little impact on disease outcome. Moreover, our combinatory platform serves as a foundation for generating attenuated forms of the virus to develop live attenuated vaccines for the treatment of SARS-CoV-2.

Genetic Variability of the SARS-CoV-2 Pocketome

In the absence of effective treatment, COVID-19 is likely to remain a global disease burden. Compounding this threat is the near certainty that novel coronaviruses with pandemic potential will emerge in years to come. Pan-coronavirus drugs-agents active against both SARS-CoV-2 and other coronaviruses-would address both threats. A strategy to develop such broad-spectrum inhibitors is to pharmacologically target binding sites on SARS-CoV-2 proteins that are highly conserved in other known coronaviruses, the assumption being that any selective pressure to keep a site conserved across past viruses will apply to future ones. Here we systematically mapped druggable binding pockets on the experimental structure of 15 SARS-CoV-2 proteins and analyzed their variation across 27 α- and β-coronaviruses and across thousands of SARS-CoV-2 samples from COVID-19 patients. We find that the two most conserved druggable sites are a pocket overlapping the RNA binding site of the helicase nsp13 and the catalytic site of the RNA-dependent RNA polymerase nsp12, both components of the viral replication-transcription complex. We present the data on a public web portal (https://www.thesgc.org/SARSCoV2_pocketome/), where users can interactively navigate individual protein structures and view the genetic variability of drug-binding pockets in 3D.

Molecular characterization of SARS-CoV-2 from Bangladesh: implications in genetic diversity, possible origin of the virus, and functional significance of the mutations

In a try to understand the pathogenesis, evolution and epidemiology of the SARS-CoV-2 virus, scientists from all over the world are tracking its genomic changes in real-time. Genomic studies can be helpful in understanding the disease dynamics. We have downloaded 324 complete and near complete SARS-CoV-2 genomes submitted in GISAID database from Bangladesh which were isolated between 30 March to 7 September, 2020. We then compared these genomes with Wuhan reference sequence and found 4160 mutation events including 2253 missense single nucleotide variations, 38 deletions and 10 insertions. The C>T nucleotide change was most prevalent (41% of all mutations) possibly due to selective mutation pressure to reduce CpG sites to evade CpG targeted host immune response. The most frequent mutation that occurred in 98% isolates was 3037C>T which is a synonymous change that usually accompanied 3 other mutations that include 241C>T, 14408C>T (P323L in RdRp) and 23403A>G (D614G in spike protein). The P323L was reported to increase mutation rate and D614G is associated with increased viral replication and currently most prevalent variant circulating all over the world. We identified multiple missense mutations in B-cell and T-cell predicted epitope regions and/or PCR target regions (including R203K and G204R that occurred in 86% of the isolates) that may impact immunogenicity and/or RT-PCR based diagnosis. Our analysis revealed 5 large deletion events in ORF7a and ORF8 gene products that may be associated with less severity of the disease and increased viral clearance. Our phylogeny analysis identified most of the isolates belonged to the Nextstrain clade 20B (86%) and GISAID clade GR (88%). Most of our isolates shared common ancestors either directly with European countries or jointly with middle eastern countries as well as Australia and India. Interestingly, the 19B clade (GISAID S clade) was unique to Chittagong, which was originally prevalent in China. This reveals possible multiple introductions of the virus in Bangladesh via different routes. Hence, more genome sequencing and analysis with related clinical data is needed to interpret functional significance and better predict the disease dynamics that may be helpful for policy makers to control the COVID-19 pandemic.

A daily-updated database and tools for comprehensive SARS-CoV-2 mutation-annotated trees

The vast scale of SARS-CoV-2 sequencing data has made it increasingly challenging to comprehensively analyze all available data using existing tools and file formats. To address this, we present a database of SARS-CoV-2 phylogenetic trees inferred with unrestricted public sequences, which we update daily to incorporate new sequences. Our database uses the recently-proposed mutation-annotated tree (MAT) format to efficiently encode the tree with branches labeled with parsimony-inferred mutations as well as Nextstrain clade and Pango lineage labels at clade roots. As of June 9, 2021, our SARS-CoV-2 MAT consists of 834,521 sequences and provides a comprehensive view of the virus’ evolutionary history using public data. We also present matUtils – a command-line utility for rapidly querying, interpreting and manipulating the MATs. Our daily-updated SARS-CoV-2 MAT database and matUtils software are available at http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/ and https://github.com/yatisht/usher, respectively.

Genome-Wide Variation in Betacoronaviruses

The Severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2 originated in bats and adapted to infect humans. Several SARS-CoV-2 strains have been identified. Genetic variation is fundamental to virus evolution and, in response to selection pressure, is manifested as the emergence of new strains and species adapted to different hosts or with novel pathogenicity. The combination of variation and selection forms a genetic footprint on the genome, consisting of the preferential accumulation of mutations in particular areas. Properties of betacoronaviruses contributing to variation and the emergence of new strains and species are beginning to be elucidated. To better understand their variation, we profiled the accumulation of mutations in all species in the genus Betacoronavirus, including SARS-CoV-2 and two other species that infect humans: SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Variation profiles identified both genetically stable and variable areas at homologous locations across species within the genus Betacoronavirus. The S glycoprotein is the most variable part of the genome and is structurally disordered. Other variable parts include proteins 3 and 7 and ORF8, which participate in replication and suppression of antiviral defense. In contrast, replication proteins in ORF1b are the least variable. Collectively, our results show that variation and structural disorder in the S glycoprotein is a general feature of all members of the genus Betacoronavirus, including SARS-CoV-2. These findings highlight the potential for the continual emergence of new species and strains with novel biological properties and indicate that the S glycoprotein has a critical role in host adaptation.

IMPORTANCE Natural infection with SARS-CoV-2 and vaccines triggers the formation of antibodies against the S glycoprotein, which are detected by antibody-based diagnostic tests. Our analysis showed that variation in the S glycoprotein is a general feature of all species in the genus Betacoronavirus, including three species that infect humans: SARS-CoV, SARS-CoV-2, and MERS-CoV. The variable nature of the S glycoprotein provides an explanation for the emergence of SARS-CoV-2, the differentiation of SARS-CoV-2 into strains, and the probability of SARS-CoV-2 repeated infections in people. Variation of the S glycoprotein also has important implications for the reliability of SARS-CoV-2 antibody-based diagnostic tests and the design and deployment of vaccines and antiviral drugs. These findings indicate that adjustments to vaccine design and deployment and to antibody-based diagnostic tests are necessary to account for S glycoprotein variation.

Single-nucleotide conservation state annotation of the SARS-CoV-2 genome

Given the global impact and severity of COVID-19, there is a pressing need for a better understanding of the SARS-CoV-2 genome and mutations. Multi-strain sequence alignments of coronaviruses (CoV) provide important information for interpreting the genome and its variation. We apply a comparative genomics method, ConsHMM, to the multi-strain alignments of CoV to annotate every base of the SARS-CoV-2 genome with conservation states based on sequence alignment patterns among CoV. The learned conservation states show distinct enrichment patterns for genes, protein domains, and other regions of interest. Certain states are strongly enriched or depleted of SARS-CoV-2 mutations, which can be used to predict potentially consequential mutations. We expect the conservation states to be a resource for interpreting the SARS-CoV-2 genome and mutations.

Ultrafast Sample placement on Existing tRees (UShER) enables real-time phylogenetics for the SARS-CoV-2 pandemic

As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering in a new era of 'genomic contact tracing'-that is, using viral genomes to trace local transmission dynamics. However, because the viral phylogeny is already so large-and will undoubtedly grow many fold-placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach greatly improves the speed of phylogenetic placement of new samples and data visualization, making it possible to complete the placements under the constraints of real-time contact tracing. Thus, our method addresses an important need for maintaining a fully updated reference phylogeny. We make these tools available to the research community through the University of California Santa Cruz SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for SARS-CoV-2 specifically for laboratories worldwide.

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.

Unlocking capacities of viral genomics for the COVID-19 pandemic response

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.

A comprehensive analysis and resource to use CRISPR-Cas13 for broad-spectrum targeting of RNA viruses

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and variants has led to significant mortality. We recently reported that an RNA-targeting CRISPR-Cas13 system, called prophylactic antiviral CRISPR in human cells (PAC-MAN), offered an antiviral strategy against SARS-CoV-2 and influenza A virus. Here, we expand in silico analysis to use PAC-MAN to target a broad spectrum of human- or livestock-infectious RNA viruses with high specificity, coverage, and predicted efficiency. Our analysis reveals that a minimal set of 14 CRISPR RNAs (crRNAs) is able to target >90% of human-infectious viruses across 10 RNA virus families. We predict that a set of 5 experimentally validated crRNAs can target new SARS-CoV-2 variant sequences with zero mismatches. We also build an online resource (crispr-pacman.stanford.edu) to support community use of CRISPR-Cas13 for broad-spectrum RNA virus targeting. Our work provides a new bioinformatic resource for using CRISPR-Cas13 to target diverse RNA viruses to facilitate the development of CRISPR-based antivirals.