Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Yu D

PROVIDER: S-EPMC8921643 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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

Yu Dalang D Yang Xiao X Tang Bixia B Pan Yi-Hsuan YH Yang Jianing J Duan Guangya G Zhu Junwei J Hao Zi-Qian ZQ Mu Hailong H Dai Long L Hu Wangjie W Zhang Mochen M Cui Ying Y Jin Tong T Li Cui-Ping CP Ma Lina L Su Xiao X Zhang Guoqing G Zhao Wenming W Li Haipeng H

Briefings in bioinformatics 20220301 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 ...[more]

PMID: 35043153

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Project description:The novel coronavirus, SARS-coronavirus (CoV)-2 (SARS-CoV-2), has caused over 17 million infections in just a few months, with disease manifestations ranging from largely asymptomatic infection to critically severe disease. The remarkable spread and unpredictable disease outcomes continue to challenge management of this infection. Among the hypotheses to explain the heterogeneity of symptoms is the possibility that exposure to other coronaviruses (CoVs), or overall higher capability to develop immunity against respiratory pathogens, may influence the evolution of immunity to SARS-CoV-2. Thus, we profiled the immune response across multiple coronavirus receptor binding domains (RBDs), respiratory viruses, and SARS-CoV-2, to determine whether heterologous immunity to other CoV-RBDs or other infections influenced the evolution of the SARS-CoV-2 humoral immune response. Overall changes in subclass, isotype, and Fc-receptor binding were profiled broadly across a cohort of 43 individuals against different coronaviruses-RBDs of SARS-CoV-2 and the more common HKU1 and NL63 viruses. We found rapid functional evolution of responses to SARS-CoV-2 over time, along with broad but relatively more time-invariant responses to the more common CoVs. Moreover, there was little evidence of correlation between SARS-CoV-2 responses and HKU1, NL63, and respiratory infection (influenza and respiratory syncytial virus) responses. These findings suggest that common viral infections including common CoV immunity, targeting the receptor binding domain involved in viral infection, do not appear to influence the rapid functional evolution of SARS-CoV-2 immunity, and thus should not impact diagnostics or shape vaccine-induced immunity.IMPORTANCE A critical step to ending the spread of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the ability to detect, diagnose, and understand why some individuals develop mild and others develop severe disease. For example, defining the early evolutionary patterns of humoral immunity to SARS-CoV-2, and whether prevalent coronaviruses or other common infections influence the evolution of immunity, remains poorly understood but could inform diagnostic and vaccine development. Here, we deeply profiled the evolution of SARS-CoV-2 immunity, and how it is influenced by other coinfections. Our data suggest an early and rapid rise in functional humoral immunity in the first 2 weeks of infection across antigen-specific targets, which is negligibly influenced by cross-reactivity to additional common coronaviruses or common respiratory infections. These data suggest that preexisting receptor binding domain-specific immunity does not influence or bias the evolution of immunity to SARS-CoV-2 and should have negligible influence on shaping diagnostic or vaccine-induced immunity.

Project description:The mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution and transmission is elusive and its understanding, a prerequisite to forecast emerging variants, is of paramount importance. SARS-CoV-2 evolution is driven by the mechanisms at molecular and organism scales and regulated by the transmission pathways at the population scale. In this review, we show that infectivity-based natural selection was discovered as the mechanism for SARS-CoV-2 evolution and transmission in July 2020. In April 2021, we proved beyond all doubt that such a natural selection via infectivity-based transmission pathway remained the sole mechanism for SARS-CoV-2 evolution. However, we reveal that antibody-disruptive co-mutations [Y449S, N501Y] on the spike protein receptor-binding domain (RBD) debuted as a new vaccine-resistant transmission pathway of viral evolution in highly vaccinated populations a few months ago. Over one year ago, we foresaw that mutations on RBD residues, 452 and 501, would "both have high chances to mutate into significantly more infectious COVID-19 strains". Mutations on these residues underpin prevailing SARS-CoV-2 variants Alpha, Beta, Gamma, Delta, Epsilon, Theta, Kappa, Lambda, and Mu at present and are expected to be vital to emerging variants in the future. We anticipate that viral evolution will combine RBD co-mutations at these two sites, creating future variants that are about ten times more infectious than the original SARS-CoV-2. Additionally, two complementary transmission pathways of viral evolution, i.e., infectivity and vaccine resistance will prolong our battle with COVID-19 for years. We predict that RBD co-mutation sets [A411S, L452R, T478K], [L452R, T478K, N501Y], [L452R, T478K, E484K, N501Y], [K417N, L452R, T478K], and [P384L, K417N, E484K, N501Y] will have a high chance to grow into dominating variants due to their high infectivity and/or strong ability to break through current vaccines, calling for the development of new vaccines and antibody therapies.

Project description:BackgroundThe COVID-19 pandemic poses an unprecedented public health challenge in Malaysia. The impact of COVID-19 varies between countries, including geographically divided states within a country. The deadly transmission of COVID-19 has taken a heavy toll in Sabah, Malaysia's third most populous state, contributing nearly 10% to the recorded national death toll as of 31 December 2022. Although several SARS-CoV-2 genome sequences have been analysed in Malaysia, molecular epidemiology data from Sabah focusing on the diversity and evolution of SARS-CoV-2 variants are still lacking. This study examines the major SARS-CoV-2 variants and emerging mutations from Sabah, the Malaysian Borneo, which is geographically divided from West Malaysia by the South China Sea.MethodsA total of 583 COVID-19 samples were subjected to whole genome sequencing and analysed with an additional 1123 Sabah COVID-19 sequences retrieved from the GISAID EpiCoV consortium. Nextclade and Pangolin were used to classify these sequences according to the clades and lineages. To determine the molecular evolutionary characteristics, Bayesian time-scaled phylogenetic analysis employing the maximum likelihood algorithm was performed on selected SARS-CoV-2 genome sequences, using the Wuhan-Hu-1 sequence as a reference.ResultsSabah was affected starting from the second COVID-19 wave in Malaysia, and the early sequences were classified under the O clade. The clade was gradually replaced during subsequent waves by G, GH, GK and GRA, with the latter being dominant as of December 2022. Phylogenetically, the Delta isolates in this study belong to the three main subclades 21A, 21J and 21I, while Omicron isolates belong to 21M, 21L and 22B. The time-scaled phylogeny suggested that SARS-CoV-2 introduced into Sabah originated from Peninsular Malaysia in early March 2020, and phylodynamic analysis indicated that increased viral spread was observed in early March and declined in late April, followed by an evolutionary stationary phase in June 2020.ConclusionContinuous molecular epidemiology of SARS-CoV-2 in Sabah will provide a deeper understanding of the emergence and dominance of each variant in the locality, thus facilitating public health intervention measures.

Dataset Information

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

Publications

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

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