Distinct mutations and lineages of SARS‐CoV‐2 virus in the early phase of COVID‐19 pandemic and subsequent 1‐year global expansion

Abstract

A novel coronavirus, SARS‐CoV‐2, has caused over 274 million cases and over 5.3 million deaths worldwide since it occurred in December 2019 in Wuhan, China. Here we conceptualized the temporospatial evolutionary and expansion dynamics of SARS‐CoV‐2 by taking a series of the cross‐sectional view of viral genomes from early outbreak in January 2020 in Wuhan to the early phase of global ignition in early April, and finally to the subsequent global expansion by late December 2020. Based on the phylogenetic analysis of the early patients in Wuhan, Wuhan/WH04/2020 is supposed to be a more appropriate reference genome of SARS‐CoV‐2, instead of the first sequenced genome Wuhan‐Hu‐1. By scrutinizing the cases from the very early outbreak, we found a viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations (i.e., M type) had become the overwhelmingly dominant genotype (95.3%) of the pandemic 1 year later. By analyzing 4013 SARS‐CoV‐2 genomes from different continents by early April, we were able to interrogate the viral genomic composition dynamics of the initial phase of global ignition over a time span of 14 weeks. Eleven major viral genotypes with unique geographic distributions were also identified. WE1 type, a descendant of M and predominantly witnessed in western Europe, consisted of half of all the cases (50.2%) at the time. The mutations of major genotypes at the same hierarchical level were mutually exclusive, which implies that various genotypes bearing the specific mutations were propagated during human‐to‐human transmission, not by accumulating hot‐spot mutations during the replication of individual viral genomes. As the pandemic was unfolding, we also used the same approach to analyze 261 323 SARS‐CoV‐2 genomes from the world since the outbreak in Wuhan (i.e., including all the publicly available viral genomes) to recapitulate our findings over 1‐year time span. By December 25, 2020, 95.3% of global cases were M type and 93.0% of M‐type cases were WE1. In fact, at present all the five variants of concern (VOC) are the descendants of WE1 type. This study demonstrates that viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures. Moreover, the dynamics of viral mutational spectrum in the study may help the early identification of new strains in patients to reduce further spread of infection, guide the development of molecular diagnosis and vaccines against COVID‐19, and help assess their accuracy and efficacy in real world at real time.

Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations

“…To validate the results obtained from the Pearson correlation, the hierarchical clustering technique was applied; this method groups similar objects together. Since highly frequent mutations tend to play a critical role in the evolution of the virus ( 17 ), the 25 most significant mutations that were present in more than 10% of the genomes were tested for similarity using the hierarchical clustering technique. The figure_factory method from the plotly library of Python was used to perform the hierarchical clustering on the binary matrix of the 25 most significant mutations.…”

“…They identified 3037C>T as the most frequent mutation, as it occurred in 98% of isolates. Though synonymous, this mutation was shown to co-occur with 3 other mutations, including 241C>T, 14408C>T, and 23403A>G. In another study, Chen et al ( 17 ) analyzed 261,323 sequences of SARS-CoV-2 from across the globe to study the evolution of the virus. The authors observed that the initial SARS-CoV-2 M genotype ignited the COVID-19 outbreak.…”

“…The authors observed that the initial SARS-CoV-2 M genotype ignited the COVID-19 outbreak. The M genotype harbored two concurrent mutations and was transformed to WE1 by acquiring four additional concurrent mutations ( 17 ). The WE1 genotype further evolved into WE1.1 by incorporating three additional concurrent mutations.…”

Development and Characterization of Phage Display-Derived Monoclonal Antibodies to the S2 Domain of Spike Proteins of Wild-Type SARS-CoV-2 and Multiple Variants

“…The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus [ 1 ]. Ever since the initial SARS-CoV-2 outbreak in early December 2019, high-frequency mutations in SARS-CoV-2 have altered the infectivity of the virus and led to the emergence of a variety of SARS-CoV-2 variants, including Alpha, Beta, Gamma, Delta, Kappa, and Omicron [ 2 , 3 ]. As of January 2023, approximately 662 million confirmed COVID-19 cases and more than 6.7 million deaths have been reported worldwide [ 4 ].…”

Understanding mental health conditions and key coping strategies utilized during major lockdowns in the Caribbean based on Google trends searches

“…Past research found persons with specific affective temperament types (depressive, cyclothymic, hyperthymic, irritable, and anxious) prone to adverse clinical outcomes such as higher suicide behavior [ 16 , 17 ]. For these reasons, the impact of COVID-19 on mental health is becoming an increasing concern among policymakers and health practitioners, particularly in the face of multiple waves of infections and longer and more intensive SIPOs measures adopted by Governments [ [18] , [19] , [20] ]. Equally important but not fully explored in terms of research is understanding coping strategies (positive and negative) used by citizens to manage the social isolation and distress that come with prolonged lockdowns [ 21 , 22 ].…”