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Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.

ABSTRACT: SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to May 2022, 10 million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches based on sets of correlated single nucleotide variations (SNVs) for comprehensive subtyping and pattern recognition of transmission dynamics. The approach outperformed single-SNV and spike-centric scans. Moreover, the derived subtypes elucidate the relationship of signature SNVs and transmission dynamics. We found that different subtypes of the same variant, including Delta and Omicron exhibited distinct temporal trajectories. For example, some Delta and Omicron subtypes did not spread rapidly, while others did. We identified sets of characteristic SNVs that appeared to enhance transmission or decrease efficacy of antibodies for some subtypes. We also identified a set of SNVs that appeared to suppress transmission or increase viral sensitivity to antibodies. For the Omicron variant, the dominant type in the world, we identified the subtypes with enhanced and suppressed transmission in an analysis of eight million genomes as of March 2022 and further confirmed the findings in a later analysis of ten million genomes as of May 2022. While the "enhancer" SNVs exhibited an enriched presence on the spike protein, the "suppressor" SNVs are mainly elsewhere. Disruption of the SNV correlation largely destroyed the enhancer-suppressor phenomena. These results suggest the importance of fine subtyping of variants, and point to potential complex interactions among SNVs.

SUBMITTER: Yang HC

PROVIDER: S-EPMC9802201 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.

Yang Hsin-Chou HC Wang Jen-Hung JH Yang Chih-Ting CT Lin Yin-Chun YC Hsieh Han-Ni HN Chen Po-Wen PW Liao Hsiao-Chi HC Chen Chun-Houh CH Liao James C JC

PNAS nexus 20220901 4

SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to May 2022, 10 million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches based on sets of correlated single nucleotide variations (SNVs) for comprehensive subtyping and pattern recognition of transmission dynamics. The approach outperforme ...[more]

PMID: 36714842

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Project description:With the progression of the global SARS-CoV-2 pandemic, the new variants have become more infectious and continue spreading at a higher rate than pre-existing ones. Thus, we conducted a study to explore the epidemiology of emerging variants of SARS-CoV-2 that circulated in Bangladesh from December 2020 to September 2021, representing the 2nd and 3rd waves. We collected new cases and deaths per million daily data with the reproduction rate. We retrieved 928 SARS-CoV-2 sequences from GISAID and performed phylogenetic tree construction and mutation analysis. Case counts were lower initially at the end of 2020, during January-February and April-May 2021, whereas the death toll reached the highest value of 1.587 per million on the first week of August and then started to decline. All the variants (α, β, δ, η) were prevalent in the capital city, Dhaka, with dispersion to large cities, such as Sylhet and Chattogram. The B.1.1.25 lineage was prevalent during December 2020, but the B.1.617.2/δ variant was later followed by the B.1.351/β variant. The phylogeny revealed that the various strains found in Bangladesh could be from numerous countries. The intra-cluster and inter-cluster communication began in Bangladesh soon after the virus arrived. The prominent amino acid substitution was D614G from December 2020 to July 2021 (93.5 to 100%). From February-April, one of the VOC's important mutations, N501Y substitution, was also estimated at 51.8%, 76.1%, and 65.1% for the α, β and γ variants, respectively. The γ variant's unique mutation K417T was detected only at 1.8% in February. Another frequent mutation was P681R, a salient feature of the δ variant, detected in June (88.2%) and July (100%). Furthermore, only one γ variant was detected during the entire second and third wave, whereas no η variant was observed in this period. This rapid growth in the number of variants identified across Bangladesh shows virus adaptation and a lack of strict quarantine, prompting periodic genomic surveillance to foresee the spread of new variants, if any, and to take preventive measures as soon as possible.

Project description:IntroductionAfter three years since the beginning of the pandemic, the new coronavirus continues to raise several questions regarding its infectious process and host response. Several mutations occurred in different regions of the SARS-CoV-2 genome, such as in the spike gene, causing the emergence of variants of concern and interest (VOCs and VOIs), of which some present higher transmissibility and virulence, especially among patients with previous comorbidities. It is essential to understand its spread dynamics to prevent and control new biological threats that may occur in the future. In this population_based retrospective observational study, we generated data and used public databases to understand SARS-CoV-2 dynamics.MethodsWe sequenced 1,003 SARS-CoV-2 genomes from naso-oropharyngeal swabs and saliva samples from Pará from May 2020 to October 2022. To gather epidemiological data from Brazil and the world, we used FIOCRUZ and GISAID databases.ResultsRegarding our samples, 496 (49.45%) were derived from female participants and 507 (50.55%) from male participants, and the average age was 43 years old. The Gamma variant presented the highest number of cases, with 290 (28.91%) cases, followed by delta with 53 (5.28%). Moreover, we found seven (0.69%) Omicron cases and 651 (64.9%) non-VOC cases. A significant association was observed between sex and the clinical condition (female, p = 8.65e-08; male, p = 0.008961) and age (p = 3.6e-10).DiscussionAlthough gamma had been officially identified only in December 2020/January 2021, we identified a gamma case from Belém (capital of Pará State) dated May 2020 and three other cases in October 2020. This indicates that this variant was circulating in the North region of Brazil several months before its formal identification and that Gamma demonstrated its actual transmission capacity only at the end of 2020. Furthermore, the public data analysis showed that SARS-CoV-2 dispersion dynamics differed in Brazil as Gamma played an important role here, while most other countries reported a new infection caused by the Delta variant. The genetic and epidemiological information of this study reinforces the relevance of having a robust genomic surveillance service that allows better management of the pandemic and that provides efficient solutions to possible new disease-causing agents.

Dataset Information

Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.

Publications

Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.

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