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2022;12 868414.

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

Ranjeet Maurya, Pallavi Mishra, Aparna Swaminathan, Varsha Ravi, Sheeba Saifi, Akshay Kanakan, Priyanka Mehta, Priti Devi, Shaista Praveen, Sandeep Budhiraja, Bansidhar Tarai, Shimpa Sharma, Rajesh J Khyalappa, Meghnad G Joshi, Rajesh Pandey
Author Information
  1. Ranjeet Maurya: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  2. Pallavi Mishra: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  3. Aparna Swaminathan: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  4. Varsha Ravi: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  5. Sheeba Saifi: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  6. Akshay Kanakan: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  7. Priyanka Mehta: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  8. Priti Devi: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  9. Shaista Praveen: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
  10. Sandeep Budhiraja: Max Super Speciality Hospital (A Unit of Devki Devi Foundation), Max Healthcare, Delhi, India.
  11. Bansidhar Tarai: Max Super Speciality Hospital (A Unit of Devki Devi Foundation), Max Healthcare, Delhi, India.
  12. Shimpa Sharma: Dr. D. Y. Patil Medical College, Pune, India.
  13. Rajesh J Khyalappa: Dr. D. Y. Patil Medical College, Pune, India.
  14. Meghnad G Joshi: Dr. D. Y. Patil Medical College, Pune, India.
  15. Rajesh Pandey: INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research (CSIR)-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
PMID: 35386683 DOI: 10.3389/fcimb.2022.868414

Abstract

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

Keywords

COVID-19 SARS-CoV-2 disease outcome global frequency flip molecular dynamics simulation mutation analysis

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MeSH Term

COVID-19
Genome, Viral
Humans
Mutation
Pandemics
Phylogeny
SARS-CoV-2
Journal Article Research Support, U.S. Gov't, Non-P.H.S.
Article has an altmetric score of 3

Word Cloud

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