Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution
Various lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have contributed to prolongation of the Coronavirus Disease 2019 (COVID-19) pandemic. Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have...
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creator | Hassan, Sk Sarif Basu, Pallab Redwan, Elrashdy M. Lundstrom, Kenneth Choudhury, Pabitra Pal Serrano-Aroca, Ángel Azad, Gajendra Kumar Aljabali, Alaa A.A. Palu, Giorgio Abd El-Aziz, Tarek Mohamed Barh, Debmalya Uhal, Bruce D. Adadi, Parise Takayama, Kazuo Bazan, Nicolas G. Tambuwala, Murtaza M. Lal, Amos Chauhan, Gaurav Baetas-da-Cruz, Wagner Sherchan, Samendra P. Uversky, Vladimir N. |
description | Various lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have contributed to prolongation of the Coronavirus Disease 2019 (COVID-19) pandemic. Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown that an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least 500 in each SARS-CoV-2 protein, we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frame (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. Characterization of the periodically aperiodic nature of the demographic spread of SARS-CoV-2 variants in various countries can contribute to the identification of the origin of SARS-CoV-2. |
doi_str_mv | 10.1016/j.envres.2021.112092 |
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Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown that an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least 500 in each SARS-CoV-2 protein, we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frame (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. Characterization of the periodically aperiodic nature of the demographic spread of SARS-CoV-2 variants in various countries can contribute to the identification of the origin of SARS-CoV-2.</description><identifier>ISSN: 0013-9351</identifier><identifier>EISSN: 1096-0953</identifier><identifier>DOI: 10.1016/j.envres.2021.112092</identifier><identifier>PMID: 34562480</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Aperiodically periodic ; COVID-19 ; Humans ; Invariant residues ; Mutation ; Mutations ; Relative frequency ; SARS-CoV-2 ; Uncertainty</subject><ispartof>Environmental research, 2022-03, Vol.204 (Pt B), p.112092-112092, Article 112092</ispartof><rights>2021 Elsevier Inc.</rights><rights>Copyright © 2021 Elsevier Inc. All rights reserved.</rights><rights>2021 Elsevier Inc. All rights reserved. 2021 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c463t-3451d301ce89d072a02e646dfb5109b6a864c22bad062e3468976bf365cc11483</citedby><cites>FETCH-LOGICAL-c463t-3451d301ce89d072a02e646dfb5109b6a864c22bad062e3468976bf365cc11483</cites><orcidid>0000-0003-4724-9463 ; 0000-0002-9953-3848 ; 0000-0002-0021-2033 ; 0000-0001-5478-526X ; 0000-0002-3441-9673 ; 0000-0002-0580-5209</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.envres.2021.112092$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,315,781,785,886,3551,27929,27930,46000</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34562480$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hassan, Sk Sarif</creatorcontrib><creatorcontrib>Basu, Pallab</creatorcontrib><creatorcontrib>Redwan, Elrashdy M.</creatorcontrib><creatorcontrib>Lundstrom, Kenneth</creatorcontrib><creatorcontrib>Choudhury, Pabitra Pal</creatorcontrib><creatorcontrib>Serrano-Aroca, Ángel</creatorcontrib><creatorcontrib>Azad, Gajendra Kumar</creatorcontrib><creatorcontrib>Aljabali, Alaa A.A.</creatorcontrib><creatorcontrib>Palu, Giorgio</creatorcontrib><creatorcontrib>Abd El-Aziz, Tarek Mohamed</creatorcontrib><creatorcontrib>Barh, Debmalya</creatorcontrib><creatorcontrib>Uhal, Bruce D.</creatorcontrib><creatorcontrib>Adadi, Parise</creatorcontrib><creatorcontrib>Takayama, Kazuo</creatorcontrib><creatorcontrib>Bazan, Nicolas G.</creatorcontrib><creatorcontrib>Tambuwala, Murtaza M.</creatorcontrib><creatorcontrib>Lal, Amos</creatorcontrib><creatorcontrib>Chauhan, Gaurav</creatorcontrib><creatorcontrib>Baetas-da-Cruz, Wagner</creatorcontrib><creatorcontrib>Sherchan, Samendra P.</creatorcontrib><creatorcontrib>Uversky, Vladimir N.</creatorcontrib><title>Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution</title><title>Environmental research</title><addtitle>Environ Res</addtitle><description>Various lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have contributed to prolongation of the Coronavirus Disease 2019 (COVID-19) pandemic. 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No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. 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Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown that an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least 500 in each SARS-CoV-2 protein, we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frame (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. 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subjects | Aperiodically periodic COVID-19 Humans Invariant residues Mutation Mutations Relative frequency SARS-CoV-2 Uncertainty |
title | Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution |
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