Global landscape of SARS-CoV-2 mutations and conserved regions

Abbasian, MH; Mahmanzar, M; Rahimian, K; Mahdavi, B; Tokhanbigli, S; Moradi, B; Sisakht, MM; Deng, Y

Global landscape of SARS-CoV-2 mutations and conserved regions

Abbasian, MH Mahmanzar, M Rahimian, K Mahdavi, B Tokhanbigli, S Moradi, B Sisakht, MM Deng, Y

Permalink

Publisher:: Springer Nature
Publication Type:: Journal Article
Citation:: Journal of Translational Medicine, 2023, 21, (1), pp. 152
Issue Date:: 2023-02-25

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (4.92 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Abbasian, MH
dc.contributor.author	Mahmanzar, M
dc.contributor.author	Rahimian, K
dc.contributor.author	Mahdavi, B
dc.contributor.author	Tokhanbigli, S
dc.contributor.author	Moradi, B
dc.contributor.author	Sisakht, MM
dc.contributor.author	Deng, Y
dc.date.accessioned	2024-05-04T03:03:49Z
dc.date.available	2023-02-15
dc.date.available	2024-05-04T03:03:49Z
dc.date.issued	2023-02-25
dc.identifier.citation	Journal of Translational Medicine, 2023, 21, (1), pp. 152
dc.identifier.issn	1479-5876
dc.identifier.issn	1479-5876
dc.identifier.uri	http://hdl.handle.net/10453/178648
dc.description.abstract	BackgroundAt the end of December 2019 a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 SARS CoV 2 disease COVID 19 has been identified in Wuhan a central city in China and then spread to every corner of the globe As of October 8 2022 the total number of COVID 19 cases had reached over 621 million worldwide with more than 6 56 million confirmed deaths Since SARS CoV 2 genome sequences change due to mutation and recombination it is pivotal to surveil emerging variants and monitor changes for improving pandemic management Methods10 287 271 SARS CoV 2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24 2020 to April 2022 Python programming language version 3 8 0 software was utilized to process FASTA files to identify variants and sequence conservation The NCBI RefSeq SARS CoV 2 genome accession no NC 045512 2 was considered as the reference sequence ResultsSix mutations had more than 50 frequency in global SARS CoV 2 These mutations include the P323L 99 3 in NSP12 D614G 97 6 in S the T492I 70 4 in NSP4 R203M 62 8 in N T60A 61 4 in Orf9b and P1228L 50 0 in NSP3 In the SARS CoV 2 genome no mutation was observed in more than 90 of nsp11 nsp7 nsp10 nsp9 nsp8 and nsp16 regions On the other hand N nsp3 S nsp4 nsp12 and M had the maximum rate of mutations In the S protein the highest mutation frequency was observed in aa 508 635 0 77 and aa 381 508 0 43 The highest frequency of mutation was observed in aa 66 88 2 19 aa 7 14 and aa 164 246 2 92 in M E and N proteins respectively ConclusionTherefore monitoring SARS CoV 2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS CoV 2 diagnostic efficiency and design safe and effective vaccines against emerging variants
dc.format	Electronic
dc.language	eng
dc.publisher	Springer Nature
dc.relation.ispartof	Journal of Translational Medicine
dc.relation.isbasedon	10.1186/s12967-023-03996-w
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	11 Medical and Health Sciences
dc.subject.classification	Immunology
dc.subject.classification	32 Biomedical and clinical sciences
dc.subject.classification	42 Health sciences
dc.subject.mesh	Humans
dc.subject.mesh	SARS-CoV-2
dc.subject.mesh	COVID-19
dc.subject.mesh	Proteomics
dc.subject.mesh	Mutation
dc.subject.mesh	Mutation Rate
dc.subject.mesh	Humans
dc.subject.mesh	Proteomics
dc.subject.mesh	Mutation
dc.subject.mesh	Mutation Rate
dc.subject.mesh	COVID-19
dc.subject.mesh	SARS-CoV-2
dc.subject.mesh	Humans
dc.subject.mesh	SARS-CoV-2
dc.subject.mesh	COVID-19
dc.subject.mesh	Proteomics
dc.subject.mesh	Mutation
dc.subject.mesh	Mutation Rate
dc.title	Global landscape of SARS-CoV-2 mutations and conserved regions
dc.type	Journal Article
utslib.citation.volume	21
utslib.location.activity	England
utslib.for	11 Medical and Health Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.date.updated	2024-05-04T03:03:42Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	21
utslib.citation.issue	1

Abstract:

BackgroundAt the end of December 2019 a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 SARS CoV 2 disease COVID 19 has been identified in Wuhan a central city in China and then spread to every corner of the globe As of October 8 2022 the total number of COVID 19 cases had reached over 621 million worldwide with more than 6 56 million confirmed deaths Since SARS CoV 2 genome sequences change due to mutation and recombination it is pivotal to surveil emerging variants and monitor changes for improving pandemic management Methods10 287 271 SARS CoV 2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24 2020 to April 2022 Python programming language version 3 8 0 software was utilized to process FASTA files to identify variants and sequence conservation The NCBI RefSeq SARS CoV 2 genome accession no NC 045512 2 was considered as the reference sequence ResultsSix mutations had more than 50 frequency in global SARS CoV 2 These mutations include the P323L 99 3 in NSP12 D614G 97 6 in S the T492I 70 4 in NSP4 R203M 62 8 in N T60A 61 4 in Orf9b and P1228L 50 0 in NSP3 In the SARS CoV 2 genome no mutation was observed in more than 90 of nsp11 nsp7 nsp10 nsp9 nsp8 and nsp16 regions On the other hand N nsp3 S nsp4 nsp12 and M had the maximum rate of mutations In the S protein the highest mutation frequency was observed in aa 508 635 0 77 and aa 381 508 0 43 The highest frequency of mutation was observed in aa 66 88 2 19 aa 7 14 and aa 164 246 2 92 in M E and N proteins respectively ConclusionTherefore monitoring SARS CoV 2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS CoV 2 diagnostic efficiency and design safe and effective vaccines against emerging variants

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/178648