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AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot...

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Detalles Bibliográficos
Autores principales: Xi, Binbin, Chen, Zixi, Li, Shuhua, Liu, Wei, Jiang, Dawei, Bai, Yunmeng, Qu, Yimo, Lon, Jerome Rumdon, Huang, Lizhen, Du, Hongli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416686/
https://www.ncbi.nlm.nih.gov/pubmed/34512928
http://dx.doi.org/10.1016/j.csbj.2021.09.002
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author Xi, Binbin
Chen, Zixi
Li, Shuhua
Liu, Wei
Jiang, Dawei
Bai, Yunmeng
Qu, Yimo
Lon, Jerome Rumdon
Huang, Lizhen
Du, Hongli
author_facet Xi, Binbin
Chen, Zixi
Li, Shuhua
Liu, Wei
Jiang, Dawei
Bai, Yunmeng
Qu, Yimo
Lon, Jerome Rumdon
Huang, Lizhen
Du, Hongli
author_sort Xi, Binbin
collection PubMed
description In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it’s much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future.
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spelling pubmed-84166862021-09-07 AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus Xi, Binbin Chen, Zixi Li, Shuhua Liu, Wei Jiang, Dawei Bai, Yunmeng Qu, Yimo Lon, Jerome Rumdon Huang, Lizhen Du, Hongli Comput Struct Biotechnol J Research Article In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it’s much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future. Research Network of Computational and Structural Biotechnology 2021-09-04 /pmc/articles/PMC8416686/ /pubmed/34512928 http://dx.doi.org/10.1016/j.csbj.2021.09.002 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Xi, Binbin
Chen, Zixi
Li, Shuhua
Liu, Wei
Jiang, Dawei
Bai, Yunmeng
Qu, Yimo
Lon, Jerome Rumdon
Huang, Lizhen
Du, Hongli
AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title_full AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title_fullStr AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title_full_unstemmed AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title_short AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus
title_sort autovem2: a flexible automated tool to analyze candidate key mutations and epidemic trends for virus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416686/
https://www.ncbi.nlm.nih.gov/pubmed/34512928
http://dx.doi.org/10.1016/j.csbj.2021.09.002
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