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Identifying New Clusterons: Application of TBEV Analyzer 3.0

Early knowledge about novel emerging viruses and rapid determination of their characteristics are crucial for public health. In this context, development of theoretical approaches to model viral evolution are important. The clusteron approach is a recent bioinformatics tool which analyzes genetic pa...

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Autores principales: Forghani, Majid, Kovalev, Sergey, Khachay, Michael, Ramsay, Edward, Bolkov, Mikhail, Vasev, Pavel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966418/
https://www.ncbi.nlm.nih.gov/pubmed/36838289
http://dx.doi.org/10.3390/microorganisms11020324
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author Forghani, Majid
Kovalev, Sergey
Khachay, Michael
Ramsay, Edward
Bolkov, Mikhail
Vasev, Pavel
author_facet Forghani, Majid
Kovalev, Sergey
Khachay, Michael
Ramsay, Edward
Bolkov, Mikhail
Vasev, Pavel
author_sort Forghani, Majid
collection PubMed
description Early knowledge about novel emerging viruses and rapid determination of their characteristics are crucial for public health. In this context, development of theoretical approaches to model viral evolution are important. The clusteron approach is a recent bioinformatics tool which analyzes genetic patterns of a specific E protein fragment and provides a hierarchical network structure of the viral population at three levels: subtype, lineage, and clusteron. A clusteron is a group of strains with identical amino acid (E protein fragment) signatures; members are phylogenetically closely related and feature a particular territorial distribution. This paper announces TBEV Analyzer 3.0, an analytical platform for rapidly characterizing tick-borne encephalitis virus (TBEV) strains based on the clusteron approach, workflow optimizations, and simplified parameter settings. Compared with earlier versions of TBEV Analyzer, we provide theoretical and practical enhancements to the platform. Regarding the theoretical aspect, the model of the clusteron structure, which is the core of platform analysis, has been updated by analyzing all suitable TBEV strains available in GenBank, while the practical enhancements aim at improving the platform’s functionality. Here, in addition to expanding the strain sets of prior clusterons, we introduce eleven novel clusterons through our experimental results, predominantly of the European subtype. The obtained results suggest effective application of the proposed platform as an analytical and exploratory tool in TBEV surveillance.
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spelling pubmed-99664182023-02-26 Identifying New Clusterons: Application of TBEV Analyzer 3.0 Forghani, Majid Kovalev, Sergey Khachay, Michael Ramsay, Edward Bolkov, Mikhail Vasev, Pavel Microorganisms Article Early knowledge about novel emerging viruses and rapid determination of their characteristics are crucial for public health. In this context, development of theoretical approaches to model viral evolution are important. The clusteron approach is a recent bioinformatics tool which analyzes genetic patterns of a specific E protein fragment and provides a hierarchical network structure of the viral population at three levels: subtype, lineage, and clusteron. A clusteron is a group of strains with identical amino acid (E protein fragment) signatures; members are phylogenetically closely related and feature a particular territorial distribution. This paper announces TBEV Analyzer 3.0, an analytical platform for rapidly characterizing tick-borne encephalitis virus (TBEV) strains based on the clusteron approach, workflow optimizations, and simplified parameter settings. Compared with earlier versions of TBEV Analyzer, we provide theoretical and practical enhancements to the platform. Regarding the theoretical aspect, the model of the clusteron structure, which is the core of platform analysis, has been updated by analyzing all suitable TBEV strains available in GenBank, while the practical enhancements aim at improving the platform’s functionality. Here, in addition to expanding the strain sets of prior clusterons, we introduce eleven novel clusterons through our experimental results, predominantly of the European subtype. The obtained results suggest effective application of the proposed platform as an analytical and exploratory tool in TBEV surveillance. MDPI 2023-01-27 /pmc/articles/PMC9966418/ /pubmed/36838289 http://dx.doi.org/10.3390/microorganisms11020324 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Forghani, Majid
Kovalev, Sergey
Khachay, Michael
Ramsay, Edward
Bolkov, Mikhail
Vasev, Pavel
Identifying New Clusterons: Application of TBEV Analyzer 3.0
title Identifying New Clusterons: Application of TBEV Analyzer 3.0
title_full Identifying New Clusterons: Application of TBEV Analyzer 3.0
title_fullStr Identifying New Clusterons: Application of TBEV Analyzer 3.0
title_full_unstemmed Identifying New Clusterons: Application of TBEV Analyzer 3.0
title_short Identifying New Clusterons: Application of TBEV Analyzer 3.0
title_sort identifying new clusterons: application of tbev analyzer 3.0
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966418/
https://www.ncbi.nlm.nih.gov/pubmed/36838289
http://dx.doi.org/10.3390/microorganisms11020324
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