Development of a methodology for molecular genetic monitoring for the cholera causative agent

Autor: Alexey S. Vodopyanov, Sergey O. Vodopyanov, Ruslan V. Pisanov, Igor P. Oleynikov, Aleksey K. Noskov
Jazyk: ruština
Rok vydání: 2024
Předmět:
Zdroj: Журнал микробиологии, эпидемиологии и иммунобиологии, Vol 100, Iss 6, Pp 462-471 (2024)
Druh dokumentu: article
ISSN: 0372-9311
2686-7613
DOI: 10.36233/0372-9311-388
Popis: Background. The ongoing cholera pandemic determines the relevance of the development and improvement of methods for analysis of data on genome-wide sequencing of the cholera pathogen. This is of particular importance in the light of the challenges of import substitution of foreign products, including software. The aim of the study was to develop a methodology for molecular genetic monitoring for the cholera causative agent using online geographic information system (GIS) and analysis with its help of strains isolated in Russia earlier. Materials and methods. Data from genome-wide sequencing of 2598 toxigenic (ctxAB+tcpA+) strains of V. cholerae O1 El Tor, both obtained by the authors on the MiSeq (Illumina) platform, and retrieved from the NCBI database were used in the study. The SNP analysis software was developed in the Java and Python programming languages. Cytoscape program was used to visualize the dendrogram. The development of online GIS was carried out using the programming languages HTML, JavaScript and PHP. The freely distributed Leaflet library written in JavaScript was used as the core. Maps obtained from the OpenStreetMap community were used as cartographic data. Results and discussion. A universal set of SNPs and software have been developed to analyze the data of genome-wide sequencing of cholera vibrio strains. It was shown that the majority of strains were distributed among several large clusters. The most closely related strains for cholera vibrions isolated in Russia since 2001 have been identified. An online GIS "Molecular genetic monitoring for V. cholerae" has been created, which allows the recognition of closely related strains directly on an electronic map.
Databáze: Directory of Open Access Journals
Externí odkaz: