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

A. S. Vodopyanov, S. O. Vodopyanov, R. V. Pisanov, I. P. Oleynikov, A. Noskov
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Abstract

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.
开发霍乱病原体分子遗传监测方法
背景。霍乱的持续流行决定了开发和改进霍乱病原体全基因组测序数据分析方法的重要性。鉴于包括软件在内的外国产品的进口替代所带来的挑战,这一点尤为重要。本研究的目的是利用在线地理信息系统(GIS)开发霍乱病原体分子遗传监测方法,并在其帮助下对俄罗斯早期分离的菌株进行分析。材料和方法本研究使用了作者在 MiSeq(Illumina)平台上获得的 2598 株霍乱弧菌 O1 El Tor 致病菌株(ctxAB+tcpA+)的全基因组测序数据,这些数据是从 NCBI 数据库中检索的。SNP 分析软件是用 Java 和 Python 编程语言开发的。Cytoscape程序用于树枝图的可视化。在线 GIS 的开发使用了 HTML、JavaScript 和 PHP 编程语言。以 JavaScript 编写的免费发布的 Leaflet 库为核心。从 OpenStreetMap 社区获得的地图被用作制图数据。结果与讨论我们开发了一套通用的 SNPs 和软件来分析霍乱弧菌菌株的全基因组测序数据。结果表明,大多数菌株分布在几个大的菌群中。自 2001 年以来在俄罗斯分离到的霍乱弧菌中,关系最密切的菌株已经确定。创建了在线地理信息系统 "霍乱弧菌分子遗传监测",可在电子地图上直接识别近缘菌株。
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