基于全基因组测序数据的分型方法。

One Health Outlook Pub Date : 2020-02-18 eCollection Date: 2020-01-01 DOI:10.1186/s42522-020-0010-1
Laura Uelze, Josephine Grützke, Maria Borowiak, Jens Andre Hammerl, Katharina Juraschek, Carlus Deneke, Simon H Tausch, Burkhard Malorny
{"title":"基于全基因组测序数据的分型方法。","authors":"Laura Uelze, Josephine Grützke, Maria Borowiak, Jens Andre Hammerl, Katharina Juraschek, Carlus Deneke, Simon H Tausch, Burkhard Malorny","doi":"10.1186/s42522-020-0010-1","DOIUrl":null,"url":null,"abstract":"<p><p>Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.</p>","PeriodicalId":19490,"journal":{"name":"One Health Outlook","volume":"2 ","pages":"3"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993478/pdf/","citationCount":"0","resultStr":"{\"title\":\"Typing methods based on whole genome sequencing data.\",\"authors\":\"Laura Uelze, Josephine Grützke, Maria Borowiak, Jens Andre Hammerl, Katharina Juraschek, Carlus Deneke, Simon H Tausch, Burkhard Malorny\",\"doi\":\"10.1186/s42522-020-0010-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.</p>\",\"PeriodicalId\":19490,\"journal\":{\"name\":\"One Health Outlook\",\"volume\":\"2 \",\"pages\":\"3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993478/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"One Health Outlook\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s42522-020-0010-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"One Health Outlook","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s42522-020-0010-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

食源性病原体的全基因组测序(WGS)已成为研究细菌病原体基因组序列信息的有效方法。此外,WGS 的高分辨能力甚至可以在亚种水平上比较细菌之间的遗传亲缘关系。因此,WGS 正在全球范围内跨领域(人类、兽医、食品和环境)应用,用于调查疾病爆发、来源归因和改进风险特征模型。为了从 WGS 产生的大量复杂数据中提取相关信息,开发了大量生物信息学工具,使用户能够分析和解释测序数据,从简单的基因搜索到复杂的系统发育研究。根据研究问题、数据集的复杂程度以及用户的生物信息学技能,用户可以选择多种工具来分析 WGS 数据。在本综述中,我们将介绍用于疫情研究的系统发生组学研究的相关方法,并概述基于 WGS 数据鉴定食源性病原体特征的选定工具。尽管在过去几年中做出了很多努力,但目前仍迫切需要统一和标准化分型工具,以便于实验室之间进行数据比较,从而逐步建立全球统一的食源性病原体健康监测系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Typing methods based on whole genome sequencing data.

Typing methods based on whole genome sequencing data.

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信