权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Using genome data from highly recombinant bacteria of the genus Neisseria to examine bacterial population structure, antibiotic resistance, and geneti

使用奈瑟氏球菌属高度重组细菌的基因组数据来检查细菌种群结构、抗生素耐药性和遗传学

基本信息

批准号：
2270225
负责人：
金额：
--
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2270225
关键词：
Using genome data highly recombinant

项目摘要

The availability of bacterial whole genome sequence (WGS) data, the complete DNA blueprint of a bacterium, has improved our understanding of these organisms and facilitated population-level approaches to delineate related strains and investigate antibiotic resistance. As DNA sequencing has become cheaper and easier, the volume of WGS data has increased exponentially. However, resources for examining these large genetic datasets are typically lacking or under-utilised. Analysis is further complicated by the diversity in genome complexity found across different bacterial species, often generated by high levels of genetic exchange through horizontal gene transfer (HGT) between individuals. This process also facilitates the rapid spread of genes that confer antibiotic resistance, while simultaneously making current approaches for tracking related groups of these organisms less effective, hindering their surveillance. Members of the Neisseria genus, particularly Neisseria gonorrhoeae, have highly complex genomes resulting from extensive genetic exchange. The proposed research will exploit Neisseria WGS from over 30,000 isolates to develop new computational approaches that enable the full utilisation of large genetic datasets including genomes affected by frequent HGT. This will include tools to analyse bacterial population structure and predict antibiotic resistance phenotypes, alongside an examination of the impact of HGT through 'mosaic' genes implicated in antibiotic resistance and an investigation into gene networks.

细菌全基因组序列（WGS）数据（细菌的完整DNA蓝图）的可用性提高了我们对这些生物的理解，并促进了群体水平的方法来描述相关菌株和研究抗生素耐药性。随着DNA测序变得越来越便宜和容易，WGS数据量呈指数级增长。然而，用于检查这些大型遗传数据集的资源通常缺乏或利用不足。分析进一步复杂化的基因组复杂性的多样性，发现在不同的细菌物种，通常产生的高水平的遗传交换，通过水平基因转移（HGT）之间的个人。这一过程也促进了赋予抗生素耐药性的基因的快速传播，同时使目前追踪这些生物体相关群体的方法效率降低，阻碍了对它们的监测。奈瑟氏菌属的成员，特别是淋病奈瑟氏菌，由于广泛的遗传交换而具有高度复杂的基因组。该研究将利用来自30，000多个分离株的奈瑟菌WGS来开发新的计算方法，从而能够充分利用大型遗传数据集，包括受频繁HGT影响的基因组。这将包括分析细菌种群结构和预测抗生素耐药性表型的工具，以及通过与抗生素耐药性有关的“马赛克”基因检查HGT的影响和对基因网络的调查。