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

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调查抗生素耐药性。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未得到充分利用。在不同细菌物种之间发现的基因组复杂性的多样性使分析进一步复杂化，这通常是由个体之间通过水平基因转移（HGT）进行的高水平遗传交换产生的。这一过程还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不那么有效，阻碍了对它们的监测。奈瑟菌属的成员，特别是淋病奈瑟菌，由于广泛的遗传交换而具有高度复杂的基因组。拟议的研究将利用来自3万多个分离株的WGS奈瑟菌开发新的计算方法，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。

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.