Laing Chad R, Whiteside Matthew D, Gannon Victor P J
National Microbiology Laboratory, Public Health Agency of CanadaLethbridge, AB, Canada.
Front Microbiol. 2017 Jul 31;8:1345. doi: 10.3389/fmicb.2017.01345. eCollection 2017.
Food safety is a global concern, with upward of 2.2 million deaths due to enteric disease every year. Current whole-genome sequencing platforms allow routine sequencing of enteric pathogens for surveillance, and during outbreaks; however, a remaining challenge is the identification of genomic markers that are predictive of strain groups that pose the most significant health threats to humans, or that can persist in specific environments. We have previously developed the software program Panseq, which identifies the pan-genome among a group of sequences, and the SuperPhy platform, which utilizes this pan-genome information to identify biomarkers that are predictive of groups of bacterial strains. In this study, we examined the pan-genome of 4893 genomes of , an enteric pathogen responsible for the loss of more disability adjusted life years than any other enteric pathogen. We identified a pan-genome of 25.3 Mbp, a strict core of 1.5 Mbp present in all genomes, and a conserved core of 3.2 Mbp found in at least 96% of these genomes. We also identified 404 genomic regions of 1000 bp that were specific to the species . These species-specific regions were found to encode mostly hypothetical proteins, effectors, and other proteins related to virulence. For each of the six subspecies, markers unique to each were identified. No serovar had pan-genome regions that were present in all of its genomes and absent in all other serovars; however, each serovar did have genomic regions that were universally present among all constituent members, and statistically predictive of the serovar. The phylogeny based on SNPs within the conserved core genome was found to be highly concordant to that produced by a phylogeny using the presence/absence of 1000 bp regions of the entire pan-genome. Future studies could use these predictive regions as components of a vaccine to prevent salmonellosis, as well as in simple and rapid diagnostic tests for both and wet-lab applications, with uses ranging from food safety to public health. Lastly, the tools and methods described in this study could be applied as a pan-genomics framework to other population genomic studies seeking to identify markers for other bacterial species and their sub-groups.
食品安全是一个全球关注的问题，每年因肠道疾病导致超过220万人死亡。当前的全基因组测序平台允许对肠道病原体进行常规测序以用于监测以及在疫情爆发期间进行测序；然而，一个仍然存在的挑战是识别那些能够预测对人类构成最重大健康威胁的菌株组，或者能够在特定环境中持续存在的基因组标记。我们之前开发了软件程序Panseq，它可以识别一组序列中的泛基因组，以及SuperPhy平台，该平台利用这些泛基因组信息来识别能够预测细菌菌株组的生物标志物。在这项研究中，我们研究了4893个肠炎沙门氏菌基因组的泛基因组，肠炎沙门氏菌是一种肠道病原体，其导致的伤残调整生命年损失比任何其他肠道病原体都要多。我们识别出一个25.3兆碱基对的泛基因组，一个在所有基因组中都存在的1.5兆碱基对的严格核心基因组，以及一个在至少96%的这些基因组中都能找到的3.2兆碱基对的保守核心基因组。我们还识别出了404个1000碱基对的基因组区域，这些区域是肠炎沙门氏菌所特有的。这些物种特异性区域被发现主要编码假设蛋白、效应蛋白以及其他与毒力相关的蛋白。对于六个肠炎沙门氏菌亚种中的每一个，都识别出了各自特有的标记。没有任何一个血清型具有在其所有基因组中都存在而在所有其他血清型中都不存在的泛基因组区域；然而，每个血清型确实都有在其所有组成成员中普遍存在且在统计学上能够预测该血清型的基因组区域。基于保守核心基因组内单核苷酸多态性的系统发育树被发现与使用整个泛基因组的1000碱基对区域的存在/缺失构建的系统发育树高度一致。未来的研究可以将这些预测区域用作预防沙门氏菌病疫苗的组成部分，以及用于肠炎沙门氏菌的简单快速诊断测试和湿实验室应用，其用途涵盖从食品安全到公共卫生等领域。最后，本研究中描述的工具和方法可以作为一个泛基因组学框架应用于其他旨在识别其他细菌物种及其亚组标记的群体基因组研究。
