Centre for Immunology and Infection Control, School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia.
Microb Genom. 2023 Jun;9(6). doi: 10.1099/mgen.0.001042.
The outer core locus (OCL) that includes genes for the synthesis of the variable outer core region of the lipooligosaccharide (LOS) is one of the key epidemiological markers used for tracing the spread of , a bacterial pathogen of global concern. In this study, we screened 12 476 publicly available genome assemblies for novel OCL sequences, detecting six new OCL types that were designated OCL17-OCL22. These were compiled with previously characterized OCL sequences to create an updated version of the OCL reference database, providing a total of 22 OCL reference sequences for use with the bioinformatics tool . Use of this database against the 12 476 downloaded assemblies found OCL1 to be the most common locus, present in 73.6 % of sequenced genomes assigned by with a match confidence score of good or above. OCL1 was most common amongst isolates belonging to sequence types (STs) ST1, ST2, ST3 and ST78, all of which are over-represented clonal lineages. The highest level of diversity in OCL types was found in ST2, with eight different OCLs identified. The updated OCL reference database is available for download from GitHub (https://github.com/klebgenomics/Kaptive; under version ), and has been integrated for use on Web (https://kaptive-web.erc.monash.edu/) and PathogenWatch (https://pathogen.watch/), enhancing current methods for strain identification, classification and surveillance.
外核基因座（OCL）是一种关键的流行病学标记，用于追踪全球关注的细菌病原体 的传播。该基因座包含脂寡糖（LOS）可变外核区域合成的基因。在本研究中，我们筛选了 12476 个公开可用的 基因组序列，以检测新的 OCL 序列，共发现了 6 种新的 OCL 类型，分别命名为 OCL17-OCL22。这些新的 OCL 类型与之前已鉴定的 OCL 序列一起，用于创建更新的 OCL 参考数据库，共包含 22 个 OCL 参考序列，可用于生物信息学工具 。使用该数据库对 12476 个下载的基因组进行分析，发现 OCL1 是最常见的基因座，73.6%的测序基因组被 分配到 OCL1 型，匹配置信度评分为良好或以上。OCL1 在属于序列型（ST）ST1、ST2、ST3 和 ST78 的分离株中最为常见，这些 ST 型都是过度代表的克隆谱系。在 OCL 型中发现了最高水平的多样性，在 ST2 中鉴定出了 8 种不同的 OCL 型。更新的 OCL 参考数据库可从 GitHub 下载（https://github.com/klebgenomics/Kaptive；版本 ），并已整合到 Web（https://kaptive-web.erc.monash.edu/）和 PathogenWatch（https://pathogen.watch/）中，增强了当前用于 菌株鉴定、分类和监测的方法。
