Department of Genetics, Yale School of Medicine, New Haven, Connecticut, USA.
Infection and Immunity, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Microb Genom. 2021 Jan;7(1). doi: 10.1099/mgen.0.000494.
Serotyping of is a critical tool in the surveillance of the pathogen and in the development and evaluation of vaccines. Whole-genome DNA sequencing and analysis is becoming increasingly common and is an effective method for pneumococcal serotype identification of pure isolates. However, because of the complexities of the pneumococcal capsular loci, current analysis software requires samples to be pure (or nearly pure) and only contain a single pneumococcal serotype. We introduce a new software tool called SeroCall, which can identify and quantitate the serotypes present in samples, even when several serotypes are present. The sample preparation, library preparation and sequencing follow standard laboratory protocols. The software runs as fast as or faster than existing identification tools on typical computing servers and is freely available under an open source licence at https://github.com/knightjimr/serocall. Using samples with known concentrations of different serotypes as well as blinded samples, we were able to accurately quantify the abundance of different serotypes of pneumococcus in mixed cultures, with 100 % accuracy for detecting the major serotype and up to 86 % accuracy for detecting minor serotypes. We were also able to track changes in serotype frequency over time in an experimental setting. This approach could be applied in both epidemiological field studies of pneumococcal colonization and experimental laboratory studies, and could provide a cheaper and more efficient method for serotyping than alternative approaches.
对 进行血清型分型是监测病原体以及开发和评估疫苗的重要工具。全基因组 DNA 测序和分析越来越普遍，是鉴定纯分离株肺炎球菌血清型的有效方法。然而，由于肺炎球菌荚膜基因座的复杂性，当前的分析软件要求样本是纯（或几乎纯）的，并且只含有单一的肺炎球菌血清型。我们引入了一种名为 SeroCall 的新软件工具，即使存在多种血清型，它也可以识别和定量样品中的血清型。样品制备、文库制备和测序遵循标准实验室方案。该软件在典型的计算服务器上的运行速度与现有鉴定工具一样快，甚至更快，并且可以在 https://github.com/knightjimr/serocall 上以开源许可证免费获得。使用具有不同血清型已知浓度的样品以及盲样，我们能够准确地定量混合培养物中不同血清型肺炎球菌的丰度，主要血清型的检测准确率为 100%，次要血清型的检测准确率高达 86%。我们还能够在实验环境中跟踪血清型频率随时间的变化。这种方法可以应用于肺炎球菌定植的流行病学现场研究和实验性实验室研究，并为血清分型提供一种比替代方法更便宜、更有效的方法。
