Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemination of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here.

中文翻译：

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可视化全球肺炎球菌序列簇 (GPSC) 和国家人口快照中的变异，以了解肺炎球菌菌株的背景。


了解肺炎球菌谱系、地理分布和抗生素耐药性模式，可以深入了解全球肺炎球菌疾病。我们提供交互式生物信息输出来探索这些主题，旨在增加基因组见解向更广泛社区的传播，而无需专业培训。我们准备了 12 个国家/地区特定的系统发育快照，以及先前使用 PopPUNK 定义的 73 个常见全球肺炎球菌序列簇 (GPSC) 的国际系统发育快照，并将它们呈现在 Microreact 中。使用 Roary 定义的基因存在和缺失，以及源自 Gubbins 的重组图谱在 Phandango 中针对每个 GPSC 呈现。使用 BactDating 评估每个 GPSC 的时间系统发育信号。我们提供了如何使用此类资源的示例。在我们使用特定国家系统发育快照的示例中，我们确定在南非 9 个不相关的遗传背景中观察到血清型 14。 GPSC9 的国际系统发育快照中观察到了来自南非的大多数血清型 14 分离株，强调存在以南非血清型 14 分离株为代表的三个独立亚群。我们根据 GPSC9 日期的树估计，每个子簇都是在 20 世纪 80 年代在南非建立的。我们展示了重组图如何识别 GPSC97 内跨越荚膜多糖基因座的 20 kb 重组。这与估计在 20 世纪 90 年代从 GPSC97 日期树中发生的从血清型 6A 到 19A 的转变一致。 GPSC23 系统发育中抗性基因（ tet 、 erm 、 cat ）存在/不存在的图与复合转座子的获得一致。我们根据 GPSC23 日期树估计收购发生在 1953 年至 1975 年间。最后，我们通过 Pathogenwatch 演示了将 GPSC31 分配给来自犹他州的 17 个外部生成的肺炎球菌血清型 1 组件。大多数犹他州分离株聚集在 GPSC31 内，属于美国特有的分支，其最近的共同祖先估计在 1958 年至 1981 年间。我们提供的资源可用于探索数据、检验假设并生成新假设。 GPSC 的可访问分配允许其他人将自己的集合置于此处提供的数据之外的背景中。