We developed an analysis pipeline that can extract microbial sequences from spatial transcriptomic (ST) data and assign taxonomic labels, generating a spatial microbial abundance matrix in addition to the default host expression matrix, enabling simultaneous analysis of host expression and microbial distribution. We called the pipeline spatial metatranscriptome (SMT) and applied it on both human and murine intestinal sections and validated the spatial microbial abundance information with alternative assays. Biological insights were gained from these novel data that showed host–microbe interaction at various spatial scales. Finally, we tested experimental modification that can increase microbial capture while preserving host spatial expression quality and, by use of positive controls, quantitatively showed the capture efficiency and recall of our methods. This proof-of-concept work shows the feasibility of SMT analysis and paves the way for further experimental optimization and application.

中文翻译：

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通过空间宏转录组测序同时分析宿主表达和微生物丰度

我们开发了一个分析管道，可以从空间转录组（ST）数据中提取微生物序列并分配分类标签，除了默认宿主表达矩阵之外还生成空间微生物丰度矩阵，从而能够同时分析宿主表达和微生物分布。我们将该管道称为空间宏转录组（SMT），并将其应用于人类和小鼠肠道切片，并通过替代测定验证空间微生物丰度信息。从这些显示宿主与微生物在不同空间尺度上相互作用的新数据中获得了生物学见解。最后，我们测试了实验修改，可以增加微生物捕获，同时保留宿主空间表达质量，并通过使用阳性对照，定量显示我们方法的捕获效率和召回率。这项概念验证工作展示了 SMT 分析的可行性，并为进一步的实验优化和应用铺平了道路。