Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20910, USA.
Sci Adv. 2024 Jul 5;10(27):eadj7402. doi: 10.1126/sciadv.adj7402. Epub 2024 Jul 3.
The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like Β and , while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.
肿瘤微生物组的研究受到了越来越多的关注。我们开发了一种计算管道（CSI-Microbes），用于从单细胞 RNA 测序（scRNA-seq）数据中识别微生物读数，并分析分类群的差异丰度。通过一系列对照实验和分析，我们对通过多种 scRNA-seq 技术恢复微生物独特分子标识符的功效进行了首次系统评估，结果表明较新的 10x 化学方法（3'v3 和 5'）是最合适的方法。我们分析了患者的食管和结直肠癌，并发现来自不同属的读数往往在同一宿主细胞中共存，证明了可能存在细胞内多微生物相互作用。微生物读数在髓样细胞中不成比例地丰富，这些细胞会上调促炎细胞因子，如 Β 和 ，而感染的肿瘤细胞则会上调抗原加工和呈递途径。这些结果表明，吞噬细菌的髓样细胞是肿瘤微环境（TME）中细菌 RNA 的主要来源，可能会引发 TME 并影响免疫疗法反应。
