Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes

使用 CSI-Microbes 从多个单细胞 RNA 测序平台中鉴定细胞内细菌

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作者:Welles Robinson, Joshua K Stone, Fiorella Schischlik, Billel Gasmi, Michael C Kelly, Charlie Seibert, Kimia Dadkhah, E Michael Gertz, Joo Sang Lee, Kaiyuan Zhu, Lichun Ma, Xin Wei Wang, S Cenk Sahinalp, Rob Patro, Mark D M Leiserson, Curtis C Harris, Alejandro A Schäffer, Eytan Ruppin

Abstract

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 IL1Β and CXCL8, 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.

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