Mucosal and barrier tissues such as the gut, lung or skin, are composed of a complex network of cells and

microbes forming a tight niche that prevents pathogen colonization and supports host-microbiome

symbiosis. Characterizing these networks at high molecular and cellular resolution is crucial for our

understanding of homeostasis and disease. Here, we present spatial host-microbiome sequencing (SHM-

seq), an all-sequencing based approach that captures tissue histology, polyadenylated RNAs and bacterial

16S sequences directly from a tissue by modifying spatially barcoded glass surfaces to enable

simultaneous capture of host transcripts and hypervariable regions of the 16S bacterial rRNA. We apply

our approach to the mouse gut as a model system, use a deep learning approach for data mapping, and

detect spatial niches defined by cellular composition and microbial geography. We show that

subpopulations of gut cells express specific gene programs in different microenvironments characteristic

of regional commensal bacteria and impact host-bacteria interactions. SHM-seq should enhance the study

of native host-microbe interactions in health and disease.

Code availability: https://github.com/nygctech/shmseq

For questions, please email: svickovic@nygenome.org