PROJECT SUMMARY/ABSTRACT Microbial cell populations can be highly heterogeneous, which is crucial for strain survival in complex conditions such as antibiotic treatment. Apparently, the cell-to-cell heterogeneity cannot be revealed using traditional bulk sequencing techniques. Single-cell based approaches for microbial cells are emerging to tackle this question, however, the spatial context information, crucial for understanding the microbe-host interactions, is not collected. As of current, we still lack high resolution spatial omics tools to study microbes and their residing mammalian host. Most currently available NGS based spatial transcriptome platforms are not compatible with bacteria profiling due to three reasons: 1) Bacteria cell walls are highly diverse in thickness and composition, which prevents the reagents such as reverse transcriptase and primers to enter the cell, especially for Gram Positive ones with thick cell walls; 2) mRNAs of bacteria cells are sparse and have short half-life; 3) bacteria mRNA lacks poly-A tail in RNA sequence. During the past 5 years, I developed DBiT-seq (Deterministic barcoding in tissue), the first high resolution spatial proteo-transcriptome platform, which have been widely applied to neuroscience, development, and cancer studies in human. I further reported the Spatial-CITE-seq technique which can co-mapping ~300 surface proteins and the whole transcriptome of various tissue types. I propose in the next five years the development of a new spatial sequencing technology called microDBiT, which will be the first spatial proteo-transcriptome platform that can map microbes and the host cells within the spatial context. At the initial stage, we will design and use the slides of cultured Gram positive bacteria S.aureus and negative bacteria E. coli as a model to optimize the key steps of microDBiT protocol, including cell wall digestion, mRNA polyadenylation, reverse transcription and in cell ligation. We will next develop the microDBiT protocol for microbe and host cell co-mapping using gut tissues obtained from bacteria colonized germ-free C57BL/6 mice. Lastly, we will apply the microDBiT to map out the gene expression profile of pathogens and the patient cells in inflammatory bowel disease (IBD). Since metabolites of microbes are considered important pathways that influence the host cell behavior, we will meanwhile include an antibody panel of host receptors and study how the metabolites will influence the gene expression of host cells. This technique will ultimately enable high-throughput and high-resolution characterization of spatial heterogeneity of microbes and their interaction with the host cells. In the long run, we will build microDBiT into a comprehensive platform that could be applied to diverse microbe and host systems at different omics levels (Genomics, Transcriptomics, Epigenomics, etc.).