Spatial transcriptomics revealing host-microbe interactions

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 Meta-transcriptome (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 this novel data that that demonstrated 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 demonstrated the capture efficiency and recall of our methods. This proof of concept work demonstrates the feasibility of Spatial Meta-transcriptomic analysis, and paves the way for further experimental optimization and application. Six-week-old male C57BL/6 mice were ordered from Shanghai SLAC Laboratory Animal Co.,Ltd. All mice were maintained under 12hr:12hr light-dark（LD）cycles and fed ad libitum in the Specific Pathogen Free(SPF) mouse facilities at Fudan University. All experimental procedures described in the study were approved by the Institutional Animal Care and Use Committees(IACUC) of Fudan University. 10-12 days later, feces and serum were collected and stored at −80℃.Intestine and colon tissue were washed in cold PBS and embedded in optimal cutting temperature(O.C.T) sectioning media(Thermo Scientific) by submersion in isopentane(2-methylbutane,Sigma Aldrich) pre-cooled to −80℃ in dry ice for ST.