アイテム詳細

要旨

Microbes form complex interaction networks between a host and microbial species. Recent studies on host response to infection and quantification of microbes have led to advances in infection biology. However, we lack a comprehensive understanding of the distribution of spatial microbial patterns across host tissues and their localized impact on host gene expression.
To fill this gap, we present Spatial metaTranscriptomics (SmT), a sequencing-based approach that leverages 16S-18S/ITS-poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-μm resolution. We showcase the SmT in Arabidopsis thaliana leaves to study the spatial microbial distributions and the associated host response. We validated SmT by comparing the taxonomical profiles of the leaves detected by amplicon sequencing and our multimodal array and found that the SmT outperforms amplicon-sequencing by increasing 11.9 times the number of captured bacterial taxa.
Subsequently, we identified 1,376 unique bacterial taxa and 1,159 unique fungal taxa of in outdoor-grown leaves. We spatially unveiled leaf-scale spatial microbial hotspots and employed network analysis to study inter- and intra-kingdom diversity.We uncovered that the spatial distribution of microbes consistently drives their interactions. Moreover, we studied the host response in the microbial hotspots identifying alterations of genes responsible for hormone mediated defence responses and microbial recognition.
In conclusion, our results demonstrate the feasibility of studying spatially resolved host-pathogen interactions on a tissue section. Importantly, our approach can be extended to different organisms, such as mammalian species, to elucidate complex infection processes where the spatial context is key for understanding infection processes.