Spatial multi-organism interactions

Spatial organization of gene expression underlies how organisms interact, adapt, maintain homeostasis and health, and cause disease. Recent advances in spatially resolved transcriptomics have enabled unbiased, transcriptome-wide profiling directly in intact tissues, thereby preserving the tissue microenvironment in which biological interactions occur. However, most SRT applications have focused on single organisms, primarily mammalian tissues, leaving multi-organism systems, host–pathogen, multicellular pathogens, and host–microbe interactions less explored. In this thesis, we develop and apply spatial molecular tools to investigate multi-organism interactions across different biological scales. We introduce methodological advances that enable spatial profiling of (i) dual host–pathogen transcriptomes, (ii) multicellular pathogens with their own tissue organization and symbionts, (iii) complex microbial communities in relation to adaptive immune responses, and (iv) custom probe design for probe-based Spatial Transcriptomics in non-model organisms. In Article I, we developed Dual Spatial Transcriptomics (DualST), which enables the simultaneous and unbiased detection of host and pathogen transcriptomes in situ in clinical formalin-fixed paraffin-embedded samples. We applied DualST to human lung tissue infected with SARS-CoV-2 to map viral RNA localization and characterize the surrounding host response within the tissue microenvironment. In Article II, we developed Miniature Spatial Transcriptomics (MiniatureST) to spatially resolve small multicellular pathogens using polyA-based RNA capture in a high-throughput manner. We applied MiniatureST to the parasitic filarial worm Brugia malayi, which causes lymphatic filariasis. This approach resolved the worm’s spatial transcriptomic architecture and enabled detection of its endosymbiotic bacterium Wolbachia, providing insight into the worm–endosymbiont interactions within the context of infection in the human host. In Article III, we introduced Spatial metaTranscriptomics and Spatial VDJ (SmT-SVDJ), a method that combines microbial rRNA phylogenetic marker capture with enrichment of full-length B cell (BCR) and T cell (TCR) antigen receptor sequences, encompassing their V (variable), D (diversity), and J (joining) regions. This approach enables spatial mapping of microbial composition together with B and T cell clones, thereby linking microbiome organization to adaptive immune responses within tissues. We demonstrated SmT-SVDJ on two distinct human clinical samples, tonsil and breast cancer, unveiling microbiome-host-VDJ repertoire spatial profiles unique to each tissue type. In Article IV, we developed Probe Spatial Transcriptomics (ProbeST), an open-source, scalable computational pipeline for designing custom gene-specific probe sets beyond human and mouse compatible with probe-based Visium Spatial Transcriptomics assays. A DualST experiment using ProbeST custom Salmonella pathogen probes together with the commercial mouse probe panel enabled simultaneous detection of host-pathogen transcripts, linking bacterial gene expression to localized host inflammatory responses. ProbeST expands probe-based Spatial Transcriptomics to non-model organisms and supports multi-organism and host–pathogen studies. Together, these studies establish a framework for spatially interrogating host–pathogen, host–symbiont, and host–microbiome interactions. By developing adaptable molecular and computational tools, this work expands the application of spatially resolved transcriptomics to multi-organism systems and provides approaches that can be applied to diverse biological and clinical contexts.