Poster #49: Jason LaPierre

Klee-HD: A Spatial Framework for Decoding Host-Microbe Interactions and Characterizing Microbe-Associated Niches

Jason LaPierre, BS (1); Mallory Cunningham, BS (2); Chris Oldfield, PhD (2); Megan Williams, PhD (2); Myrna Serrano, PhD (2,3); Gregory Buck, PhD (2,3,4); Katarzyna M. Tyc, PhD (5,6). (1) School of Life Sciences and Sustainability, Virginia Commonwealth University (2) Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University (3) Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University (4) VCU Genomics Core, Virginia Commonwealth University (5) Department of Biostatistics, School of Public Health, Virginia Commonwealth University (6) Massey Bioinformatics Shared Resource, Virginia Commonwealth University

Recent advances in spatial transcriptomics enable high-resolution characterization of cellular states and tissue organization but limit the ability to systematically investigate localized host–microbe interactions. We developed an experimental and computational framework that integrates microbial detection with Visium HD spatial transcriptomics to identify and characterize microbe-associated inflammatory niches in intact tissues. Visium HD provides transcriptomic profiling at 2 × 2 µM spatial resolution using a probe-based RNA-templated ligation (RTL) chemistry that can be extended with custom probes. We designed microbial RTL probes targeting 16S rRNA V1–V3 and chaperonin 60 (cpn60) regions informed by microbial species profiling. When integrated into the standard spatial capture workflow, we have shown these probes can successfully localize and quantify bacterial targets alongside host transcriptomes in murine and human tissues. To systematically interrogate these spatial host–microbe relationships, we are developing Klee-HD, a disease-agnostic computational framework for microbial hotspot detection, host–microbe colocalization analysis, cellular recruitment quantification, spatial niche characterization, and comparison of localized host responses. Klee-HD identifies regions of high microbial burden and constructs microbial-negative reference regions matched for size and host-cell composition. This design enables the comparison of host transcriptional states associated with localized microbial exposure while minimizing underlying differences in tissue architecture to provide two distinct but comparable groups. Subsequently, pseudobulk differential expression and pathway analyses identify host programs associated with microbial presence. Klee-HD further integrates spatial neighborhood analysis to characterize changes in cellular organization and/or immune recruitment surrounding microbial hotspots, providing a systematic framework for defining microbe-associated niches. Together, integration of custom microbial detection with high-resolution spatial transcriptomics and scalable computational analysis transforms spatial microbial localization into a quantitative approach for determining how localized microbial exposure shapes host transcriptional states and cellular organization. Klee-HD is being implemented as an open-source R and Nextflow framework to facilitate reproducible application across tissues and disease contexts.