Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA).
Mol Syst Biol
; 20(2): 98-119, 2024 Feb.
Article
en En
| MEDLINE
| ID: mdl-38225383
ABSTRACT
Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or on the transcript expression levels, but rather on their spatial association in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a Visium dataset of human ulcerative colitis patients, and validated our findings at single-cell resolution on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Colitis Ulcerosa
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Mol Syst Biol
/
Molecular systems biology
Asunto de la revista:
BIOLOGIA MOLECULAR
/
BIOTECNOLOGIA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Suiza