Deciphering Cell State Covariation with NiCo (Niche Covariation): Insights from Integrating Spatial-omics Data
To be announce
Abstract
Understanding cellular activities in tissue homeostasis, inflammation, and disease states remains challenging. Cell types, characterized by specific gene expression patterns, play pivotal roles in these processes. However, interactions among cell types and communication among cellular states within the tissue niche are poorly understood. To address this gap, we present NiCo (Niche Covariation), which models the colocalization of cellular states from single-cell resolution spatial transcriptomics data to unravel niche cell type interactions. NiCo further infers spatial covariation of latent factors, capturing cell state variability in tissue niches and interpreting these factors by leveraging transcriptome-wide information from scRNAseq reference data. Applying NiCo to diverse biological contexts, including the developing mouse embryo, small intestine, and liver, we predict novel niche interactions contributing to cell state variation. NiCo predicts a feedback mechanism between Kupffer cells and neighboring stellate cells that limits stellate cell activation in the normal liver. NiCo presents a valuable tool for understanding omics data and opens avenues for further exploration into the intricate language of cellular communication, promising deeper insights into the dynamics of health and disease tissues.