Integrated intra‐ and intercellular signaling knowledge for multicellular omics analysis

TLDR

Molecular knowledge of biological processes underpins omics analysis, yet intercellular communication data remain sparse and fragmented. The study aims to integrate over 100 resources to create a unified knowledge base linking inter‑ and intracellular signaling, transcriptional and post‑transcriptional regulation. The authors compiled protein complexes, functional annotations, and disease roles into a resource for human, mouse, and rat, accessible through OmniPath’s web service, Cytoscape plug‑in, and R/Python packages, and provided tutorials for analyzing cell‑cell interactions and downstream signaling. OmniPath enables integrated analysis of intra‑ and intercellular processes, demonstrated in studies of SARS‑CoV‑2 infection and ulcerative colitis.

Abstract

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.