CCCdb: a comprehensive manually curated database for cell-cell communication in human and mouse.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Cell-cell communication (CCC) is crucial for multicellular organism organization, function, and plasticity.
• Advancing experimental technologies necessitate curated, experimentally validated CCC data across diverse biological contexts.
• Understanding complex multicellular systems and disease microenvironments requires systematic data on CCC.

Purpose of the Study:

• To present CCCdb, a comprehensive, manually curated database of experimentally validated CCCs for human and mouse.
• To provide standardized annotations for cell types, tissues, and phenotypes involved in CCC.
• To enhance accessibility and biological interpretability of CCC data through an AI assistant.

Main Methods:

• Manual curation of thousands of publications to extract CCC information.
• Systematic annotation of 8467 CCC entries with standardized data on cell types, tissues, and phenotypes.
• Integration of a ReAct-based AI assistant for natural-language querying and navigation.

Main Results:

• CCCdb contains 8467 experimentally validated CCC entries for human and mouse.
• The database covers 98 tissues, 1132 cell types, and 548 phenotypes.
• CCCs are mediated through direct contact, autocrine, paracrine, and endocrine signaling.

Conclusions:

• CCCdb serves as a foundational resource for studying CCC.
• The database facilitates elucidation of mechanisms underlying tissue homeostasis and disease progression.
• The integrated AI assistant enhances user interaction and data interpretation.