FlyPhoneDB2: A computational framework for analyzing cell-cell communication in Drosophila scRNA-seq data integrating...

Area of Science:

• Computational Biology
• Genomics
• Molecular Signaling

Background:

• Cell-cell communication (CCC) is vital for organismal physiology and implicated in diseases.
• Previous tool FlyPhoneDB enabled CCC exploration in Drosophila single-cell RNA-sequencing data but had a limited ligand-receptor pair database.

Purpose of the Study:

• To introduce FlyPhoneDB2, an upgraded tool for analyzing CCC in Drosophila.
• To expand the ligand-receptor knowledgebase and enhance algorithmic performance and functionalities.

Main Methods:

• Expanded ligand-receptor database incorporating mammalian annotations and AlphaFold-Multimer predictions.
• Optimized algorithm for performance and noise filtering.
• Integrated new features: downstream reporter genes, multi-sample comparison, and network-level visualizations.

Main Results:

• FlyPhoneDB2 successfully analyzed Drosophila tumor models, confirming known biological insights.
• Identified novel potential ligand-receptor pairs involved in tumor-induced cachexia.
• Demonstrated enhanced capabilities for CCC analysis and pathway activity evaluation.

Conclusions:

• FlyPhoneDB2 offers a significantly improved platform for dissecting cell-cell communication in Drosophila.
• The expanded database and new features facilitate deeper understanding of signaling in physiological and pathological contexts.
• The tool aids in identifying novel molecular players in disease, such as cachexia in tumor models.