Extracellular vesicle-derived miRNA-mediated cell-cell communication inference for single-cell transcriptomic data...

Area of Science:

• Molecular Biology
• Genomics
• Cell Biology

Background:

• MicroRNAs (miRNAs) are crucial regulators of gene expression.
• Extracellular vesicles (EVs) facilitate cell-cell communication (CCC) by transporting miRNAs.
• Single-cell RNA sequencing (scRNA-seq) enables CCC analysis at high resolution.

Purpose of the Study:

• To introduce miRTalk, a novel computational approach for inferring CCC mediated by EV-derived miRNA-target interactions (MiTIs).
• To evaluate miRTalk's performance using simulated and real-world datasets.
• To explore MiTI-mediated CCC mechanisms in various disease contexts.

Main Methods:

• Development of the miRTalk algorithm for inferring miRNA-target interactions within EVs.
• Benchmarking miRTalk against existing methods using simulated and experimental scRNA-seq data.
• Application of miRTalk to analyze intercellular communication in four distinct disease scenarios.

Main Results:

• miRTalk demonstrates superior performance in inferring EV-derived MiTIs compared to other methods.
• The tool successfully identified key MiTI-mediated CCC mechanisms in disease contexts.
• Analysis revealed intricate intercellular dynamics driven by EV-encapsulated miRNAs.

Conclusions:

• miRTalk provides a robust method for inferring EV-derived MiTI-mediated CCC from scRNA-seq data.
• The approach offers valuable insights into the role of miRNAs in intercellular communication and disease.
• miRTalk advances the understanding of biological processes at the single-cell level.