CytoSignal Detects Locations and Dynamics of Ligand-Receptor Signaling at Cellular Resolution From Spatial Transcriptomic Data

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Authors: Jialin Liu, Hiroaki Manabe, Weizhou Qian, Shion Orikasa, Javid Ghaemmaghami, Yichen Wang, Yichen Gu, Angel Ka Yan Chu, Gaurav Gadhvi, Yuxuan Song, Patrick McClinden, Vibha N. Lama
+2 more Noriaki Ono, Joshua D. Welch
Cited by: 2

Abstract

Cells communicate through ligand-receptor (LR) signaling interactions, but identifying when and where these interactions are active remains challenging. We developed CytoSignal to infer the locations and dynamics of cell-cell communication at cellular resolution from spatial transcriptomic data. Here we show that our cellular resolution, spatially resolved signaling scores enable several important analyses-identifying spatial gradients in signaling strength, quantifying the locations of contact-dependent and diffusible interactions, detecting signaling-associated genes and identifying differential signaling across multisample data. Additionally, we can predict the temporal dynamics of a signaling interaction at each spatial location. We experimentally validate our results in situ by proximity ligation assay, confirming that CytoSignal predicts the locations of LR interactions more accurately than previous approaches. This study addresses the field's current need for a robust and scalable tool to detect cell-cell signaling interactions and their dynamics at cellular resolution from spatial transcriptomic data.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Cell Image Analysis Techniques Bioinformatics and Genomic Networks

Publication details

Journal / source
Digital Commons-TMC (Texas Medical Center)
Publication date
1 June 2026
Language
EN