MetaLigand provides a prior-knowledge-guided framework for predicting non-peptide ligand mediated cell-cell communication

Non-peptide ligands (NPLs), including lipids, amino acids, carbohydrates, and non-peptide neurotransmitters and hormones, play a critical role in ligand-receptor-mediated cell-cell communication, driving diverse physiological and pathological processes. To facilitate the study of NPL-dependent intercellular interactions, we introduce MetaLigand, a tool designed to infer NPL availability and NPL-receptor interactions using transcriptomic data. MetaLigand compiles data for 233 NPLs, including their biosynthetic enzymes, transporter genes, and receptor genes, through a combination of automated pipelines and manual curation from comprehensive databases. The tool integrates both de novo and salvage synthesis pathways, incorporating multiple biosynthetic steps and transport mechanisms. Comparisons with existing tools demonstrate MetaLigand's ability to account for complex biogenesis pathways and model NPL availability across diverse tissues and cell types. Furthermore, analysis of single-nucleus RNA sequencing (RNA-seq) datasets from age-related macular degeneration samples revealed that distinct retinal cell types exhibit unique NPL profiles and participate in specific NPL-mediated pathological cell-cell interactions.

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Publication Details

Journal
Cell Reports Methods
Published
2025-10-31
DOI
https://doi.org/10.1016/j.crmeth.2025.101217
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

MetaLigand provides a prior-knowledge-guided framework for predicting non-peptide ligand mediated cell-cell communication

Jin Yang, Ying Xin, Seth Blackshaw, Jiang Qian et al.
Cell Reports Methods
Single-cell and spatial transcriptomics
article

MetaLigand provides a prior-knowledge-guided framework for predicting non-peptide ligand mediated cell-cell communication

Jin Yang, Ying Xin, Seth Blackshaw, Jiang Qian, Cheng Qian
article en

Abstract

Non-peptide ligands (NPLs), including lipids, amino acids, carbohydrates, and non-peptide neurotransmitters and hormones, play a critical role in ligand-receptor-mediated cell-cell communication, driving diverse physiological and pathological processes. To facilitate the study of NPL-dependent intercellular interactions, we introduce MetaLigand, a tool designed to infer NPL availability and NPL-receptor interactions using transcriptomic data. MetaLigand compiles data for 233 NPLs, including their biosynthetic enzymes, transporter genes, and receptor genes, through a combination of automated pipelines and manual curation from comprehensive databases. The tool integrates both de novo and salvage synthesis pathways, incorporating multiple biosynthetic steps and transport mechanisms. Comparisons with existing tools demonstrate MetaLigand's ability to account for complex biogenesis pathways and model NPL availability across diverse tissues and cell types. Furthermore, analysis of single-nucleus RNA sequencing (RNA-seq) datasets from age-related macular degeneration samples revealed that distinct retinal cell types exhibit unique NPL profiles and participate in specific NPL-mediated pathological cell-cell interactions.

Cell Reports MethodsVol. 5(11)
Johns Hopkins University (US), Johns Hopkins Medicine (US)
Openalex Percentile: Top 72%
Single-cell and spatial transcriptomics
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MetaLigand provides a prior-knowledge-guided framework for predicting non-peptide ligand mediated cell-cell communication — Jin Yang, Ying Xin, et al. · Cell Reports Methods (2025) | TGRS Research Map | TGRS