Cellinker: a platform of ligand–receptor interactions for intercellular communication analysis

Abstract

Motivation Ligand-receptor (L-R) interactions mediate cell adhesion, recognition and communication and play essential roles in physiological and pathological signaling. With the rapid development of single-cell RNA sequencing (scRNA-seq) technologies, systematically decoding the intercellular communication network involving L-R interactions has become a focus of research. Therefore, construction of a comprehensive, high-confidence and well-organized resource to retrieve L-R interactions in order to study the functional effects of cell-cell communications would be of great value. Results In this study, we developed Cellinker, a manually curated resource of literature-supported L-R interactions that play roles in cell-cell communication. We aimed to provide a useful platform for studies on cell-cell communication mediated by L-R interactions. The current version of Cellinker documents over 3,700 human and 3,200 mouse L-R protein-protein interactions (PPIs) and embeds a practical and convenient webserver with which researchers can decode intercellular communications based on scRNA-seq data. And over 400 endogenous small molecule (sMOL) related L-R interactions were collected as well. Moreover, to help with research on coronavirus (CoV) infection, Cellinker collects information on 16 L-R PPIs involved in CoV-human interactions (including 12 L-R PPIs involved in SARS-CoV-2 infection). In summary, Cellinker provides a user-friendly interface for querying, browsing and visualizing L-R interactions as well as a practical and convenient web tool for inferring intercellular communications based on scRNA-seq data. We believe this platform could promote intercellular communication research and accelerate the development of related algorithms for scRNA-seq studies. Availability Cellinker is available at http://www.rna-society.org/cellinker/. Supplementary information Supplementary data are available at Bioinformatics online.

CellCall: integrating paired ligand–receptor and transcription factor activities for cell–cell communication

“…The remaining tools include L–R interactions from known databases and the literature (ranging from 380 to 3251 entries). In addition, CellCall CellPhoneDB, CellChat ( 15 ) and ICELLNET ( 74 ) contain ligand/receptor complex information, which should not be ignored because many ligands/receptors act as multisubunit complexes ( 25 ). CellCall and Nichenet scored intercellular communication based on L/R/TG expression.…”

“…Cells rely on intercellular signal transduction to recognize and respond to cues in their environment ( 25 ). This process not only promotes the proper functioning of individual cells but also allows communication and coordination among groups of cells to carry out tasks no single cell could accomplish on its own ( 75 ).…”

“…The L–R–TF axis dataset was extracted from the KEGG pathway analysis using the following steps. (1) We collected human L–R interactions from the NATMI ( 14 ), Cellinker ( 25 ), CellTalkDB ( 26 ), CellChat ( 15 ) and STRING v11 databases (only literature or experimental supported data were collected) ( 27 ); ligand/receptor complexes were included among the L–R interactions. (2) We extracted the TFs downstream of the L–R interaction from the KEGG pathway.…”

“…A total of 587,248 human experimental supported interactions were collected. Moreover, a total of 12 069 mouse L–R–TF axes and 554 207 TF–TG interactions were obtained by the orthology majority-voting scheme described in Cellinker ( 25 ).…”

Single-cell RNA sequencing reveals cell heterogeneity and transcriptome profile of breast cancer lymph node metastasis

“…Cell–cell interactions inside the microenvironment are crucial to understanding the mechanisms underlying tumorigenesis, cancer metastasis, and drug response of cancer cells. Interactions among cell-surface proteins, secreted proteins, and the respective ligand-receptor (L-R) are vital components of the intercellular cross-talk network [ 14 ]. We identified cell-to-cell communications that BCSC and metastatic cancer cells take part in and demonstrated the corresponding contributions to lymph node metastasis.…”