Yang Zhang1, Tianyuan Liu2, Jing Wang2, Bohao Zou3, Le Li4, Linhui Yao2, Kechen Chen2, Lin Ning2, Bingyi Wu1, Xiaoyang Zhao1,5, Dong Wang1,2,6. 1. Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan 528308, China. 2. Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China. 3. Department of Statistics, University of California Davis, Davis, California, USA. 4. Department of Pathology, Harbin Medical University, Harbin 150081, China. 5. Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China. 6. Dermatology Hospital, Southern Medical University, Guangzhou 510091, China.
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.
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 mouseL-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.
Authors: Alberto Valdeolivas; Aurélien Dugourd; Daniel Dimitrov; Dénes Türei; Martin Garrido-Rodriguez; Paul L Burmedi; James S Nagai; Charlotte Boys; Ricardo O Ramirez Flores; Hyojin Kim; Bence Szalai; Ivan G Costa; Julio Saez-Rodriguez Journal: Nat Commun Date: 2022-06-09 Impact factor: 17.694