Cell-Cell Interactions

Overview

Cell-Cell interactions were computed by a similar method as described by Qiao et al (1) . Using a set of proteins designated as receptors, and ligands defined with a set of GO terms (2,3) and other data sources calculate the set of interactions that represent cell-cell interactions (for example Ligand-receptor, receptor-receptor, ...). This analysis is not limited to Cell-Cell interactions. You can define your own protein types, either manually or by choosing different go terms, and create your customized protein-protein interaction network.

Defining Receptor and Ligands

Receptors

Receptor genes were defined based on

1. a set of GO terms:

   • GO:0043235 - receptor complex,

   • GO:0008305 - integrin complex,

   • GO:0072657 - protein localized to membrane

   • GO:0043113 - receptor clustering

   • GO:0004872 -receptor activity,

   • GO:0009897 - external side of plasma membrane)

2. Uniprot annotations
   • search term -"Receptor [KW-0675]" go:0005886 organism:human.

Ligands

Ligand genes were defined based on

1. the GO terms:

   • GO:0005102 - receptor binding

2. the set of proteins labelled as secreted in the Secretome dataset (http://www.proteinatlas.org/humanproteome/secretome) (4).

Manual Curation

Receptor and ligand lists were further manually curated

• removing genes that were neither receptors or ligands and
• moving misclassified genes were moved to the correct list (i.e. receptors found on the ligand list or vice versa)

Interaction Data

• The set of protien interactions were downloaded from irefindex (version 14) (5). The entire interaction set was filtered to only included interaction that contained receptor-ligand, receptor - receptor, or ligand-ligand interactions where the receptor and ligands were defined by the above process.

References

1. Qiao W, Wang W, Laurenti E, Turinsky AL, Wodak SJ, Bader GD, Dick JE, Zandstra PW Intercellular network structure and regulatory motifs in the human hematopoietic system
   Pubmed

2. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000 May;25(1):25-9
   Pubmed

3. The Gene Ontology Consortium. Expansion of the Gene Ontology knowledgebase and resources. Nucleic Acids Res. 2017 Jan 4;45(D1):D331-D338
   Pubmed

4. Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson Å, Kampf C, Sjöstedt E, Asplund A, Olsson I, Edlund K, Lundberg E, Navani S, Szigyarto CA, Odeberg J, Djureinovic D, Takanen JO, Hober S, Alm T, Edqvist PH, Berling H, Tegel H, Mulder J, Rockberg J, Nilsson P, Schwenk JM, Hamsten M, von Feilitzen K, Forsberg M, Persson L, Johansson F, Zwahlen M, von Heijne G, Nielsen J, Pontén F. Proteomics. Tissue-based map of the human proteome. Science. 2015 Jan 23;347(6220)
   Pubmed

5. Razick S, Magklaras G, Donaldson IM. iRefIndex: a consolidated protein interaction database with provenance. BMC Bioinformatics. 2008 Sep 30;9:405
   Pubmed