Inferring Protein-protein Interaction Complexes from Immunoprecipitation Data

Overview

Journal BMC Res Notes

Publisher Biomed Central

Specialties Biology
General Medicine

Date 2013 Nov 19

PMID 24237943

Citations 3

Authors

Joachim Kutzera

Huub C J Hoefsloot

Anna Malovannaya

August B Smit

Iven Van Mechelen

Age K Smilde

Affiliations

Soon will be listed here.

Abstract

Background: Protein-protein interactions in cells are widely explored using small-scale experiments. However, the search for protein complexes and their interactions in data from high throughput experiments such as immunoprecipitation is still a challenge. We present "4N", a novel method for detecting protein complexes in such data. Our method is a heuristic algorithm based on Near Neighbor Network (3N) clustering. It is written in R, it is faster than model-based methods, and has only a small number of tuning parameters. We explain the application of our new method to real immunoprecipitation results and two artificial datasets. We show that the method can infer protein complexes from protein immunoprecipitation datasets of different densities and sizes.

Findings: 4N was applied on the immunoprecipitation dataset that was presented by the authors of the original 3N in Cell 145:787-799, 2011. The test with our method shows that it can reproduce the original clustering results with fewer manually adapted parameters and, in addition, gives direct insight into the complex-complex interactions. We also tested 4N on the human "Tip49a/b" dataset. We conclude that 4N can handle the contaminants and can correctly infer complexes from this very dense dataset. Further tests were performed on two artificial datasets of different sizes. We proved that the method predicts the reference complexes in the two artificial datasets with high accuracy, even when the number of samples is reduced.

Conclusions: 4N has been implemented in R. We provide the sourcecode of 4N and a user-friendly toolbox including two example calculations. Biologists can use this 4N-toolbox even if they have a limited knowledge of R. There are only a few tuning parameters to set, and each of these parameters has a biological interpretation. The run times for medium scale datasets are in the order of minutes on a standard desktop PC. Large datasets can typically be analyzed within a few hours.

Citing Articles

Rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) for analysis of chromatin complexes.

Mohammed H, Taylor C, Brown G, Papachristou E, Carroll J, DSantos C Nat Protoc. 2016; 11(2):316-26.

PMID: 26797456 DOI: 10.1038/nprot.2016.020.

Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes.

Kutzera J, Smilde A, Wilderjans T, Hoefsloot H PLoS One. 2015; 10(10):e0139704.

PMID: 26448546 PMC: 4598013. DOI: 10.1371/journal.pone.0139704.

Interaction of myelin basic protein with cytoskeletal and signaling proteins in cultured primary oligodendrocytes and N19 oligodendroglial cells.

Boggs J, Homchaudhuri L, Ranagaraj G, Liu Y, Smith G, Harauz G BMC Res Notes. 2014; 7:387.

PMID: 24956930 PMC: 4078013. DOI: 10.1186/1756-0500-7-387.

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