Abstract
Protein interaction in cells can be described at different levels. At a low interaction level, proteins function together in small, stable complexes and at a higher level, in sets of interacting complexes. All interaction levels are crucial for the living organism, and one of the challenges in proteomics is to measure the proteins at their different interaction levels. One common method for such measurements is immunoprecipitation followed by mass spectrometry (IP/MS), which has the potential to probe the different protein interaction forms. However, IP/MS data are complex because proteins, in their diverse interaction forms, manifest themselves in different ways in the data. Numerous bioinformatic tools for finding protein complexes in IP/MS data are currently available, but most tools do not provide information about the interaction level of the discovered complexes, and no tool is geared specifically to unraveling and visualizing these different levels. We present a new bioinformatic tool to explore IP/MS datasets for protein complexes at different interaction levels and show its performance on several real–life datasets. Our tool creates clusters that represent protein complexes, but unlike previous methods, it arranges them in a tree–shaped structure, reporting why specific proteins are predicted to build a complex and where it can be divided into smaller complexes. In every data analysis method, parameters have to be chosen. Our method can suggest values for its parameters and comes with adapted visualization tools that display the effect of the parameters on the result. The tools provide fast graphical feedback and allow the user to interact with the data by changing the parameters and examining the result. The tools also allow for exploring the different organizational levels of the protein complexes in a given dataset. Our method is available as GNU-R source code and includes examples at www.bdagroup.nl.
Highlights
Proteins in a living cell interact and build functional units to play their role in the cellular machinery [1,2,3,4]
Characterizing protein complexes in a cell sample is still a delicate task, the research field has progressed considerably and proteins can be identified and quantified using high–throughput methods, such as immunoprecipitation followed by mass spectrometry (IP/MS) [3, 8, 9]
Protein complexes can be found at different organizational levels in IP/MS data, and these levels must be explored together
Summary
Proteins in a living cell interact and build functional units to play their role in the cellular machinery [1,2,3,4]. These units, called protein complexes, carry out many functions in the cell, and comprehending their composition is the key to understanding the cellular machinery in PLOS ONE | DOI:10.1371/journal.pone.0139704. Protein complex formation takes place at different levels of interaction [5, 6]. A protein complex itself represents the higher interaction level and is assembled from one or more cores. At still higher interaction levels, proteins build larger functional units that can consist of physically bound complexes or complexes that interact transiently [7]
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