A Web Resource for Improved Analysis of AP-MS Protein Interaction Data
Year: 2013
Type: article
Abstract: Affinity purification coupled with mass spectrometry (AP-MS) is now a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (e.g. proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. While the standard approach is to identify nonspecific interactions using one or more negative controls, most small-scale AP-MS studies do not capture a complete, accurate background protein set. Fortunately, since negative controls are largely bait-independent, we reasoned that the negative controls generated by the proteomics research community could be developed as a resource for scoring AP-MS data. Here we present the Contaminant Repository for Affinity Purification (The CRAPome), currently containing AP-MS data from 343 control purifications conducted by 11 different research groups (www.crapome.org). Users employ an intuitive graphical user interface to explore the database, by either querying one protein at a time, downloading background contaminant lists for selected experimental conditions, or uploading their own data (alongside their own negative controls when available) and performing data analysis. The CRAPome database scores contaminants vs. true interactors based on semi-quantitative mass spectrometry data (normalized spectral counts) embedded in most mass spectrometry experiments. The Significance Analysis of INTeractome (SAINT) scoring scheme, in addition to a simpler Fold Change calculation (FC score) are used to score user-supplied data and return a ranked list of putative interactors. We also describe database structure and composition, provide examples of the use of this resource to filter contaminants with properly chosen controls, and demonstrate the utility of the scoring scheme for identifying bona fide interaction partners. The CRAPome accommodates a variety of purification schemes and, while currently focused on human data, will be expanded to other species.
Source: Europe PMC (PubMed Central)
Authors: Mellacheruvu, Dattatreya, Wright, Zachary, Couzens, Amber L., Lambert, Jean-Philippe, St-Denis, Nicole, Li, Tuo, Mitev, Yana V., Hauri, Simon, Sardiu, Mihaela E., Low, Teck Yew, Halim, Vincentius A., Bagshaw, Richard D., Hubner, Nina C., al-Hakim, Abdallah, Bouchard, Annie, Faubert, Denis, Fermin, Damian, Dunham, Wade H., Goudreault, Marilyn, Lin, Zhen-Yuan, Badillo, Beatriz Gonzalez, Pawson, Tony, Durocher, Daniel, Coulombe, Benoit, Aebersold, Ruedi, Superti-Furga, Giulio, Colinge, Jacques, Heck, Albert J. R., Choi, Hyungwon, Gstaiger, Matthias, Mohammed, Shabaz, Cristea, Ileana M., Bennett, Keiryn L., Washburn, Mike P., Raught, Brian, Ewing, Rob M., Gingras, Anne-Claude, Nesvizhskii, Alexey
Institutions: University of Michigan, Mount Sinai Hospital, Lunenfeld-Tanenbaum Research Institute, Princeton University, ETH Zurich, Institute for Molecular Systems Biology, Stowers Institute for Medical Research, Netherlands Proteomics Centre, The Netherlands Cancer Institute, Radboud University Nijmegen, Montreal Clinical Research Institute, University of Toronto, Université de Montréal, Austrian Academy of Sciences, CeMM Research Center for Molecular Medicine, National University of Singapore, University of Kansas Medical Center, Case Western Reserve University
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W264977805