Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

Yuen Ho, Albrecht Gruhler, Adrian Heilbut, Gary D. Bader, Lynda Moore, Sally-Lin Adams, Anna Millar, Paul Taylor, Keiryn Bennett, Kelly Boutilier, Lingyun Yang, Cheryl Wolting, Ian Donaldson, Søren Schandorff, Juanita Shewnarane, Mai Vo, Joanne Taggart, Marilyn Goudreault, Brenda Muskat, Cris Alfarano, Danielle Dewar, Zhen Lin, Katerina Michalickova, Andrew R. Willems, Holly Sassi, Peter A. Nielsen, Karina J. Rasmussen, Jens R. Andersen, Lene E. Johansen, Lykke H. Hansen, Hans Jespersen, Alexandre Podtelejnikov, Eva Nielsen, Janne Crawford, Vibeke Poulsen, Birgitte D. Sørensen, Jesper Matthiesen, Ronald C. Hendrickson, Frank Gleeson, Tony Pawson, Michael F. Moran, Daniel Durocher, Matthias Mann, Christopher W. V. Hogue, Daniel Figeys () and Mike Tyers
Additional contact information
Yuen Ho: MDS Proteomics
Albrecht Gruhler: MDS Proteomics
Adrian Heilbut: MDS Proteomics
Gary D. Bader: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Lynda Moore: MDS Proteomics
Sally-Lin Adams: MDS Proteomics
Anna Millar: MDS Proteomics
Paul Taylor: MDS Proteomics
Keiryn Bennett: MDS Proteomics
Kelly Boutilier: MDS Proteomics
Lingyun Yang: MDS Proteomics
Cheryl Wolting: MDS Proteomics
Ian Donaldson: MDS Proteomics
Søren Schandorff: MDS Proteomics
Juanita Shewnarane: MDS Proteomics
Mai Vo: MDS Proteomics
Joanne Taggart: MDS Proteomics
Marilyn Goudreault: MDS Proteomics
Brenda Muskat: MDS Proteomics
Cris Alfarano: MDS Proteomics
Danielle Dewar: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Zhen Lin: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Katerina Michalickova: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Andrew R. Willems: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Holly Sassi: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Peter A. Nielsen: MDS Proteomics
Karina J. Rasmussen: MDS Proteomics
Jens R. Andersen: MDS Proteomics
Lene E. Johansen: MDS Proteomics
Lykke H. Hansen: MDS Proteomics
Hans Jespersen: MDS Proteomics
Alexandre Podtelejnikov: MDS Proteomics
Eva Nielsen: MDS Proteomics
Janne Crawford: MDS Proteomics
Vibeke Poulsen: MDS Proteomics
Birgitte D. Sørensen: MDS Proteomics
Jesper Matthiesen: MDS Proteomics
Ronald C. Hendrickson: MDS Proteomics
Frank Gleeson: MDS Proteomics
Tony Pawson: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Michael F. Moran: MDS Proteomics
Daniel Durocher: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Matthias Mann: MDS Proteomics
Christopher W. V. Hogue: MDS Proteomics
Daniel Figeys: MDS Proteomics
Mike Tyers: Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital

Nature, 2002, vol. 415, issue 6868, 180-183

Abstract: Abstract The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function1. To date, generation of large-scale protein–protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression2,3,4. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale5,6. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies3,4. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.

Date: 2002
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DOI: 10.1038/415180a

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