Author
Listed:
- 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
University of Toronto)
- 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
Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital)
- Joanne Taggart
(MDS Proteomics
Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital)
- Marilyn Goudreault
(MDS Proteomics
Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital)
- 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
University of Toronto)
- Andrew R. Willems
(Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
University of Toronto)
- 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
University of Toronto)
- Michael F. Moran
(MDS Proteomics)
- Daniel Durocher
(Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
University of Toronto)
- Matthias Mann
(MDS Proteomics)
- Christopher W. V. Hogue
(MDS Proteomics
Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
University of Toronto)
- Daniel Figeys
(MDS Proteomics)
- Mike Tyers
(Programme in Molecular Biology and Cancer, Samuel Lunenfeld Research Institute, Mount Sinai Hospital
University of Toronto)
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.
Suggested Citation
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 Donalds, 2002.
"Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry,"
Nature, Nature, vol. 415(6868), pages 180-183, January.
Handle:
RePEc:nat:nature:v:415:y:2002:i:6868:d:10.1038_415180a
DOI: 10.1038/415180a
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Cited by:
- Andrew R. M. Michael & Bruno C. Amaral & Kallie L. Ball & Kristen H. Eiriksson & David C. Schriemer, 2024.
"Cell fixation improves performance of in situ crosslinking mass spectrometry while preserving cellular ultrastructure,"
Nature Communications, Nature, vol. 15(1), pages 1-10, December.
- Jie Zhao & Xiujuan Lei & Fang-Xiang Wu, 2017.
"Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC,"
Complexity, Hindawi, vol. 2017, pages 1-11, August.
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