1
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Blaszczak E, Lazarewicz N, Sudevan A, Wysocki R, Rabut G. Protein-fragment complementation assays for large-scale analysis of protein-protein interactions. Biochem Soc Trans 2021; 49:1337-1348. [PMID: 34156434 PMCID: PMC8286835 DOI: 10.1042/bst20201058] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 05/10/2021] [Accepted: 05/14/2021] [Indexed: 12/25/2022]
Abstract
Protein-protein interactions (PPIs) orchestrate nearly all biological processes. They are also considered attractive drug targets for treating many human diseases, including cancers and neurodegenerative disorders. Protein-fragment complementation assays (PCAs) provide a direct and straightforward way to study PPIs in living cells or multicellular organisms. Importantly, PCAs can be used to detect the interaction of proteins expressed at endogenous levels in their native cellular environment. In this review, we present the principle of PCAs and discuss some of their advantages and limitations. We describe their application in large-scale experiments to investigate PPI networks and to screen or profile PPI targeting compounds.
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Affiliation(s)
- Ewa Blaszczak
- Department of Genetics and Cell Physiology, Faculty of Biological Sciences, University of Wroclaw, Kanonia 6/8, 50-328 Wroclaw, Poland
| | - Natalia Lazarewicz
- Department of Genetics and Cell Physiology, Faculty of Biological Sciences, University of Wroclaw, Kanonia 6/8, 50-328 Wroclaw, Poland
- Univ Rennes, CNRS, IGDR (Institute of Genetics and Development of Rennes) – UMR 6290, F-35000 Rennes, France
| | - Aswani Sudevan
- Univ Rennes, CNRS, IGDR (Institute of Genetics and Development of Rennes) – UMR 6290, F-35000 Rennes, France
| | - Robert Wysocki
- Department of Genetics and Cell Physiology, Faculty of Biological Sciences, University of Wroclaw, Kanonia 6/8, 50-328 Wroclaw, Poland
| | - Gwenaël Rabut
- Univ Rennes, CNRS, IGDR (Institute of Genetics and Development of Rennes) – UMR 6290, F-35000 Rennes, France
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2
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Liu Z, Miller D, Li F, Liu X, Levy SF. A large accessory protein interactome is rewired across environments. eLife 2020; 9:e62365. [PMID: 32924934 PMCID: PMC7577743 DOI: 10.7554/elife.62365] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 09/04/2020] [Indexed: 12/30/2022] Open
Abstract
To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in the yeast Saccharomyces cerevisiae across nine growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a threefold increase over PPIs identified in one condition. A few 'immutable' PPIs are present across all conditions, while most 'mutable' PPIs are rarely observed. Immutable PPIs aggregate into highly connected 'core' network modules, with most network remodeling occurring within a loosely connected 'accessory' module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.
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Affiliation(s)
- Zhimin Liu
- Department of Biochemistry, Stony Brook UniversityStony BrookUnited States
- Laufer Center for Physical and Quantitative Biology, Stony Brook UniversityStony BrookUnited States
| | - Darach Miller
- Joint Initiative for Metrology in BiologyStanfordUnited States
- Department of Genetics, Stanford UniversityStanfordUnited States
| | - Fangfei Li
- Laufer Center for Physical and Quantitative Biology, Stony Brook UniversityStony BrookUnited States
- Department of Applied Mathematics and Statistics, Stony Brook UniversityStony BrookUnited States
| | - Xianan Liu
- Department of Biochemistry, Stony Brook UniversityStony BrookUnited States
- Laufer Center for Physical and Quantitative Biology, Stony Brook UniversityStony BrookUnited States
| | - Sasha F Levy
- Department of Biochemistry, Stony Brook UniversityStony BrookUnited States
- Laufer Center for Physical and Quantitative Biology, Stony Brook UniversityStony BrookUnited States
- Joint Initiative for Metrology in BiologyStanfordUnited States
- Department of Genetics, Stanford UniversityStanfordUnited States
- Department of Applied Mathematics and Statistics, Stony Brook UniversityStony BrookUnited States
- SLAC National Accelerator LaboratoryMenlo ParkUnited States
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3
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Levray YS, Berhe AD, Osborne AR. Use of split-dihydrofolate reductase for the detection of protein-protein interactions and simultaneous selection of multiple plasmids in Plasmodium falciparum. Mol Biochem Parasitol 2020; 238:111292. [PMID: 32505674 DOI: 10.1016/j.molbiopara.2020.111292] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 05/04/2020] [Accepted: 05/09/2020] [Indexed: 11/22/2022]
Abstract
Defining protein-protein interactions is fundamental to the understanding of gene function. Protein-fragment complementation assays have been used for the analysis of protein-protein interactions in various organisms. The split-dihydrofolate reductase (DHFR) protein-fragment complementation assay utilises two complementary fragments of the enzyme fused to a pair of potentially interacting proteins. If these proteins interact, the DHFR fragments associate, fold into their native structure, reconstitute their function and confer resistance to antifolate drugs. We show that murine DHFR fragments fused to interacting proteins reconstitute a functional enzyme and confer resistance to the antifolate drug WR99210 in Plasmodium falciparum. These data demonstrate that the split-DHFR method can be used to detect in vivo protein-protein interactions in the parasite. Additionally, we show that split-DHFR fragments can be used as selection markers, permitting simultaneous selection of two plasmids in the presence of a single antifolate drug. Taken together, these experiments show that split-DHFR represents a valuable tool for the characterisation of Plasmodium protein function and genetic manipulation of the parasite.
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Affiliation(s)
- Yvette S Levray
- Institute of Structural and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Anne D Berhe
- Pomona College, 333 N. College Way, Claremont, CA 91711, United States
| | - Andrew R Osborne
- Institute of Structural and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, United Kingdom; Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, Malet Street, London, WC1E 7HX, United Kingdom.
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4
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Gauthier L, Stynen B, Serohijos AWR, Michnick SW. Genetics' Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome-Wide Protein-Protein Interaction Dynamics. Bioessays 2019; 42:e1900169. [PMID: 31854021 DOI: 10.1002/bies.201900169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/15/2019] [Indexed: 11/07/2022]
Abstract
How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein-protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment.
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Affiliation(s)
- Louis Gauthier
- Departement de Biochimie, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada.,Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada
| | - Bram Stynen
- Departement de Biochimie, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada.,Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada
| | - Adrian W R Serohijos
- Departement de Biochimie, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada.,Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada
| | - Stephen W Michnick
- Departement de Biochimie, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada.,Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, 2900 Édouard-Montpetit, Montréal, Quebec, H3T 1J4, Canada
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5
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Marchant A, Cisneros AF, Dubé AK, Gagnon-Arsenault I, Ascencio D, Jain H, Aubé S, Eberlein C, Evans-Yamamoto D, Yachie N, Landry CR. The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs. eLife 2019; 8:46754. [PMID: 31454312 PMCID: PMC6711710 DOI: 10.7554/elife.46754] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 08/11/2019] [Indexed: 01/07/2023] Open
Abstract
Gene duplication is a driver of the evolution of new functions. The duplication of genes encoding homomeric proteins leads to the formation of homomers and heteromers of paralogs, creating new complexes after a single duplication event. The loss of these heteromers may be required for the two paralogs to evolve independent functions. Using yeast as a model, we find that heteromerization is frequent among duplicated homomers and correlates with functional similarity between paralogs. Using in silico evolution, we show that for homomers and heteromers sharing binding interfaces, mutations in one paralog can have structural pleiotropic effects on both interactions, resulting in highly correlated responses of the complexes to selection. Therefore, heteromerization could be preserved indirectly due to selection for the maintenance of homomers, thus slowing down functional divergence between paralogs. We suggest that paralogs can overcome the obstacle of structural pleiotropy by regulatory evolution at the transcriptional and post-translational levels.
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Affiliation(s)
- Axelle Marchant
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
| | - Angel F Cisneros
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada
| | - Alexandre K Dubé
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
| | - Isabelle Gagnon-Arsenault
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
| | - Diana Ascencio
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
| | - Honey Jain
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Department of Biological Sciences, Birla Institute of Technology and Sciences, Pilani, India
| | - Simon Aubé
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada
| | - Chris Eberlein
- PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
| | - Daniel Evans-Yamamoto
- Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan.,Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan.,Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | - Nozomu Yachie
- Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan.,Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan.,Graduate School of Media and Governance, Keio University, Fujisawa, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan
| | - Christian R Landry
- Département de biochimie, de microbiologie et de bio-informatique, Université Laval, Québec, Canada.,PROTEO, le réseau québécois de recherche sur la fonction, la structure et l'ingénierie des protéines, Université Laval, Québec, Canada.,Centre de Recherche en Données Massives (CRDM), Université Laval, Québec, Canada.,Département de biologie, Université Laval, Québec, Canada
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6
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Stynen B, Abd-Rabbo D, Kowarzyk J, Miller-Fleming L, Aulakh SK, Garneau P, Ralser M, Michnick SW. Changes of Cell Biochemical States Are Revealed in Protein Homomeric Complex Dynamics. Cell 2018; 175:1418-1429.e9. [PMID: 30454649 PMCID: PMC6242466 DOI: 10.1016/j.cell.2018.09.050] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 09/04/2018] [Accepted: 09/24/2018] [Indexed: 01/22/2023]
Abstract
We report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins, or other small molecules based on "homomer dynamics" protein-fragment complementation assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating the confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health span-affecting drugs, the immunosuppressant rapamycin and the type 2 diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency and includes a change in protein-bound iron levels. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatment of diabetes, cancers, and other chronic diseases of aging.
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Affiliation(s)
- Bram Stynen
- Département de Biochimie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC H3C 3J7, Canada
| | - Diala Abd-Rabbo
- Département de Biochimie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC H3C 3J7, Canada; Centre Robert-Cedergren, Bio-Informatique et Génomique, Université de Montréal, C.P. 6128, Succursale centre-ville, Montréal, QC H3C 3J7, Canada
| | - Jacqueline Kowarzyk
- Département de Biochimie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC H3C 3J7, Canada
| | - Leonor Miller-Fleming
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
| | - Simran Kaur Aulakh
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Philippe Garneau
- Département de Biochimie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC H3C 3J7, Canada
| | - Markus Ralser
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK; Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK; Department of Biochemistry, Charité University Medicine, Berlin, Germany
| | - Stephen W Michnick
- Département de Biochimie, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC H3C 3J7, Canada; Centre Robert-Cedergren, Bio-Informatique et Génomique, Université de Montréal, C.P. 6128, Succursale centre-ville, Montréal, QC H3C 3J7, Canada.
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7
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Chrétien AÈ, Gagnon-Arsenault I, Dubé AK, Barbeau X, Després PC, Lamothe C, Dion-Côté AM, Lagüe P, Landry CR. Extended Linkers Improve the Detection of Protein-protein Interactions (PPIs) by Dihydrofolate Reductase Protein-fragment Complementation Assay (DHFR PCA) in Living Cells. Mol Cell Proteomics 2017; 17:373-383. [PMID: 29203496 DOI: 10.1074/mcp.tir117.000385] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Indexed: 01/08/2023] Open
Abstract
Understanding the function of cellular systems requires describing how proteins assemble with each other into transient and stable complexes and to determine their spatial relationships. Among the tools available to perform these analyses on a large scale is Protein-fragment Complementation Assay based on the dihydrofolate reductase (DHFR PCA). Here we test how longer linkers between the fusion proteins and the reporter fragments affect the performance of this assay. We investigate the architecture of the RNA polymerases, the proteasome and the conserved oligomeric Golgi (COG) complexes in living cells and performed large-scale screens with these extended linkers. We show that longer linkers significantly improve the detection of protein-protein interactions and allow to measure interactions further in space than the standard ones. We identify new interactions, for instance between the retromer complex and proteins related to autophagy and endocytosis. Longer linkers thus contribute an enhanced additional tool to the existing toolsets for the detection and measurements of protein-protein interactions and protein proximity in living cells.
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Affiliation(s)
- Andrée-Ève Chrétien
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie
| | - Isabelle Gagnon-Arsenault
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie
| | - Alexandre K Dubé
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie
| | - Xavier Barbeau
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,**Département de biochimie, microbiologie et bioinformatique. Université Laval, Québec, Québec, G1V 0A6, Canada
| | - Philippe C Després
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie.,**Département de biochimie, microbiologie et bioinformatique. Université Laval, Québec, Québec, G1V 0A6, Canada
| | - Claudine Lamothe
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie.,**Département de biochimie, microbiologie et bioinformatique. Université Laval, Québec, Québec, G1V 0A6, Canada
| | - Anne-Marie Dion-Côté
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie
| | - Patrick Lagüe
- From the ‡Institut de Biologie Intégrative et des Systèmes.,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,**Département de biochimie, microbiologie et bioinformatique. Université Laval, Québec, Québec, G1V 0A6, Canada
| | - Christian R Landry
- From the ‡Institut de Biologie Intégrative et des Systèmes; .,§The Quebec Network for Research on Protein Function, Engineering, and Applications.,¶Centre de Recherche en Données Massives de l'Université Laval.,‖Département de biologie.,**Département de biochimie, microbiologie et bioinformatique. Université Laval, Québec, Québec, G1V 0A6, Canada
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8
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Stynen B, Abd-rabbo D, Kowarzyk J, Miller-fleming L, Ralser M, Michnick S. A Yeast Global Genetic Screen Reveals that Metformin Induces an Iron Deficiency-Like State.. [DOI: 10.1101/190389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
AbstractWe report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins or other small molecules based on “homomer dynamics” Protein-fragment Complementation Assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health-span-affecting drugs, immunosuppressant rapamycin and type II diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatments of diabetes, cancers and other chronic diseases of aging.
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9
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Celaj A, Schlecht U, Smith JD, Xu W, Suresh S, Miranda M, Aparicio AM, Proctor M, Davis RW, Roth FP, St Onge RP. Quantitative analysis of protein interaction network dynamics in yeast. Mol Syst Biol 2017; 13:934. [PMID: 28705884 PMCID: PMC5527849 DOI: 10.15252/msb.20177532] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.
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Affiliation(s)
- Albi Celaj
- Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON, Canada.,Donnelly Centre, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Ulrich Schlecht
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Justin D Smith
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Weihong Xu
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
| | - Sundari Suresh
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Molly Miranda
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Ana Maria Aparicio
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Proctor
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald W Davis
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA.,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Frederick P Roth
- Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON, Canada .,Donnelly Centre, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Canadian Institute for Advanced Research, Toronto, ON, Canada.,Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Robert P St Onge
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA .,Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
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10
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Diss G, Landry CR. Combining the Dihydrofolate Reductase Protein-Fragment Complementation Assay with Gene Deletions to Establish Genotype-to-Phenotype Maps of Protein Complexes and Interaction Networks. Cold Spring Harb Protoc 2016; 2016:2016/11/pdb.prot090035. [PMID: 27803253 DOI: 10.1101/pdb.prot090035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Systematically measuring the impact of gene deletion on protein-protein interactions is a promising approach to reveal the structural bases of protein interaction networks and to allow a better understanding of how genotypes translate into phenotypes. Genetic and protein-interaction tools in yeast now allow us to explore this third dimension of protein-protein interaction networks. Because it is scalable and quantitative, the protein-fragment complementation assay (PCA) using dihydrofolate reductase (DHFR) as the reporter protein provides an exceptionally powerful tool for such a purpose. Here, we describe a fully automated protocol that combines DHFR PCA for protein-protein interaction measurement and synthetic genetic array (SGA) technology for introducing mutant and other alleles into PCA strains using genetic crosses. In this, PCA strains are crossed with strains carrying a gene deletion and SGA markers, and the recombinant haploid progeny are selected by SGA. The resulting haploid strains, each expressing a DHFR-fragment fusion protein in a gene-specific haploid deletion background, are crossed to measure the interaction between the two recombinant proteins by PCA in a diploid homozygous deletion background. This approach can be used to measure a single protein interaction in a large array of genetic backgrounds or a large number of protein interactions in a small number of genetic backgrounds.
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Affiliation(s)
- Guillaume Diss
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes, PROTEO-Québec Research Network on Protein Function, Structure and Engineering, Université Laval, Québec, Québec G1V 0A6, Canada
| | - Christian R Landry
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes, PROTEO-Québec Research Network on Protein Function, Structure and Engineering, Université Laval, Québec, Québec G1V 0A6, Canada
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Zhou M, Li Q, Wang R. Current Experimental Methods for Characterizing Protein-Protein Interactions. ChemMedChem 2016; 11:738-56. [PMID: 26864455 PMCID: PMC7162211 DOI: 10.1002/cmdc.201500495] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 01/08/2016] [Indexed: 12/14/2022]
Abstract
Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.
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Affiliation(s)
- Mi Zhou
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China
| | - Qing Li
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China
| | - Renxiao Wang
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China.
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Avenida Wai Long, Macau, 999078, People's Republic of China.
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12
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Zhou M, Li Q, Wang R. Current Experimental Methods for Characterizing Protein-Protein Interactions. ChemMedChem 2016. [PMID: 26864455 DOI: 10.1002/cmdc.201500495.] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.
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Affiliation(s)
- Mi Zhou
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China
| | - Qing Li
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China
| | - Renxiao Wang
- State Key Laboratory of Bioorganic & Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Rd, Shanghai, 200032, People's Republic of China. .,State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Avenida Wai Long, Macau, 999078, People's Republic of China.
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Filteau M, Vignaud H, Rochette S, Diss G, Chrétien AÈ, Berger CM, Landry CR. Multi-scale perturbations of protein interactomes reveal their mechanisms of regulation, robustness and insights into genotype-phenotype maps. Brief Funct Genomics 2015; 15:130-7. [PMID: 26476431 DOI: 10.1093/bfgp/elv043] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Cellular architectures and signaling machineries are organized through protein-protein interactions (PPIs). High-throughput methods to study PPIs in yeast have opened a new perspective on the organization of the cell by allowing the study of whole protein interactomes. Recent investigations have moved from the description of this organization to the analysis of its dynamics by experimenting how protein interaction networks (PINs) are rewired in response to perturbations. Here we review studies that have used the budding yeast as an experimental system to explore these altered networks. Given the large space of possible PPIs and the diversity of potential genetic and environmental perturbations, high-throughput methods are an essential requirement to survey PIN perturbations on a large scale. Network perturbations are typically conceptualized as the removal of entire proteins (nodes), the modification of single PPIs (edges) or changes in growth conditions. These studies have revealed mechanisms of PPI regulation, PIN architectural organization, robustness and sensitivity to perturbations. Despite these major advances, there are still inherent limits to current technologies that lead to a trade-off between the number of perturbations and the number of PPIs that can be considered simultaneously. Nevertheless, as we exemplify here, targeted approaches combined with the existing resources remain extremely powerful to explore the inner organization of cells and their responses to perturbations.
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Rochette S, Diss G, Filteau M, Leducq JB, Dubé AK, Landry CR. Genome-wide protein-protein interaction screening by protein-fragment complementation assay (PCA) in living cells. J Vis Exp 2015:52255. [PMID: 25867901 PMCID: PMC4401175 DOI: 10.3791/52255] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Proteins are the building blocks, effectors and signal mediators of cellular processes. A protein's function, regulation and localization often depend on its interactions with other proteins. Here, we describe a protocol for the yeast protein-fragment complementation assay (PCA), a powerful method to detect direct and proximal associations between proteins in living cells. The interaction between two proteins, each fused to a dihydrofolate reductase (DHFR) protein fragment, translates into growth of yeast strains in presence of the drug methotrexate (MTX). Differential fitness, resulting from different amounts of reconstituted DHFR enzyme, can be quantified on high-density colony arrays, allowing to differentiate interacting from non-interacting bait-prey pairs. The high-throughput protocol presented here is performed using a robotic platform that parallelizes mating of bait and prey strains carrying complementary DHFR-fragment fusion proteins and the survival assay on MTX. This protocol allows to systematically test for thousands of protein-protein interactions (PPIs) involving bait proteins of interest and offers several advantages over other PPI detection assays, including the study of proteins expressed from their endogenous promoters without the need for modifying protein localization and for the assembly of complex reporter constructs.
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Affiliation(s)
- Samuel Rochette
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval
| | - Guillaume Diss
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval
| | - Marie Filteau
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval
| | - Jean-Baptiste Leducq
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval
| | - Alexandre K Dubé
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval
| | - Christian R Landry
- Département de Biologie, Institut de biologie intégrative et des systémes & PROTEO, Université Laval;
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Truman AW, Kristjansdottir K, Wolfgeher D, Ricco N, Mayampurath A, Volchenboum SL, Clotet J, Kron SJ. Quantitative proteomics of the yeast Hsp70/Hsp90 interactomes during DNA damage reveal chaperone-dependent regulation of ribonucleotide reductase. J Proteomics 2014; 112:285-300. [PMID: 25452130 DOI: 10.1016/j.jprot.2014.09.028] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Revised: 09/05/2014] [Accepted: 09/27/2014] [Indexed: 12/11/2022]
Abstract
UNLABELLED The highly conserved molecular chaperones Hsp90 and Hsp70 are indispensible for folding and maturation of a significant fraction of the proteome, including many proteins involved in signal transduction and stress response. To examine the dynamics of chaperone-client interactions after DNA damage, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to characterize interactomes of the yeast Hsp70 isoform Ssa1 and Hsp90 isoform Hsp82 before and after exposure to methyl methanesulfonate. Of 256 proteins identified and quantified via (16)O(/18)O labeling and LC-MS/MS, 142 are novel Hsp70/90 interactors. Nearly all interactions remained unchanged or decreased after DNA damage, but 5 proteins increased interactions with Ssa1 and/or Hsp82, including the ribonucleotide reductase (RNR) subunit Rnr4. Inhibiting Hsp70 or 90 chaperone activity destabilized Rnr4 in yeast and its vertebrate homolog hRMM2 in breast cancer cells. In turn, pre-treatment of cancer cells with chaperone inhibitors sensitized cells to the RNR inhibitor gemcitabine, suggesting a novel chemotherapy strategy. All MS data have been deposited in the ProteomeXchange with identifier PXD001284. BIOLOGICAL SIGNIFICANCE This study provides the dynamic interactome of the yeast Hsp70 and Hsp90 under DNA damage which suggest key roles for the chaperones in a variety of signaling cascades. Importantly, the cancer drug target ribonucleotide reductase was shown to be a client of Hsp70 and Hsp90 in both yeast and breast cancer cells. As such, this study highlights the potential of a novel cancer therapeutic strategy that exploits the synergy of chaperone and ribonucleotide reductase inhibitors.
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Affiliation(s)
- Andrew W Truman
- Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL 60637, USA
| | | | - Donald Wolfgeher
- Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Natalia Ricco
- Departament de Ciències Bàsiques, Universitat Internacional de Catalunya, Barcelona, Catalunya, Spain
| | - Anoop Mayampurath
- Computation Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Samuel L Volchenboum
- Computation Institute, The University of Chicago, Chicago, IL 60637, USA; Department of Pediatrics, The University of Chicago, Chicago, IL 60637, USA
| | - Josep Clotet
- Departament de Ciències Bàsiques, Universitat Internacional de Catalunya, Barcelona, Catalunya, Spain
| | - Stephen J Kron
- Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL 60637, USA.
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Environmental and structural proteomics. J Proteomics 2014; 104:1-3. [PMID: 24881956 DOI: 10.1016/j.jprot.2014.04.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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17
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Different subunits belonging to the same protein complex often exhibit discordant expression levels and evolutionary properties. Curr Opin Struct Biol 2014; 26:113-20. [DOI: 10.1016/j.sbi.2014.06.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Revised: 04/27/2014] [Accepted: 06/04/2014] [Indexed: 11/21/2022]
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