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Rizzolo K, Houry WA. Multiple functionalities of molecular chaperones revealed through systematic mapping of their interaction networks. J Biol Chem 2018; 294:2142-2150. [PMID: 30194284 DOI: 10.1074/jbc.tm118.002805] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Chaperones are a highly interactive group of proteins that function globally in many cellular processes involved in maintaining protein homeostasis. Traditional biochemical assays typically do not provide a complete view of the intricate networks through which chaperones collaborate to promote proteostasis. Recent advances in high-throughput systematic analyses of chaperone interactions have uncovered that chaperones display a remarkable cooperativity in their interactions with numerous client proteins. This cooperativity has been found to be a fundamental aspect of a properly functioning cell. Aberrant formation or improper regulation of these interactions can easily lead to disease states. Herein, we provide an overview of the use of large-scale interaction assays, whether physical (protein-protein) or genetic (epistatic), to study chaperone interaction networks. Importantly, we discuss the ongoing need for such studies to determine the mechanisms by which protein homeostasis is controlled in the cell.
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Affiliation(s)
- Kamran Rizzolo
- From the Department of Biochemistry, University of Toronto, Toronto, Ontario M5G 1M1 and
| | - Walid A Houry
- From the Department of Biochemistry, University of Toronto, Toronto, Ontario M5G 1M1 and .,the Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
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Rizzolo K, Huen J, Kumar A, Phanse S, Vlasblom J, Kakihara Y, Zeineddine HA, Minic Z, Snider J, Wang W, Pons C, Seraphim TV, Boczek EE, Alberti S, Costanzo M, Myers CL, Stagljar I, Boone C, Babu M, Houry WA. Features of the Chaperone Cellular Network Revealed through Systematic Interaction Mapping. Cell Rep 2018; 20:2735-2748. [PMID: 28903051 DOI: 10.1016/j.celrep.2017.08.074] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 07/21/2017] [Accepted: 08/23/2017] [Indexed: 10/18/2022] Open
Abstract
A comprehensive view of molecular chaperone function in the cell was obtained through a systematic global integrative network approach based on physical (protein-protein) and genetic (gene-gene or epistatic) interaction mapping. This allowed us to decipher interactions involving all core chaperones (67) and cochaperones (15) of Saccharomyces cerevisiae. Our analysis revealed the presence of a large chaperone functional supercomplex, which we named the naturally joined (NAJ) chaperone complex, encompassing Hsp40, Hsp70, Hsp90, AAA+, CCT, and small Hsps. We further found that many chaperones interact with proteins that form foci or condensates under stress conditions. Using an in vitro reconstitution approach, we demonstrate condensate formation for the highly conserved AAA+ ATPases Rvb1 and Rvb2, which are part of the R2TP complex that interacts with Hsp90. This expanded view of the chaperone network in the cell clearly demonstrates the distinction between chaperones having broad versus narrow substrate specificities in protein homeostasis.
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Affiliation(s)
- Kamran Rizzolo
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada
| | - Jennifer Huen
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada
| | - Ashwani Kumar
- Department of Computer Science, University of Regina, Regina, SK S4S 0A2, Canada
| | - Sadhna Phanse
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada
| | - James Vlasblom
- Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada
| | - Yoshito Kakihara
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada
| | | | - Zoran Minic
- Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada
| | - Jamie Snider
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Wen Wang
- Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA; Program in Bioinformatics and Computational Biology, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain
| | - Thiago V Seraphim
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada; Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada
| | - Edgar Erik Boczek
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Simon Alberti
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Michael Costanzo
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Chad L Myers
- Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA; Program in Bioinformatics and Computational Biology, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA
| | - Igor Stagljar
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada; The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Charles Boone
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Mohan Babu
- Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada.
| | - Walid A Houry
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada; Department of Chemistry, University of Toronto, Toronto, ON M5S 3H6, Canada.
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Leung GP, Aristizabal MJ, Krogan NJ, Kobor MS. Conditional genetic interactions of RTT107, SLX4, and HRQ1 reveal dynamic networks upon DNA damage in S. cerevisiae. G3 (Bethesda) 2014; 4:1059-69. [PMID: 24700328 DOI: 10.1534/g3.114.011205] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The DNA damage response (DDR) is a dynamic process that is crucial for protecting the cell from challenges to genome integrity. Although many genome-wide studies in Saccharomyces cerevisiae have identified genes that contribute to resistance to DNA-damaging agents, more work is needed to elucidate the changes in genetic interaction networks in response to DNA lesions. Here we used conditional epistatic miniarray profiling to analyze the genetic interaction networks of the DDR genes RTT107, SLX4, and HRQ1 under three DNA-damaging conditions: camptothecin, hydroxyurea, and methyl methanesulfonate. Rtt107 and its interaction partner Slx4 are targets of the checkpoint kinase Mec1, which is central to the DDR-signaling cascades. Hrq1 recently was identified as a novel member of the RecQ helicase family in S. cerevisiae but is still poorly characterized. The conditional genetic networks that we generated revealed functional insights into all three genes and showed that there were varied responses to different DNA damaging agents. We observed that RTT107 had more genetic interactions under camptothecin conditions than SLX4 or HRQ1, suggesting that Rtt107 has an important role in response to this type of DNA lesion. Although RTT107 and SLX4 function together, they also had many distinct genetic interactions. In particular, RTT107 and SLX4 showed contrasting genetic interactions for a few genes, which we validated with independently constructed strains. Interestingly, HRQ1 had a genetic interaction profile that correlated with that of SLX4 and both were enriched for very similar gene ontology terms, suggesting that they function together in the DDR.
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