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Ramakrishnan R, Houben B, Rousseau F, Schymkowitz J. Differential proteostatic regulation of insoluble and abundant proteins. Bioinformatics 2020; 35:4098-4107. [PMID: 30903148 PMCID: PMC6792106 DOI: 10.1093/bioinformatics/btz214] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 03/13/2019] [Accepted: 03/20/2019] [Indexed: 12/19/2022] Open
Abstract
Motivation Despite intense effort, it has been difficult to explain chaperone dependencies of proteins from sequence or structural properties. Results We constructed a database collecting all publicly available data of experimental chaperone interaction and dependency data for the Escherichia coli proteome, and enriched it with an extensive set of protein-specific as well as cell-context-dependent proteostatic parameters. Employing this new resource, we performed a comprehensive meta-analysis of the key determinants of chaperone interaction. Our study confirms that GroEL client proteins are biased toward insoluble proteins of low abundance, but for client proteins of the Trigger Factor/DnaK axis, we instead find that cellular parameters such as high protein abundance, translational efficiency and mRNA turnover are key determinants. We experimentally confirmed the finding that chaperone dependence is a function of translation rate and not protein-intrinsic parameters by tuning chaperone dependence of Green Fluorescent Protein (GFP) in E.coli by synonymous mutations only. The juxtaposition of both protein-intrinsic and cell-contextual chaperone triage mechanisms explains how the E.coli proteome achieves combining reliable production of abundant and conserved proteins, while also enabling the evolution of diverging metabolic functions. Availability and implementation The database will be made available via http://phdb.switchlab.org. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Reshmi Ramakrishnan
- Switch Laboratory, Center for Brain and Disease Research, VIB.,Department of Cellular and Molecular Medicine, KULeuven, Leuven Belgium
| | - Bert Houben
- Switch Laboratory, Center for Brain and Disease Research, VIB.,Department of Cellular and Molecular Medicine, KULeuven, Leuven Belgium
| | - Frederic Rousseau
- Switch Laboratory, Center for Brain and Disease Research, VIB.,Department of Cellular and Molecular Medicine, KULeuven, Leuven Belgium
| | - Joost Schymkowitz
- Switch Laboratory, Center for Brain and Disease Research, VIB.,Department of Cellular and Molecular Medicine, KULeuven, Leuven Belgium
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De Geyter J, Portaliou AG, Srinivasu B, Krishnamurthy S, Economou A, Karamanou S. Trigger factor is a bona fide secretory pathway chaperone that interacts with SecB and the translocase. EMBO Rep 2020; 21:e49054. [PMID: 32307852 DOI: 10.15252/embr.201949054] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 03/09/2020] [Accepted: 03/19/2020] [Indexed: 11/09/2022] Open
Abstract
Bacterial secretory preproteins are translocated across the inner membrane post-translationally by the SecYEG-SecA translocase. Mature domain features and signal peptides maintain preproteins in kinetically trapped, largely soluble, folding intermediates. Some aggregation-prone preproteins require chaperones, like trigger factor (TF) and SecB, for solubility and/or targeting. TF antagonizes the contribution of SecB to secretion by an unknown molecular mechanism. We reconstituted this interaction in vitro and studied targeting and secretion of the model preprotein pro-OmpA. TF and SecB display distinct, unsuspected roles in secretion. Tightly associating TF:pro-OmpA targets the translocase at SecA, but TF prevents pro-OmpA secretion. In solution, SecB binds TF:pro-OmpA with high affinity. At the membrane, when bound to the SecA C-tail, SecB increases TF and TF:pro-OmpA affinities for the translocase and allows pro-OmpA to resume translocation. Our data reveal that TF, a main cytoplasmic folding pathway chaperone, is also a bona fide post-translational secretory chaperone that directly interacts with both SecB and the translocase to mediate regulated protein secretion. Thus, TF links the cytoplasmic folding and secretion chaperone networks.
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Affiliation(s)
- Jozefien De Geyter
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
| | - Athina G Portaliou
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
| | - Bindu Srinivasu
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
| | - Srinath Krishnamurthy
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
| | - Anastassios Economou
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
| | - Spyridoula Karamanou
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, Leuven, Belgium
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Ramakrishnan R, Houben B, Kreft Ł, Botzki A, Schymkowitz J, Rousseau F. Protein Homeostasis Database: protein quality control in E.coli. Bioinformatics 2019; 36:948-949. [PMID: 31392322 PMCID: PMC9883681 DOI: 10.1093/bioinformatics/btz628] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 07/09/2019] [Accepted: 08/06/2019] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION In vivo protein folding is governed by molecular chaperones, that escort proteins from their translational birth to their proteolytic degradation. In E.coli the main classes of chaperones that interact with the nascent chain are trigger factor, DnaK/J and GroEL/ES and several authors have performed whole-genome experiments to construct exhaustive client lists for each of these. RESULTS We constructed a database collecting all publicly available data of experimental chaperone-interaction and -dependency data for the E.coli proteome, and enriched it with an extensive set of protein-specific as well as cell context-dependent proteostatic parameters. We made this publicly accessible via a web interface that allows to search for proteins or chaperone client lists, but also to profile user-specified datasets against all the collected parameters. We hope this will accelerate research in this field by quickly identifying differentiating features in datasets. AVAILABILITY AND IMPLEMENTATION The Protein Homeostasis Database is freely available without any registration requirement at http://PHDB.switchlab.org/.
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Affiliation(s)
| | | | - Łukasz Kreft
- VIB Bioinformatics Core, VIB, Gent 9052, Belgium
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Fan D, Cao S, Zhou Q, Zhang Y, Yue L, Han C, Yang B, Wang Y, Ma Z, Zhu L, Liu C. Exploring the roles of substrate-binding surface of the chaperone site in the chaperone activity of trigger factor. FASEB J 2018; 32:fj201701576. [PMID: 29906241 DOI: 10.1096/fj.201701576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Trigger factor (TF) is a key component of the prokaryotic chaperone network, which is involved in many basic cellular processes, such as protein folding, protein trafficking, and ribosome assembly. The major chaperone site of TF has a cradle-like structure in which protein substrate may fold without interference from other proteins. Here, we investigated in vivo and in vitro the roles of hydrophobic and charged patches on the edge and interior of cradle during TF-assisted protein folding. Our results showed that most of the surface of the cradle was involved in TF-assisted protein folding, which was larger than found in early studies. Although the inner surface of cradle was mostly hydrophobic, both hydrophobic and electrostatic patches were indispensable for TF to facilitate correct protein folding. However, hydrophobic patches were more important for the antiaggregation activity of TF. Furthermore, it was found that the patches on the surface of cradle were involved in TF-assisted protein folding in a spatial and temporal order. These results suggest that the folding-favorable interface between the cradle and substrate was dynamic during TF-assisted protein folding, which enabled TF to be involved in the folding of substrate in an aggressive manner rather than acting as a classic holdase.-Fan, D., Cao, S., Zhou, Q., Zhang, Y., Yue, L., Han, C., Yang, B., Wang, Y., Ma, Z., Zhu, L., Liu, C. Exploring the roles of substrate-binding surface of chaperone site in the chaperone activity of trigger factor.
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Affiliation(s)
- Dongjie Fan
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shunan Cao
- Key Laboratory for Polar Science, State Ocean Administration, Polar Research Institute of China, Shanghai, China
| | - Qiming Zhou
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
- ChosenMed Technology Company Limited, Jinghai Industrial Park, Economic and Technological Development Area, Beijing, China
| | - You Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Lei Yue
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Chang Han
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Bo Yang
- School of Life Sciences, Nantong University, Nantong, Jiangsu, China
| | - Yu Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Zhuo Ma
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Lingxiang Zhu
- National Research Institute for Family Planning (NRIFP), Beijing, China
| | - Chuanpeng Liu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
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