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Jehle S, Kunowska N, Benlasfer N, Woodsmith J, Weber G, Wahl MC, Stelzl U. A human kinase yeast array for the identification of kinases modulating phosphorylation-dependent protein-protein interactions. Mol Syst Biol 2022; 18:e10820. [PMID: 35225431 PMCID: PMC8883442 DOI: 10.15252/msb.202110820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 01/28/2022] [Accepted: 01/31/2022] [Indexed: 12/11/2022] Open
Abstract
Protein kinases play an important role in cellular signaling pathways and their dysregulation leads to multiple diseases, making kinases prime drug targets. While more than 500 human protein kinases are known to collectively mediate phosphorylation of over 290,000 S/T/Y sites, the activities have been characterized only for a minor, intensively studied subset. To systematically address this discrepancy, we developed a human kinase array in Saccharomyces cerevisiae as a simple readout tool to systematically assess kinase activities. For this array, we expressed 266 human kinases in four different S. cerevisiae strains and profiled ectopic growth as a proxy for kinase activity across 33 conditions. More than half of the kinases showed an activity-dependent phenotype across many conditions and in more than one strain. We then employed the kinase array to identify the kinase(s) that can modulate protein-protein interactions (PPIs). Two characterized, phosphorylation-dependent PPIs with unknown kinase-substrate relationships were analyzed in a phospho-yeast two-hybrid assay. CK2α1 and SGK2 kinases can abrogate the interaction between the spliceosomal proteins AAR2 and PRPF8, and NEK6 kinase was found to mediate the estrogen receptor (ERα) interaction with 14-3-3 proteins. The human kinase yeast array can thus be used for a variety of kinase activity-dependent readouts.
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Affiliation(s)
- Stefanie Jehle
- Otto-Warburg-Laboratory, Max-Planck-Institute for Molecular Genetics (MPIMG), Berlin, Germany
| | - Natalia Kunowska
- Institute of Pharmaceutical Sciences, University of Graz, Graz, Austria
| | - Nouhad Benlasfer
- Otto-Warburg-Laboratory, Max-Planck-Institute for Molecular Genetics (MPIMG), Berlin, Germany
| | - Jonathan Woodsmith
- Otto-Warburg-Laboratory, Max-Planck-Institute for Molecular Genetics (MPIMG), Berlin, Germany
- Institute of Pharmaceutical Sciences, University of Graz, Graz, Austria
| | - Gert Weber
- Institut für Chemie und Biochemie, Freie Universität, Berlin, Germany
- Helmholtz-Zentrum Berlin für Materialien und Energie, Macromolecular Crystallography, Berlin, Germany
| | - Markus C Wahl
- Institut für Chemie und Biochemie, Freie Universität, Berlin, Germany
| | - Ulrich Stelzl
- Otto-Warburg-Laboratory, Max-Planck-Institute for Molecular Genetics (MPIMG), Berlin, Germany
- Institute of Pharmaceutical Sciences, University of Graz, Graz, Austria
- Field of Excellence BioHealth, University of Graz and BioTechMed-Graz, Graz, Austria
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Rouhani M, Hadi-Alijanvand H. Effect of Lithium Drug on Binding Affinities of Glycogen Synthase Kinase-3 β to Its Network Partners: A New Computational Approach. J Chem Inf Model 2021; 61:5280-5292. [PMID: 34533953 DOI: 10.1021/acs.jcim.1c00952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Finding new methods to study the effect of small molecules on protein interaction networks provides us with invaluable tools in the fields of pharmacodynamics and drug design. Lithium is an antimanic drug that has been used for the treatment of bipolar disorder for more than 60 years. Here, we utilized a new approach to study the effect of lithium as a drug on the protein interaction network of GSK-3β as a hub protein and computed the affinities of GSK-3β to its partners in the presence of lithium or sodium ions. For this purpose, ensembles of GSK-3β protein structures were created in the presence of either lithium or sodium ions using adaptive tempering molecular dynamics simulations. The protein binding patches of GSK-3β for its partners were determined, and finally, the affinity of each binding patch to the related partner was computed for structures of ensembles using a monomer-based approach. Besides, by comparing structural dynamics of GSK-3β during MD simulations in the presence of LiCl and NaCl, we suggested a new mechanism for the inhibitory effect of lithium on GSK-3β.
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Affiliation(s)
- Maryam Rouhani
- Department of Biological Sciences, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
| | - Hamid Hadi-Alijanvand
- Department of Biological Sciences, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
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Gupta G, Ndiaye A, Filteau M. Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions. Front Microbiol 2021; 12:700752. [PMID: 34646243 PMCID: PMC8503676 DOI: 10.3389/fmicb.2021.700752] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 08/31/2021] [Indexed: 12/27/2022] Open
Abstract
Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.
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Affiliation(s)
- Gunjan Gupta
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
| | - Amadou Ndiaye
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
| | - Marie Filteau
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
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Routh S, Acharyya A, Dhar R. A two-step PCR assembly for construction of gene variants across large mutational distances. Biol Methods Protoc 2021; 6:bpab007. [PMID: 33928191 PMCID: PMC8062255 DOI: 10.1093/biomethods/bpab007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/09/2021] [Accepted: 04/01/2021] [Indexed: 11/14/2022] Open
Abstract
Construction of empirical fitness landscapes has transformed our understanding of genotype–phenotype relationships across genes. However, most empirical fitness landscapes have been constrained to the local genotype neighbourhood of a gene primarily due to our limited ability to systematically construct genotypes that differ by a large number of mutations. Although a few methods have been proposed in the literature, these techniques are complex owing to several steps of construction or contain a large number of amplification cycles that increase chances of non-specific mutations. A few other described methods require amplification of the whole vector, thereby increasing the chances of vector backbone mutations that can have unintended consequences for study of fitness landscapes. Thus, this has substantially constrained us from traversing large mutational distances in the genotype network, thereby limiting our understanding of the interactions between multiple mutations and the role these interactions play in evolution of novel phenotypes. In the current work, we present a simple but powerful approach that allows us to systematically and accurately construct gene variants at large mutational distances. Our approach relies on building-up small fragments containing targeted mutations in the first step followed by assembly of these fragments into the complete gene fragment by polymerase chain reaction (PCR). We demonstrate the utility of our approach by constructing variants that differ by up to 11 mutations in a model gene. Our work thus provides an accurate method for construction of multi-mutant variants of genes and therefore will transform the studies of empirical fitness landscapes by enabling exploration of genotypes that are far away from a starting genotype.
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Affiliation(s)
- Shreya Routh
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
| | - Anamika Acharyya
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
| | - Riddhiman Dhar
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
- Correspondence address. Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India. Tel. +91-3222-304562; E-mail:
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Leroux M, Boutchueng-Djidjou M, Faure R. Insulin's Discovery: New Insights on Its Hundredth Birthday: From Insulin Action and Clearance to Sweet Networks. Int J Mol Sci 2021; 22:ijms22031030. [PMID: 33494161 PMCID: PMC7864324 DOI: 10.3390/ijms22031030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 11/28/2022] Open
Abstract
In 2021, the 100th anniversary of the isolation of insulin and the rescue of a child with type 1 diabetes from death will be marked. In this review, we highlight advances since the ingenious work of the four discoverers, Frederick Grant Banting, John James Rickard Macleod, James Bertram Collip and Charles Herbert Best. Macleoad closed his Nobel Lecture speech by raising the question of the mechanism of insulin action in the body. This challenge attracted many investigators, and the question remained unanswered until the third part of the 20th century. We summarize what has been learned, from the discovery of cell surface receptors, insulin action, and clearance, to network and precision medicine.
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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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