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Methodological approaches for the analysis of transmembrane domain interactions: A systematic review. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2021; 1863:183712. [PMID: 34331948 DOI: 10.1016/j.bbamem.2021.183712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/28/2021] [Accepted: 07/21/2021] [Indexed: 11/20/2022]
Abstract
The study of protein-protein interactions (PPI) has proven fundamental for the understanding of the most relevant cell processes. Any protein domain can participate in PPI, including transmembrane (TM) segments that can establish interactions with other TM domains (TMDs). However, the hydrophobic nature of TMDs and the environment they occupy complicates the study of intramembrane PPI, which demands the use of specific approaches and techniques. In this review, we will explore some of the strategies available to study intramembrane PPI in vitro, in vivo, and, in silico, focusing on those techniques that could be carried out in a standard molecular biology laboratory regarding its previous experience with membrane proteins.
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Xiao Y, Zeng B, Berner N, Frishman D, Langosch D, George Teese M. Experimental determination and data-driven prediction of homotypic transmembrane domain interfaces. Comput Struct Biotechnol J 2020; 18:3230-3242. [PMID: 33209210 PMCID: PMC7649602 DOI: 10.1016/j.csbj.2020.09.035] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/22/2022] Open
Abstract
Homotypic TMD interfaces identified by different techniques share strong similarities. The GxxxG motif is the feature most strongly associated with interfaces. Other features include conservation, polarity, coevolution, and depth in the membrane The role of each of each feature strongly depends on the individual protein. Machine-learning helps predict interfaces from evolutionary sequence data
Interactions between their transmembrane domains (TMDs) frequently support the assembly of single-pass membrane proteins to non-covalent complexes. Yet, the TMD-TMD interactome remains largely uncharted. With a view to predicting homotypic TMD-TMD interfaces from primary structure, we performed a systematic analysis of their physical and evolutionary properties. To this end, we generated a dataset of 50 self-interacting TMDs. This dataset contains interfaces of nine TMDs from bitopic human proteins (Ire1, Armcx6, Tie1, ATP1B1, PTPRO, PTPRU, PTPRG, DDR1, and Siglec7) that were experimentally identified here and combined with literature data. We show that interfacial residues of these homotypic TMD-TMD interfaces tend to be more conserved, coevolved and polar than non-interfacial residues. Further, we suggest for the first time that interface positions are deficient in β-branched residues, and likely to be located deep in the hydrophobic core of the membrane. Overrepresentation of the GxxxG motif at interfaces is strong, but that of (small)xxx(small) motifs is weak. The multiplicity of these features and the individual character of TMD-TMD interfaces, as uncovered here, prompted us to train a machine learning algorithm. The resulting prediction method, THOIPA (www.thoipa.org), excels in the prediction of key interface residues from evolutionary sequence data.
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Affiliation(s)
- Yao Xiao
- Center for Integrated Protein Science Munich (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Bo Zeng
- Department of Bioinformatics, Wissenschaftszentrum, Weihenstephan, Maximus-von-Imhof-Forum 3, Freising 85354, Germany
| | - Nicola Berner
- Center for Integrated Protein Science Munich (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Dmitrij Frishman
- Department of Bioinformatics, Wissenschaftszentrum, Weihenstephan, Maximus-von-Imhof-Forum 3, Freising 85354, Germany.,Department of Bioinformatics, Peter the Great Saint Petersburg Polytechnic University, St. Petersburg 195251, Russian Federation
| | - Dieter Langosch
- Center for Integrated Protein Science Munich (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Mark George Teese
- Center for Integrated Protein Science Munich (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany.,TNG Technology Consulting GmbH, Beta-Straße 13a, 85774 Unterföhring, Germany
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Schanzenbach C, Schmidt FC, Breckner P, Teese MG, Langosch D. Identifying ionic interactions within a membrane using BLaTM, a genetic tool to measure homo- and heterotypic transmembrane helix-helix interactions. Sci Rep 2017; 7:43476. [PMID: 28266525 PMCID: PMC5339904 DOI: 10.1038/srep43476] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/23/2017] [Indexed: 12/15/2022] Open
Abstract
The assembly of integral membrane protein complexes is frequently supported by transmembrane domain (TMD) interactions. Here, we present the BLaTM assay that measures homotypic as well as heterotypic TMD-TMD interactions in a bacterial membrane. The system is based on complementation of β-lactamase fragments genetically fused to interacting TMDs, which confers ampicillin resistance to expressing cells. We validated BLaTM by showing that the assay faithfully reports known sequence-specific interactions of both types. In a practical application, we used BLaTM to screen a focussed combinatorial library for heterotypic interactions driven by electrostatic forces. The results reveal novel patterns of ionizable amino acids within the isolated TMD pairs. Those patterns indicate that formation of heterotypic TMD pairs is most efficiently supported by closely spaced ionizable residues of opposite charge. In addition, TMD heteromerization can apparently be driven by hydrogen bonding between basic or between acidic residues.
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Affiliation(s)
- Christoph Schanzenbach
- Munich Center For Integrated Protein Science (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Fabian C. Schmidt
- Munich Center For Integrated Protein Science (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Patrick Breckner
- Munich Center For Integrated Protein Science (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Mark G. Teese
- Munich Center For Integrated Protein Science (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
| | - Dieter Langosch
- Munich Center For Integrated Protein Science (CIPSM) at the Lehrstuhl für Chemie der Biopolymere, Technische Universität München, Weihenstephaner Berg 3, 85354 Freising, Germany
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Maurice P, Baud S, Bocharova OV, Bocharov EV, Kuznetsov AS, Kawecki C, Bocquet O, Romier B, Gorisse L, Ghirardi M, Duca L, Blaise S, Martiny L, Dauchez M, Efremov RG, Debelle L. New Insights into Molecular Organization of Human Neuraminidase-1: Transmembrane Topology and Dimerization Ability. Sci Rep 2016; 6:38363. [PMID: 27917893 PMCID: PMC5137157 DOI: 10.1038/srep38363] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 11/09/2016] [Indexed: 11/09/2022] Open
Abstract
Neuraminidase 1 (NEU1) is a lysosomal sialidase catalyzing the removal of terminal sialic acids from sialyloconjugates. A plasma membrane-bound NEU1 modulating a plethora of receptors by desialylation, has been consistently documented from the last ten years. Despite a growing interest of the scientific community to NEU1, its membrane organization is not understood and current structural and biochemical data cannot account for such membrane localization. By combining molecular biology and biochemical analyses with structural biophysics and computational approaches, we identified here two regions in human NEU1 - segments 139-159 (TM1) and 316-333 (TM2) - as potential transmembrane (TM) domains. In membrane mimicking environments, the corresponding peptides form stable α-helices and TM2 is suited for self-association. This was confirmed with full-size NEU1 by co-immunoprecipitations from membrane preparations and split-ubiquitin yeast two hybrids. The TM2 region was shown to be critical for dimerization since introduction of point mutations within TM2 leads to disruption of NEU1 dimerization and decrease of sialidase activity in membrane. In conclusion, these results bring new insights in the molecular organization of membrane-bound NEU1 and demonstrate, for the first time, the presence of two potential TM domains that may anchor NEU1 in the membrane, control its dimerization and sialidase activity.
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Affiliation(s)
- Pascal Maurice
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Stéphanie Baud
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France.,Plateau de Modélisation Moléculaire Multi-échelle, UFR Sciences Exactes et Naturelles, URCA, Reims, France
| | - Olga V Bocharova
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Eduard V Bocharov
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Andrey S Kuznetsov
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Charlotte Kawecki
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Olivier Bocquet
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Beatrice Romier
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Laetitia Gorisse
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Maxime Ghirardi
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Laurent Duca
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Sébastien Blaise
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Laurent Martiny
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
| | - Manuel Dauchez
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France.,Plateau de Modélisation Moléculaire Multi-échelle, UFR Sciences Exactes et Naturelles, URCA, Reims, France
| | - Roman G Efremov
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Higher School of Economics, Myasnitskaya ul. 20, 101000 Moscow, Russia
| | - Laurent Debelle
- Laboratoire Signalisation et Récepteurs Matriciels (SiRMa), UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Université de Reims Champagne Ardenne (URCA), UFR Sciences Exactes et Naturelles, Reims, France
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