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Structural model for the protein-translocating element of the twin-arginine transport system.

ABSTRACT: The twin-arginine translocase (Tat) carries out the remarkable process of translocating fully folded proteins across the cytoplasmic membrane of prokaryotes and the thylakoid membrane of plant chloroplasts. Tat is required for bacterial pathogenesis and for photosynthesis in plants. TatA, the protein-translocating element of the Tat system, is a small transmembrane protein that assembles into ring-like oligomers of variable size. We have determined a structural model of the Escherichia coli TatA complex in detergent solution by NMR. TatA assembly is mediated entirely by the transmembrane helix. The amphipathic helix extends outwards from the ring of transmembrane helices, permitting assembly of complexes with variable subunit numbers. Transmembrane residue Gln8 points inward, resulting in a short hydrophobic pore in the center of the complex. Simulations of the TatA complex in lipid bilayers indicate that the short transmembrane domain distorts the membrane. This finding suggests that TatA facilitates protein transport by sensitizing the membrane to transient rupture.

SUBMITTER: Rodriguez F

PROVIDER: S-EPMC3607022 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Structural model for the protein-translocating element of the twin-arginine transport system.

Rodriguez Fernanda F Rouse Sarah L SL Tait Claudia E CE Harmer Jeffrey J De Riso Antonio A Timmel Christiane R CR Sansom Mark S P MS Berks Ben C BC Schnell Jason R JR

Proceedings of the National Academy of Sciences of the United States of America 20130307 12

The twin-arginine translocase (Tat) carries out the remarkable process of translocating fully folded proteins across the cytoplasmic membrane of prokaryotes and the thylakoid membrane of plant chloroplasts. Tat is required for bacterial pathogenesis and for photosynthesis in plants. TatA, the protein-translocating element of the Tat system, is a small transmembrane protein that assembles into ring-like oligomers of variable size. We have determined a structural model of the Escherichia coli TatA ...[more]

PMID: 23471988

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Project description:BACKGROUND: Biological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan. METHODS: A Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP) technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma. RESULTS: The numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met. CONCLUSION: The developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient information for unique simultaneous estimation of diffusion coefficient and binding rate parameters. Care should be exercised in drawing inferences, from FRAP data, regarding concentrations of free and bound proteins, average binding and diffusion times, and protein mobility unless they are confirmed by long-range Markov Chain-Monte Carlo (MCMC) methods and experimental observations.

Dataset Information

Structural model for the protein-translocating element of the twin-arginine transport system.

Publications

Structural model for the protein-translocating element of the twin-arginine transport system.

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