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      TDP-43 α-helical structure tunes liquid–liquid phase separation and function

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          Significance

          TDP-43 is an essential RNA-binding protein that assembles into protein inclusions in >95% of cases of amyotrophic lateral sclerosis (ALS). A partially helical region in the predominantly disordered C-terminal domain harbors several mutations associated with ALS and is important for TDP-43 function and liquid–liquid phase separation. We directly demonstrate that this helical region undergoes large structural changes upon helix–helix dimerization and that point mutations can enhance helix–helix assembly. Furthermore, we demonstrate that these point variants can be used to control the material properties of phase-separated TDP-43 constructs in cells and can enhance TDP-43 RNA-splicing function. Therefore, engineered forms of the TDP-43 helical domain could be used to control in-cell phase separation, dynamic assembly, and function.

          Abstract

          Liquid–liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. The RNA-binding protein TDP-43 is present in several MLOs, undergoes LLPS, and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some ALS-associated mutations in TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes upon dimerization of TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix–helix interaction, which are removed in part by variants at these positions, including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase-separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a minigene assay. Therefore, the TDP-43 helical region serves as a short but uniquely tunable module where application of biophysical principles can precisely control assembly and function in cellular and synthetic biology applications of LLPS.

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          Most cited references83

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          NMRPipe: a multidimensional spectral processing system based on UNIX pipes.

          The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.
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            GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.

            Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.
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              Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.

                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                17 March 2020
                4 March 2020
                4 March 2020
                : 117
                : 11
                : 5883-5894
                Affiliations
                [1] aDepartment of Molecular Pharmacology, Physiology, and Biotechnology, Brown University , Providence, RI 02912;
                [2] bGraduate Program in Molecular Biology, Cell Biology, and Biochemistry, Brown University , Providence, RI 02912;
                [3] cDepartment of Chemistry, University of Toronto , Toronto, ON M5S 1A8, Canada;
                [4] dDepartment of Chemical and Biomolecular Engineering, Lehigh University , Bethlehem, PA 18015;
                [5] eLaufer Center for Physical and Quantitative Biology, Stony Brook University , Stony Brook, NY 11794;
                [6] fDepartment of Chemical and Biological Engineering, Princeton University , Princeton, NJ 08540;
                [7] gDepartment of Biochemistry, Stanford University School of Medicine , Stanford, CA 94305;
                [8] hCenter for Materials Physics and Technology, Naval Research Laboratory , Washington, DC 20375;
                [9] iDepartment of Medicine, Stanford University School of Medicine , Stanford, CA 94305;
                [10] jEdward Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine , St. Louis, MO 63103
                Author notes
                2To whom correspondence may be addressed. Email: jeetain@ 123456lehigh.edu or nicolas_fawzi@ 123456brown.edu .

                Edited by Arup K. Chakraborty, Massachusetts Institute of Technology, Cambridge, MA, and approved February 3, 2020 (received for review July 12, 2019)

                Author contributions: J.M. and N.L.F. conceived of research; A.E.C., G.L.D., G.H.Z., H.B.S., A.M.D., Y.M.A., and N.L.F. performed research; Y.C.K. contributed new reagents/analytic tools; A.E.C., G.L.D., G.H.Z., H.B.S., R.R., Y.M.A., J.M., and N.L.F. analyzed data; A.E.C., G.L.D., J.M., and N.L.F. wrote the paper; and H.B.S., R.R., Y.M.A., J.M., and N.L.F. supervised research.

                1A.E.C. and G.L.D. contributed equally to this work.

                Author information
                http://orcid.org/0000-0001-7609-8858
                http://orcid.org/0000-0001-5483-0577
                Article
                201912055
                10.1073/pnas.1912055117
                7084079
                32132204
                6b707b27-2285-4248-a504-e52c9f0d66f8
                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 12
                Funding
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS) 100000057
                Award ID: R01GM118530
                Award Recipient : Alexander E Conicella Award Recipient : Alexandra M D'Ordine Award Recipient : Rajat Rohatgi Award Recipient : Nicolas L. Fawzi
                Funded by: National Science Foundation (NSF) 100000001
                Award ID: MCB1845734
                Award Recipient : Nicolas L. Fawzi
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS) 100000057
                Award ID: T32GM007601
                Award Recipient : Alexander E Conicella Award Recipient : Alexandra M D'Ordine Award Recipient : Rajat Rohatgi Award Recipient : Nicolas L. Fawzi
                Funded by: U.S. Department of Energy (DOE) 100000015
                Award ID: DESC0013979
                Award Recipient : Jeetain Mittal
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS) 100000057
                Award ID: DP2GM105448
                Award Recipient : Alexander E Conicella Award Recipient : Alexandra M D'Ordine Award Recipient : Rajat Rohatgi Award Recipient : Nicolas L. Fawzi
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS) 100000057
                Award ID: R35GM118082
                Award Recipient : Alexander E Conicella Award Recipient : Alexandra M D'Ordine Award Recipient : Rajat Rohatgi Award Recipient : Nicolas L. Fawzi
                Funded by: Deutsche Forschungsgemeinschaft (DFG) 501100001659
                Award ID: SCHM 3082/2-1
                Award Recipient : Hermann Broder Schmidt
                Categories
                Biological Sciences
                Biophysics and Computational Biology

                liquid–liquid phase separation,nmr spectroscopy,protein interactions,molecular simulation

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