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      Phosphorylation regulates tau’s phase separation behavior and interactions with chromatin

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          Abstract

          Tau is a microtubule-associated protein often found in neurofibrillary tangles (NFTs) in the brains of patients with Alzheimer’s disease. Beyond this context, mounting evidence suggests that tau localizes into the nucleus, where it may play a role in DNA protection and heterochromatin regulation. The molecular mechanisms behind these observations are currently unclear. Using in vitro biophysical experiments, here we demonstrate that tau can undergo liquid-liquid phase separation (LLPS) with DNA, mononucleosomes, and reconstituted nucleosome arrays under low salt conditions. Low concentrations of tau promote chromatin compaction and protect DNA from digestion. While the material state of samples at physiological salt is dominated by chromatin oligomerization, tau can still associate strongly and reversibly with nucleosome arrays. These properties are driven by tau’s strong interactions with linker and nucleosomal DNA. In addition, tau co-localizes into droplets formed by nucleosome arrays and phosphorylated HP1α, a key heterochromatin constituent thought to function through an LLPS mechanism. Importantly, LLPS and chromatin interactions are disrupted by aberrant tau hyperphosphorylation. These biophysical properties suggest that tau may directly impact DNA and chromatin accessibility and that loss of these interactions could contribute to the aberrant nuclear effects seen in tau pathology.

          Abstract

          An investigation of tau’s phase separation propensity and interactions with DNA, nucleosome arrays, and heterochromatin proteins shows that these properties are dependent on tau’s phosphorylation state.

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          Most cited references92

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          UCSF Chimera--a visualization system for exploratory research and analysis.

          The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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            The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

            MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http://www.maxquant.org.
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              NMRFAM-SPARKY: enhanced software for biomolecular NMR spectroscopy

              Summary: SPARKY (Goddard and Kneller, SPARKY 3) remains the most popular software program for NMR data analysis, despite the fact that development of the package by its originators ceased in 2001. We have taken over the development of this package and describe NMRFAM-SPARKY, which implements new functions reflecting advances in the biomolecular NMR field. NMRFAM-SPARKY has been repackaged with current versions of Python and Tcl/Tk, which support new tools for NMR peak simulation and graphical assignment determination. These tools, along with chemical shift predictions from the PACSY database, greatly accelerate protein side chain assignments. NMRFAM-SPARKY supports automated data format interconversion for interfacing with a variety of web servers including, PECAN , PINE, TALOS-N, CS-Rosetta, SHIFTX2 and PONDEROSA-C/S. Availability and implementation: The software package, along with binary and source codes, if desired, can be downloaded freely from http://pine.nmrfam.wisc.edu/download_packages.html. Instruction manuals and video tutorials can be found at http://www.nmrfam.wisc.edu/nmrfam-sparky-distribution.htm. Contact: whlee@nmrfam.wisc.edu or markley@nmrfam.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                gdebelouchina@ucsd.edu
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                1 March 2024
                1 March 2024
                2024
                : 7
                : 251
                Affiliations
                [1 ]Department of Chemistry and Biochemistry, University of California San Diego, ( https://ror.org/0168r3w48) La Jolla, CA 92093 USA
                [2 ]Department of Cellular and Molecular Medicine, University of California San Diego, ( https://ror.org/0168r3w48) La Jolla, CA 92093 USA
                [3 ]Department of Molecular Biology, University of California San Diego, ( https://ror.org/0168r3w48) La Jolla, CA 92093 USA
                Author information
                http://orcid.org/0000-0001-7570-0616
                http://orcid.org/0000-0003-2003-2889
                http://orcid.org/0000-0001-6775-9415
                Article
                5920
                10.1038/s42003-024-05920-4
                10907630
                38429335
                ebf43611-3b82-4409-9f25-75eb7ea7610d
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 December 2023
                : 16 February 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R21AG079239
                Award ID: T32GM139795
                Award ID: T32GM008326
                Award ID: R35GM144121
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Categories
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                © Springer Nature Limited 2024

                intrinsically disordered proteins,gene regulation

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