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      Zinc finger protein ZNF384 is an adaptor of Ku to DNA during classical non-homologous end-joining

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          Abstract

          DNA double-strand breaks (DSBs) are among the most deleterious types of DNA damage as they can lead to mutations and chromosomal rearrangements, which underlie cancer development. Classical non-homologous end-joining (cNHEJ) is the dominant pathway for DSB repair in human cells, involving the DNA-binding proteins XRCC6 (Ku70) and XRCC5 (Ku80). Other DNA-binding proteins such as Zinc Finger (ZnF) domain-containing proteins have also been implicated in DNA repair, but their role in cNHEJ remained elusive. Here we show that ZNF384, a member of the C2H2 family of ZnF proteins, binds DNA ends in vitro and is recruited to DSBs in vivo. ZNF384 recruitment requires the poly(ADP-ribosyl) polymerase 1 (PARP1)-dependent expansion of damaged chromatin, followed by binding of its C2H2 motifs to the exposed DNA. Moreover, ZNF384 interacts with Ku70/Ku80 via its N-terminus, thereby promoting Ku70/Ku80 assembly and the accrual of downstream cNHEJ factors, including APLF and XRCC4/LIG4, for efficient repair at DSBs. Altogether, our data suggest that ZNF384 acts as a ‘Ku-adaptor’ that binds damaged DNA and Ku70/Ku80 to facilitate the build-up of a cNHEJ repairosome, highlighting a role for ZNF384 in DSB repair and genome maintenance.

          Abstract

          Classical non-homologous end-joining (cNHEJ) is the dominant pathway used by human cells to repair DNA double-strand breaks (DSBs) and maintain genome stability. Here the authors show that PARP1-driven chromatin expansion allows the recruitment of ZNF384, which in turn recruits Ku70/Ku80 to facilitate cNHEJ.

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          The PRIDE database and related tools and resources in 2019: improving support for quantification data

          Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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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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              The DNA-damage response in human biology and disease.

              The prime objective for every life form is to deliver its genetic material, intact and unchanged, to the next generation. This must be achieved despite constant assaults by endogenous and environmental agents on the DNA. To counter this threat, life has evolved several systems to detect DNA damage, signal its presence and mediate its repair. Such responses, which have an impact on a wide range of cellular events, are biologically significant because they prevent diverse human diseases. Our improving understanding of DNA-damage responses is providing new avenues for disease management.
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                Author and article information

                Contributors
                h.van.attikum@lumc.nl
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                12 November 2021
                12 November 2021
                2021
                : 12
                : 6560
                Affiliations
                [1 ]GRID grid.10419.3d, ISNI 0000000089452978, Department of Human Genetics, , Leiden University Medical Center, ; Leiden, The Netherlands
                [2 ]GRID grid.410368.8, ISNI 0000 0001 2191 9284, Univ Rennes, CNRS, IGDR (Institut de génétique et développement de Rennes)—UMR 6290, ; BIOSIT–UMS3480, F-35000 Rennes, France
                [3 ]GRID grid.457349.8, ISNI 0000 0004 0623 0579, Institut de Biologie François Jacob, Institute of Cellular and Molecular Radiobiology, , Université Paris-Saclay, Université de Paris, CEA, ; F-92265 Fontenay-aux-Roses, France
                [4 ]GRID grid.10419.3d, ISNI 0000000089452978, Department of Cell and Chemical Biology, , Leiden University Medical Center, ; Leiden, The Netherlands
                [5 ]GRID grid.16872.3a, ISNI 0000 0004 0435 165X, Department of Medical Biology, , Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, ; Amsterdam, The Netherlands
                [6 ]GRID grid.440891.0, ISNI 0000 0001 1931 4817, Institut Universitaire de France, ; F-75000 Paris, France
                Author information
                http://orcid.org/0000-0002-1658-5635
                http://orcid.org/0000-0002-4215-8469
                http://orcid.org/0000-0003-1834-8673
                http://orcid.org/0000-0001-8997-2321
                http://orcid.org/0000-0002-3978-0003
                http://orcid.org/0000-0001-8590-0240
                Article
                26691
                10.1038/s41467-021-26691-0
                8589989
                34772923
                91cf59c9-efc4-457a-a17b-efc096250f61
                © The Author(s) 2021

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 July 2020
                : 19 October 2021
                Funding
                Funded by: Fondation ARC pour la recherche sur le cancer (PDF20181208405)
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: ERC-StG 310913
                Award ID: ERC-CoG 50364
                Award Recipient :
                Funded by: Ligue contre le Cancer du Grand-Ouest (committees 22 and 35), the Fondation ARC pour la recherche sur le cancer (20161204883), the Agence Nationale de la Recherche (PRC-2018 REPAIRCHROM) and the Institut Universitaire de France (all grants to S.H.).
                Categories
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                Custom metadata
                © The Author(s) 2021

                Uncategorized
                dna-binding proteins,non-homologous-end joining
                Uncategorized
                dna-binding proteins, non-homologous-end joining

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