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      Lysine deserts prevent adventitious ubiquitylation of ubiquitin-proteasome components

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          Abstract

          In terms of its relative frequency, lysine is a common amino acid in the human proteome. However, by bioinformatics we find hundreds of proteins that contain long and evolutionarily conserved stretches completely devoid of lysine residues. These so-called lysine deserts show a high prevalence in intrinsically disordered proteins with known or predicted functions within the ubiquitin-proteasome system (UPS), including many E3 ubiquitin-protein ligases and UBL domain proteasome substrate shuttles, such as BAG6, RAD23A, UBQLN1 and UBQLN2. We show that introduction of lysine residues into the deserts leads to a striking increase in ubiquitylation of some of these proteins. In case of BAG6, we show that ubiquitylation is catalyzed by the E3 RNF126, while RAD23A is ubiquitylated by E6AP. Despite the elevated ubiquitylation, mutant RAD23A appears stable, but displays a partial loss of function phenotype in fission yeast. In case of UBQLN1 and BAG6, introducing lysine leads to a reduced abundance due to proteasomal degradation of the proteins. For UBQLN1 we show that arginine residues within the lysine depleted region are critical for its ability to form cytosolic speckles/inclusions. We propose that selective pressure to avoid lysine residues may be a common evolutionary mechanism to prevent unwarranted ubiquitylation and/or perhaps other lysine post-translational modifications. This may be particularly relevant for UPS components as they closely and frequently encounter the ubiquitylation machinery and are thus more susceptible to nonspecific ubiquitylation.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00018-023-04782-z.

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            A Mathematical Theory of Communication

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              MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

              Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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                Author and article information

                Contributors
                wb@di.ku.dk
                kay.hofmann@uni-koeln.de
                rhpetersen@bio.ku.dk
                Journal
                Cell Mol Life Sci
                Cell Mol Life Sci
                Cellular and Molecular Life Sciences
                Springer International Publishing (Cham )
                1420-682X
                1420-9071
                9 May 2023
                9 May 2023
                2023
                : 80
                : 6
                : 143
                Affiliations
                [1 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Department of Biology, The Linderstrøm-Lang Centre for Protein Science, , University of Copenhagen, ; Copenhagen, Denmark
                [2 ]GRID grid.6190.e, ISNI 0000 0000 8580 3777, Institute for Genetics, , University of Cologne, ; Cologne, Germany
                [3 ]GRID grid.8241.f, ISNI 0000 0004 0397 2876, Centre for Gene Regulation and Expression, Sir James Black Centre, School of Life Sciences, , University of Dundee, ; Dundee, UK
                [4 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Department of Computer Science, , University of Copenhagen, ; Copenhagen, Denmark
                Author information
                http://orcid.org/0000-0002-4155-7791
                Article
                4782
                10.1007/s00018-023-04782-z
                10169902
                37160462
                bedaab96-624d-472d-8b77-06559ad764a1
                © The Author(s) 2023

                Open AccessThis 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 2022
                : 15 March 2023
                : 17 April 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100008398, Villum Fonden;
                Award ID: 40526
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100009708, Novo Nordisk Fonden;
                Award ID: NNF18OC0033950
                Award ID: NNF18OC0033950
                Award ID: NNF18OC0033926
                Award ID: NNF18OC0052441
                Award ID: NNF20OC0062606
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100008394, Natur og Univers, Det Frie Forskningsråd;
                Award ID: 10.46540/2032-00007B
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK;
                Award ID: C434/A21747
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 217196/Z/19/Z
                Award Recipient :
                Funded by: Royal Library, Copenhagen University Library
                Categories
                Original Article
                Custom metadata
                © Springer Nature Switzerland AG 2023

                Molecular biology
                lysine,ubiquitin,proteasome,degradation,ptm,intrinsically disordered protein
                Molecular biology
                lysine, ubiquitin, proteasome, degradation, ptm, intrinsically disordered protein

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