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      Comparing extraction method efficiency for high-throughput palaeoproteomic bone species identification

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          Abstract

          High-throughput proteomic analysis of archaeological skeletal remains provides information about past fauna community compositions and species dispersals in time and space. Archaeological skeletal remains are a finite resource, however, and therefore it becomes relevant to optimize methods of skeletal proteome extraction. Ancient proteins in bone specimens can be highly degraded and consequently, extraction methods for well-preserved or modern bone might be unsuitable for the processing of highly degraded skeletal proteomes. In this study, we compared six proteomic extraction methods on Late Pleistocene remains with variable levels of proteome preservation. We tested the accuracy of species identification, protein sequence coverage, deamidation, and the number of post-translational modifications per method. We find striking differences in obtained proteome complexity and sequence coverage, highlighting that simple acid-insoluble proteome extraction methods perform better in highly degraded contexts. For well-preserved specimens, the approach using EDTA demineralization and protease-mix proteolysis yielded a higher number of identified peptides. The protocols presented here allowed protein extraction from ancient bone with a minimum number of working steps and equipment and yielded protein extracts within three working days. We expect further development along this route to benefit large-scale screening applications of relevance to archaeological and human evolution research.

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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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              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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                Author and article information

                Contributors
                dorothea.mylopotamitaki@palaeoproteomics.org
                frido.welker@sund.ku.dk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                26 October 2023
                26 October 2023
                2023
                : 13
                : 18345
                Affiliations
                [1 ]Chaire de Paléoanthropologie, CIRB (UMR 7241–U1050), Collège de France, ( https://ror.org/04ex24z53) Paris, France
                [2 ]Max Planck Institute for Evolutionary Anthropology, ( https://ror.org/02a33b393) Leipzig, Germany
                [3 ]Center for Protein Research, University of Copenhagen, ( https://ror.org/035b05819) Copenhagen, Denmark
                [4 ]Globe Institute, University of Copenhagen, ( https://ror.org/035b05819) Copenhagen, Denmark
                [5 ]Interdisciplinary Center for Archaeology and Evolution of Human Behaviour, University of Algarve, ( https://ror.org/014g34x36) Faro, Portugal
                [6 ]School of Anthropology and Conservation, University of Kent, ( https://ror.org/00xkeyj56) Kent, UK
                [7 ]GRID grid.5330.5, ISNI 0000 0001 2107 3311, Institut für Ur- und Frühgeschichte, , Friedrich-Alexander-Universität, ; Erlangen, Germany
                [8 ]Thuringian State Office for the Preservation of Historical Monuments and Archaeology, Weimar, Germany
                [9 ]Department of Human Origins, Max Planck Institute for Evolutionary Anthropology, ( https://ror.org/02a33b393) Leipzig, Germany
                [10 ]State Office for Heritage Management and Archaeology, Saxony-Anhalt—State Museum of Prehistory, Halle (Saale), Germany
                Article
                44885
                10.1038/s41598-023-44885-y
                10603084
                37884544
                69e1ef05-5267-4a5a-be84-ad4a699e7d2b
                © The Author(s) 2023

                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
                : 22 May 2023
                : 13 October 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100018694, HORIZON EUROPE Marie Sklodowska-Curie Actions;
                Award ID: 861389
                Funded by: FundRef http://dx.doi.org/10.13039/501100004189, Max-Planck-Gesellschaft;
                Funded by: Danish National Research Foundation
                Award ID: PROTEIOS (DNRF128)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100019180, HORIZON EUROPE European Research Council;
                Award ID: 948365
                Funded by: FundRef http://dx.doi.org/10.13039/501100001871, Fundação para a Ciência e a Tecnologia;
                Award ID: 2020.00499.CEECIND
                Award ID: FCT R&D 2022.07737.PTDC
                Award ID: DL57/2016/CP1361/CT0026
                Award Recipient :
                Funded by: Portuguese Ministry for Science and Technology
                Award ID: ALG-01-0145-FEDER-27833
                Award Recipient :
                Categories
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                © Springer Nature Limited 2023

                Uncategorized
                proteomics,archaeology
                Uncategorized
                proteomics, archaeology

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