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      Proteomics as a new tool to study fingermark ageing in forensics

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          Abstract

          Fingermarks are trace evidence of great forensic importance, and their omnipresence makes them pivotal in crime investigation. Police and law enforcement authorities have exploited fingermarks primarily for personal identification, but crucial knowledge on when fingermarks were deposited is often lacking, thereby hindering crime reconstruction. Biomolecular constituents of fingermark residue, such as amino acids, lipids and proteins, may provide excellent means for fingermark age determination, however robust methodologies or detailed knowledge on molecular mechanisms in time are currently not available. Here, we address fingermark age assessment by: (i) drafting a first protein map of fingermark residue, (ii) differential studies of fresh and aged fingermarks and (iii), to mimic real-world scenarios, estimating the effects of donor contact with bodily fluids on the identification of potential age biomarkers. Using a high-resolution mass spectrometry-based proteomics approach, we drafted a characteristic fingermark proteome, of which five proteins were identified as promising candidates for fingermark age estimation. This study additionally demonstrates successful identification of both endogenous and contaminant proteins from donors that have been in contact with various bodily fluids. In summary, we introduce state-of-the-art proteomics as a sensitive tool to monitor fingermark aging on the protein level with sufficient selectivity to differentiate potential age markers from body fluid contaminants.

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          Antimicrobial psoriasin (S100A7) protects human skin from Escherichia coli infection.

          Human healthy skin is continuously exposed to bacteria, but is particularly resistant to the common gut bacterium Escherichia coli. We show here that keratinocytes secrete, as the main E. coli-killing compound, the S100 protein psoriasin in vitro and in vivo in a site-dependent way. In vivo treatment of human skin with antibodies to psoriasin inhibited its E. coli-killing properties. Psoriasin was induced in keratinocytes in vitro and in vivo by E. coli, indicating that its focal expression in skin may derive from local microbial induction. Zn(2+)-saturated psoriasin showed diminished antimicrobial activity, suggesting that Zn(2+) sequestration could be a possible antimicrobial mechanism. Thus, psoriasin may be key to the resistance of skin against E. coli.
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            A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.

            This manuscript provides a comprehensive review of the peptide and protein identification process using tandem mass spectrometry (MS/MS) data generated in shotgun proteomic experiments. The commonly used methods for assigning peptide sequences to MS/MS spectra are critically discussed and compared, from basic strategies to advanced multi-stage approaches. A particular attention is paid to the problem of false-positive identifications. Existing statistical approaches for assessing the significance of peptide to spectrum matches are surveyed, ranging from single-spectrum approaches such as expectation values to global error rate estimation procedures such as false discovery rates and posterior probabilities. The importance of using auxiliary discriminant information (mass accuracy, peptide separation coordinates, digestion properties, and etc.) is discussed, and advanced computational approaches for joint modeling of multiple sources of information are presented. This review also includes a detailed analysis of the issues affecting the interpretation of data at the protein level, including the amplification of error rates when going from peptide to protein level, and the ambiguities in inferring the identifies of sample proteins in the presence of shared peptides. Commonly used methods for computing protein-level confidence scores are discussed in detail. The review concludes with a discussion of several outstanding computational issues. Copyright © 2010 Elsevier B.V. All rights reserved.
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              SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches.

              The identification of proteins by mass spectrometry is a standard technique in the field of proteomics, relying on search engines to perform the identifications of the acquired spectra. Here, we present a user-friendly, lightweight and open-source graphical user interface called SearchGUI (http://searchgui.googlecode.com), for configuring and running the freely available OMSSA (open mass spectrometry search algorithm) and X!Tandem search engines simultaneously. Freely available under the permissible Apache2 license, SearchGUI is supported on Windows, Linux and OSX. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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                Author and article information

                Contributors
                stijnoonk@yahoo.com
                m.de.puit@nfi.minvenj.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 November 2018
                6 November 2018
                2018
                : 8
                : 16425
                Affiliations
                [1 ]Netherlands Forensic Institute, Digital Technology and Biometrics, Laan van Ypenburg 6, 2497 GB Den Haag, Netherlands
                [2 ]ISNI 0000 0001 2097 4740, GRID grid.5292.c, Delft University of Technology, Faculty of Applied Sciences, Department of Chemical Engineering, ; Van der Maasweg 9, 2629 HZ Delft, The Netherlands
                [3 ]ISNI 0000 0001 2097 4740, GRID grid.5292.c, Delft University of Technology, Faculty of Applied Sciences, Department of Biotechnology, ; Van der Maasweg 9, 2629 HZ Delft, The Netherlands
                [4 ]ISNI 0000 0001 0791 5666, GRID grid.4818.5, Wageningen University & Research, Laboratory of Organic Chemistry, ; Stippeneng 4, 6708 WE Wageningen, The Netherlands
                Article
                34791
                10.1038/s41598-018-34791-z
                6219553
                61aad3f6-6a41-4b0d-9b24-e8a5c80286b2
                © The Author(s) 2018

                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
                : 21 May 2018
                : 26 October 2018
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