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Lookup NU author(s): Dr Pawel PalmowskiORCiD, Dr Andrew Porter
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 The Authors. Published by American Chemical Society.The application of proteomic analysis to forensic skeletal remains has gained significant interest in improving biological and chronological estimations in medico-legal investigations. To enhance the applicability of these analyses to forensic casework, it is crucial to maximize throughput and proteome recovery while minimizing interoperator variability and laboratory-induced post-translational protein modifications (PTMs). This work compared different workflows for extracting, purifying, and analyzing bone proteins using liquid chromatography with tandem mass spectrometry (LC-MS)/MS including an in-StageTip protocol previously optimized for forensic applications and two protocols using novel suspension-trap technology (S-Trap) and different lysis solutions. This study also compared data-dependent acquisition (DDA) with data-independent acquisition (DIA). By testing all of the workflows on 30 human cortical tibiae samples, S-Trap workflows resulted in increased proteome recovery with both lysis solutions tested and in decreased levels of induced deamidations, and the DIA mode resulted in greater sensitivity and window of identification for the identification of lower-abundance proteins, especially when open-source software was utilized for data processing in both modes. The newly developed S-Trap protocol is, therefore, suitable for forensic bone proteomic workflows and, particularly when paired with DIA mode, can offer improved proteomic outcomes and increased reproducibility, showcasing its potential in forensic proteomics and contributing to achieving standardization in bone proteomic analyses for forensic applications.
Author(s): Gent L, Chiappetta ME, Hesketh S, Palmowski P, Porter A, Bonicelli A, Schwalbe EC, Procopio N
Publication type: Article
Publication status: Published
Journal: Journal of Proteome Research
Year: 2024
Pages: epub ahead of print
Online publication date: 15/04/2024
Acceptance date: 03/04/2024
Date deposited: 29/04/2024
ISSN (print): 1535-3893
ISSN (electronic): 1535-3907
Publisher: ACS
URL: https://doi.org/10.1021/acs.jproteome.4c00151
DOI: 10.1021/acs.jproteome.4c00151
Data Access Statement: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the MASSIVE55 partner repository with the data set identifier MSV000093803
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