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Postmortem proteomics to discover biomarkers for forensic PMI estimation.

ABSTRACT: The assessment of postmortem degradation of skeletal muscle proteins has emerged as a novel approach to estimate the time since death in the early to mid-postmortem phase (approximately 24 h postmortem (hpm) to 120 hpm). Current protein-based methods are limited to a small number of skeletal muscle proteins, shown to undergo proteolysis after death. In this study, we investigated the usability of a target-based and unbiased system-wide protein analysis to gain further insights into systemic postmortem protein alterations and to identify additional markers for postmortem interval (PMI) delimitation. We performed proteomic profiling to globally analyze postmortem alterations of the rat and mouse skeletal muscle proteome at defined time points (0, 24, 48, 72, and 96 hpm), harnessing a mass spectrometry-based quantitative proteomics approach. Hierarchical clustering analysis for a total of 579 (rat) and 896 (mouse) quantified proteins revealed differentially expressed proteins during the investigated postmortem period. We further focused on two selected proteins (eEF1A2 and GAPDH), which were shown to consistently degrade postmortem in both rat and mouse, suggesting conserved intra- and interspecies degradation behavior, and thus preserved association with the PMI and possible transferability to humans. In turn, we validated the usefulness of these new markers by classical Western blot experiments in a rat model and in human autopsy cases. Our results demonstrate the feasibility of mass spectrometry-based analysis to discover novel protein markers for PMI estimation and show that the proteins eEF1A2 and GAPDH appear to be valuable markers for PMI estimation in humans.

SUBMITTER: Choi KM

PROVIDER: S-EPMC6469664 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Postmortem proteomics to discover biomarkers for forensic PMI estimation.

Choi Kyoung-Min KM Zissler Angela A Kim Eunjung E Ehrenfellner Bianca B Cho Eunji E Lee Se-In SI Steinbacher Peter P Yun Ki Na KN Shin Jong Hwan JH Kim Jin Young JY Stoiber Walter W Chung Heesun H Monticelli Fabio Carlo FC Kim Jae-Young JY Pittner Stefan S

International journal of legal medicine 20190312 3

The assessment of postmortem degradation of skeletal muscle proteins has emerged as a novel approach to estimate the time since death in the early to mid-postmortem phase (approximately 24 h postmortem (hpm) to 120 hpm). Current protein-based methods are limited to a small number of skeletal muscle proteins, shown to undergo proteolysis after death. In this study, we investigated the usability of a target-based and unbiased system-wide protein analysis to gain further insights into systemic post ...[more]

PMID: 30864069

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Project description:The combined use of multiple omics allows to study complex interrelated biological processes in their entirety. We applied a combination of metabolomics, lipidomics and proteomics to human bones to investigate their combined potential to estimate time elapsed since death (i.e., the postmortem interval [PMI]). This 'ForensOMICS' approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors before their placement at the Forensic Anthropology Research Facility owned by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219-790-834-872days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic, and proteomic profiles from the pre- and post-placement bone samples. The three omics blocks were investigated independently by univariate and multivariate analyses, followed by Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers describing postmortem changes and discriminating the individuals based on their PMI. The resulting model showed that pre-placement metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement ones. Metabolites in the pre-placement samples suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules with an excellent potential for PMI estimation, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different postmortem stability, in the future we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by using proteins.

Dataset Information

Postmortem proteomics to discover biomarkers for forensic PMI estimation.

Publications

Postmortem proteomics to discover biomarkers for forensic PMI estimation.

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