Dataset Information

Insights on the Differential Preservation of Bone Proteomes in Inhumated and Entombed Cadavers from Italian Forensic Caseworks

ABSTRACT: Bone is a long-lasting biological tissue often used in forensic investigations as it retains vital biomolecular information commonly used for identification purposes. Bone proteins have attracted interest for their potential in estimating post-mortem interval (PMI) and age-at-death (AAD). However, the preservation of such proteins is highly dependent on intrinsic and extrinsic factors, and these have an impact in the potential application of molecular techniques to forensic sciences. The present study aims at investigating the effect that two commonly used types of burial practices (entombment and inhumation) have on bone protein survival. The sample consists in 14 exhumed individuals from cemeteries in south of Italy at with different AADs (29-85 yeas) and PMIs (1-37 years). LC-MS/MS analyses show that 16 proteins are better preserved in the entombed condition and four in the inhumated one, while no clear cluster separation is detected with principal component analysis. Besides the different burial environments, several potential protein markers are identified for PMI and AAD estimation. Overall, preliminary results show that the two burial environments seem to play a marginal role in the differential preservation of non-collagenous proteins and in the accumulation of post-translational modifications, confirming the potential of LC-MS/MS based proteomics in forensic sciences.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Long Bone

SUBMITTER: Noemi Procopio

LAB HEAD: Noemi Procopio

PROVIDER: PXD029911 | Pride | 2022-03-25

REPOSITORIES: Pride

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Insights into the Differential Preservation of Bone Proteomes in Inhumed and Entombed Cadavers from Italian Forensic Caseworks.

Bonicelli Andrea A Bonicelli Andrea A Di Nunzio Aldo A Di Nunzio Ciro C Procopio Noemi N

Journal of proteome research 20220322 5

Bone is a hard biological tissue and a precious reservoir of information in forensic investigations as it retains key biomolecules commonly used for identification purposes. Bone proteins have recently attracted significant interest for their potential in estimating post-mortem interval (PMI) and age at death (AAD). However, the preservation of such proteins is highly dependent on intrinsic and extrinsic factors that can hinder the potential application of molecular techniques to forensic scienc ...[more]

PMID: 35316604

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Project description:The combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem 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 in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with 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 from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins.

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