Forens-omics
How a multi-omics approach can reveal the mysteries of the postmortem interval
Noemi Procopio | | 5 min read | Future
When a body is discovered, scientists play a crucial role in helping investigators piece together the story. They work to uncover the identity of the victim, determine the cause of death, and, most importantly, estimate the time since death. This estimation, known as the postmortem interval (PMI), can be crucial when solving a case.
Traditional methods for estimating PMI – such as analyzing body temperature or insect activity – have limitations, especially as time passes. These methods can be subjective, often lack reproducibility, and become unusable when only skeletal remains are left.
That's where the “Forens-OMICS” approach comes into play. This emerging field, led by my team at the University of Central Lancashire, uses advanced molecular techniques to study the changes that occur in a body after death.
The Forens-OMICS team employs proteomics, metabolomics, and metabarcoding (analyzing microbial populations) to identify and measure various biological molecules in human remains. By examining how proteins, metabolites, and microbes change over time, the team is working toward more accurate PMI estimates.
In the bones
This work began with proteomics analysis on animal bones left to decompose in different environments (1). The goal was to identify proteins whose abundance decreased with increasing PMI and proteins with chemical modifications (post-translational modifications) that grew over time. The same method was later applied to human bones from taphonomy facilities in Texas and cemeteries in Italy, where similar patterns emerged, confirming that bone proteomics is a reliable tool for estimating PMI, especially for intervals greater than six months (2,3).
Proteomics analyses first require the extraction of proteins from the bone mineral matrix (4). This is done by reducing in powder a small subsample of bone (approximately 25 mg) in liquid nitrogen, and adding a series of reagents such as weak acids, denaturants and enzymes (trypsin) to obtain peptides – ready to be analyzed via high-accuracy liquid chromatograph–tandem mass spectrometry (LC-MS/MS) instruments. The mass spectrometry analysis returns a list of identified proteins in addition to their relative abundance in the sample. It also identifies the presence of post-translational chemical modifications. This information is used to identify protein markers correlating with PMI.
Similarly, metabolites and lipids found in bones can offer valuable information about PMI (5). As decomposition progresses, internal metabolites, microbial metabolites, and decaying lipids create a unique signature over time. Proteins and lipids, due to their larger, more stable structures, are better suited for estimating longer PMIs, while smaller, more dynamic metabolites provide precise estimates for shorter intervals, typically up to six months. Metabolites and lipids are extracted from bone powder samples in a way similar to the extraction of proteins, but using a combination of aqueous and organic solvents, and are subsequently analyzed in LC-MS/MS instruments similarly to proteomics experiments.
The team is currently combining proteomics, metabolomics, and lipidomics analyses on skeletal remains from individuals who died up to six years ago. These samples, exposed to environmental elements during decomposition, come from two human taphonomy facilities in Texas: the Southeast Texas Applied Forensic Science Facility (STAFS) and the Forensic Anthropology Center at Texas State (FACTS). Preliminary results show an estimation error of 230 days (6). Although this margin may seem wide, it represents a major advancement, given that PMI estimation from bones is often labeled “N/D” – not determined. The team is actively refining this approach by focusing on specific biomarkers, aiming to improve accuracy.
Tissue dating
Microbial successions in soft tissues after death can also help estimate PMI with precision. The team also uses metabarcoding to analyze the 16S rRNA bacterial gene, which identifies bacterial species by tracking how microbial communities change over time. By applying this technique to soft tissues and swab samples from both animals and humans, the team has achieved highly accurate PMI estimates, with an average error of nine days for samples up to six and a half months old in extreme cold environments (7) and just eight hours for samples with a 10-day decomposition period in a temperate climate (8).
Similarly, metabolomics conducted by the same team and applied to soft tissues has shown comparable accuracy, with a 12-hour error over a 10-day decomposition period (9). Combining metabolomics and metabarcoding for PMI estimation on shorter timescales could represent the future of forensic science, while protein and lipid biomarkers remain key for skeletal remains with longer PMIs.
The team is now working on targeted approaches to reliably quantify the key molecular markers already identified. The ultimate goal is to develop easy-to-use assays that forensic laboratories can implement with their existing equipment, eliminating the need for specialized expertise in -omics disciplines. By validating the current findings and translating them into practical tools, this research aims to significantly improve the capabilities of forensic practitioners, ultimately helping solve real cases with greater accuracy and confidence.
In court
Proteomics is beginning to gain acceptance in legal proceedings, marking an important step for the broader application of molecular methods in forensic science. A notable case involved the use of proteomics to confirm the presence of vomit at a crime scene, which played a crucial role in a sexual assault investigation (10). Additionally, the Department of Forensic Biology of the Office of Chief Medical Examiner of New York City has recently become accredited for forensic proteomics in identifying biological fluids, further cementing the technique’s forensic utility (11).
However, though proteomics is being applied to specific forensic questions, such as bodily fluid identification, omics and metabarcoding strategies have not yet been employed for PMI estimation in court. For these methods to be accepted in legal contexts, it’s not only necessary to have a validated technique, but also for practitioners to be aware of the new possibilities and open to integrating them into their practice. They must also collect the appropriate samples once the technique is approved. For example, body swabs should be collected at the time of discovery and stored properly in a freezer (ideally at -80 °C), along with relevant environmental data. Similarly, tissue samples should be collected during autopsies to ensure the preservation of material suitable for molecular analyses.
As Principal Investigator of the Forens-OMICS team, I will be more than keen to provide training to colleagues interested in these advancements, so we can collectively position ourselves to apply this technology effectively when it is validated, ultimately bringing cutting-edge tools into the courtroom to solve real cases.
Hero Image Credit: Collage created using Adobe Stock images
- N Procopio et al., “Forensic proteomics for the evaluation of the post-mortem decay in bones,” J Proteomics, 177 (2018). PMID: 29407476.
- HL Mickleburgh et al., “Human bone proteomes before and after decomposition: investigating the effects of biological variation and taphonomic alteration on bone protein profiles and the implications for forensic proteomics,” J Proteome Res, 20, 5 (2021). PMID: 33683123.
- A Binicello et al., “Insights into the differential preservation of bone proteomes in inhumed and entombed cadavers from Italian forensic caseworks,” J Proteome Res, 21,5 (2022). PMID: 35316604.
- L Gent et al., “Bone proteomics method optimization for forensic investigations,” J Proteome Res,23,5 (2024). PMID: 38621258.
- A Bonicelli et al., “Extraction and untargeted analysis of metabolome from undemineralised cortical bone matrix,” Mol Omics, 20, 8 (2024). PMID: 39073399.
- A Bonicelli and N Procopio, “Developing a multi-omics biomelocular signature by integrating metabolomics, lipidomics, and proteomics to estimate postmortem interval,” Proceedings of the 76th Annual Conference of the American Academy of Forensic Sciences (2024) Abstract I119.
- L Iancu, “Decomposition in an extreme cold environment and associated microbiome-prediction model implications for the postmortem interval estimation,” Front Microbiol, 15 (2024). PMID: 38803371.
- N Procopio and A Bonicelli., “Microbiome Across the Pond: Decomposition in North Dakota Extreme Winter Temperatures Versus United Kingdom Summer Temperatures and Their Effect on the Microbiome for PMI Estimation,” Proceedings of the 76th Annual Conference of the American Academy of Forensic Sciences (2024) Abstract I118.
- A Bonicelli et al., “A longitudinal study for PMI estimation via GC/MS metabolomics applied to porcine muscle tissue,” Proceedings of the 76th Annual Conference of the American Academy of Forensic Sciences (2024) Abstract I122.
- M Pieri et al., “Mass spectrometry-based proteomics for the forensic identification of vomit traces,” J Proteomics, 209 (2019). PMID: 31526901.
- Forensic Technology Center of Excellence, “Validation of a confirmatory proteomic mass spectrometry body fluid assay” (2023). Available from: https://forensiccoe.org/webinar-2023-nijrd-proteomicms-bodyfluid/
UKRI Future Leaders Fellow and Principal Investigator at the University of Central Lancashire, UK