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Estimating the Postmortem Interval at Longer Timescales Using Bone

Award Information

Award #
2018-R2-CX-0018
Location
Congressional District
Status
Open
Funding First Awarded
2018
Total funding (to date)
$150,000

Description of original award (Fiscal Year 2018, $150,000)

Estimating postmortem interval (PMI), or time since death, is an important piece of evidence in crime scene investigations. It allows investigators to validate alibis, narrow down suspects, and identify the deceased.

The postmortem interval can be estimated using evidence such as rigor mortis, algor mortis, livor mortis, and the presence of certain insects. However, these forms of evidence are not always present or reliable. Microbes could serve as a solution to estimating PMI because they are ubiquitous, and thus always present at a crime scene. Microbes have been used as physical evidence since the late 19th century, and recent studies have shown that the microbiome can be successful in generating a microbial stopwatch for estimating PMI. Thus far, researchers have mostly focused on the succession of skin and soil microbiomes to estimate PMI. However, microbially-based PMI predictions based on these sample types become less accurate after the first few weeks of decomposition. The hypothesis is that microbial invasion into bones is occurring during human decomposition, and at a much slower rate. If so, then tracking this microbial succession may provide more accurate estimates of PMI for longer time frames of decomposition.

Six rib bones have been collected from six human bodies that decomposed in the spring and summer of 2016-2017. They have been characterized as bacterial, archaeal, and eukaryotic microbiomes in each sample. Results revealed that the microbial communities associated with rib bones changed in a similar way across bodies during decomposition, indicating a trend in microbial succession. This project aims to collect additional timeseries sample sets of ribs from six additional human donor bodies decomposing in the fall and winter to provide sufficient power for building a robust machine learning regression model to estimate PMI. This will be done in collaboration with the Southeast Texas Applied Forensic Science (STAFS) facility in Huntsville, TX. This model aims to determine whether the microbial succession in decomposing human ribs can be used to accurately estimate PMI on a weeks to months time scale, and whether changes in rib bone microbial communities during decomposition are similar across different temperatures and seasons.

This will introduce a novel form of physical evidence that will complement forensic tools for estimating PMI, which will support the mission of criminal justice practices in the United States.

"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).

ca/ncf

Date Created: September 20, 2018