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Estimating the postmortem interval of human skeletal remains using rapid, inexpensive microbiome tools

Award Information

Award #
2019-DU-BX-0010
Funding Category
Competitive Discretionary
Location
Congressional District
Status
Closed
Funding First Awarded
2019
Total funding (to date)
$390,748

Description of original award (Fiscal Year 2019, $390,748)

The postmortem interval (PMI), or the time elapsed since death, is important to establish in forensic investigations to reconstruct death scenes, identify the deceased, and validate alibis. However, estimating PMI of human remains is challenging with limited forensic tools available to investigators. Therefore, the development of new tools is warranted. We have previously demonstrated that cadaver-associated microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. We demonstrated that over the first 21 days of decomposition, PMI of human remains can be estimated with errors as low as +/- 3 days using rapid and inexpensive microbiome tools (high throughput sequencing of microbial genes in an environment) and machine learning regression methods. In our proposed research, we will expand these tools to include extended decomposition time frames of advanced decay to dry/remains, during which very limited forensic tools exist. In a pilot study at Sam Houston State Applied Anatomy Research Center (SHSU AARC), we demonstrated that microbes invade bone in a predictable manner, which provides a proof-of-concept for developing a tool for estimating PMI based on bone microbial communities. By sampling rib bones every three weeks, we estimated PMI +/-36 days over 9 months. Because model error can be reduced by increasing sampling frequency of the training data set, we will investigate whether we can improve model error by sampling rib bones from cadavers every seven days during advanced decay to dry/remains. Additionally, we will sample cadaver skin and associated soil samples at the same time points to compare microbial-based PMI accuracy across sample types. Finally, for a subset of bodies, we will analyze additional bone types to determine whether a microbial clock trained on rib bone microbes is generalizable to other bone sites that may be more accessible at death scenes. To accomplish this project, we will leverage expertise of the Colorado State University Microbiome Initiative, SHSU forensic science program, and AARC willed-body donor center. Anticipated outcomes of this 2-year, 2-phase project include publicly-available microbiome datasets, validated regression models that predict PMI, peer-reviewed scientific articles, and presentations aimed at stakeholders in the criminal justice system. Additionally, we aim to train a futurefocused workforce by cross-training undergraduate students in both forensic science and microbiome big data analyses. The proposed research satisfies the NIJ Basic Research Goal by advancing a new forensic analysis.

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 13, 2019