Abstract
Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations.
Highlights
The human body is inhabited by a vast number of microorganisms, which have occupied every conceivable ecological niche
The microbiome may provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death
Each swab is annotated with a time-since-death measurement that accounts for both temperature and time elapsed in a single variable, accumulated degree days (ADD)
Summary
The human body is inhabited by a vast number of microorganisms, which have occupied every conceivable ecological niche. Recent advances in sequencing has resulted in a great deal of research focused on the human microbiome. [1] In particular, the microbiota of the skin is increasingly the subject of research into inter-personal differences and microbe-host interactions, revealing that microbial communities differ between individuals and between different. Student stipends to DT, SG, ZK, and JP were provided by the PRISM program at John Jay College, funded by the Title V and HSI-STEM programs of the US Department of Education and the New York state CSTEP Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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