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, th...Continue Reading
A statistical approach based on accumulated degree-days to predict decomposition-related processes in forensic studies
The potential use of bacterial community succession in forensics as described by high throughput metagenomic sequencing
The living dead: bacterial community structure of a cadaver at the onset and end of the bloat stage of decomposition
A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition
Effect of temperature and time on the thanatomicrobiome of the cecum, ileum, kidney, and lung of domestic rabbits
Uncharted waters: Next-generation sequencing and machine learning software allow forensic science to expand into phenotype prediction from DNA samples
Predicting postmortem interval based on microbial community sequences and machine learning algorithms.
Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition
Thanatomicrobiome and epinecrotic community signatures for estimation of post-mortem time interval in human cadaver
Cadaver Thanatomicrobiome Signatures: The Ubiquitous Nature of Clostridium Species in Human Decomposition
Microbial assemblages and bioindicators as proxies for ecosystem health status: potential and limitations
Potential use of molecular and structural characterization of the gut bacterial community for postmortem interval estimation in Sprague Dawley rats
Comparative Decomposition of Humans and Pigs: Soil Biogeochemistry, Microbial Activity and Metabolomic Profiles.
Tonsil Mycobiome in PFAPA (Periodic Fever, Aphthous Stomatitis, Pharyngitis, Adenitis) Syndrome: A Case-Control Study.
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