Affiliation:
1. School of Forensic Medicine Shanxi Medical University Jinzhong Shanxi P. R. China
2. Department of Biotechnology Biomedical Sciences College Shandong First Medical University & Shandong Academy of Medical Sciences Jinan Shandong P. R. China
3. Institute of Forensic Science Ministry of Public Security Beijing P. R. China
Abstract
AbstractDetermining the burial time of skeletal remains is one of the most important issues of forensic medicine. We speculated that the microbiome of gravesoil may be a promising method to infer burial time by virtue of time‐dependent. As we know, forensic scientists have established various models to predict the postmortem interval of a decedent based on the changes in body and soil microbiome communities. However, limited data are available on the burial time prediction for bones, especially dismembered bones. In this exploratory study, we initially conducted 16S rRNA amplicon high‐throughput sequencing on the burial soil of 10 porcine femurs within a 120‐day period and analyzed the changes in soil microbial communities. Compared with the control soil, a higher Shannon index in the microbial diversity of burial soil containing bones was observed. Correlation analysis identified 61 time‐related bacterial families and the best subset selection method obtained best subset, containing Thermomonosporaceae, Clostridiaceae, 0319‐A21, and Oxalobacteraceae, which were used to construct a simplified multiple linear regression model with a mean absolute error (MAE) of 56.69 accumulated degree day (ADD). An additional random forest model was established based on indicators for the minimum cross‐validation error of Thermomonosporaceae, Clostridiaceae, 0319‐A21, Oxalobacteraceae, and Syntrophobacteraceae, with an MAE of 55.65 ADD. The produced empirical data in this pilot study provided the evidence of feasibility that the microbial successional changes of burial soil will predict the burial time of dismembered bones and may also expand the current knowledge of the effects of bone burial on soil bacterial communities.
Funder
National Natural Science Foundation of China