A pilot study characterizing gravesoil bacterial communities a decade after swine decomposition

Vertebrate decomposition leads to an efflux of fluids rich with biochemicals and microbes from the carcass into the surrounding soil affecting the endogenous soil bacterial community. These perturbations are detectable in soils associated with carcasses (gravesoil) and influence soil bacterial ecology for years after the decomposition event, but it is unknown for how long. Measuring these impacts over extended timescales is critical to expanding vertebrate decomposition's role in the ecosystem and may provide useful information to forensic science. Using 16S rRNA gene amplicon data, this study surveyed bacterial composition in terrestrial soils associated with surface-exposed swine decomposition for 10 years after carcass placement. This pilot study utilizes the increased statistical power associated with repeated measure/within-subjects sampling to analyze bacterial diversity trends over time. Our results demonstrate that the soil bacterial diversity was significantly impacted by decomposition, with this impact being localized to the area underneath the carcass. Bacterial community dissimilarity was greatest 12 months postmortem before beginning recovery. Additionally, random forest regressions were utilized to determine 10 important genera for distinguishing decomposition timepoints, an important component of forensic investigations. Of these 10 genera, four were further analyzed for their significant relative abundance shifts underneath the carcass. This pilot study helps expand the current knowledge of long-term effects of carcass decomposition on soil bacterial communities, and is the first to our knowledge to characterize these communities temporally from placement through a decade of decomposition. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Vertebrate decomposition affects soil bacterial communities for years, with greatest impact localized under the carcass. Understanding bacterial diversity trends over time is important for forensic investigations. Random forest regressions identified important genera for distinguishing decomposition timepoints.