Cargando…
Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation
Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672931/ https://www.ncbi.nlm.nih.gov/pubmed/38004822 http://dx.doi.org/10.3390/microorganisms11112811 |
_version_ | 1785149566492868608 |
---|---|
author | Yang, Fan Zhang, Xiangyan Hu, Sheng Nie, Hao Gui, Peng Zhong, Zengtao Guo, Yadong Zhao, Xingchun |
author_facet | Yang, Fan Zhang, Xiangyan Hu, Sheng Nie, Hao Gui, Peng Zhong, Zengtao Guo, Yadong Zhao, Xingchun |
author_sort | Yang, Fan |
collection | PubMed |
description | Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0–8Dvs. WPG 16–40D, p < 0.0001; WPS 0–16Dvs. WPS 24–40D, p = 0.003; SPG 0D vs. SPG 8–40D, p = 0.0005; and SPS 0D vs. SPS 8–40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI. |
format | Online Article Text |
id | pubmed-10672931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106729312023-11-20 Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation Yang, Fan Zhang, Xiangyan Hu, Sheng Nie, Hao Gui, Peng Zhong, Zengtao Guo, Yadong Zhao, Xingchun Microorganisms Article Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0–8Dvs. WPG 16–40D, p < 0.0001; WPS 0–16Dvs. WPS 24–40D, p = 0.003; SPG 0D vs. SPG 8–40D, p = 0.0005; and SPS 0D vs. SPS 8–40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI. MDPI 2023-11-20 /pmc/articles/PMC10672931/ /pubmed/38004822 http://dx.doi.org/10.3390/microorganisms11112811 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Fan Zhang, Xiangyan Hu, Sheng Nie, Hao Gui, Peng Zhong, Zengtao Guo, Yadong Zhao, Xingchun Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title | Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title_full | Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title_fullStr | Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title_full_unstemmed | Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title_short | Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation |
title_sort | changes in microbial communities using pigs as a model for postmortem interval estimation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672931/ https://www.ncbi.nlm.nih.gov/pubmed/38004822 http://dx.doi.org/10.3390/microorganisms11112811 |
work_keys_str_mv | AT yangfan changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT zhangxiangyan changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT husheng changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT niehao changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT guipeng changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT zhongzengtao changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT guoyadong changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation AT zhaoxingchun changesinmicrobialcommunitiesusingpigsasamodelforpostmortemintervalestimation |