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Wang X, Le C, Jin X, Feng Y, Chen L, Huang X, Tian S, Wang Q, Ji J, Liu Y, Zhang H, Huang J, Ren Z. Estimating postmortem interval based on oral microbial community succession in rat cadavers. Heliyon 2024; 10:e31897. [PMID: 38882314 PMCID: PMC11177140 DOI: 10.1016/j.heliyon.2024.e31897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 05/18/2024] [Accepted: 05/23/2024] [Indexed: 06/18/2024] Open
Abstract
The accurate estimation of the postmortem interval has been one of the crucial issues to be solved in forensic research, and it is influenced by various factors in the process of decay. With the development of high-throughput sequencing technology, forensic microbiology has become the major hot topic in forensic science, which provides new research options for postmortem interval estimation. The oral microbial community is one of the most diverse of microbiomes, ranking as the second most abundant microbiota following the gastrointestinal tract. It is remarkable that oral microorganisms have a significant function in the decay process of cadavers. Therefore, we collected outdoor soil to simulate the death environment and focused on the relationship between oral microbial community succession and PMI in rats above the soil. In addition, linear regression models and random forest regression models were developed for the relationship between the relative abundance of oral microbes and PMI. We also identified a number of microorganisms that may be important to estimate PMI, including: Ignatzschineria, Morganella, Proteus, Lysinibacillus, Pseudomonas, Globicatella, Corynebacterium, Streptococcus, Rothia, Aerococcus, Staphylococcus, and so on.
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Affiliation(s)
- Xiaoxue Wang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Cuiyun Le
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Xiaoye Jin
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Yuhang Feng
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Li Chen
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Xiaolan Huang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Shunyi Tian
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Qiyan Wang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Jingyan Ji
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Yubo Liu
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Hongling Zhang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Jiang Huang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Zheng Ren
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China
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Javan GT, Singh K, Finley SJ, Green RL, Sen CK. Complexity of human death: its physiological, transcriptomic, and microbiological implications. Front Microbiol 2024; 14:1345633. [PMID: 38282739 PMCID: PMC10822681 DOI: 10.3389/fmicb.2023.1345633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 12/28/2023] [Indexed: 01/30/2024] Open
Abstract
Human death is a complex, time-governed phenomenon that leads to the irreversible cessation of all bodily functions. Recent molecular and genetic studies have revealed remarkable experimental evidence of genetically programmed cellular death characterized by several physiological processes; however, the basic physiological function that occurs during the immediate postmortem period remains inadequately described. There is a paucity of knowledge connecting necrotic pathologies occurring in human organ tissues to complete functional loss of the human organism. Cells, tissues, organs, and organ systems show a range of differential resilience and endurance responses that occur during organismal death. Intriguingly, a persistent ambiguity in the study of postmortem physiological systems is the determination of the trajectory of a complex multicellular human body, far from life-sustaining homeostasis, following the gradual or sudden expiry of its regulatory systems. Recent groundbreaking investigations have resulted in a paradigm shift in understanding the cell biology and physiology of death. Two significant findings are that (i) most cells in the human body are microbial, and (ii) microbial cell abundance significantly increases after death. By addressing the physiological as well as the microbiological aspects of death, future investigations are poised to reveal innovative insights into the enigmatic biological activities associated with death and human decomposition. Understanding the elaborate crosstalk of abiotic and biotic factors in the context of death has implications for scientific discoveries important to informing translational knowledge regarding the transition from living to the non-living. There are important and practical needs for a transformative reestablishment of accepted models of biological death (i.e., artificial intelligence, AI) for more precise determinations of when the regulatory mechanisms for homeostasis of a living individual have ceased. In this review, we summarize mechanisms of physiological, genetic, and microbiological processes that define the biological changes and pathways associated with human organismal death and decomposition.
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Affiliation(s)
- Gulnaz T. Javan
- Department of Physical and Forensic Sciences, Alabama State University, Montgomery, AL, United States
| | - Kanhaiya Singh
- Department of Surgery, School of Medicine, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Sheree J. Finley
- Department of Physical and Forensic Sciences, Alabama State University, Montgomery, AL, United States
| | - Robert L. Green
- Department of Physical and Forensic Sciences, Alabama State University, Montgomery, AL, United States
| | - Chandan K. Sen
- Department of Surgery, School of Medicine, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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Yang F, Zhang X, Hu S, Nie H, Gui P, Zhong Z, Guo Y, Zhao X. Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation. Microorganisms 2023; 11:2811. [PMID: 38004822 PMCID: PMC10672931 DOI: 10.3390/microorganisms11112811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/06/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
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.
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Affiliation(s)
- Fan Yang
- Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China; (F.Y.); (S.H.); (H.N.)
| | - Xiangyan Zhang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China; (X.Z.); (Y.G.)
| | - Sheng Hu
- Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China; (F.Y.); (S.H.); (H.N.)
| | - Hao Nie
- Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China; (F.Y.); (S.H.); (H.N.)
| | - Peng Gui
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China; (P.G.); (Z.Z.)
| | - Zengtao Zhong
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China; (P.G.); (Z.Z.)
| | - Yadong Guo
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China; (X.Z.); (Y.G.)
| | - Xingchun Zhao
- Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China; (F.Y.); (S.H.); (H.N.)
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Miguel M, Kim SH, Lee SS, Cho YI. Composition and functional diversity of bacterial communities during swine carcass decomposition. Anim Biosci 2023; 36:1453-1464. [PMID: 37402447 PMCID: PMC10472150 DOI: 10.5713/ab.23.0140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/08/2023] [Accepted: 06/14/2023] [Indexed: 07/06/2023] Open
Abstract
OBJECTIVE This study investigated the changes in bacterial communities within decomposing swine microcosms, comparing soil with or without intact microbial communities, and under aerobic and anaerobic conditions. METHODS The experimental microcosms consisted of four conditions: UA, unsterilized soil-aerobic condition; SA, sterilized soil-aerobic condition; UAn, unsterilized soil-anaerobic condition; and San, sterilized soil-anaerobic condition. The microcosms were prepared by mixing 112.5 g of soil and 37.5 g of ground carcass, which were then placed in sterile containers. The carcass-soil mixture was sampled at day 0, 5, 10, 30, and 60 of decomposition, and the bacterial communities that formed during carcass decomposition were assessed using Illumina MiSeq sequencing of the 16S rRNA gene. RESULTS A total of 1,687 amplicon sequence variants representing 22 phyla and 805 genera were identified in the microcosms. The Chao1 and Shannon diversity indices varied in between microcosms at each period (p<0.05). Metagenomic analysis showed variation in the taxa composition across the burial microcosms during decomposition, with Firmicutes being the dominant phylum, followed by Proteobacteria. At the genus level, Bacillus and Clostridium were the main genera within Firmicutes. Functional prediction revealed that the most abundant Kyoto encyclopedia of genes and genomes metabolic functions were carbohydrate and amino acid metabolisms. CONCLUSION This study demonstrated a higher bacteria diversity in UA and UAn microcosms than in SA and SAn microcosms. In addition, the taxonomic composition of the microbial community also exhibited changes, highlighting the impact of soil sterilization and oxygen on carcass decomposition. Furthermore, this study provided insights into the microbial communities associated with decomposing swine carcasses in microcosm.
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Affiliation(s)
- Michelle Miguel
- Department of Animal Science and Technology, Sunchon National University, Suncheon, Jeonnam 57922,
Korea
| | - Seon-Ho Kim
- Department of Animal Science and Technology, Sunchon National University, Suncheon, Jeonnam 57922,
Korea
| | - Sang-Suk Lee
- Department of Animal Science and Technology, Sunchon National University, Suncheon, Jeonnam 57922,
Korea
| | - Yong-Il Cho
- Department of Animal Science and Technology, Sunchon National University, Suncheon, Jeonnam 57922,
Korea
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Nilendu D. Toward Oral Thanatomicrobiology-An Overview of the Forensic Implications of Oral Microflora. Acad Forensic Pathol 2023; 13:51-60. [PMID: 37457549 PMCID: PMC10338735 DOI: 10.1177/19253621231176411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/01/2023] [Indexed: 07/18/2023]
Abstract
Introduction The oral cavity is home to numerous microorganisms including bacteria, fungi, and viruses which together form the oral microflora. It is the second most diverse microbial site in the human body after the gastrointestinal tract. Microbial degradation is a common phenomenon that occurs after death, with the early and advanced stages of decomposition being closely associated with oral microbial activity. Methods This article reviews the current state of knowledge on the role of the oral microflora in postmortem events, and highlights the growing importance of terms such as forensic microbiology and thanatomicrobiome. This article also discusses next-generation sequencing, metagenomic sequencing studies, and RNA sequencing to study the oral thanatomicrobiome and epinecrotic communities in forensic oral genetics. Results The indigenous microorganisms in the oral cavity are among the first to respond to the process of decomposition. DNA/RNA sequencing is a relatively simple, precise, and cost-effective method to estimate biological diversity during various stages of postmortem decomposition. The field of thanatomicrobiology is rapidly evolving into a key area in forensic research. Conclusion This article briefly narrates oral microflora and its implications in forensic odontology. The role of microbial activity in postmortem events is gaining importance in forensic research, and further studies are needed to fully understand the potential applications of advanced technology in the study of the oral thanatomicrobiome.
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Affiliation(s)
- Debesh Nilendu
- Debesh Nilendu PhD, Department of Oral Medicine and Radiology, K. M. Shah Dental College and Hospital, Sumandeep Vidyapeeth Deemed to be University, Waghodia Road, Piparia, Taluk Waghodia, Vadodara, Gujarat 391760, India,
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Yuan H, Wang Z, Wang Z, Zhang F, Guan D, Zhao R. Trends in forensic microbiology: From classical methods to deep learning. Front Microbiol 2023; 14:1163741. [PMID: 37065115 PMCID: PMC10098119 DOI: 10.3389/fmicb.2023.1163741] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 03/08/2023] [Indexed: 04/18/2023] Open
Abstract
Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology.
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Affiliation(s)
- Huiya Yuan
- Department of Forensic Analytical Toxicology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-Evidence Science, Shenyang, China
| | - Ziwei Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Zhi Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Fuyuan Zhang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Dawei Guan
- Liaoning Province Key Laboratory of Forensic Bio-Evidence Science, Shenyang, China
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- *Correspondence: Dawei Guan
| | - Rui Zhao
- Liaoning Province Key Laboratory of Forensic Bio-Evidence Science, Shenyang, China
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Rui Zhao
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Wang Z, Zhang F, Wang L, Yuan H, Guan D, Zhao R. Advances in artificial intelligence-based microbiome for PMI estimation. Front Microbiol 2022; 13:1034051. [PMID: 36267183 PMCID: PMC9577360 DOI: 10.3389/fmicb.2022.1034051] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 09/15/2022] [Indexed: 11/13/2022] Open
Abstract
Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.
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Affiliation(s)
- Ziwei Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Fuyuan Zhang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Linlin Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
| | - Huiya Yuan
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
| | - Dawei Guan
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- *Correspondence: Dawei Guan,
| | - Rui Zhao
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Rui Zhao,
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