Estimation of the post-mortem interval by modelling the changes in oral bacterial diversity during decomposition

Zhao, Xingchun; Zhong, Zengtao; Hua, Zichun

doi:10.1111/jam.15771

Cited by 13 publications

(13 citation statements)

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“…The buildup of these gases compresses and expands the cadaver and then forces the liquid out. 5,15,16 There are two types of post-mortem microbiome in humans, namely the thanatomicrobiome and the epinecrotic microbiome. The microorganisms studied in the thanatomicrobiome are internal organs such as the brain, spleen, heart, intestines, liver, and others.…”

Section: Human Post-mortem Microbiomesmentioning

confidence: 99%

Estimation of Time of Death through Observation of Microbiota Changes in the Oral Cavity

Oktaviana,

Gultom,

Pasaribu

et al. 2024

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Various methods for estimating post-mortem (PMI) have been investigated such as rigor mortis, livor mortis, molecular, chemical, and forensic entomology (insect) methods. However, these methods have weaknesses, therefore researchers are looking for more accurate methods in determining the time of death of a person. Molecular methods are unreliable due to the degradation of DNA, RNA, and proteins in corpses over time. In different parts of the body, the amount of diversity of microbes will be different. The oral cavity is the most abundant microbial area among other parts of the body due to its continuous exposure to the respiratory and digestive systems. This area has great potential in estimating time intervals of death because of its ease of access and the types of microbiomes that predominate at any given time. Therefore, this narrative review was conducted to describe studies that used oral microbiota communities to estimate post-mortem intervals. Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes are the dominant microbial types found in corpses. Firmicutes became one of the dominant bacterial phyla in the early stages of decomposition. Actinobacteria were found to decrease as PMI increased. Studies have shown that the oral microbiome has excellent potential as a parameter to determine the post-mortem interval. However, further research is needed with more complex environmental conditions such as different humidity and temperature. In addition, further research requires more samples of human remains to obtain more valid results. Keywords: oral microbiome; post-mortem interval; human identification; forensic odontology

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Section: Human Post-mortem Microbiomesmentioning

confidence: 99%

Estimation of Time of Death through Observation of Microbiota Changes in the Oral Cavity

Oktaviana,

Gultom,

Pasaribu

et al. 2024

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“…In addition, machine learning can be used for PMI estimation in microbial forensics (Johnson et al, 2016 ; Liu et al, 2020 , 2021 ; Cao et al, 2021 ; Cartozzo et al, 2021 ; Randall et al, 2021 ; Zhang et al, 2021 ; Kaszubinski et al, 2022 ; Zhao et al, 2022 ). RF models are widely used for PMI estimation and postmortem submersion interval (PMSI) diagnosis (Metcalf et al, 2013 ; Pechal et al, 2014 ; Cartozzo et al, 2021 ; Randall et al, 2021 ; Zhang et al, 2021 ; Kaszubinski et al, 2022 ; Zhao et al, 2022 ). In 2013, Metcalf et al ( 2013 ) first proposed the concept of a “microbial clock” to infer PMI by setting up regression models using an RF.…”

Section: Applications Of Machine Learning In Forensic Microbiologymentioning

confidence: 99%

Trends in forensic microbiology: From classical methods to deep learning

Yuan

Wang

et al. 2023

Front. Microbiol.

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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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“…The durability is influenced by the postmortem interval and other extrinsic factors. Though there is a significant change in the composition and abundance of the bacterial taxa over time, the overall diversity remains relatively stable and can be very helpful in the early postmortem period (12,(23)(24)(25)(26)(27)(28)(29)(30).…”

Section: Durabilitymentioning

confidence: 99%

Toward Oral Thanatomicrobiology—An Overview of the Forensic Implications of Oral Microflora

Nilendu¹

2023

Academic Forensic Pathology

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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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Estimation of the post-mortem interval by modelling the changes in oral bacterial diversity during decomposition

Cited by 13 publications

References 50 publications

Estimation of Time of Death through Observation of Microbiota Changes in the Oral Cavity

Estimation of Time of Death through Observation of Microbiota Changes in the Oral Cavity

Trends in forensic microbiology: From classical methods to deep learning

Toward Oral Thanatomicrobiology—An Overview of the Forensic Implications of Oral Microflora

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