Initial insights into bacterial succession during human decomposition

Chemical elemental composition and human taphonomy: A comparative analysis between skeletonised and preserved individuals from six Portuguese public cemeteries

INTRODUCTION

In Portugal, it is common practice to reuse burial graves in cemeteries with exhumations occurring after a minimum period of three years after entombment. However, if the human remains still retain soft tissues when the grave is opened, inhumations must continue for successive periods of two years until complete skeletonization is achieved. For the past decade, several Portuguese public cemeteries have been struggling with the lack of burial space mainly due to a slow cadaveric decomposition. As such, this work aims to understand if the chemical elemental concentrations found in the depositional environment of deceased individuals is influencing human taphonomy.

METHODS

A total of 112 soil samples were collected from graves of five Portuguese public cemeteries and the concentration of 28 chemical elements was measured by inductively coupled plasma mass spectrometry (ICP-MS). A total of 56 head hair samples and 19 fingernail samples were also collected from cadaveric remains and analysed for the same purpose.

RESULTS

Overall, all matrices showed statistically significant differences (p < 0.05) between skeletonised and preserved individuals. Although it was considered that the preserved bodies would display higher elemental concentrations than the skeletonised ones, this hypothesis was not confirmed.

CONCLUSIONS

The authors believe that changes in the burial conditions over time may have enable the disintegration of soft tissues even if they were initially preserved due to the presence of chemical elements. Similar studies on a global scale should be considered as they could bring together distinct perspectives and lead to more comprehensive and innovative solutions for cemetery management.

Envenomation with Snake Venoms as a Cause of Death: A Forensic Investigation of the Decomposition Stages and the Impact on Differential Succession Pattern of Carcass-Attracted Coleopteran Beetles

BACKGROUND

Coleoptera is the second-most significant insect group associated with decomposing carcasses, yet its role in the decomposition process and postmortem colonization following envenomation is poorly understood.

PURPOSE OF THE STUDY

This study aimed to investigate the effects of the venoms from Cerastes cerastes and Naja haje on the decomposition of rabbit carcasses while evaluating the main beetle taxa attracted to these decaying remains.

METHODS

Three groups of rabbits, each with five individuals, were utilized. The first group was injected with the venom of Cerastes cerastes, the second with Naja haje venom, and the control group received 0.85% physiological saline before euthanasia with CO2.

RESULTS

Four decomposition stages (fresh, bloating, decay, and dry) with durations varying based on venom type and carcass condition were observed. A total of 647 individual beetles of six species (Necrobia rufipes, Attagenus sp., Dermestes frischii, D. maculatus, Bledius sp., and Apentanodes sp.) belonging to four families (Cleridae, Dermestidae, Staphylinidae, and Tenebrionidae) were collected and identified. D. maculatus was the most abundant species. Fewer beetles were attracted to carcasses envenomed with N. haje compared to the other groups.

CONCLUSIONS

Envenomation by snake venom influences the attraction and succession rate of necrophilous coleopterans to carcasses, which is important for forensic investigations.

Influence of Drugs and Toxins on Decomposition Dynamics: Forensic Implications

Drug and toxin-related deaths are common worldwide, making it essential to detect the postmortem concentration of various toxic substances at different stages of decomposition in a corpse. Indeed, determining the postmortem interval (PMI) and cause of death in an advanced stage of decomposed corpses has been a significant challenge in forensic investigations. Notably, the presence of drugs or toxins can have a significant impact on the microbial profile, potentially altering the succession of microbial communities and subsequent production of volatile organic compounds (VOCs), which, in turn, affect insect colonization patterns. This review aims to highlight the importance of investigating the interactions between drugs or toxins, microbial succession, VOC profiles, and insect behavior, which can provide valuable insights into forensic investigations as well as the ecological consequences of toxins occurring in decomposition. Overall, the detection of drugs and other toxins at different stages of decomposition can yield more precise forensic evidence, thereby enhancing the accuracy of PMI estimation and determination of the cause of death in decomposed remains.

Multimodal Approaches Based on Microbial Data for Accurate Postmortem Interval Estimation

Accurate postmortem interval (PMI) estimation is critical for forensic investigations, aiding case classification and providing vital trial evidence. Early postmortem signs, such as body temperature and rigor mortis, are reliable for estimating PMI shortly after death. However, these indicators become less useful as decomposition progresses, making late-stage PMI estimation a significant challenge. Decomposition involves predictable microbial activity, which may serve as an objective criterion for PMI estimation. During decomposition, anaerobic microbes metabolize body tissues, producing gases and organic acids, leading to significant changes in skin and soil microbial communities. These shifts, especially the transition from anaerobic to aerobic microbiomes, can objectively segment decomposition into pre- and post-rupture stages according to rupture point. Microbial communities change markedly after death, with anaerobic bacteria dominating early stages and aerobic bacteria prevalent post-rupture. Different organs exhibit distinct microbial successions, providing valuable PMI insights. Alongside microbial changes, metabolic and volatile organic compound (VOC) profiles also shift, reflecting the body's biochemical environment. Due to insufficient information, unimodal models could not comprehensively reflect the PMI, so a muti-modal model should be used to estimate the PMI. Machine learning (ML) offers promising methods for integrating these multimodal data sources, enabling more accurate PMI predictions. Despite challenges such as data quality and ethical considerations, developing human-specific multimodal databases and exploring microbial-insect interactions can significantly enhance PMI estimation accuracy, advancing forensic science.

Enhancing late postmortem interval prediction: a pilot study integrating proteomics and machine learning to distinguish human bone remains over 15 years

BACKGROUND

Determining the postmortem interval (PMI) accurately remains a significant challenge in forensic sciences, especially for intervals greater than 5 years (late PMI). Traditional methods often fail due to the extensive degradation of soft tissues, necessitating reliance on bone material examinations. The precision in estimating PMIs diminishes with time, particularly for intervals between 1 and 5 years, dropping to about 50% accuracy. This study aims to address this issue by identifying key protein biomarkers through proteomics and machine learning, ultimately enhancing the accuracy of PMI estimation for intervals exceeding 15 years.

METHODS

Proteomic analysis was conducted using LC-MS/MS on skeletal remains, specifically focusing on the tibia and ribs. Protein identification was performed using two strategies: a tryptic-specific search and a semitryptic search, the latter being particularly beneficial in cases of natural protein degradation. The Random Forest algorithm was used to model protein abundance data, enabling the prediction of PMI. A thorough screening process, combining importance scores and SHAP values, was employed to identify the most informative proteins for model's training and accuracy.

RESULTS

A minimal set of three biomarkers-K1C13, PGS1, and CO3A1-was identified, significantly improving the prediction accuracy between PMIs of 15 and 20 years. The model, based on protein abundance data from semitryptic peptides in tibia samples, achieved sustained 100% accuracy across 100 iterations. In contrast, non-supervised methods like PCA and MCA did not yield comparable results. Additionally, the use of semitryptic peptides outperformed tryptic peptides, particularly in tibia proteomes, suggesting their potential reliability in late PMI prediction.

CONCLUSIONS

Despite limitations such as sample size and PMI range, this study demonstrates the feasibility of combining proteomics and machine learning for accurate late PMI predictions. Future research should focus on broader PMI ranges and various bone types to further refine and standardize forensic proteomic methodologies for PMI estimation.

Environmental predictors impact microbial-based postmortem interval (PMI) estimation models within human decomposition soils

Microbial succession has been suggested to supplement established postmortem interval (PMI) estimation methods for human remains. Due to limitations of entomological and morphological PMI methods, microbes are an intriguing target for forensic applications as they are present at all stages of decomposition. Previous machine learning models from soil necrobiome data have produced PMI error rates from two and a half to six days; however, these models are built solely on amplicon sequencing of biomarkers (e.g., 16S, 18S rRNA genes) and do not consider environmental factors that influence the presence and abundance of microbial decomposers. This study builds upon current research by evaluating the inclusion of environmental data on microbial-based PMI estimates from decomposition soil samples. Random forest regression models were built to predict PMI using relative taxon abundances obtained from different biological markers (bacterial 16S, fungal ITS, 16S-ITS combined) and taxonomic levels (phylum, class, order, OTU), both with and without environmental predictors (ambient temperature, soil pH, soil conductivity, and enzyme activities) from 19 deceased human individuals that decomposed on the soil surface (Tennessee, USA). Model performance was evaluated by calculating the mean absolute error (MAE). MAE ranged from 804 to 997 accumulated degree hours (ADH) across all models. 16S models outperformed ITS models (p = 0.006), while combining 16S and ITS did not improve upon 16S models alone (p = 0.47). Inclusion of environmental data in PMI prediction models had varied effects on MAE depending on the biological marker and taxonomic level conserved. Specifically, inclusion of the measured environmental features reduced MAE for all ITS models, but improved 16S models at higher taxonomic levels (phylum and class). Overall, we demonstrated some level of predictability in soil microbial succession during human decomposition, however error rates were high when considering a moderate population of donors.

Aquatic conditions & bacterial communities as drivers of the decomposition of submerged remains

Aquatic decomposition, as a forensic discipline, has been largely under-investigated as a consequence of the highly complex and influential variability of the water environment. The limitation to the adaptability of scenario specific results justifies the necessity for experimental research to increase our understanding of the aquatic environment and the development of post-mortem submersion interval (PMSI) methods of estimation. This preliminary research aims to address this contextual gap by assessing the variation in the bacterial composition of aquatic biofilms as explained by water parameter measurements over time, associated with clothed and bare decomposing remains. As part of three field investigations, a total of 9 still-born piglets (n = 3, per trial) were used as human analogues and were submerged bare or clothed in either natural cotton or synthetic nylon. Changes in the bacterial community composition of the water surrounding the submerged remains were assessed at 4 discrete time points post submersion (7, 14, 21 and 28 days) by 16 S rRNA gene Next Generation Sequencing analysis and compared to coinciding water parameter measurements (i.e. conductivity, total dissolved solids (TDS), salinity, pH, and dissolved oxygen (DO)). Bacterial diversity was found to change over time and relative to clothing type, where significant variation was observed between synthetic nylon samples and bare/cotton samples. Seasonality was a major driver of bacterial diversity, where substantial variation was found between samples collected in early winter to those collected in mid - late winter. Water parameter measures of pH, salinity and DO were identified to best explain the global bacterial community composition and their corresponding dynamic trajectory patterns overtime. Further investigation into bacterial community dynamics in accordance with varying environmental conditions could potentially lead to the determination of influential extrinsic factors that may drive bacterial activity in aquatic decomposition. Together with the identification of potential bacterial markers that complement the different stages of decomposition, this may provide a future approach to PMSI estimations.

Estimating postmortem interval based on oral microbial community succession in rat cadavers

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.

Forensic Microbiology: When, Where and How

Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.

Decomposition in an extreme cold environment and associated microbiome-prediction model implications for the postmortem interval estimation

Introduction

The accurate estimation of postmortem interval (PMI), the time between death and discovery of the body, is crucial in forensic science investigations as it impacts legal outcomes. PMI estimation in extremely cold environments becomes susceptible to errors and misinterpretations, especially with prolonged PMIs. This study addresses the lack of data on decomposition in extreme cold by providing the first overview of decomposition in such settings. Moreover, it proposes the first postmortem microbiome prediction model for PMI estimation in cold environments, applicable even when the visual decomposition is halted.

Methods

The experiment was conducted on animal models in the second-coldest region in the United States, Grand Forks, North Dakota, and covered 23 weeks, including the winter months with temperatures as low as -39°C. Random Forest analysis models were developed to estimate the PMI based either uniquely on 16s rRNA gene microbial data derived from nasal swabs or based on both microbial data and measurable environmental parameters such as snow depth and outdoor temperatures, on a total of 393 samples.

Results

Among the six developed models, the best performing one was the complex model based on both internal and external swabs. It achieved a Mean Absolute Error (MAE) of 1.36 weeks and an R2 value of 0.91. On the other hand, the worst performing model was the minimal one that relied solely on external swabs. It had an MAE of 2.89 weeks and an R2 of 0.73. Furthermore, among the six developed models, the commonly identified predictors across at least five out of six models included the following genera: Psychrobacter (ASV1925 and ASV1929), Carnobacterium (ASV2872) and Pseudomonas (ASV1863).

Discussion

The outcome of this research provides the first microbial model able to predict PMI with an accuracy of 9.52 days over a six-month period of extreme winter conditions.

A conserved interdomain microbial network underpins cadaver decomposition despite environmental variables

Microbial breakdown of organic matter is one of the most important processes on Earth, yet the controls of decomposition are poorly understood. Here we track 36 terrestrial human cadavers in three locations and show that a phylogenetically distinct, interdomain microbial network assembles during decomposition despite selection effects of location, climate and season. We generated a metagenome-assembled genome library from cadaver-associated soils and integrated it with metabolomics data to identify links between taxonomy and function. This universal network of microbial decomposers is characterized by cross-feeding to metabolize labile decomposition products. The key bacterial and fungal decomposers are rare across non-decomposition environments and appear unique to the breakdown of terrestrial decaying flesh, including humans, swine, mice and cattle, with insects as likely important vectors for dispersal. The observed lockstep of microbial interactions further underlies a robust microbial forensic tool with the potential to aid predictions of the time since death.

Complexity of human death: its physiological, transcriptomic, and microbiological implications

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.

Alterations in microbiome of COVID-19 patients and its impact on forensic investigations

The human microbiome is vital for maintaining human health and has garnered substantial attention in recent years, particularly in the context of the coronavirus disease 2019 (COVID-19) outbreak. Studies have underscored significant alterations in the microbiome of COVID-19 patients across various body niches, including the gut, respiratory tract, oral cavity, skin, and vagina. These changes manifest as shifts in microbiota composition, characterized by an increase in opportunistic pathogens and a decrease in beneficial commensal bacteria. Such microbiome transformations may play a pivotal role in influencing the course and severity of COVID-19, potentially contributing to the inflammatory response. This ongoing relationship between COVID-19 and the human microbiome serves as a compelling subject of research, underscoring the necessity for further investigations into the underlying mechanisms and their implications for patient health. Additionally, these alterations in the microbiome may have significant ramifications for forensic investigations, given the microbiome's potential in establishing individual characteristics. Consequently, changes in the microbiome could introduce a level of complexity into forensic determinations. As research progresses, a more profound understanding of the human microbiome within the context of COVID-19 may offer valuable insights into disease prevention, treatment strategies, and its potential applications in forensic science. Consequently, this paper aims to provide an overarching review of microbiome alterations due to COVID-19 and the associated impact on forensic applications, bridging the gap between the altered microbiome of COVID-19 patients and the challenges forensic investigations may encounter when analyzing this microbiome as a forensic biomarker.

[Use of microbiological data for the purposes of forensic medical examination]

The study objective was to describe the formation of forensic microbiological examination as an analysis of a new type, defined as the detection and registration of reliably measured environmental and physiological changes within the microbial community of corpse in order to substantiate the possibility of using microbiological parameters to establish the prescription of death coming. It has been determined that the knowledge of the patterns of interaction of a human and his corpse with endogenous and exogenous flora provides the basis for solving a number of traditional and new application-oriented expert tasks and the allocation of such a variety of forensic examination as forensic microbiological examination. Endogenous and exogenous human flora and its interaction with living and dead biological tissues are the objects of this kind of examination, and the dynamic patterns of such interaction are the subject of study. One of the initial relevant tasks of forensic microbiological examination consists in development of methods, adequate for the expert task to be solved, choice of the research «target», «models» for comparative analysis and medium, adequate for task in hand, as well as certification of these methods and standardization of assessment criteria for the obtained results.

The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations

The relevance of postmortem microbiological examinations has been controversial for decades, but the boom in advanced sequencing techniques over the last decade is increasingly demonstrating their usefulness, namely for the estimation of the postmortem interval. This comprehensive review aims to present the current knowledge about the human postmortem microbiome (the necrobiome), highlighting the main factors influencing this complex process and discussing the principal applications in the field of forensic sciences. Several limitations still hindering the implementation of forensic microbiology, such as small-scale studies, the lack of a universal/harmonized workflow for DNA extraction and sequencing technology, variability in the human microbiome, and limited access to human cadavers, are discussed. Future research in the field should focus on identifying stable biomarkers within the dominant Bacillota and Pseudomonadota phyla, which are prevalent during postmortem periods and for which standardization, method consolidation, and establishment of a forensic microbial bank are crucial for consistency and comparability. Given the complexity of identifying unique postmortem microbial signatures for robust databases, a promising future approach may involve deepening our understanding of specific bacterial species/strains that can serve as reliable postmortem interval indicators during the process of body decomposition. Microorganisms might have the potential to complement routine forensic tests in judicial processes, requiring robust investigations and machine-learning models to bridge knowledge gaps and adhere to Locard's principle of trace evidence.

Applications of microbiology to different forensic scenarios - A narrative review

In contrast to other forensic disciplines, forensic microbiology is still too often considered a "side activity" and is not able to make a real and concrete contribution to forensic investigations. Indeed, the various application aspects of this discipline still remain a niche activity and, as a result, microbiological investigations are often omitted or only approximated, in part due to poor report in the literature. However, in certain situations, forensic microbiology can prove to be extremely effective, if not crucial, when all other disciplines fail. Precisely because microorganisms can represent forensic evidence, in this narrative review all the major pathological forensic applications described in the literature have been presented. The goal of our review is to highlight the versatility and transversality of microbiology in forensic science and to provide a comprehensive source of literature to refer to when needed.

Postmortem skin microbiome signatures associated with human cadavers within the first 12 h at the morgue

Introduction

Forensic microbiome studies expanded during the last decade, aiming to identify putative bacterial biomarkers to be used for the postmortem interval (PMI) estimation. Bacterial diversity and dynamics during decomposition are influenced by each individual's micro and macroenvironment, ante and postmortem conditions, varying across body sites and time. The skin, the largest organ of the human body, hosts a diverse microbial diversity, representing the first line of defense of a living individual. Targeting the investigation of the postmortem skin microbiome could help understanding the role of microbes during decomposition, and association with the ante and postmortem conditions.

Methods

The current study aimed to identify the postmortem skin microbiome signatures associated with eight human bodies, received at the Institute of Legal Medicine Iasi, Romania, during April and May 2021. A total of 162 samples (including triplicate) representing face and hands skin microbiome were investigated via Illumina MiSeq, upon arrival at the morgue (T0) and after 12 hours (T1).

Results

The taxonomic characteristics of the skin microbiota varied across different body sites. However, there were no significant differences in taxonomic profiles between collection time, T0 and T1, except for some dynamic changes in the abundance of dominant bacteria. Moreover, different microbial signatures have been associated with a specific cause of death, such as cardiovascular disease, while an elevated blood alcohol level could be associated with a decrease in bacterial richness and diversity.

Discussion

The places where the bodies were discovered seemed to play an important role in explaining the bacterial diversity composition. This study shows promising results towards finding common postmortem bacterial signatures associated with human cadavers within the first 12h at the morgue.

Exploring postmortem succession of rat intestinal microbiome for PMI based on machine learning algorithms and potential use for humans

The microbial communities may undergo a meaningful successional change during the progress of decay and decomposition that could aid in determining the post-mortem interval (PMI). However, there are still challenges to applying microbiome-based evidence in law enforcement practice. In this study, we attempted to investigate the principles governing microbial community succession during decomposition of rat and human corpse, and explore their potential use for PMI of human cadavers. A controlled experiment was conducted to characterize temporal changes in microbial communities associated with rat corpses as they decomposed for 30 days. Obvious differences of microbial community structures were observed among different stages of decomposition, especially between decomposition of 0-7d and 9-30d. Thus, a two-layer model for PMI prediction was developed based on the succession of bacteria by combining classification and regression models using machine learning algorithms. Our results achieved 90.48% accuracy for discriminating groups of PMI 0-7d and 9-30d, and yielded a mean absolute error of 0.580d within 7d decomposition and 3.165d within 9-30d decomposition. Furthermore, samples from human cadavers were collected to gain the common succession of microbial community between rats and humans. Based on the 44 shared genera of rats and humans, a two-layer model of PMI was rebuilt to be applied for PMI prediction of human cadavers. Accurate estimates indicated a reproducible succession of gut microbes across rats and humans. Together these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating PMI.

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

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.

Dissecting the microbial community structure of internal organs during the early postmortem period in a murine corpse model

BACKGROUND

Microorganisms distribute and proliferate both inside and outside the body, which are the main mediators of decomposition after death. However, limited information is available on the postmortem microbiota changes of extraintestinal body sites in the early decomposition stage of mammalian corpses.

RESULTS

This study investigated microbial composition variations among different organs and the relationship between microbial communities and time since death over 1 day of decomposition in male C57BL/6 J mice by 16S rRNA sequencing. During 1 day of decomposition, Agrobacterium, Prevotella, Bacillus, and Turicibacter were regarded as time-relevant genera in internal organs at different timepoints. Pathways associated with lipid, amino acid, carbohydrate and terpenoid and polyketide metabolism were significantly enriched at 8 h than that at 0.5 or 4 h. The microbiome compositions and postmortem metabolic pathways differed by time since death, and more importantly, these alterations were organ specific.

CONCLUSION

The dominant microbes differed by organ, while they tended toward similarity as decomposition progressed. The observed thanatomicrobiome variation by body site provides new knowledge into decomposition ecology and forensic microbiology. Additionally, the microbes detected at 0.5 h in internal organs may inform a new direction for organ transplantation.

Microbial ecology of vertebrate decomposition in terrestrial ecosystems

Vertebrate decomposition results in an ephemeral disturbance of the surrounding environment. Microbial decomposers are recognized as key players in the breakdown of complex organic compounds, controlling carbon and nutrient fate in the ecosystem and potentially serving as indicators of time since death for forensic applications. As a result, there has been increasing attention on documenting the microbial communities associated with vertebrate decomposition, or the 'necrobiome'. These necrobiome studies differ in the vertebrate species, microhabitats (e.g. skin vs. soil), and geographic locations studied, but many are narrowly focused on the forensic application of microbial data, missing the larger opportunity to understand the ecology of these communities. To further our understanding of microbial dynamics during vertebrate decomposition and identify knowledge gaps, there is a need to assess the current works from an ecological systems perspective. In this review, we examine recent work pertaining to microbial community dynamics and succession during vertebrate (human and other mammals) decomposition in terrestrial ecosystems, through the lens of a microbial succession ecological framework. From this perspective, we describe three major microbial microhabitats (internal, external, and soil) in terms of their unique successional trajectories and identify three major knowledge gaps that remain to be addressed.

Optimization of DNA extraction and sampling methods for successful forensic microbiome analyses of the skin and saliva

Microbiome studies have contributed to many fields, such as healthcare and medicine; however, these studies are relatively limited in forensics. Microbiome analyses can provide information, such as geolocation and ancestry information, when short tandem repeat (STR) profiling fails. In this study, methods for DNA extraction and sampling from the skin and saliva were optimized for the construction of a Korean Forensic Microbiome Database (KFMD). DNA yields were estimated using four DNA extraction kits, including two automated kits (Maxwell® FSC DNA IQ™ Casework Kit and PrepFiler™ Forensic DNA Extraction Kit, updated) and two manual kits (QIAamp DNA Mini Kit and QIAamp DNA Micro Kit) commonly used in forensic DNA profiling laboratories. Next-generation sequencing of the 16S rRNA V4 region was performed to analyze microbial communities in samples. The Bacterial Transport Swab with Liquid Media (NobleBio), two cotton swabs (PoongSung and Puritan), and nylon-flocked swabs (NobleBio and COPAN) were tested for DNA recovery. The PrepFiler and Maxwell kits showed the highest yields of 3.884 ng/μL and 23.767 ng/μL from the scalp and saliva, respectively. With respect to DNA recovery, nylon-flocked swabs performed better than cotton swabs. The relative abundances of taxa sorted by DNA extraction kits were similar contributions; however, with significant differences in community composition between scalp and saliva samples. Lawsonella and Veillonella were the most abundant genera in the two sample types. Thus, the Maxwell® FSC DNA IQ™ Casework Kit and nylon-flocked swab (NobleBio) were optimal for DNA extraction and collection in microbiome analyses.

Postmortem submersion interval estimation of cadavers recovered from freshwater based on gut microbial community succession

Microbial community succession during decomposition has been proven to be a useful tool for postmortem interval (PMI) estimation. Numerous studies have shown that the intestinal microbial community presented chronological changes after death and was stable in terrestrial corpses with different causes of death. However, the postmortem pattern of intestinal microbial community succession in cadavers retrieved from water remains unclear. For immersed corpses, the postmortem submersion interval (PMSI) is a useful indicator of PMI. To provide reliable estimates of PMSI in forensic investigations, we investigated the gut microbial community succession of corpses submersed in freshwater and explored its potential application in forensic investigation. In this study, the intestinal microbial community of mouse submersed in freshwater that died of drowning or CO2 asphyxia (i.e., postmortem submersion) were characterized by 16S rDNA amplification and high-throughput sequencing, followed by bioinformatic analyses. The results demonstrated that the chronological changes in intestinal bacterial communities were not different between the drowning and postmortem submersion groups. α-diversity decreased significantly within 14 days of decomposition in both groups, and the β-diversity bacterial community structure ordinated chronologically, inferring the functional pathway and phenotype. To estimate PMSI, a regression model was established by random forest (RF) algorithm based on the succession of postmortem microbiota. Furthermore, 15 genera, including Proteus, Enterococcus, and others, were selected as candidate biomarkers to set up a concise predicted model, which provided a prediction of PMSI [MAE (± SE) = 0.818 (± 0.165) d]. Overall, our present study provides evidence that intestinal microbial community succession would be a valuable marker to estimate the PMSI of corpses submerged in an aquatic habitat.

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

AIMS

Decomposition, a complicated process, depends on several factors, including carrion insects, bacteria and the environment. However, the composition of and variation in oral bacteria over long periods of decomposition remain unclear. The current study aims to illustrate the composition of oral bacteria and construct an informative model for estimating the post-mortem interval (PMI) during decomposition.

METHODS AND RESULTS

Samples were collected from rats' oral cavities for 59 days, and 12 time points in the PMI were selected to detect bacterial community structure by sequencing the V3-V4 region of the bacterial 16S ribosomal RNA (16S rRNA) gene on the Ion S5 XL platform. The results indicated that microorganisms in the oral cavity underwent great changes during decomposition, with a tendency for variation to first decrease and then increase at day 24. Additionally, to predict the PMI, an informative model was established using the random forest algorithm. Three genera of bacteria (Atopostipes, Facklamia and Cerasibacillus) were linearly correlated at all 12 time points in the 59-day period. Planococcaceae was selected as the best feature for the last 6 time points. The R² of the model reached 93.94%, which suggested high predictive accuracy. Furthermore, to predict the functions of the oral microbiota, PICRUSt results showed that energy metabolism was increased on day 3 post-mortem and carbohydrate metabolism surged significantly on days 3 and 24 post-mortem.

CONCLUSIONS

Overall, our results suggested that post-mortem oral microbial community data can serve as a forensic resource to estimate the PMI over long time periods.

SIGNIFICANCE AND IMPACT OF THE STUDY

The results of the present study are beneficial for estimating the PMI. Identifying changes in the bacterial community is of great significance for further understanding the applicability of oral flora in forensic medicine.

Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater

Introduction

Bodies recovered from water, especially in the late phase of decomposition, pose difficulties to the investigating authorities. Various methods have been proposed for postmortem submersion interval (PMSI) estimation and drowning identification, but some limitations remain. Many recent studies have proved the value of microbiota succession in viscera for postmortem interval estimation. Nevertheless, the visceral microbiota succession and its application for PMSI estimation and drowning identification require further investigation.

Methods

In the current study, mouse drowning and CO₂ asphyxia models were developed, and cadavers were immersed in freshwater for 0 to 14 days. Microbial communities in the liver and brain were characterized via 16S rDNA high-throughput sequencing.

Results

Only livers and brains collected from 5 to 14 days postmortem were qualified for sequencing. There was significant variation between microbiota from liver and brain. Differences in microbiota between the cadavers of mice that had drowned and those only subjected to postmortem submersion decreased over the PMSI. Significant successions in microbial communities were observed among the different subgroups within the late phase of the PMSI in livers and brains. Eighteen taxa in the liver which were mainly related to Clostridium_sensu_stricto and Aeromonas, and 26 taxa in the brain which were mainly belonged to Clostridium_sensu_stricto, Acetobacteroides, and Limnochorda, were selected as potential biomarkers for PMSI estimation based on a random forest algorithm. The PMSI estimation models established yielded accurate prediction results with mean absolute errors ± the standard error of 1.282 ± 0.189 d for the liver and 0.989 ± 0.237 d for the brain.

Conclusions

The present study provides novel information on visceral postmortem microbiota succession in corpses submerged in freshwater which sheds new light on PMSI estimation based on the liver and brain in forensic practice.

Analysis of Postmortem Intestinal Microbiota Successional Patterns with Application in Postmortem Interval Estimation

Microorganisms play a vital role in the decomposition of vertebrate remains in natural nutrient cycling, and the postmortem microbial succession patterns during decomposition remain unclear. The present study used hierarchical clustering based on Manhattan distances to analyze the similarities and differences among postmortem intestinal microbial succession patterns based on microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns were obtained. Generally, the normal intestinal flora in the cecum was gradually decreased with changes in the living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied upon oxygen consumption. Furthermore, a random forest regression model was developed to predict the postmortem interval based on the microbial succession trend dataset. The model demonstrated a mean absolute error of 20.01 h and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and the Lachnospiraceae NK4A136 group were considered significant biomarkers for this model according to the ranked list. The present study explored microbial succession patterns in terms of relative abundances and variety, aiding in the prediction of postmortem intervals and offering some information on microbial behaviors in decomposition ecology.

Application of artificial intelligence and machine learning technology for the prediction of postmortem interval: A systematic review of preclinical and clinical studies

BACKGROUND /PURPOSE

Establishing an accurate postmortem interval (PMI) is exceptionally crucial in forensic investigation. Artificial intelligence (AI) and Machine learning (ML) models are widely employed in forensic practice. ML is a part of AI, both terms are highly associated and sometimes used interchangeably. This systematic review aims to evaluate the application and performance of AI technology for the prediction of PMI.

METHODS

Systematic literature search across different electronic databases using PubMed/Google Scholar/EMBASE/Scopus/CINAHL/Web of Science/Cochrane library was conducted from inception to 3 December 2021 for preclinical and clinical studies reported ML models for PMI estimation.

RESULTS

We identified 18 studies (12 preclinical and 06 clinical) that met the inclusion criteria in the qualitative analysis. Most of the studies employed supervised learning (N = 15), and others employed unsupervised learning (N = 3). Due to the heterogeneity of the samples, quantitative analysis was not performed.

CONCLUSION

In this systematic review, we discussed the performance of AI-based automated systems in PMI estimation. ML models have demonstrated accuracy and precision and the ability to overcome human errors and bias. However, the research is limited, conducted in primarily small, selected human populations. In addition, we suggest further research in larger population-based studies is needed to fully understand the extent of integrated ML models.

Linking bacteria, volatiles and insects on carrion: the role of temporal and spatial factors regulating inter-kingdom communication via volatiles

Multi-kingdom community complexity and the chemically mediated dynamics between bacteria and insects have recently received increased attention in carrion research. However, the strength of these inter-kingdom interactions and the factors that regulate them are poorly studied. We used 75 piglet cadavers across three forest regions to survey the relationship between three actors (epinecrotic bacteria, volatile organic compounds (VOCs) and flies) during the first 4 days of decomposition and the factors that regulate this interdependence. The results showed a dynamic bacterial change during decomposition (temperature-time index) and across the forest management gradient, but not between regions. Similarly, VOC emission was dynamic across a temperature-time index and the forest management gradient but did not differ between regions. However, fly occurrence was dynamic across both space and time. The strong interdependence between the three actors was mainly regulated by the temperature-time index and the study regions, thereby revealing regulation at temporal and spatial scales. Additionally, the actor interdependence was stable across a gradient of forest management intensity. By combining different actors of decomposition, we have expanded our knowledge of the holistic mechanisms regulating carrion community dynamics and inter-kingdom interactions, an important precondition for better describing food web dynamics and entire ecosystem functions.

Microbiota succession throughout life from the cradle to the grave

Associations between age and the human microbiota are robust and reproducible. The microbial composition at several body sites can predict human chronological age relatively accurately. Although it is largely unknown why specific microorganisms are more abundant at certain ages, human microbiota research has elucidated a series of microbial community transformations that occur between birth and death. In this Review, we explore microbial succession in the healthy human microbiota from the cradle to the grave. We discuss the stages from primary succession at birth, to disruptions by disease or antibiotic use, to microbial expansion at death. We address how these successions differ by body site and by domain (bacteria, fungi or viruses). We also review experimental tools that microbiota researchers use to conduct this work. Finally, we discuss future directions for studying the microbiota's relationship with age, including designing consistent, well-powered, longitudinal studies, performing robust statistical analyses and improving characterization of non-bacterial microorganisms.

Insights into the Differential Preservation of Bone Proteomes in Inhumed and Entombed Cadavers from Italian Forensic Caseworks

Bone is a hard biological tissue and a precious reservoir of information in forensic investigations as it retains key biomolecules commonly used for identification purposes. Bone proteins have recently attracted significant interest for their potential in estimating post-mortem interval (PMI) and age at death (AAD). However, the preservation of such proteins is highly dependent on intrinsic and extrinsic factors that can hinder the potential application of molecular techniques to forensic sciences. The present study aims at investigating the effects that two commonly used types of burial practices (entombment and inhumation) have on bone protein survival. The sample consists of 14 exhumed individuals from cemeteries in Southern Italy with different AADs (29-85 years) and PMIs (1-37 years). LC-MS/MS analyses show that 16 proteins are better preserved under the entombed conditions and 4 proteins are better preserved under the inhumed conditions, whereas no clear differences are detected for post-translational protein modifications. Furthermore, several potential "stable" protein markers (i.e., proteins not affected by the burial environment) are identified for PMI and AAD estimation. Overall, these results show that the two burial environments play a role in the differential preservation of noncollagenous proteins, confirming the potential of LC-MS/MS-based proteomics in forensic sciences.

MALDI-TOF Mass Spectrometry Analysis and Human Post-Mortem Microbial Community: A Pilot Study

Introduction: The human post-mortem microbiome (HPM) plays a major role in the decomposition process. Successional changes in post-mortem bacterial communities have been recently demonstrated using high throughput metagenomic sequencing techniques, showing great potential as a post-mortem interval (PMI) predictor. The aim of this study is to verify the application of the mass spectrometry technique, better known as MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry), as a cheap and quick method for microbe taxonomic identification and for studying the PM microbiome. Methods: The study was carried out on 18 human bodies, ranging from 4 months to 82 years old and with a PMI range from 24 h up to 15 days. The storage time interval in the coolers was included in the final PMI estimates. Using the PMI, the sample study was divided into three main groups: seven cases with a PMI < 72 h; six cases with a PMI of 72−168 h and five cases with a PMI > 168 h. For each body, microbiological swabs were sampled from five external anatomical sites (eyes, ears, nose, mouth, and rectum) and four internal organs (brain, spleen, liver, and heart). Results: The HPM became increasingly different from the starting communities over time in the internal organs as well as at skin sites; the HPM microbiome was mostly dominated by Firmicutes and Proteobacteria phyla; and a PM microbial turnover existed during decomposition, evolving with the PMI. Conclusions: MALDI-TOF is a promising method for PMI estimation, given its sample handling, good reproducibility, and high speed and throughput. Although several intrinsic and extrinsic factors can affect the structure of the HPM, MALDI-TOF can detect the overall microbial community turnover of most prevalent phyla during decomposition. Limitations are mainly related to its sensitivity due to the culture-dependent method and bias in the identification of new isolates.

Microbial DNA in human nucleic acid extracts: Recoverability of the microbiome in DNA extracts stored frozen long-term and its potential and ethical implications for forensic investigation

Human DNA samples can remain unaltered for years and preserve important genetic information for forensic investigations. In fact, besides human genetic information, these extracts potentially contain additional valuable information: microbiome signatures. Forensic microbiology is rapidly becoming a significant tool for estimating post-mortem interval (PMI), and establishing cause of death and personal identity. To date, the possibility to recover unaltered microbiome signatures from human DNA extracts has not been proven. This study examines the microbiome signatures within human DNA extracts obtained from six cadavers with different PMIs, which were stored frozen for 5-16 years. Results demonstrated that the microbiome can be co-extracted with human DNA using forensic kits designed to extract the human host's DNA from different tissues and fluids during decomposition. We compared the microbial communities identified in these samples with microbial DNA recovered from two human cadavers donated to the Forensic Anthropology Center at Texas State University (FACTS) during multiple decomposition stages, to examine whether the microbial signatures recovered from "old" (up to 16 years) extracts are consistent with those identified in recently extracted microbial DNA samples. The V4 region of 16 S rRNA gene was amplified and sequenced using Illumina MiSeq for all DNA extracts. The results obtained from the human DNA extracts were compared with each other and with the microbial DNA from the FACTS samples. Overall, we found that the presence of specific microbial taxa depends on the decomposition stage, the type of tissue, and the depositional environment. We found no indications of contamination in the microbial signatures, or any alterations attributable to the long-term frozen storage of the extracts, demonstrating that older human DNA extracts are a reliable source of such microbial signatures. No shared Core Microbiome (CM) was identified amongst the total 18 samples, but we identified certain species in association with the different decomposition stages, offering potential for the use of microbial signatures co-extracted with human DNA samples for PMI estimation in future. Unveiling the new significance of older human DNA extracts brings with it important ethical-legal considerations. Currently, there are no shared legal frameworks governing the long-term storage and use of human DNA extracts obtained from crime scene evidence for additional research purposes. It is therefore important to create common protocols on the storage of biological material collected at crime scenes. We review existing legislation and guidelines, and identify some important limitations for the further development and application of forensic microbiomics.

Microbial traces and their role in forensic science

Forensic microbiology, also known as the microbiology of death, is an emerging branch of science that is still underused in criminal investigations. Some of the cases might be difficult to solve with commonly-used forensic methods, and then they become an operational field for microbiological and mycological analysis. The aim of our review is to present significant achievements of selected studies on the thanatomicrobiome (microorganisms found in the body, organs and fluids after death) and epinecrotic community (microorganisms found on decaying corpses) that can be used in forensic sciences. Research carried out as a part of the forensic microbiology deals with the thanatomicrobiome and the necrobiome - communities of microorganisms that live inside and outside of a putrefying corpse. Change of species composition observed in each community is a valuable feature that gives a lot of information related to the crime. It is mainly used in the estimation of post-mortem interval (PMI). In some criminal investigations, such noticeable changes in the microbiome and mycobiome can determine the cause or the actual place of death. The microbial traces found at the crime scene can also provide clear evidence of guilt. Nowadays, identification of microorganisms isolated from the body or environment is based on metagenome analysis and 16S rRNA gene amplicon-based sequencing for bacteria and ITS rRNA gene amplicon-based sequencing for fungi. Cultivation methods are still in use and seem to be more accurate; however, they require much more time to achieve a final result, which is an unwanted feature in any criminal investigation.

Integrating the human microbiome in the forensic toolkit: Current bottlenecks and future solutions

Over the last few years, advances in massively parallel sequencing technologies (also referred to next generation sequencing) and bioinformatics analysis tools have boosted our knowledge on the human microbiome. Such insights have brought new perspectives and possibilities to apply human microbiome analysis in many areas, particularly in medicine. In the forensic field, the use of microbial DNA obtained from human materials is still in its infancy but has been suggested as a potential alternative in situations when other human (non-microbial) approaches present limitations. More specifically, DNA analysis of a wide variety of microorganisms that live in and on the human body offers promises to answer various forensically relevant questions, such as post-mortem interval estimation, individual identification, and tissue/body fluid identification, among others. However, human microbiome analysis currently faces significant challenges that need to be considered and overcome via future forensically oriented human microbiome research to provide the necessary solutions. In this perspective article, we discuss the most relevant biological, technical and data-related issues and propose future solutions that will pave the way towards the integration of human microbiome analysis in the forensic toolkit.

Corpse decomposition increases the diversity and abundance of antibiotic resistance genes in different soil types in a fish model

As a common natural phenomenon, corpse decomposition may lead to serious environmental pollution such as nitrogen pollution. However, less is known about antibiotic resistance genes (ARGs), an emerging contaminant, during corpse degradation. Here, ARGs and microbiome in three soil types (black, red and yellow soil) have been investigated between experimental and control groups based on next-generation sequencing and high-throughput quantitative PCR techniques. We found that the absolute abundance of total ARGs and mobile genetic elements (MGEs) in the experimental groups were respectively enriched 536.96 and 240.60 times in different soil types, and the number of ARGs in experimental groups was 7-25 more than that in control groups. For experimental groups, the distribution of ARGs was distinct in different soil types, but sulfonamide resistance genes were always enriched. Corpse decomposition was a primary determinant for ARGs profiles. Microbiome, NH₄⁺ concentrates and pH also significantly affected ARGs profiles. Nevertheless, soil types had few effects on ARGs. For soil microbiome, some genera were elevated in experimental groups such as the Ignatzschineria and Myroides. The alpha diversity is decreased in experimental groups and microbial community structures are different between treatments. Additionally, the Escherichia and Neisseria were potential pathogens elevated in experimental groups. Network analysis indicated that most of ARGs like sulfonamide and multidrug resistance genes presented strong positively correlations with NH₄⁺ concentrates and pH, and some genera like Ignatzschineria and Dysgonomonas were positively correlated with several ARGs such as aminoglycoside and sulfonamide resistance genes. Our study reveals a law of ARGs' enrichment markedly during corpse decomposing in different soil types, and these ARGs contaminant maintaining in environment may pose a potential threat to environmental safety and human health.

Predicting the postmortem interval using human intestinal microbiome data and random forest algorithm

Gradual changes in microbial communities in a human body after death can be used to determine postmortem interval (PMI). In this study, gut microflora samples were collected from the vermiform appendix and the transverse colon of human cadavers with PMIs between 5 and 192 h. The results revealed that the appendix might be an excellent intestinal sampling site and the appendix flora had an inferred succession rule during human body decomposition. Firmicutes, Bacteroidetes, and their respective subclasses showed a predictable successionrule in relative abundance over time. A Random Forest regression model was developed to correlate human gut microbiota with PMI. We believe that our findings have increased the knowledge of the composition and abundance of the gut microbiota in human corpses, and suggest that the use of the human appendix microbial succession may be a potential method for forensic estimation of the time of death.

A walk on the dirt: soil microbial forensics from ecological theory to the crime lab

Forensics aims at using physical evidence to solve investigations with science-based principles, thus operating within a theoretical framework. This however is often rather weak, the exception being DNA-based human forensics that is well anchored in theory. Soil is a most commonly encountered, easily and unknowingly transferred evidence but it is seldom employed as soil analyses require extensive expertise. In contrast, comparative analyses of soil bacterial communities using nucleic acid technologies can efficiently and precisely locate the origin of forensic soil traces. However, this application is still in its infancy, and is very rarely used. We posit that understanding the theoretical bases and limitations of their uses is essential for soil microbial forensics to be judiciously implemented. Accordingly, we review the ecological theory and experimental evidence explaining differences between soil microbial communities, i.e. the generation of beta diversity, and propose to integrate a bottom-up approach of interactions at the microscale, reflecting historical contingencies with top-down mechanisms driven by the geographic template, providing a potential explanation as to why bacterial communities map according to soil types. Finally, we delimit the use of soil microbial forensics based on the present technologies and ecological knowledge, and propose possible venues to remove existing bottlenecks.

At the Interface of Life and Death: Post-mortem and Other Applications of Vaginal, Skin, and Salivary Microbiome Analysis in Forensics

Microbial forensics represents a promising tool to strengthen traditional forensic investigative methods and fill related knowledge gaps. Large-scale microbiome studies indicate that microbial fingerprinting can assist forensics in areas such as trace evidence, source tracking, geolocation, and circumstances of death. Nevertheless, the majority of forensic microbiome studies focus on soil and internal organ samples, whereas the microbiome of skin, mouth, and especially vaginal samples that are routinely collected in sexual assault and femicide cases remain underexplored. This review discusses the current and emerging insights into vaginal, skin, and salivary microbiome-modulating factors during life (e.g., lifestyle and health status) and after death (e.g., environmental influences and post-mortem interval) based on next-generation sequencing. We specifically highlight the key aspects of female reproductive tract, skin, and mouth microbiome samples relevant in forensics. To fill the current knowledge gaps, future research should focus on the degree to which the post-mortem succession rate and profiles of vaginal, skin, and saliva microbiota are sensitive to abiotic and biotic factors, presence or absence of oxygen and other gases, and the nutrient richness of the environment. Application of this microbiome-related knowledge could provide valuable complementary data to strengthen forensic cases, for example, to shed light on the circumstances surrounding death with (post-mortem) microbial fingerprinting. Overall, this review synthesizes the present knowledge and aims to provide a framework to adequately comprehend the hurdles and potential application of vaginal, skin, and salivary post-mortem microbiomes in forensic investigations.

Exploring microbial communities, assessment methodologies and applications of animal's carcass decomposition: a review

Animals are an essential part of the ecosystem, and their carcasses are the nutrient patches or hotspots where nutrients accumulate for a long time. After death, the physical and chemical properties undergo alterations inside the carcass. The animal carcass is decomposed by many decomposers such as bacteria, fungi, microeukaryotes and insects. The role of microbial symbionts in living organisms is well explored and studied, but there is a scarcity of knowledge and research related to their role in decomposing animal carcasses. Microbes play an important role in carcass decomposition. The origins of microbial communities associated with a carcass, including the internal and external microbiome, are discussed in this review. The succession and methods used for the detection and exploration of decomposition-associated microbial communities have been briefly described. Also, the applications of carcass-associated microbial taxa have been outlined. This review is intended to understand the dynamics of microbial communities associated with the carcass and pave the way to estimate postmortem interval and its role in recycling nutrients.

Characterization of Bacterial Community Dynamics of the Human Mouth Throughout Decomposition via Metagenomic, Metatranscriptomic, and Culturing Techniques

The postmortem microbiome has recently moved to the forefront of forensic research, and many studies have focused on the idea that predictable fluctuations in decomposer communities could be used as a “microbial clock” to determine time of death. Commonly, the oral microbiome has been evaluated using 16S rRNA gene sequencing to assess the changes in community composition throughout decomposition. We sampled the hard palates of three human donors over time to identify the prominent members of the microbiome. This study combined 16S rRNA sequencing with whole metagenomic (MetaG) and metatranscriptomic (MetaT) sequencing and culturing methodologies in an attempt to broaden current knowledge about how these postmortem microbiota change and might function throughout decomposition. In all four methods, Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were the dominant phyla, but their distributions were insufficient in separating samples based on decomposition stage or time or by donor. Better resolution was observed at the level of genus, with fresher samples from decomposition clustering away from others via principal components analysis (PCA) of the sequencing data. Key genera in driving these trends included Rothia; Lysinibacillus, Lactobacillus, Staphylococcus, and other Firmicutes; and yeasts including Candida and Yarrowia. The majority of cultures (89%) matched to sequences obtained from at least one of the sequencing methods, while 11 cultures were found in the same samples using all three methods. These included Acinetobacter gerneri, Comamonas terrigena, Morganella morganii, Proteus vulgaris, Pseudomonas koreensis, Pseudomonas moraviensis, Raoutella terrigena, Stenotrophomonas maltophilia, Bacillus cereus, Kurthia zopfii, and Lactobacillus paracasei. MetaG and MetaT data also revealed many novel insects as likely visitors to the donors in this study, opening the door to investigating them as potential vectors of microorganisms during decomposition. The presence of cultures at specific time points in decomposition, including samples for which we have MetaT data, will yield future studies tying specific taxa to metabolic pathways involved in decomposition. Overall, we have shown that our 16S rRNA sequencing results from the human hard palate are consistent with other studies and have expanded on the range of taxa shown to be associated with human decomposition, including eukaryotes, based on additional sequencing technologies.

Characterising Post-mortem Bacterial Translocation Under Clinical Conditions Using 16S rRNA Gene Sequencing in Two Animal Models

Sudden unexpected death in infancy (SUDI) is the sudden and unexpected death of an apparently healthy infant occurring within the first year of life where the cause is not immediately obvious. It is believed that a proportion of unexplained infant deaths are due to an infection that remains undiagnosed. The interpretation of post-mortem microbiology results is difficult due to the potential false-positives, a source of which is post-mortem bacterial translocation. Post-mortem bacterial translocation is the spread of viable bacteria from highly colonised sites to extra-intestinal tissues. We hypothesise that although post-mortem bacterial translocation occurs, when carcasses are kept under controlled routine clinical conditions it is not extensive and can be defined using 16S rRNA gene sequencing. With this knowledge, implementation of the 16S rRNA gene sequencing technique into routine clinical diagnostics would allow a more reliable retrospective diagnosis of ante-mortem infection. Therefore, the aim of this study was to establish the extent of post-mortem bacterial translocation in two animal models to establish a baseline sequencing signal for the post-mortem process. To do this we used 16S rRNA gene sequencing in two animal models over a 2 week period to investigate (1) the bacterial community succession in regions of high bacterial colonisation, and (2) the bacterial presence in visceral tissues routinely sampled during autopsy for microbiological investigation. We found no evidence for significant and consistent post-mortem bacterial translocation in the mouse model. Although bacteria were detected in tissues in the piglet model, we did not find significant and consistent evidence for post-mortem bacterial translocation from the gastrointestinal tract or nasal cavity. These data do not support the concept of significant post-mortem translocation as part of the normal post-mortem process.

Bone Diagenesis in Short Timescales: Insights from an Exploratory Proteomic Analysis

The evaluation of bone diagenetic phenomena in archaeological timescales has a long history; however, little is known about the origins of the microbes driving bone diagenesis, nor about the extent of bone diagenesis in short timeframes-such as in forensic contexts. Previously, the analysis of non-collagenous proteins (NCPs) through bottom-up proteomics revealed the presence of potential biomarkers useful in estimating the post-mortem interval (PMI). However, there is still a great need for enhancing the understanding of the diagenetic processes taking place in forensic timeframes, and to clarify whether proteomic analyses can help to develop better models for estimating PMI reliably. To address these knowledge gaps, we designed an experiment based on whole rat carcasses, defleshed long rat bones, and excised but still-fleshed rat limbs, which were either buried in soil or exposed on a clean plastic surface, left to decompose for 28 weeks, and retrieved at different time intervals. This study aimed to assess differences in bone protein relative abundances for the various deposition modalities and intervals. We further evaluated the effects that extrinsic factors, autolysis, and gut and soil bacteria had on bone diagenesis via bottom-up proteomics. Results showed six proteins whose abundance was significantly different between samples subjected to either microbial decomposition (gut or soil bacteria) or to environmental factors. In particular, muscle- and calcium-binding proteins were found to be more prone to degradation by bacterial attack, whereas plasma and bone marrow proteins were more susceptible to exposure to extrinsic agents. Our results suggest that both gut and soil bacteria play key roles in bone diagenesis and protein decay in relatively short timescales, and that bone proteomics is a proficient resource with which to identify microbially-driven versus extrinsically-driven diagenesis.

Prediction of minimum postmortem submersion interval (PMSImin) based on eukaryotic community succession on skeletal remains recovered from a lentic environment

Although recent studies explored using microbial succession during decomposition to estimate the postmortem interval (PMI) and postmortem submersion interval (PMSI), there is currently no published research using aquatic eukaryotic community succession to estimate the minimum postmortem submersion interval (PMSImin). The goals of this study were to determine whether eukaryotic community succession occurs on porcine skeletal remains in a lentic environment, and, if so, to develop a statistical model for PMSImin prediction. Fresh porcine bones (rib N = 100, scapula N = 100) were placed in cages (10'' x 10'') attached to floatation devices and submerged in a fresh water lake (Crozet, VA), using waterproof loggers and a YSI Sonde to record temperature and water quality variables, respectively. In addition to baseline samples, one cage, containing five ribs and five scapulae, and water samples (500 mL) were collected approximately every 250 accumulated degree days (ADD). Nineteen sample cohorts were collected over a period of 5200 ADD (579 Days). Variable region nine (V9) of the 18S ribosomal DNA (rDNA) was amplified and sequenced using a dual-index strategy on the MiSeq FGx sequencing platform. Resulting sequences underwent quality control parameters and analysis in mothur v 1.42.3, R v 3.5.3, and R v 3.6.0. Permutational multivariate analysis of variance (PERMANOVA) revealed a significant difference in phylogenetic β-diversity among ribs, scapulae and water (p = 0.001) and among ADD (p ≤ 0.011), which was supported by distinct clustering of samples associated with each ADD in UniFrac distance based non-metric multidimensional scaling (NMDS) ordinations. Using similarity percentage (SIMPER) analysis of class and family level taxa, differences observed between bone types were attributed to Peronosporomycetes_cl, Eukaryota_unclassified, and Intramacronucleata (e.g., Armophorida), however these differences were not statistically significant. Alpha diversity revealed a non-linear increase in phylogenetic diversity with an increase in ADD. Random forest models for ribs and scapulae predicted PMSImin with an error rate within±104 days (937 ADD) and±63 days (564 ADD), respectively. In conclusion, this study suggests that eukaryotic succession is capable of predicting long term PMSImin in lentic systems.

Postmortem submersion interval (PMSI) estimation from the microbiome of sus scrofa bone in a freshwater lake

While many studies have developed microbial succession-based models for the prediction of postmortem interval (PMI) in terrestrial systems, similar well-replicated long-term decomposition studies are lacking for aquatic systems. Therefore, this study sought to identify temporal changes in bacterial community structure associated with porcine skeletal remains (n = 198) for an extended period in a fresh water lake. Every ca. 250 ADD, one cage, containing 5 ribs and 5 scapulae, was removed from the lake for a total of nineteen collections. Water was also sampled at each interval. Variable region 4 (V4) of 16S rDNA was amplified and sequenced for all collected samples using Illumina MiSeq FGx Sequencing platform; resulting data were analyzed with the mothur (v1.39.5) and R (v3.6.0). Bacterial communities associated with ribs differed significantly from those associated with scapulae. This difference was mainly attributed to Clostridia, Holophagae, and Spirochaete relative abundances. For each bone type, α-diversity increased with ADD; similarly, β-diversity bacterial community structure changed significantly with ADD and were explained using environmental parameters and inferred functional pathways. Models developed using 24 rib and 34 scapula family-level taxa allowed the prediction of PMSI with root mean square error of 522.97 ADD (~57 days) and 333.8 ADD (~37 days), respectively.

Microbiome in Death and Beyond: Current Vistas and Future Trends

Forensic medicine has, for a long time, been relying on biochemical, anthropologic, and histopathologic evidences in solving various investigations. However, depending on the method used, lengthy sample processing time, scanty sample, and less sensitivity and accuracy pervade these procedures. Accordingly, newer arenas such as the thanatomicrobiome have come forward to aid in its quandaries; furthermore, the parallel advances in genomic and proteomic techniques have complemented and are still emerging to be used in forensic experiments and investigations. Postmortem interval (PMI) is one of the most important aspects of medico-legal investigations. The current trend in PMI estimation is toward genomic analyses of autopsy samples. Similarly, determination of cause of death, although a domain of medical sciences, is being targeted as the next level of forensic casework. With the current trend in laboratory sciences moving to the discovery of newer disease-specific markers for diagnostic and prognostic purposes, the same is being explored for the determination of the cause of death by using techniques such as Real-Time PCR, DNA micro-array, to Next-Gen Sequencing. Establishing an individual’s biological profile has been done using medicolegal methods and anthropology as well as bar-bodies/Davidson bodies (gender determination); and in cases where the determination of age/gender is a challenge using morphological characteristics; the recent advances in the field of genomics and proteomics have played a significant role, e.g., use of mitochondrial DNA in age estimation and in maternity disputes. The major hurdle forensic medical research faces is the fact that most of the studies are conducted in animal models, which are often difficult to mimic in human and real-time scenarios. Additionally, the high accuracy required in criminal investigations to be used in a court of law as evidence has prevented these results to come out of the labs and be used to the optimum. The current review aims at giving a comprehensive and critical account of the various molecular biology techniques including “thanatogenomics,” currently being utilized in the veritable fields of forensic medicine.

MinION technology for microbiome sequencing applications for the conservation of cultural heritage

The MinION single-molecule sequencing system has been attracting the attention of the community of microbiologists involved in the conservation of cultural heritage. The use of MinION for the conservation of cultural heritage is extremely recent, but surprisingly the only few applications available have been exploring many different substrates: stone, textiles, paintings and wax. The use of MinION sequencing is mainly used to address the metataxonomy (with special emphasis on non-cultivable microorganisms) with the effort to identify species involved in the degradation of the substrates. In this review, we show the current applications available on different artworks, showing how this technology can be a useful tool for microbiologists and conservators also in light of its low cost and the easy chemistry.

The applicability of forensic time since death estimation methods for buried bodies in advanced decomposition stages

Estimation of the postmortem interval in advanced postmortem stages is a challenging task. Although there are several approaches available for addressing postmortem changes of a (human) body or its environment (ecologically and/or biochemically), most are restricted to specific timeframes and/or individual and environmental conditions. It is well known, for instance, that buried bodies decompose in a remarkably different manner than on the ground surface. However, data on how established methods for PMI estimation perform under these conditions are scarce. It is important to understand whether and how postmortem changes are affected under burial conditions, if corrective factors could be conceived, or if methods have to be excluded for respective cases. We present the first multi-methodological assessment of human postmortem decomposition carried out on buried body donors in Europe, at the Amsterdam Research Initiative for Sub-surface Taphonomy and Anthropology (ARISTA) in the Netherlands. We used a multidisciplinary approach to investigate postmortem changes of morphology, skeletal muscle protein decomposition, presence of insects and other necrophilous animals as well as microbial communities (i.e., microbiomes) from August to November 2018 associated with two complete body exhumations and eight partial exhumations. Our results clearly display the current possibilities and limitations of methods for PMI estimation in buried remains and provide a baseline for future research and application.