Potential use of high-throughput sequencing of bacterial communities for postmortem submersion interval estimation

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.

[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.

Advances in artificial intelligence-based microbiome for PMI estimation

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.

Bacterial Succession in Microbial Biofilm as a Potential Indicator for Postmortem Submersion Interval Estimation

Bacteria acts as the main decomposer during the process of biodegradation by microbial communities in the ecosystem. Numerous studies have revealed the bacterial succession patterns during carcass decomposition in the terrestrial setting. The machine learning algorithm-generated models based on such temporal succession patterns have been developed for the postmortem interval (PMI) estimation. However, the bacterial succession that occurs on decomposing carcasses in the aquatic environment is poorly understood. In the forensic practice, the postmortem submersion interval (PMSI), which approximately equals to the PMI in most of the common drowning cases, has long been problematic to determine. In the present study, bacterial successions in the epinecrotic biofilm samples collected from the decomposing swine cadavers submerged in water were analyzed by sequencing the variable region 4 (V4) of 16S rDNA. The succession patterns between the repeated experimental settings were repeatable. Using the machine learning algorithm for establishing random forest (RF) models, the microbial community succession patterns in the epinecrotic biofilm samples taken during the 56-day winter trial and 21-day summer trial were determined to be used as the PMSI predictors with the mean absolute error (MAE) of 17.87 ± 2.48 ADD (≈1.3 day) and 20.59 ± 4.89 ADD (≈0.7 day), respectively. Significant differences were observed between the seasons and between the substrates. The data presented in this research suggested that the influences of the environmental factors and the aquatic bacterioplankton on succession patterns of the biofilm bacteria were of great significance. The related mechanisms of such influence need to be further studied and clarified in depth to consider epinecrotic biofilm as a reliable predictor in the forensic investigations.

Estimating the Postmortem Interval of Carcasses in the Water Using the Carrion Insect, Brain Tissue RNA, Bacterial Biofilm, and Algae

The accurate estimation of postmortem interval (PMI) is crucial in the investigation of homicide cases. Unlike carcasses on land, various biological and abiotic factors affect the decomposition of carcasses in water. In addition, the insect evidence (e.g., blow flies) that is commonly used to estimate the PMI are unavailable before the carcasses float on water. Therefore, it is difficult to estimate the PMI of a carcass in water. This study aimed to explore an effective way of estimating the PMI of a carcass in water. Carrion insects, brain tissue RNA, bacterial biofilm on the skin surface, and algae in water with PMI were studied using 45 rat carcasses in a small river. The results showed that carrion insects might not be suitable for the estimation of PMI of a carcass in water since they do not have a regular succession pattern as a carcass on land, and the flies only colonized six of the carcasses. The target genes (β-actin, GAPDH, and 18S) in the brain tissue were associated with the PMI in a time-dependent manner within 1 week after death. A polynomial regression analysis was used to assess the relationship between the gene expression profiles and PMI. The correlation coefficient R² of each regression equation was ≥ 0.924. A third-generation sequencing analysis showed that the bacteria on the skin surface of the carcass and the algae in the water samples around the carcass had a regular succession pattern, where Cryptomonas and Placoneis incased and decreased, respectively, within first 9 days. The results of this study provide a promising way to use the brain tissue RNA, bacterial biofilm, and algae to estimate the PMI of a carcass in water.

Water volume influences antibiotic resistomes and microbiomes during fish corpse decomposition

Corpse decomposition may cause serious pollution (e.g., releasing antibiotic resistance genes) to the water environment, thereby threatening public health. However, whether antibiotic resistance genes (ARGs) and microbiomes are affected by different water volumes during carcass decomposition remains unknown. Here, we investigated the effects of large/small water volumes on microbial communities and ARGs during fish cadaver decomposition by 16S rRNA high-throughput sequencing and high-throughput quantitative PCR. The results showed that the large water volume almost eliminated the effects of corpse decomposition on pH, total organic carbon (TOC), and total nitrogen (TN). When the water volume enlarged by 62.5 fold, the relative abundances of some ARGs resisting tetracycline and sulfonamide during carcass decomposition decreased by 217 fold on average, while there was also a mean 5267 fold increase of vancomycin resistance genes. Compared with the control group, the enriched types of ARGs varied between the large and small volume. Water volume, mobile genetic elements, and carcass decomposition were the most important factors affecting ARG profiles. Many opportunistic pathogens (like Bacteroides and Comamonas) were enriched in the corpse group. Bacteroides and Comamonas may be potential hosts of ARGs, indicating the potential for the spread of ARGs to humans by water pathogenic bacteria. This research highlights that the "dilution effect" can contribute to eliminating this adverse effect during corpse decomposition to a certain extent. It may provide references for environmental governance and public health.

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.

Temporal succession of water microbiomes and resistomes during carcass decomposition in a fish model

Carcass decomposition in water may cause serious environmental pollution, which poses a great threat to water quality and public health. However, water microbial community succession and antibiotic resistance genes (ARGs) during carcass decomposition process are less explored. Using high-throughput sequencing and high-throughput quantitative PCR techniques, the temporal succession of water bacterial communities and ARGs profiles in experimental groups (fish carcasses) and control groups (no carcasses) containing two different types of water (the Yellow River water and tap water) in different successional stages were studied. Our results showed that NH₃-N concentration in the corpse groups has greatly risen and exceeded more than 28 times on average over the safety thresholds of water quality. Some potential pathogenic genera Comamonas, Bacteroides and Pseudomonas significantly increased during carcass decomposition process. The bacterial communities of the Yellow River water and tap water in the experimental groups exhibited similar succession patterns, and community dissimilarities between the two groups decreased and smaller over time, indicating that bacterial community convergence. NH₃-N, NO₃-N and time were three most important factors in determining bacteria community structures. The influence of water type on corpse bacterial community structures was significant but weak. The gene copy number of seven detected ARGs (cmlA1-01, floR, sul1, sul2, tetG-01, tetM-01 and tetQ) in the experimental groups was more abundant than that in the control groups. The ARGs concentrations in the corpse groups were even enriched 19-fold (minimum) to 148-fold (maximum) compared to the gene tetQ of the Yellow River water in the control groups on the initial stage. Redundancy analysis (RDA) indicated that Bacteroidetes and Firmicutes were significantly correlated with all detected ARGs. This study emphasizes that cadaver degradation leads to the deterioration of nitrogen pollution, the abundance increase of potential pathogens, and the transfer of ARGs from dead animals to water environment, thereby uncovering the harmful effects of related water pollution for human health.