Microbial community assembly (MCA) of both human and nonhuman animal carcasses provides indicators useful for estimating the postmortem interval (PMI) in terrestrial settings. However, there are fewer studies estimating postmortem submersion intervals (PMSIs) in aquatic habitats. No aquatic studies to date assessed MCA in the context of a death investigation, with all previous studies focusing on important basic ecological questions. Within the context of a cold case investigation, we performed an experiment using replicate adult swine carcasses to describe postmortem MCA variability within a nonflowing aquatic habitat. Using high‐throughput sequencing of carcass postmortem microbiomes, we described MCA variability and identified key taxa associated with decomposition in an aquatic habitat similar to the cold case body recovery site. We also modeled key taxa for estimating PMSIs, modeling within ±3 days (mean square error) postmortem using random forest regression. Our findings show significant changes in microbial communities as decomposition progressed, and several taxa were identified as important indicator taxa which may be useful for future estimates of PMSI. While descriptive, this study provides initial findings quantifying MCA variability within a nonflowing aquatic habitat. Within the context of the cold case investigation, we discuss how postmortem microbial samples collected at the time of body recovery could have been an important piece of evidence for understanding the PMSI of recovered remains. Additional experimental studies are needed to explicitly test and identify mechanisms associated with postmortem MCA variability in other habitats and under different temperature (e.g., seasons) conditions.

Beta-Dispersion Reflects Forensic Death Determination wound). We propose an analytical workflow that combines postmortem microbiome indicator taxa, beta-dispersion, and case demographic data for predicting MOD and COD classifications. Overall, we provide further evidence the postmortem microbiome is linked to the host's antemortem health condition(s), while also demonstrating the potential utility of including beta-dispersion (a non-taxon dependent approach) coupled with case demographic data for death determination.

Microbial communities have potential evidential utility for forensic applications. However, bioinformatic analysis of high‐throughput sequencing data varies widely among laboratories. These differences can potentially affect microbial community composition and downstream analyses. To illustrate the importance of standardizing methodology, we compared analyses of postmortem microbiome samples using several bioinformatic pipelines, varying minimum library size or minimum number of sequences per sample, and sample size. Using the same input sequence data, we found that three open‐source bioinformatic pipelines, MG‐RAST, mothur, and QIIME2, had significant differences in relative abundance, alpha‐diversity, and beta‐diversity, despite the same input data. Increasing minimum library size and sample size increased the number of low‐abundant and infrequent taxa detected. Our results show that bioinformatic pipeline and parameter choice affect results in important ways. Given the growing potential application of forensic microbiology to the criminal justice system, continued research on standardizing computational methodology will be important for downstream applications.

Death investigations in aquatic ecosystems are challenging due to abiotic and biotic factors that may influence the estimation of a postmortem submersion interval (PMSI).In this study, we examined bacterial changes throughout the decomposition process on porcine carcasses submerged in a tidal-influenced river and identified predictors of epinecrotic community succession. Fetal porcine (Sus scrofa) carcasses (N = 6) were submerged with epinecrotic samples collected every 3 days (6 collections) over a period of 19 days (~7415 accumulated degree hours (ADH)). Amplicon sequencing was performed using the Illumina MiSeq platform (16S V4 region, 2 × 250 bp format) to identify changes in bacterial relative abundance and diversity. To match bacterial succession with rough taphonomy, carcasses were visually assessed at each sampling time point to determine the decomposition stage. Notably, the three most abundant families were Moraxellaceae, Burkholderiaceae (Proteobacteria), and Clostridiaceae (Firmicutes), though communities composition varied significantly across decomposition stages. Greater bacterial phylogenetic diversity was observed in in latter decomposition stages (advanced floating decay, sunken remains). Random Forest Models were built to predict ADH and explained 77%-80.8% of variation in ADH with an error rate of +/−1943.2 ADH (Root Mean Square Error) or approx. ±2.7 days at the mean water temperature of this study. This study provided a useful model that could be used to estimate a PMSI in this river system utilizing bacterial community succession, and thus, potentially improve the accuracy of such estimations to be used in the court of law.

After death, microbes (including bacteria and fungi) colonize carrion from a variety of sources during the decomposition process. The predictable succession of microbes could be useful for forensics, such as postmortem submersion interval estimation (PMSI) for aquatic deaths. However, gaps exist in our understanding of microbial succession on submerged bone, particularly regarding longer-term decomposition (>1 year), fungal composition, and differences between internal and external microbial communities.To further explore this potential forensic tool, we described the postmortem microbial communities (bacteria and fungi) on and within submerged bones using targeted amplicon sequencing. We hypothesized predictable successional patterns of microbial colonization would be detected on the surface and within submerged bones, which would eventually converge to a similar microbial community. To best replicate forensic contexts, we sampled bones from replicate swine (Sus scrofa domesticus) carcasses submerged in a freshwater pond, every three months for nearly two years. Microbial bone (internal vs. external) community structure (taxa abundance and diversity) of bones differed for both bacteria and fungi, but internal and external communities did not converge to a similar structure. PMSI estimation models built with random forest regression of postmortem microbiomes were highly accurate (>80% variation explained in PMSI) and showed promise for forensic purposes. Overall, we provide further evidence that internal and external bone microbial communities submerged in an aquatic habitat are distinct and each community undergoes predictable succession, demonstrating potential utility in forensics for modeling PMSI in unattended deaths and/or cold cases.