Prediction of Minimum Postmortem Submersion Interval (PMSImin) Based on Eukaryotic Community Succession on Skeletal Remains Recovered from Aquatic Environments

Many recent studies were conducted concerning bacterial succession in decomposing animal carrion in terrestrial system. However, not much is known about the microorganisms involved in aquatic decomposition. To the best of our knowledge, there are currently no published studies which estimate minimum postmortem submersion interval PMSImin based on eukaryotic community succession in aquatic system. The main goal of this study was to determine the eukaryotic community succession associated with porcine skeletal remains in lentic and lotic environments, and to derive a statistical model for PMSImin prediction. The locations chosen for this research were Henleys Lake in Crozet, VA and Virginia Commonwealth University's (VCU's) Rice Rivers Center on the James River. The distance between both sites was approximately 120 miles. At each site, fresh pig bones (rib N = 100, scapula N = 100) were placed in cages (10 x 10 inch2), attached to a floatation device, and submerged together with waterproof loggers, and a Yellow Springs, OH Sonde. Every 250 Accumulated Degree Days (ADD), one cage containing 5 rib and 5 scapula samples was collected over a total research period of 5200 ADDs (559 days) at Henleys Lake, and 4972 ADDs (294 days) at the James River. Water samples were also collected every 250 ADD and filtered using a cellulose membrane filtration system. DNA extraction was performed using the Invitrogen ChargeSwitch® gDNA Plant Kit Protocol. Variable region nine (V9) of the 18S rDNA was amplified and sequenced using a dual-index strategy on the MiSeq FGX sequencing platform. Sequenced data were quality controlled and analyzed via the MiSeq SOP in Mothur version 1.42.3 and in R v3.6.0. Hierarchical classification of good quality sequences was performed using SILVA119 reference database. A phylogenetic approach was utilized for a-and ß-diversity estimation. For relative abundance and diversity estimations, sequences were subsampled at a threshold of 5048 reads (Henleys Lake) and 5287 reads (James River). Permutational multivariate analysis of variance (PERMANOVA) revealed a significant difference in eukaryotic community structure among sample types (p = 0.000999) and ADD (p = 0.01099). Non-metric multidimensional scaling (NMDS) ordinations revealed distinct clustering of samples associated with each ADD. Arthropoda_unclassified was the most influential PMSI predictor taxon at Henleys Lake, while Eukaryota_unclassified was the most influential PMSI predictor taxon at the James River. Two random forest models were generated for rib and scapula at each site. At Henley's lake, rib and scapula models predicted PMSImin with an error rate of ± 101 days (936.89 ADD) and ± 61 days (563.77 ADD) respectively. At the James River, rib and scapula models predicted PMSImin with an error rate of ± 32 days (547.44 ADD) and ± 31 days (527.08 ADD) respectively. Scapula was found to be a better predictor than Rib at both sites. Future directions include comparison of 18S rDNA data between lentic and lotic bodies of water. There is also potential for this 18S rDNA data to be combined with 16S rDNA data to increase accuracy of PMSImin prediction models. In conclusion, this study suggests that eukaryotic succession is capable of predicting long term PMSI in freshwater systems.