ArticleFrontiers in microbiology2022
Bacterial Succession in Microbial Biofilm as a Potential Indicator for Postmortem Submersion Interval Estimation.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Artificial intelligence in forensic science: a systematic review. Part II: long-range postmortem interval estimation.International journal of legal medicine · 2026Pooled it
- Estimation of postmortem submersion interval based on microbial community composition in human remains recovered from aquatic environments.Journal of forensic sciences · 2026Article
- Microbiota signature of the lung as the promising bioindicator for drowning diagnosis and postmortem submersion interval estimation.International journal of legal medicine · 2025Article
- Dynamics of Bacterial Communities and Their Relationship with Nutrients in a Full-Scale Shrimp Recirculating Aquaculture System in Brackish Water.Animals : an open access journal from MDPI · 2025Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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