Characterisation of microbial succession for the estimation of PMI and PMSI in terrestrial and aquatic environments.

Decomposition is a continuous yet environmentally friendly process, and accurate estimation of the postmortem interval (PMI) and postmortem submersion interval (PMSI) remains a major challenge in forensic investigations. Recent developments in sequencing technologies have demonstrated great potential in the use of microbial communities in determining the time since death. Here, we investigated microbial community succession in human remains via 16 S rRNA gene sequencing and estimated the potential use of bacterial succession for estimating the PMI and PMSI. Distinct temporal shifts in microbial community composition were observed during aquatic and terrestrial decomposition, indicating predictable succession patterns associated with decomposition progression. Regression modeling under leave-one-out cross-validation demonstrated encouraging predictive performance, with the aquatic PMSI model based on ridge regression achieving an R² of 0.861 (MAE = 2.45 days), whereas the terrestrial PMI model using random forest regression achieved an R² of 0.768 (MAE = 2.60 days). Integration of microbial succession data with standardized decomposition scoring systems. These findings provide preliminary proof-of-concept evidence that microbial succession patterns can support PMI and PMSI estimation in forensic investigations. To the best of our knowledge, this represents the first forensic microbiome investigation of human terrestrial and aquatic decomposition for PMI and PMSI estimation in India.