RESUMO
Multiple methods have been proposed to provide accurate time since death estimations, and recently, the discovery of bacterial community turnover during decomposition has shown itself to have predictable patterns that may prove useful. In this study, we demonstrate the use of metatranscriptomics from the postmortem microbiome to simultaneously obtain community structure and functional data across postmortem intervals (PMIs). We found that bacterial succession patterns reveal similar trends as detected through DNA analysis, such as increasing Clostridiaceae as decomposition occurs, strengthening the reliability of total RNA community analyses. We also provide one of the first analyses of RNA transcripts to characterize bacterial metabolic pathways during decomposition. We found distinct pathways, such as amino acid metabolism, to be strongly up-regulated with increasing PMIs. Elucidating the metabolic activity of postmortem microbial communities provides the first steps to discovering postmortem functional biomarkers since functional redundancy across bacteria may reduce host individual microbiome variability.