The mouse gingiva and HIF-1α, a key gene of hypoxic environment, as tools for post-mortem time estimation.

Abstract

Listen

Translate article

The post-mortem interval (PMI) is the time elapsed between the death of an individual and its forensic examination. It is a crucial information for judicial authorities, but current techniques still cannot establish a precise time interval. Novel approaches are therefore required. Recently, gingival tissue has emerged as interesting for forensic analysis thanks to the protection offered by lips to this tissue, limiting the influence of environmental factors. It is also easily accessible, and its sampling is minimally invasive even in the presence of rigor mortis. Moreover, the expression of HIF-1α, a master mediator of the hypoxic environment, has been described in gingival samples at different post-mortem (PM) times. We have hypothesized that the time-dependent post-mortem expression of HIF-1α could serve as a biomarker to more accurately predict the PMI. Our analyses were performed in an animal model, the mouse, where environment can be precisely controlled. Therewith, gingival tissue morphology was evaluated through histochemical staining and HIF-1α expression was analyzed by qPCR, western blots and immunofluorescence at different post-mortem times (0h to 100h). Our results showed (a) a global post-mortem stability of gingival tissue (b) a rapid increase in HIF-1α mRNA expression in the short post-mortem times followed by a slow decrease in transcript expression until 100h PM (c) an expression of the HIF- 1α protein and its degradation products, that follows the mRNA pattern (d) the presence of HIF-1α protein in the epithelial and connective layers of the tissue, with signal accumulation in both gingival strata until at least 32h post-mortem. This pilot study thus validated the mouse and the gingival tissue as models for post-mortem analyses, as well as for studying the fate of proteins such as HIF-1α. Transferring these approaches to human subjects may provide a more accurate estimate of PMI.