Estimating the time of human decomposition based on skeletal muscle biopsy samples utilizing an untargeted LC-MS/MS-based proteomics approach

Abstract

Accurate estimation of the postmortem interval (PMI) is crucial in forensic medico-legal investigations to understand case circumstances (e.g. narrowing down list of missing persons or include/exclude suspects). Due to the complex decomposition chemistry, estimation of PMI remains challenging and currently often relies on the subjective visual assessment of gross morphological/taphonomic changes of a body during decomposition or entomological data. The aim of the current study was to investigate the human decomposition process up to 3 months after death and propose novel time-dependent biomarkers (peptide ratios) for the estimation of decomposition time. An untargeted liquid chromatography tandem mass spectrometry-based bottom-up proteomics workflow (ion mobility separated) was utilized to analyse skeletal muscle, collected repeatedly from nine body donors decomposing in an open eucalypt woodland environment in Australia. Additionally, general analytical considerations for large-scale proteomics studies for PMI determination are raised and discussed. Multiple peptide ratios (human origin) were successfully proposed (subgroups < 200 accumulated degree days (ADD), < 655 ADD and < 1535 ADD) as a first step towards generalised, objective biochemical estimation of decomposition time. Furthermore, peptide ratios for donor-specific intrinsic factors (sex and body mass) were found. Search of peptide data against a bacterial database did not yield any results most likely due to the low abundance of bacterial proteins within the collected human biopsy samples. For comprehensive time-dependent modelling, increased donor number would be necessary along with targeted confirmation of proposed peptides. Overall, the presented results provide valuable information that aid in the understanding and estimation of the human decomposition processes.

Keywords: Data-independent acquisition; Human decomposition; Ion mobility separation; Peptide ratios; Postmortem interval; Proteomics.

Fig. 1

Normalised abundances of peptides LTQESIMDLENDKQQLDER (a) and LTQESIM[OX]DLENDKQQLDER (b) over time as well as log2 transformed peptide ratio LTQESIMDLENDKQQLDER/LTQESIM[OX]DLENDKQQLDER (c) over 655 accumulated degree days (ADD); displayed trendlines represent linear regression results; [OX]: oxidation modification

Fig. 2

Peptide ratios with the strongest coefficient of determination (r²) per subgroup; a peptide ratio IKELTYQTEEDRK/EDQVMQQNPPKFDK for < 200 accumulated degree days (ADD), b peptide ratio KLEDEC[Carba]SELKR/AITDAAM[OX]M[OX]AEELKK for samples < 655 ADD, c peptide ratio INQQLDTK/TSVFVAEPK for the complete dataset (< 1535 ADD); displayed trendlines represent linear regression results; [Carba]: carbamidomethyl modification; [OX]: oxidation modification