One of the most debated topics in forensic anthropology and archaeology is the estimation of the time elapsed since death and the biological age of the body from skeletonised bodies, or fragments of them. Usually, standard analytical and morphological approaches tend to suffer from weaknesses, highly relying on the expertise of the forensic scientists and on their subjective interpretation of the macroscopic and microscopic bone features to draw conclusions. In order to improve the accuracy and the objectivity of these estimations, biomolecular approaches seem to be the most promising way to address the problem. Between all the biomolecules available to conduct this type of studies, proteins are the ones able to survive longest in biological tissues through the decomposition process. Furthermore, they also convey several modifications which can be related with ageing phenomena both in vivo and post-mortem, with protein deamidation being the most commonly occurring in forensic and in archaeological contexts. All these features make proteins an interesting target for new applications in forensic sciences, with the potential to become new biomarkers for biological and geological age estimations. The research presented here applied proteomic methods to experimental forensic and archaeological bones and teeth to investigate how the decomposition process and the environmental conditions impact the proteins degradation and modification, and evaluated also the effects that the decomposition of a body may have on the surrounding burial environment using a metagenomic approach to evaluate changes within the soil microbial community. Results showed that proteomic analyses on bones can provide interesting information about the ageing phenomena in forensic and archaeological scenarios; in particular, the new potential biomarkers proposed here may become in future a molecular support to the estimation of post-mortem interval and age-at-death, improving the ability of scientists to find the truth behind complicated forensic contexts.
|Date of Award
|31 Dec 2018
- The University of Manchester
|Terence Brown (Supervisor), Michael Buckley (Supervisor) & Andrew Chamberlain (Supervisor)