DEININGER, Lisa (2017). Multi-Informative and Specific Detection of Blood in Fingermarks via MALDI-MS Based Strategies. Doctoral, Sheffield Hallam University. [Thesis]
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Deininger_2018_PhD_Multi-informativeAndSpecific.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Deininger_2018_PhD_Multi-informativeAndSpecific.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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Abstract
Currently employed enhancement and detection techniques for blood are not confirmatory due to targeting generic compound classes like proteins. As such, they are not sufficiently specific and are prone to false positives. The aim of this work was to confidently determine whether a crime scene sample is in fact blood and more specifically human blood. To achieve this, an in-solution bottom up proteomic approach was developed, targeting blood-specific proteins and employing MALDI-MS. The work was developed further to devise a protocol for proteomic in situ analysis of bloodied fingermarks with MALDI-MS imaging, enabling the mapping of blood peptides to fingermark ridges and thus establishing a strong link between the suspect and the event of bloodshed.
Putative peptide identifications were made for signals originating from a number of different blood-specific proteins, including not only the most abundant blood proteins like haemoglobin, but also several other proteins (e.g. complement C3 and hemopexin).
To further validate the method, a blind study was conducted analysing unknown samples ranging from different species' blood and human biofluids to other substances known to produce false positives with conventional techniques. Employing MALDI-MS, it was possible to confidently identify human blood samples of up to 34 years in age. This is potentially a huge step forward in the forensic analysis of suspected blood samples and shows potential for re-analysis of cold case samples or samples of disputed origin. It was found in this study that further optimisation of the data analysis approach is required for provenance determination of animal blood samples.
Traditionally, establishing the order of deposition of fingermarks associated with blood is difficult and subjective. Infinite focus microscopy was investigated for its potential to facilitate quantitative differentiation between the different deposition scenarios. However, results were highly dependent on the surface of deposition and thus the technique was shown to be unsuitable due to the wide range of surfaces potentially encountered in a forensic investigation.
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