Dr Sarah Elizabeth Bamford - La Trobe University

The characterisation of proteins is central to understanding and identifying biological materials and their embodied structures, processes, functions and interrelationships. In the law enforcement and intelligence context, this includes forensic investigation, for example, to identify offenders, victims and biothreats. 

Developing high throughput informatic tools to support proteomic analysis in complex samples, is a global challenge. Within Australia, there are currently very few forensic proteomics workflows in routine use. ChemCentre in Western Australia and Australian Border Force conduct specialised analyses in very specific areas. 

The nature of forensic proteomic samples is frequently incompatible with conventional proteomic workflows and bioinformatics methods; low-quantity and poor-quality samples present critical problems. Proteins are often so degraded that they cannot be uniquely identified.  

This project takes a novel approach, integrating microarray-based protein sample presentation with imaging mass spectrometry. This workflow intrinsically supports high throughput workflows and accommodates low sample quantity. The microarray format allows large numbers of replicates and discrete sample formulations to be created and controlled degradation conditions to be applied across hundreds of samples. Imaging mass spectrometry is optimised for recovering mass spectra pixel-by-pixel from two-dimensional samples on surfaces. The resulting comprehensive and large-scale data sets – paired with existing proteomics databases – are very well suited to training high-quality machine learning models to visualise, classify and identify protein and peptide species within the limits imposed by sample quantity and quality. Using clustering techniques also provides a visualisation of relationships between samples, providing indications of similar samples, even where exact matches are not possible for highly compromised sample sets.