The Identification of Biological Stains at Crime Scenes: A Promising Role for Proteomics and Machine Learning

Forensic body fluid identification is crucial for reconstructing
crime scene events. While DNA analysis provides individualization,
it lacks information about the fluid’s origin. We developed
and evaluated three complementary proteomic approaches using LC-HRMS/MS
to identify blood, saliva, semen, urine, and vaginal fluid, including
complex mixtures. The first method utilized fluid-specific peptide
biomarkers, achieving high accuracy for pure fluids. The second employed
peptide abundance ratios, demonstrating effectiveness in body fluid
mixtures. The third, a machine learning model using Classifier Chain
Random Forest, achieved 100% accuracy for pure fluids and promising
results for mixtures. Our results revealed the complementarity of
different tests, with the peptide-specific biomarker and machine-learning
approaches being the most robust. This study demonstrates the potential
of proteomics for comprehensive body fluid identification, offering
valuable tools for forensic investigations.