Body fluid prediction from microbial patterns for forensic application.

Area of Science:

• Forensic Science
• Microbiology
• Genetics

Background:

• Accurate body fluid identification is crucial for biological evidence evaluation in forensic science.
• Current presumptive tests for body fluids have limitations.
• Gene expression analysis is a common method for body fluid prediction, but novel approaches are needed.

Purpose of the Study:

• To introduce a novel method for body fluid prediction using microbial taxonomic profiles.
• To evaluate the effectiveness of 16S rRNA gene sequencing for identifying saliva on skin.
• To explore the potential of microbial profiles as a forensic tool.

Main Methods:

• Utilized standard 16S rRNA gene sequencing to obtain microbial taxonomic profiles.
• Applied pattern recognition techniques, including principal component analysis and linear discriminant analysis, for classification.
• Used saliva deposited on skin as a forensically relevant model system.

Main Results:

• The novel method successfully classified samples of saliva on skin versus pure skin samples with 94% accuracy.
• A significant person-effect was observed, particularly from skin samples, suggesting reference samples could improve accuracy.
• The study demonstrated the potential of microbial profiles for body fluid prediction.

Conclusions:

• Microbial taxonomic profiles offer a promising new avenue for body fluid prediction in forensic science.
• The method shows high accuracy in distinguishing saliva from skin, with potential for broader application to other body fluids.
• Further optimization of pattern recognition methods and incorporation of person-specific reference samples could enhance the forensic utility of this approach.