DOI

https://doi.org/10.25772/ZER2-MS76

Author ORCID Identifier

0000-0002-8251-1095

Defense Date

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Integrative Life Sciences

First Advisor

Sarah Seashols-Williams

Abstract

Body fluid identification is essential in the forensic biology workflow that assists DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the sensitivity and specificity molecular techniques can achieve; therefore, molecular methods, such as microRNA and microbial signatures, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase discrimination efficiency of multiple body fluids from a single assay. While microbial signatures have been successful in identifying fluids with high bacterial abundances, microRNAs have shown promise in fluids with low microbial abundance. A disadvantage of RNA analysis in forensic casework is RNA extraction; however, several reports have demonstrated that microRNAs co-extract with DNA, increasing implementation potential. This project synergized on the benefits of microRNAs and microbial DNA to identify body fluids using DNA extracts. First, microRNA detection in DNA extracts was confirmed, demonstrating that RNA extraction and DNase-treatment are not necessary. A reverse transcription (RT)-qPCR duplex targeting miR-891a and let-7g was validated, with significantly different relative expression observed between blood and semen. Lastly, a qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius, was designed to identify vaginal/menstrual secretions, feces, and saliva, respectively. The developed classification regression tree model that classified five body fluids with 94.6% overall accuracy, providing proof of concept that microRNAs and microbial DNA can identify multiple body fluids at the quantification step of the current forensic DNA workflow.

Rights

© Carolyn A. Lewis

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

12-20-2021

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