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Front-end differentiation of contributor cell populations and estimation of DNA content in trace biological samples using novel cellular signatures

Award Information

Award #
2020-DQ-BX-0023
Location
Congressional District
Status
Open
Funding First Awarded
2020
Total funding (to date)
$382,296

Description of original award (Fiscal Year 2020, $382,296)

The objective of this project is to develop a new method for screening trace biological samples for the number of contributors and DNA content based on the presence and relative abundance of key protein and hormone targets within cell populations. There is a critical need for presumptive techniques that could provide valuable information and enable more effective triaging of casework samples, particularly touch samples. Currently, blind sampling of potential epithelial trace/touch samples as well as the often daunting mixture interpretation present many challenges for caseworking laboratories. To address this, we have developed a novel workflow for analyzing biological evidence samples that (1) estimates the number of contributors in a mixture based upon flow cytometry histogram profiles, (2) estimates the human-specific DNA content in the sample based upon fluorescent signal intensities, and (3) differentiates cell populations in the mixture based on contributor-specific attributes. Our method utilizes signatures based on the abundance of specific molecular targets that are present within the cell (e.g., cytokeratin alleles and hormone molecules) that can be easily labelled with molecular probes. Information from probe binding is combined with intrinsic morphological attributes of the cells to enhance contributor cell differentiation. The primary advantage of this approach for forensic DNA casework is that all aspects of the workflow are inherently non-destructive, which is ideal for evidence samples since these are typically compromised and low in template quantity. Our specific aims include development of (1) probe labelling protocols for detection and differentiation of contributor cell populations (Phase I), (2) quantitative frameworks for estimating the number of contributors based on probe binding and fluorescence profiles (Phase I), (3) a workflow for predicting DNA content based on probe binding and fluorescence profiles (Phase II), and (4) protocols for separating contributor cell populations following probe binding/separation (Phase II). The expected outcomes for this project include peer-reviewed manuscripts that present project results and applications for forensic casework as well as an internal validation of the workflow on mock casework samples. All project activities will be performed collaboratively between Virginia Commonwealth University and the Virginia Department of Forensic Science. This research will provide a new high-throughput, non-destructive method for presumptively characterizing cell mixtures and predicting DNA content in trace/touch DNA samples. This has the potential to increase the probative value of many types of mixture samples in forensic casework and reduce analytical bottlenecks associated with sample processing and complicated interpretation protocols for DNA mixtures. Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF

Date Created: October 22, 2020