Previewing the Posters of our ISHI Student Ambassadors: Chastyn Smith – ISHI News

Oct 11 2022

Previewing the Posters of our ISHI Student Ambassadors: Chastyn Smith

DNA MixturesForensic

Analysis of evidentiary samples containing DNA from multiple contributors (“mixtures”) is a time intensive process for a forensic analyst and one where the contributor nature of a sample is not revealed until the end of the traditional forensic workflow. Often, at this stage, retesting or additional testing of mixture samples may not be possible, particularly if only trace amounts of a
contributor’s DNA is present. Thus, a new method that would allow for the quick and accurate identification of single source (versus mixture) samples, prior to the end-point of STR analysis would be beneficial.

 

To meet this need, an HRM screening assay has been developed and integrated into an existing step in the laboratory evidence workflow – the real-time PCR-based DNA quantification step. Using the developed assay, resulting HRM data is coupled with prediction modeling approaches to allow for the contributor status of an evidence item to be identified and a genetic comparison to be made without additional steps or delays in processing.

 

ISHI Student Ambassador, Chastyn Smith will be presenting on the above during her poster presentation at ISHI 33 this month. We chatted with her to learn a little more, and if you’ll be at the conference, be sure to stop by poster #56 to learn more!

 

 

Briefly describe your work/area of interest.

Analysis of evidentiary samples containing DNA from multiple contributors (“mixtures”) is a time intensive process for a forensic analyst and one where the contributor nature of a sample is not revealed until the end of the traditional forensic workflow. Often, at this stage, retesting or additional testing of mixture samples may not be possible, particularly if only trace amounts of a contributor’s DNA is present. Thus, a new method that would allow for the quick and accurate identification of single source (versus mixture) samples, prior to the end-point of STR analysis would be beneficial. To meet this need, an HRM screening assay has been developed and integrated into an existing step in the laboratory evidence workflow – the real-time PCR-based DNA quantification step.

Key collaborators on the project include Dayanara Torres, M.S., Andrea Williams, M.S., Sarah Seashols Williams, Ph.D., Edward Boone, Ph.D, and Tracey Dawson Green, Ph.D.

Using the developed assay, resulting HRM data is coupled with prediction modeling approaches to allow for the contributor status of an evidence item to be identified and a genetic comparison to be made without additional steps or delays in processing. The developed integrated quantification-HRM mixture screening assay adds two new amplification targets (STR loci D5S818 and D18S51) and an intercalating dye into two existing commercial human DNA quantification chemistries, the Investigator Quantiplex® kit and Quantifiler™ Trio kit, which is then used in combination with added transition and melt steps post-amplification on the QuantStudio™ 6 Flex. In the current study, ~170 single source samples and 32 two-person mixture samples were tested using both the integrated Quantiplex®-HRM assay and Quantifiler™ Trio-HRM assay, then the entire HRM datasets were exported for prediction modeling using both LDA and support vector machine (SVM) algorithms in R Studio software. For proof-of-concept, only 8 different genotypes, including a genotype of “mixture”, were represented (for each locus) in testing. A portion of the samples tested were used to “train” the software and the remaining sample data was used as unknowns (or “validation”) samples for prediction.

When samples were tested in the Quantiplex®- HRM assay, an overall accuracy of 87.88% was exhibited, correctly classifying 87.5% of single source samples as such and 90% of mixture samples. Similarly, when samples were tested in the Quantifiler™ Trio-HRM assay an overall accuracy of 79.2% was exhibited, with 89.2% of single source samples accurately classifying and 43.8% of mixtures accurately classifying. Additionally, quantification values obtained from the integrated assays as well as the quality metrics such as the slope, R2, and y-intercept, were not significantly different than those obtained in the standard assays.

 

How did you get interested in this work? Why did this particular project appeal?

At the time that I joined my lab there were two major projects being worked on and honestly, I didn’t have a preference for which project I got involved with I was just excited to finally be involved with forensics! I loved doing research and this was going to be my first forensic research project that was all mine, so I was just eager to get started! To me though, this project is appealing because of how direct and lucid the final product of this research will be. We’re talking about a low effort but big impact solution to a major problem in the forensic DNA field.

 

Can you summarize the impact of your work for the audience (ISHI attendees and some general forensic enthusiasts)? How might this advance the field? 

Ultimately, we aim to provide an easy-to-use, free, on-line tool for quick assessment of qPCR melt curve data. Upon successful validation and implementation, this tool will provide forensic examiners with a powerful way to screen and triage evidence items prior to the end point of analysis. The knowledge of the mixture status of a forensic sample is beneficial as it allows for procedural modifications that could further elucidate the major and minor contributor/s within a sample, to be made. Additionally, the developed tool may also provide genotype prediction information for identified single source samples. With early genotyping information from two STR loci, this assay could provide early exclusionary data – possibly preventing the need for additional labor-intensive investigations, saving investigative time. This assay will contribute to saving time and resources, which are limiting factors in forensic labs, that are consumed in the lengthy touch DNA and mixture detection, analysis and reanalysis process. Additionally, since this tool gives information into the probative, and potentially exclusionary, nature of a sample, it may also help triage which samples to move forward for STR analysis thus minimizing additional downstream work.

 

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