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Sexual assault sample processing, despite recent funding and research efforts, remains time-consuming, labourious, and inefficient. These limitations, combined with the prevalence of sexual assaults, have prompted the need to develop a cheaper, quicker, and more robust method for separating victim and perpetrator contributions within sexual assault evidence so that analysts can keep pace with submissions and cases can be resolved in a timely manner. Thus, this study examined the use of a combined enzymatic and alkaline approach for differential cell lysis-with the goal of developing a quick, cheap, and more efficient DNA isolation method. Quantification results for this assay revealed that (72.0 ± 18.3)%, (15.8 ± 14.2)%, and (29.5 ±  23.7)% of total DNA were retained in sperm fractions for neat semen, neat vaginal, and semen-vaginal mixture eluates, respectively. Short tandem repeat (STR) analysis of mixture samples processed with this technique exhibited sperm fraction DNA profiles with mean male-to-female ratios of 1.74:1, which was a 3.01 ± 2.30-fold improvement in male-to-female ratios and led to the recovery of 5.90 ± 7.80 unshared male contributor alleles in sperm fractions that were otherwise undetected in unseparated controls. Overall, this study presented a modified differential lysis approach using GEM™ and sodium hydroxide treatments that can accomplish cell elution and fractional lysis within 25 min. Future studies should investigate alternative \"non-sperm\" cell lysis methods to enhance lysis efficiency and minimize the potential for inhibition, as well as the optimization and automation of this technique. Traditional sexual assault sample processing methods are time-consuming and inefficient.This modified differential lysis method produces lysates with sufficient DNA yield and quality.A combined technique using enzymatic and alkaline lysis can accomplish fractional separation.Lysis with GEM and NaOH absent purification is compatible with downstream processes.

Although guidelines exist for identifying mixtures, these measures often occur at the end-point of analysis and are protracted. To facilitate early mixture detection, we integrated a high-resolution melt (HRM) mixture screening assay into the qPCR step of the forensic workflow, producing the integrated QuantifilerTM Trio-HRM assay. The assay, when coupled with a prediction tool, allowed for 75.0% accurate identification of the contributor status of a sample (single source vs. mixture). To elucidate the limitations of the developed qPCR-HRM assay, developmental validation studies were conducted assessing the reproducibility and samples with varying DNA ratios, contributors, and quality. From this work, it was determined that the integrated QuantifilerTM Trio-HRM assay is capable of accurately identifying mixtures with up to five contributors and mixtures at ratios up to 1:100. Further, the optimal performance concentration range was found to be between 0.025 and 0.5 ng/µL. With these results, evidentiary-like DNA samples were then analyzed, resulting in 100.0% of the mixture samples being accurately identified; furthermore, every time a sample was predicted as a single source, it was true, giving confidence to any single-source calls. Overall, the integrated QuantifilerTM Trio-HRM assay has exhibited an enhanced ability to discern mixture samples from single-source samples at the qPCR stage under commonly observed conditions regardless of the contributor’s sex.

Despite the improvements in forensic DNA quantification methods that allow for the early detection of low template/challenged DNA samples, complicating stochastic effects are not revealed until the final stage of the DNA analysis workflow. An assay that would provide genotyping information at the earlier stage of quantification would allow examiners to make critical adjustments prior to STR amplification allowing for potentially exclusionary information to be immediately reported. Specifically, qPCR instruments often have dissociation curve and/or high-resolution melt curve (HRM) capabilities; this, coupled with statistical prediction analysis, could provide additional information regarding STR genotypes present. Thus, this study aimed to evaluate Qiagen’s principal component analysis (PCA)-based ScreenClust ® HRM ® software and a linear discriminant analysis (LDA)-based technique for their abilities to accurately predict genotypes and similar groups of genotypes from HRM data. Melt curves from single source samples were generated from STR D5S818 and D18S51 amplicons using a Rotor-Gene ® Q qPCR instrument and EvaGreen ® intercalating dye. When used to predict D5S818 genotypes for unknown samples, LDA analysis outperformed the PCA-based method whether predictions were for individual genotypes (58.92% accuracy) or for geno-groups (81.00% accuracy). However, when a locus with increased heterogeneity was tested (D18S51), PCA-based prediction accuracy rates improved to rates similar to those obtained using LDA (45.10% and 63.46%, respectively). This study provides foundational data documenting the performance of prediction modeling for STR genotyping based on qPCR-HRM data. In order to expand the forensic applicability of this HRM assay, the method could be tested with a more commonly utilized qPCR platform.

Although guidelines exist for identifying mixtures, these measures often occur at the end-point of analysis and are protracted. To facilitate early mixture detection, we integrated a high-resolution melt (HRM) mixture screening assay into the qPCR step of the forensic workflow, producing the integrated Quantifiler[sup.TM] Trio-HRM assay. The assay, when coupled with a prediction tool, allowed for 75.0% accurate identification of the contributor status of a sample (single source vs. mixture). To elucidate the limitations of the developed qPCR-HRM assay, developmental validation studies were conducted assessing the reproducibility and samples with varying DNA ratios, contributors, and quality. From this work, it was determined that the integrated Quantifiler[sup.TM] Trio-HRM assay is capable of accurately identifying mixtures with up to five contributors and mixtures at ratios up to 1:100. Further, the optimal performance concentration range was found to be between 0.025 and 0.5 ng/µL. With these results, evidentiary-like DNA samples were then analyzed, resulting in 100.0% of the mixture samples being accurately identified; furthermore, every time a sample was predicted as a single source, it was true, giving confidence to any single-source calls. Overall, the integrated Quantifiler[sup.TM] Trio-HRM assay has exhibited an enhanced ability to discern mixture samples from single-source samples at the qPCR stage under commonly observed conditions regardless of the contributor’s sex.

Although guidelines exist for identifying mixtures, these measures often occur at the end-point of analysis and are protracted. To facilitate early mixture detection, we integrated a high-resolution melt (HRM) mixture screening assay into the qPCR step of the forensic workflow, producing the integrated Quantifiler Trio-HRM assay. The assay, when coupled with a prediction tool, allowed for 75.0% accurate identification of the contributor status of a sample (single source vs. mixture). To elucidate the limitations of the developed qPCR-HRM assay, developmental validation studies were conducted assessing the reproducibility and samples with varying DNA ratios, contributors, and quality. From this work, it was determined that the integrated Quantifiler Trio-HRM assay is capable of accurately identifying mixtures with up to five contributors and mixtures at ratios up to 1:100. Further, the optimal performance concentration range was found to be between 0.025 and 0.5 ng/µL. With these results, evidentiary-like DNA samples were then analyzed, resulting in 100.0% of the mixture samples being accurately identified; furthermore, every time a sample was predicted as a single source, it was true, giving confidence to any single-source calls. Overall, the integrated Quantifiler Trio-HRM assay has exhibited an enhanced ability to discern mixture samples from single-source samples at the qPCR stage under commonly observed conditions regardless of the contributor's sex.

In recent years, DNA analysis techniques have drastically increased in sensitivity, allowing for low template DNA samples to be more easily detected and used for identification. Since the problems inherent in low template DNA are exacerbated in DNA mixture samples, it would be advantageous to incorporate an assay earlier in the DNA workflow that could detect a mixture and, potentially, determine the number of contributors. Some real-time PCR instruments have high-resolution melt curve analysis (HRM) capabilities, allowing for an opportunity to integrate an HRM screening assay into a commercial DNA quantification kit. This work describes the integration of a mixture screening HRM assay using STR loci D5S818 and D18S51 into Qiagen’s Investigator Quantiplex ® kit. The integrated Quantiplex ® -HRM assay was tested on two qPCR platforms: The Rotor-Gene ® Q and the QuantStudio™ 6 Flex. Data from this assay was analyzed using linear discriminant and support vector machine analyses for sample classification. When HRM curve data from the Rotor-Gene ® Q was used for classification, the integrated assay exhibited an overall accuracy of 89.39%, correctly classifying 87.5% of single source samples and 100% of mixtures. When HRM curve data from the QuantStudio™ 6 Flex was used for classification, the integrated assay exhibited an overall accuracy of 87.88%, correctly classifying 87.5% of single source samples and 90% of mixtures. The overall accuracy of the integrated Quantiplex ® -HRM assay on both instruments met our goal of ≥ 80% accuracy, demonstrating the viability of the assay to detect mixtures when integrated into a commercial quantification kit.

At present, the forensic DNA workflow is not capable of providing information about the contributor status (single source vs. multiple contributors) of evidentiary samples prior to end-point analysis. This exacerbates the challenges inherent to mixtures and low-template DNA samples. If additional sample information could be provided earlier in the workflow, protocols could be implemented to mitigate these challenges. An integrated Quantiplex®- high resolution melt (HRM) assay was shown to be effective in distinguishing between single source and mixture DNA samples; however, integration of the HRM assay into a more commonly used chemistry would be beneficial to the practitioner community. Thus, the assay was redesigned as an integrated Quantifiler™ Trio-HRM assay, which included the identification of a new DNA-binding dye, an increased reaction volume, and the establishment of new data analysis and standard curve metrics for all targets. This redesigned assay produced quantification values and qualitative values that were comparable to those produced when the same samples were tested using the standard Quantifiler™ Trio chemistry and settings. Further, STR profiles generated with quantification values produced from the integrated Quantifiler™ Trio-HRM assay and standard Quantifiler™ Trio chemistry were complete and fully concordant. Most importantly, the integrated Quantifiler™ Trio-HRM assay was able to accurately predict whether a sample was single source or a mixture 79.2% of the time, demonstrating the potential of this approach. With the incorporation of an expanded training set for prediction modeling, and completion of critical developmental validation studies, this assay could prove useful to the forensic DNA practitioner community.