Sarah J. Seashols-Williams

Advances in DNA technology have significantly enhanced the forensic community's ability to develop genetic profiles from unidentified human skeletal remains. However, sampling requires mechanical grinding of hard tissues before DNA isolation. This processing can compromise genetic profiles, particularly in aged bones. We compared the industry‐standard pulverization method with an alternative powder‐free preparation involving prolonged demineralization and subsequent slicing of 19th‐century cortical bone. Data from DNA quantification, STR genotyping, and targeted SNP sequencing were used to evaluate powdered samples versus demineralized slices from paired human bones. Average human DNA yields for pulverized samples and demineralized slices were 0.032 ng and 0.692 ng, respectively. Demineralized slices recovered more amplifiable DNA than traditional homogenization methods ( p < 0.05). No pulverized samples produced STR profiles, whereas demineralized slices from the same bone samples yielded partial profiles. Samples underwent DNA repair, library preparation, and hybridization capture using the FORensic Capture Enrichment (FORCE) panel. Applying low‐coverage (1X) analysis of high‐throughput sequencing (HTS) data, demineralized slices outperformed those prepared by traditional pulverization methods ( p < 0.05) and substantially increased the information recovered compared with conventional STR analysis methods. Based on HTS data from pulverized samples, DNA fragment length ranged from 27 to 95 bp, and FORCE SNP recovery was 33.23%. In contrast, for demineralized slices, DNA fragment length ranged from 85 to 114 bp, and FORCE SNP recovery was 83.24%. The required reagents and equipment are typically available in forensic labs, and the workflow outlined herein significantly increases the success of DNA recovery from challenging skeletal samples.

When sexual assault evidence kits do not yield biological evidence demonstrating sexual contact, clothing such as undergarments is evaluated for the presence of semen. Menstrual underwear is a new type of undergarment and feminine product encountered as evidence in sexual assaults. They are composed of absorbent and leak‐proof layers and can be washed and re‐worn multiple times. The objective of this work was to determine a best practice for semen and DNA recovery from reusable menstrual underwear. Simulated postcoital samples were deposited on three different brands of menstrual underwear, and alternate light source evaluation failed for two of the three brands tested, though acid phosphatase testing was positive for all three brands tested. Testing of individual layers versus cuttings of a portion of the stain found that a full‐depth cutting results in optimal biological sample recovery. Mock postcoital deposits were then washed once or twice and subjected to serological and DNA workflows, with varying results in acid phosphatase and P30 testing after washing once or twice between brands. However, sperm recovery was successful in all samples, and complete short tandem repeat (STR) profiles were obtained from both sperm and nonsperm fractions from all samples, regardless of washing status. With these findings, while sperm recovery has the highest likelihood of success with a full‐thickness cutting, forensic scientists should be cautious in depending on ALS for stain location. Additionally, biological materials remain in these brands of menstrual underwear after washing, and therefore, biological material from previous sexual contact could remain and be detectable.

Current processing techniques for harvesting DNA from osseous elements are destructive, and success rates vary widely. When skeletal elements are homogenized into a fine powder, endogenous DNA may be subjected to fragmentation, and the likelihood of introducing co‐purified inhibitory substances to the sample increases. While a limited number of articles in the relevant literature have challenged the status quo of pulverization, powdering hard tissue samples before DNA isolation continues to be standard practice in the forensic and ancient DNA communities. In this work, we have developed and optimized an alternative front‐end processing method for demineralizing and slicing cortical bone using aged and weathered bovine skeletal samples as a model for degraded human bone. Additionally, this study evaluated the enzymatic digestion of demineralized bone slices using collagenase I as a powder‐free alternative for cell isolation. The efficacy of pulverization, demineralized slices, and collagenase‐digested demineralized slices was assessed via DNA quantitation and STR profile data. The combined treatment incorporating collagenase digestion of demineralized slices did not improve the recovery of endogenous DNA yields or STR profile development; however, profiles developed from demineralized slices retained a significantly greater percentage of expected alleles and higher peak heights than samples processed with conventional powdering and organic chemistry extraction. By eliminating pulverization of bone and employing modified silica‐based extraction chemistry, the susceptibility to inhibitory and competitive effects from native and foreign components often found in degraded skeletal remains can be minimized when utilizing total demineralization of small fragments with subsequent slicing before lysis.

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.

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^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^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^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.

Body fluid identification is an essential step in the forensic biology workflow that can assist DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the specificity that molecular techniques can achieve; therefore, molecular methods, including microRNA (miRNA) and microbial signature characterization, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase the 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 (blood and semen). This project synergized the benefits of microRNAs and microbial DNA to identify multiple body fluids using DNA extracts. A reverse transcription (RT)‐qPCR duplex targeting miR‐891a and let‐7g was validated, and miR‐891a differential expression was significantly different between blood and semen. The miRNA duplex was incorporated into a previously reported qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius to presumptively identify vaginal/menstrual secretions, feces, and saliva, respectively. The combined classification regression tree model resulted in the presumptive classification of five body fluids with 94.6% overall accuracy, now including blood and semen identification. These results provide proof of concept that microRNAs and microbial DNA can classify multiple body fluids simultaneously at the quantification step of the current forensic DNA workflow.

Optical tweezers have a wide range of uses for mechanical manipulation of objects in the microscopic range. This includes both living and static cells in a variety of biomedical and research applications. Single‐focus optical tweezers, formed by focusing a laser beam through a high numerical aperture immersion objective, create a significant force, which enables controlled transport of a variety of different cell types and morphologies in three dimensions. Optical tweezers have been previously reported to capture and separate spermatozoa from a reconstituted simulated postcoital sample. We report herein the development of a simplified, more efficient cell transfer protocol that can separate and isolate both spermatozoa as well as leukocytes, with similar efficiencies as those previously reported. The new cell transfer method was used to separate sperm cells from a reconstituted mixture of spermatozoa and vaginal epithelial cells, with complete STR profiles developed from 50 cells with little evidence of contribution from the female contributor to the mixture. This modified protocol was then used to separate 21 samples of enriched leukocytes, with trapped cells ranging from 5 to 22 cells. Complete STR profiles were developed from as few as 10 leukocytes. Thus, with minimal sample preparation and a short trapping time, this method has the potential to provide an alternative to traditional differential extraction methods for separation of sperm:nonsperm mixtures while also providing versatility for separation of cells with differing morphologies.

There is significant interest in the use of miRNA analysis for forensic body fluid identification. Demonstrated co-extraction and detection in DNA extracts could make the use of miRNAs a more streamlined molecular body fluid identification method than other RNA-based methods. We previously reported a reverse transcription-quantitative PCR (RT-qPCR) panel of eight miRNAs that classified venous and menstrual blood, feces, urine, saliva, semen, and vaginal secretions using a quadratic discriminant analysis (QDA) model with 93% accuracy in RNA extracts. Herein, miRNA expression in DNA extracts from 50 donors of each body fluid were tested using the model. Initially, a classification rate of 87% was obtained, which increased to 92% when three additional miRNAs were added. Body fluid identification was found to be reliable across population samples of mixed ages, ethnicities, and sex, with 72–98% of the unknown samples classifying correctly. The model was then tested against compromised samples and over biological cycles, where classification accuracy varied, depending on the body fluid. In conclusion, we demonstrated the ability to classify body fluids using miRNA expression from DNA extracts, eliminating the need for RNA extraction, greatly reducing evidentiary sample consumption and processing time in forensic laboratories, but acknowledge that compromised semen and saliva samples can fail to classify properly, and mixed sample classification remains untested and may have limitations.