Is it possible to predict the origin of epithelial cells? – A comparison of secondary transfer of skin epithelial cells versus vaginal mucous membrane cells by direct contact

Transfer, persistence and recovery of DNA and mRNA vaginal mucosa markers after intimate and social contact with Bayesian network analysis for activity level reporting

In sexual assault cases, it can be challenging to identify the type of body fluids/ cell types present in a crime scene sample, especially the origin of epithelial cells. Therefore, more labs are applying mRNA body fluid analysis for saliva, skin and vaginal mucosa markers. To address activity level propositions, it is necessary to assign probabilities of transfer, persistence, prevalence and recovery of DNA and mRNA markers. In this study we analysed 158 samples (fingernail swabs, penile swabs and boxershorts) from 12 couples collected at different time points post intimate contact and after non-intimate contact in order to detect DNA from the person of interest (POI) and mRNA vaginal mucosa markers. Samples were DNA and RNA co-extracted and analysed with PowerPlex®Fusion 6C System and 19-plex mRNA primer mix respectively, using Endpoint PCR and the CE platform. Vaginal mucosa was detected up to 36 h post intimate contact, but also detected in one non-intimate contact sample. In 94% of intimate contact and 50 % of non-intimate contact samples the DNA results support the proposition that POI is the donor (LR ≥ 10,000). There was a strong association between the detection of vaginal mucosa and the average RFU value of the POI. The data were used to instantiate a comprehensive Bayesian network to evaluate the evidence at activity level, given alternate propositions conditioned upon indirect or direct transfer events. It is shown that the value of the evidence is mainly affected by the high DNA quantity (measured as mean RFU) that is recovered from the POI. The detection of vaginal mucosa had low impact upon the resultant likelihood ratio.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.

An LR framework incorporating sensitivity analysis to model multiple direct and secondary transfer events on skin surface

Bayesian logistic regression is used to model the probability of DNA recovery following direct and secondary transfer and persistence over a 24 h period between deposition and sample collection. Sub-source level likelihood ratios provided the raw data for activity-level analysis. Probabilities of secondary transfer are typically low, and there are challenges with small data-sets with low numbers of positive observations. However, the persistence of DNA over time can be modelled by a single logistic regression for both direct and secondary transfer, except that the time since deposition must be compensated by an offset value for the latter. This simplifies the analysis. Probabilities are used to inform an activity-level Bayesian Network that takes account of alternative propositions e.g. time of assault and time of social activities. The model is extended in order to take account of multiple contacts between person of interest and 'victim'. Variables taken into account include probabilities of direct and secondary transfer, along with background DNA from unknown individuals. The logistic regression analysis is Bayesian - for each analysis, 4000 separate simulations were carried out. Quantile assignments enable calculation of a plausible range of probabilities and sensitivity analysis is used to describe the corresponding variation of LRs that occur when modelled by the Bayesian network. It is noted that there is need for consistent experimental design, and analysis, to facilitate inter-laboratory comparisons. Appropriate recommendations are made. The open-source program written in R-code ALTRaP (Activity Level, Transfer, Recovery and Persistence) enables analysis of complex multiple transfer propositions that are commonplace in cases-work e.g. between those who cohabit. A number of case examples are provided. ALTRaP can be used to replicate the results and can easily be modified to incorporate different sets of data and variables.

Application of fragment analysis based on methylation status mobility difference to identify vaginal secretions

Identifying vaginal secretions attaching or adhering to a suspect's belongings would be beneficial for reconstructing the events that have taken place during a sexual assault. The present study describes a novel approach to identify vaginal secretions by fragment analysis using capillary electrophoresis, based on the mobility differences of PCR amplicons from bisulfite-treated DNA depending on methylation status. We targeted three genome regions including each of three vaginal secretion-specific methylated CpG sites reported previously: cg25416153, cg09765089, and cg14991487. In all three genome regions, the amplicon peaks for methylated genomic DNA (gDNA) sequences were only detected in vaginal samples, whereas samples of other body fluids (blood, saliva, semen, and deposit on skin surface) only showed amplicon peaks for unmethylated gDNA sequences. In vaginal secretions, the methylation ratio of each of the three targeted regions between samples was variable, while the ratios at the three regions in each sample were similar. Furthermore, commercial vaginal epithelial cells were completely methylated at the three regions. Therefore, vaginal secretion-specific methylation may derive from vaginal epithelial cells present in the sample. In forensic cases with a limited amount of DNA, the reproducibility of a detected peak using the present method is not high due to degradation of DNA by bisulfite treatment and subsequent stochastic PCR bias. However, it was possible to detect peaks from methylated DNA sequences by performing PCR and capillary electrophoresis in triplicate after bisulfite treatment, even when bisulfite treatment was performed using 0.5 ng of gDNA from vaginal secretions. In addition, the level of methylation at each targeted region was found to be stable in vaginal secretions stored for 1 year at room temperature. Therefore, we conclude that detection of the visual peak from vaginal secretion-specific methylated DNA sequence is useful to prove the presence of vaginal secretions. This approach has the potential to analyze multiple marker regions simultaneously, and may provide a new multiplex assay to identify various body fluids.

Letter to the Editor: Commentary on "Is it possible to predict the origin of epithelial cells? - A comparison of secondary transfer of skin epithelial cells versus vaginal mucous membrane cells by direct contact, M.M. Bouzga et al., Science &Justice, https://doi.org/10.1016/j.scijus.2020.02.003"

This letter to the Editor comments on the paper "Is it possible to predict the origin of epithelial cells? - A comparison of secondary transfer of skin epithelial cells versus vaginal mucous membrane cells by direct contact" by M.M. Bouzga et al. (Science &Justice,https://doi.org/10.1016/j.scijus.20al.20.02.003).