Inter-sample contamination detection using mixture deconvolution comparison

© 2019 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2019) in accordance with the publisher’s archiving policyA recent publication has provided the ability to compare two mixed DNA profiles and consider their probability of occurrence if they do, compared to if they do not, have a common contributor. This ability has applications to both quality assurance (to test for sample to sample contamination) and for intelligence gathering purposes (did the same unknown offender donate DNA to multiple samples). We use a mixture to mixture comparison tool to investigate the prevalence of sample to sample contamination that could occur from two laboratory mechanisms, one during DNA extraction and one during electrophoresis. By carrying out pairwise comparisons of all samples (deconvoluted using probabilistic genotyping software STRmix™) within extraction or run batches we identify any potential common DNA donors and investigate these with respect to their risk of contamination from the two proposed mechanisms. While not identifying any contamination, we inadvertently find a potential intelligence link between samples, showing the use of a mixture to mixture comparison tool for investigative purposes

Evaluating forensic biology results given source level propositions

The evaluation of forensic evidence can occur at any level within the hierarchy of propositions depending on the question being asked and the amount and type of information that is taken into account within the evaluation. Commonly DNA evidence is reported given propositions that deal with the sub-source level in the hierarchy, which deals only with the possibility that a nominated individual is a source of DNA in a trace (or contributor to the DNA in the case of a mixed DNA trace). We explore the use of information obtained from examinations, presumptive and discriminating tests for body fluids, DNA concentrations and some case circumstances within a Bayesian network in order to provide assistance to the Courts that have to consider propositions at source level. We use a scenario in which the presence of blood is of interest as an exemplar and consider how DNA profiling results and the potential for laboratory error can be taken into account. We finish with examples of how the results of these reports could be presented in court using either numerical values or verbal descriptions of the results

RELATE comparison of Bray-Curtis similarity matrices.

<p>The Bray-Curtis similarity matrices calculated from square root transformed abundance of DNA fragments generated based on full datasets and sub-sampled datasets.</p

Induction of Cytochrome P450 CYP3A by St John's Wort in the Rat Liver and Intestine

It has been well reported that complementary medicines can significantly alter the way the body handles conventional drugs, leading to potential fatal herb-drug interactions. The aim of the present study was to investigate the molecular mechanism of drug interactions involving St John's wort (SJW) (Hypericum perforatum L) , a popular herbal medicine widely used for depression, particularly examining changes in the expression of cytochrome P450 CYP3A, the most abundant drug metabolising CYP enzymes in man. Eighteen Sprague-Dawley (SD) rats were assigned randomly into 3 groups (n = 6/group): control, low dose and high dose (500 and 1000 mg/kg/day of SJW, equal to 1500 and 3000 µg/kg/day of Hypericin). Each group was treated with SJW or control preparation, by gastric gavage, for 14 consecutive days. Liver and intestinal CYP3A activity and protein and mRNA levels, from five segments of the intestine, were examined using CYP3A-dependent erythromycin N-demethylation activity assay, quantitative immuno-blotting and real-time RT-PCR. Increase in CYP3A activity and protein level by SJW was observed in some intestinal regions, with a 3.0 fold increase in liver CYP3A activity and a 10.6 fold increase in liver CYP3A1 mRNA (p < 0.05) in a dose dependent manner. The results suggested that up regulation of liver CYP3A mRNA and differential induction of intestinal CYP3A play an important role in the molecular mechanism of herb-drug interactions

Inter-sample contamination detection using mixture deconvolution comparison

© 2019 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2019) in accordance with the publisher’s archiving policyA recent publication has provided the ability to compare two mixed DNA profiles and consider their probability of occurrence if they do, compared to if they do not, have a common contributor. This ability has applications to both quality assurance (to test for sample to sample contamination) and for intelligence gathering purposes (did the same unknown offender donate DNA to multiple samples). We use a mixture to mixture comparison tool to investigate the prevalence of sample to sample contamination that could occur from two laboratory mechanisms, one during DNA extraction and one during electrophoresis. By carrying out pairwise comparisons of all samples (deconvoluted using probabilistic genotyping software STRmix™) within extraction or run batches we identify any potential common DNA donors and investigate these with respect to their risk of contamination from the two proposed mechanisms. While not identifying any contamination, we inadvertently find a potential intelligence link between samples, showing the use of a mixture to mixture comparison tool for investigative purposes

Results of CAP model cross-validation of soil metabolic profiles discrimination generated from full sequencing datasets.

<p>Results of CAP model cross-validation of soil metabolic profiles discrimination generated from full sequencing datasets.</p

Random Whole Metagenomic Sequencing for Forensic Discrimination of Soils

<div><p>Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.</p></div