Determining the optimal forensic DNA analysis procedure following investigation of sample quality.

Crime scene traces of various types are routinely sent to forensic laboratories for analysis, generally with the aim of addressing questions about the source of the trace. The laboratory may choose to analyse the samples in different ways depending on the type and quality of the sample, the importance of the case and the cost and performance of the available analysis methods. Theoretically well-founded guidelines for the choice of analysis method are, however, lacking in most situations. In this paper, it is shown how such guidelines can be created using Bayesian decision theory. The theory is applied to forensic DNA analysis, showing how the information from the initial qPCR analysis can be utilized. It is assumed the alternatives for analysis are using a standard short tandem repeat (STR) DNA analysis assay, using the standard assay and a complementary assay, or the analysis may be cancelled following quantification. The decision is based on information about the DNA amount and level of DNA degradation of the forensic sample, as well as case circumstances and the cost for analysis. Semi-continuous electropherogram models are used for simulation of DNA profiles and for computation of likelihood ratios. It is shown how tables and graphs, prepared beforehand, can be used to quickly find the optimal decision in forensic casework.

Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases.

Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA polymerases: ExTaq HS and Immolase. By using Bayesian modeling, we show that there is no difference among the tested DNA polymerases in terms of accuracy of absolute quantification for pure template samples, i.e., without HA present. For samples containing HA, there were great differences in performance: the TaqMan Universal PCR Master Mix failed to correctly quantify DNA with more than 13 pg/nL HA, whereas Immolase (1 U) could handle up to 375 pg/nL HA. Furthermore, we found that BSA had a moderate positive effect for the TaqMan Universal PCR Master Mix, enabling accurate quantification for 25 pg/nL HA. Increasing the amount of DNA polymerase from 1 to 5 U had a strong effect for ExTaq HS, elevating HA-tolerance four times. We also show that the average Cq values of positive reactions may be used as a measure of inhibition effects, e.g., to determine whether or not a dPCR quantification result is reliable. The statistical models developed to objectively analyze the data may also be applied in quality control. We conclude that the choice of DNA polymerase in dPCR is crucial for the accuracy of quantification when analyzing challenging samples.

Assessing the consistency of shedder status under various experimental conditions.

Shedder status is defined as the propensity of an individual to leave DNA behind on touched items or surfaces and has been suggested as one of the major factors influencing DNA transfer. However, little is known about whether shedder status is a constant property of an individual across multiple measurements or when the environmental conditions are changed. We have assessed DNA depositions of six males on 20 occasions to acquire a reference data set and to classify the participants into high, intermediate, or low shedders. This data set was also used to investigate how the probability of a correct shedder status classification changed when the number of DNA deposition measurements increased. Individual sweat rates were measured with a VapoMeter and data regarding hygiene routines were collected through a questionnaire on each sampling occasion. Next, we investigated how changes in the experimental conditions such as seasonal variation, hygiene routines, the temperature of the touched object, and repeated handling of an object influenced the DNA shedding. Additionally, we assessed DNA collected from the face and from T-shirts worn by the six participants to explore whether shedder status may be associated with the relative amount of DNA obtained from other body parts. Our results indicate that shedder status is a stable property across different seasons and different temperatures of handled objects. The relative DNA amounts obtained from repeatedly handled tubes, worn T-shirts, and from faces reflected the shedder status of the participants. We suggest that an individual's shedder status is highly influenced by the DNA levels on other body parts than hands, accumulating on the palms by frequently touching e.g., the face or previously handled items harboring self-DNA. Assessing physiological differences between the participants revealed that there were no associations between DNA shedding and individual sweat rates.

Assessment of forensic findings when alternative explanations have different likelihoods-"Blame-the-brother"-syndrome.

Assessment of forensic findings with likelihood ratios is for several cases straightforward, but there are a number of situations where contemplation of the alternative explanation to the evidence needs consideration, in particular when it comes to the reporting of the evidentiary strength. The likelihood ratio approach cannot be directly applied to cases where the proposition alternative to the forwarded one is a set of multiple propositions with different likelihoods and different prior probabilities. Here we present a general framework based on the Bayes' factor as the quantitative measure of evidentiary strength from which it can be deduced whether the direct application of a likelihood ratio is reasonable or not. The framework is applied on DNA evidence in forms of an extension to previously published work. With the help of a scale of conclusions we provide a solution to the problem of communicating to the court the evidentiary strength of a DNA match when a close relative to the suspect has a non-negligible prior probability of being the source of the DNA.

Individual shedder status and the origin of touch DNA.

Due to improved laboratory techniques, touched surfaces and items are increasingly employed as sources of forensic DNA evidence. This has urged a need to better understand the mechanisms of DNA transfer between individuals. Shedder status (i.e. the propensity to leave DNA behind) has been identified as one major factor regulating DNA transfer. It is known that some individuals tend to shed more DNA than others, but the mechanisms behind shedder status are largely unknown. By comparing the amounts of DNA deposited from active hands (i.e. used "as usual") and inactive hands (i.e. not allowed to touch anything), we show that some of the self-DNA deposited from hands is likely to have accumulated on hands from other parts of the body or previously handled items (active hands: 2.1 ± 2.7 ng, inactive hands: 0.83 ± 1.1 ng, paired t-test: p = 0.014, n = 27 pairs of hands). Further investigation showed that individual levels of deposited DNA are highly associated with the level of DNA accumulation on the skin of the face (Pearson's correlation: r = 0.90, p < 0.00001 and Spearman's ranked correlation: rs = 0.56, p = 0.0016, n = 29). We hypothesized that individual differences in sebum secretion levels could influence the amount of DNA accumulation in facial areas, but no such correlation was seen (Pearson's correlation: r = - 0.13, p = 0.66, n = 14). Neither was there any correlation between DNA levels on hands or forehead and the time since hand or face wash. We propose that the amount of self-DNA deposited from hands is highly influenced by the individual levels of accumulated facial DNA, and that cells/DNA is often transferred to hands by touching or rubbing one's face.

Enhanced forensic DNA recovery with appropriate swabs and optimized swabbing technique.

Efficient sampling with swabs is crucial for optimal forensic DNA analysis. The DNA recovery is determined by the skill of the practitioner and the compatibility between the applied swab and the surface. Here we investigate the impact of swabbing technique and swab type on the DNA yield. Thirteen different swabs from four categories (cotton, flocked nylon, small foam and large foam) provided equal DNA yields for smooth/non-absorbing surfaces. Large foam swabs gave higher DNA recovery for an absorbing wood surface. Factorial design of experiments and ANOVA was applied to study swabbing techniques for cotton swabs. Two key factors for efficient sampling were found to be 1) holding the swab with an approximate 60° angle against the surface and 2) to rotate the swab during sampling. For absorbing wood, it was beneficial to wet the swab heavily. The results of the factorial experiments were used to develop swabbing protocols for different surfaces. When ten experienced practitioners sampled according to these protocols, the DNA yield was increased for ridged plastic (around 1.25 times more DNA) and absorbing wood (2.2-6.2 times more DNA). For window glass, representing a smooth/non-absorbing surface, sampling according to the protocol gave DNA yields equivalent to applying individual sampling techniques. The protocol lowered person-to-person variation for ridged plastic. In conclusion, we have developed instructive protocols for cotton swab sampling on three types of surfaces: smooth/non-absorbing, ridged/non-absorbing and smooth/absorbing. We believe that such swabbing protocols will streamline and simplify the training of new practitioners and improve sampling efficiency for invisible DNA residues in casework.

Surveillance of animal diseases through implementation of a Bayesian spatio-temporal model: A simulation example with neurological syndromes in horses and West Nile Virus.

A potentially sensitive way to detect disease outbreaks is syndromic surveillance, i.e. monitoring the number of syndromes reported in the population of interest, comparing it to the baseline rate, and drawing conclusions about outbreaks using statistical methods. A decision maker may use the results to take disease control actions or to initiate enhanced epidemiological investigations. In addition to the total count of syndromes there are often additional pieces of information to consider when assessing the probability of an outbreak. This includes clustering of syndromes in space and time as well as historical data on the occurrence of syndromes, seasonality of the disease, etc. In this paper, we show how Bayesian theory for syndromic surveillance applies to the occurrence of neurological syndromes in horses in France. Neurological syndromes in horses may be connected e.g. to West Nile Virus (WNV), a zoonotic disease of growing concern for public health in Europe. A Bayesian method for spatio-temporal cluster detection of syndromes and for determining the probability of an outbreak is presented. It is shown how surveillance can be performed simultaneously for a specific class of diseases (WNV or diseases similar to WNV in terms of the information available to the system) and a non-specific class of diseases (not similar to WNV in terms of the information available to the system). We also discuss some new extensions to the spatio-temporal models and the computational algorithms involved. It is shown step-by-step how data from historical WNV outbreaks and surveillance data for neurological syndromes can be used for model construction. The model is implemented using a Gibbs sampling procedure, and its sensitivity and specificity is evaluated. Finally, it is illustrated how predictive modelling of syndromes can be useful for decision making in animal health surveillance.

Detection probability models for bacteria, and how to obtain them from heterogeneous spiking data. An application to Bacillus anthracis.

Efficient and correct evaluation of sampling results with respect to hypotheses about the concentration or distribution of bacteria generally requires knowledge about the performance of the detection method. To assess the sensitivity of the detection method an experiment is usually performed where the target matrix is spiked (i.e. artificially contaminated) with different concentrations of the bacteria, followed by analyses of the samples using the pre-enrichment method and the analytical detection method of interest. For safety reasons or because of economic or time limits it is not always possible to perform exactly such an experiment, with the desired number of samples. In this paper, we show how heterogeneous data from diverse sources may be combined within a single model to obtain not only estimates of detection probabilities, but also, crucially, uncertainty estimates. We indicate how such results can then be used to obtain optimal conclusions about presence of bacteria, and illustrate how strongly the sampling results speak in favour of or against contamination. In our example, we consider the case when B. cereus is used as surrogate for B. anthracis, for safety reasons. The statistical modelling of the detection probabilities and of the growth characteristics of the bacteria types is based on data from four experiments where different matrices of food were spiked with B. anthracis or B. cereus and analysed using plate counts and qPCR. We show how flexible and complex Bayesian models, together with inference tools such as OpenBUGS, can be used to merge information about detection probability curves. Two different modelling approaches, differing in whether the pre-enrichment step and the PCR detection step are modelled separately or together, are applied. The relative importance on the detection curves for various existing data sets are evaluated and illustrated.

Enhanced low-template DNA analysis conditions and investigation of allele dropout patterns.

Forensic DNA analysis applying PCR enables profiling of minute biological samples. Enhanced analysis conditions can be applied to further push the limit of detection, coming with the risk of visualising artefacts and allele imbalances. We have evaluated the consecutive increase of PCR cycles from 30 to 35 to investigate the limitations of low-template (LT) DNA analysis, applying the short tandem repeat (STR) analysis kit PowerPlex ESX 16. Mock crime scene DNA extracts of four different quantities (from around 8-84 pg) were tested. All PCR products were analysed using 5, 10 and 20 capillary electrophoresis (CE) injection seconds. Bayesian models describing allele dropout patterns, allele peak heights and heterozygote balance were developed to assess the overall improvements in EPG quality with altered PCR/CE settings. The models were also used to evaluate the impact of amplicon length, STR marker and fluorescent label on the risk for allele dropout. The allele dropout probability decreased for each PCR cycle increment from 30 to 33 PCR cycles. Irrespective of DNA amount, the dropout probability was not affected by further increasing the number of PCR cycles. For the 42 and 84 pg samples, mainly complete DNA profiles were generated applying 32 PCR cycles. For the 8 and 17 pg samples, the allele dropouts decreased from 100% using 30 cycles to about 75% and 20%, respectively. The results for 33, 34 and 35 PCR cycles indicated that heterozygote balance and stutter ratio were mainly affected by DNA amount, and not directly by PCR cycle number and CE injection settings. We found 32 and 33 PCR cycles with 10 CE injection seconds to be optimal, as 34 and 35 PCR cycles did not improve allele detection and also included CE saturation problems. We find allele dropout probability differences between several STR markers. Markers labelled with the fluorescent dyes CXR-ET (red in electropherogram) and TMR-ET (shown as black) generally have higher dropout risks compared with those labelled with JOE (green) and fluorescein (blue). Overall, the marker D10S1248 has the lowest allele dropout probability and D8S1179 the highest. The marker effect is mainly pronounced for 30-32 PCR cycles. Such effects would not be expected if the amplification efficiencies were identical for all markers. Understanding allele dropout risks and the variability in peak heights and balances is important for correct interpretation of forensic DNA profiles.

Purification of crime scene DNA extracts using centrifugal filter devices.

BACKGROUND: The success of forensic DNA analysis is limited by the size, quality and purity of biological evidence found at crime scenes. Sample impurities can inhibit PCR, resulting in partial or negative DNA profiles. Various DNA purification methods are applied to remove impurities, for example, employing centrifugal filter devices. However, irrespective of method, DNA purification leads to DNA loss. Here we evaluate the filter devices Amicon Ultra 30 K and Microsep 30 K with respect to recovery rate and general performance for various types of PCR-inhibitory crime scene samples. METHODS: Recovery rates for DNA purification using Amicon Ultra 30 K and Microsep 30 K were gathered using quantitative PCR. Mock crime scene DNA extracts were analyzed using quantitative PCR and short tandem repeat (STR) profiling to test the general performance and inhibitor-removal properties of the two filter devices. Additionally, the outcome of long-term routine casework DNA analysis applying each of the devices was evaluated. RESULTS: Applying Microsep 30 K, 14 to 32% of the input DNA was recovered, whereas Amicon Ultra 30 K retained 62 to 70% of the DNA. The improved purity following filter purification counteracted some of this DNA loss, leading to slightly increased electropherogram peak heights for blood on denim (Amicon Ultra 30 K and Microsep 30 K) and saliva on envelope (Amicon Ultra 30 K). Comparing Amicon Ultra 30 K and Microsep 30 K for purification of DNA extracts from mock crime scene samples, the former generated significantly higher peak heights for rape case samples (P-values <0.01) and for hairs (P-values <0.036). In long-term routine use of the two filter devices, DNA extracts purified with Amicon Ultra 30 K were considerably less PCR-inhibitory in Quantifiler Human qPCR analysis compared to Microsep 30 K. CONCLUSIONS: Amicon Ultra 30 K performed better than Microsep 30 K due to higher DNA recovery and more efficient removal of PCR-inhibitory substances. The different performances of the filter devices are likely caused by the quality of the filters and plastic wares, for example, their DNA binding properties. DNA purification using centrifugal filter devices can be necessary for successful DNA profiling of impure crime scene samples and for consistency between different PCR-based analysis systems, such as quantification and STR analysis. In order to maximize the possibility to obtain complete STR DNA profiles and to create an efficient workflow, the level of DNA purification applied should be correlated to the inhibitor-tolerance of the STR analysis system used.