A likelihood ratio-based approach for improved source attribution in microbiological forensic investigations.

A common objective in microbial forensic investigations is to identify the origin of a recovered pathogenic bacterium by DNA sequencing. However, there is currently no consensus about how degrees of belief in such origin hypotheses should be quantified, interpreted, and communicated to wider audiences. To fill this gap, we have developed a concept based on calculating probabilistic evidential values for microbial forensic hypotheses. The likelihood-ratio method underpinning this concept is widely used in other forensic fields, such as human DNA matching, where results are readily interpretable and have been successfully communicated in juridical hearings. The concept was applied to two case scenarios of interest in microbial forensics: (1) identifying source cultures among series of very similar cultures generated by parallel serial passage of the Tier 1 pathogen Francisella tularensis, and (2) finding the production facilities of strains isolated in a real disease outbreak caused by the human pathogen Listeria monocytogenes. Evidence values for the studied hypotheses were computed based on signatures derived from whole genome sequencing data, including deep-sequenced low-frequency variants and structural variants such as duplications and deletions acquired during serial passages. In the F. tularensis case study, we were able to correctly assign fictive evidence samples to the correct culture batches of origin on the basis of structural variant data. By setting up relevant hypotheses and using data on cultivated batch sources to define the reference populations under each hypothesis, evidential values could be calculated. The results show that extremely similar strains can be separated on the basis of amplified mutational patterns identified by high-throughput sequencing. In the L. monocytogenes scenario, analyses of whole genome sequence data conclusively assigned the clinical samples to specific sources of origin, and conclusions were formulated to facilitate communication of the findings. Taken together, these findings demonstrate the potential of using bacterial whole genome sequencing data, including data on both low frequency SNP signatures and structural variants, to calculate evidence values that facilitate interpretation and communication of the results. The concept could be applied in diverse scenarios, including both epidemiological and forensic source tracking of bacterial infectious disease outbreaks.

The optimal number of offspring per gamete donor.

Our aim was to create a mathematical basis to calculate the risks for unintended matings of consanguineous half-siblings from a donor in a society with approximately 10 million inhabitants. The Curie-Cohen model for calculation of the risk for consanguineous mating was used. When the number of offspring per donor is limited to 10, then the model gives a yearly risk for consanguineous matings below 1%. Thus 10 offspring gives a risk for consanguineous matings of 0.9% per year, or approximately once in every 100 years. The risk increases exponentially: with 15 offspring it exceeds 2% and with 25 it reaches up above 5%.

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.

Assessment of approximate likelihood ratios from continuous distributions: a case study of digital camera identification.

A reported likelihood ratio for the value of evidence is very often a point estimate based on various types of reference data. When presented in court, such frequentist likelihood ratio gets a higher scientific value if it is accompanied by an error bound. This becomes particularly important when the magnitude of the likelihood ratio is modest and thus is giving less support for the forwarded proposition. Here, we investigate methods for error bound estimation for the specific case of digital camera identification. The underlying probability distributions are continuous and previously proposed models for those are used, but the derived methodology is otherwise general. Both asymptotic and resampling distributions are applied in combination with different types of point estimators. The results show that resampling is preferable for assessment based on asymptotic distributions. Further, assessment of parametric estimators is superior to evaluation of kernel estimators when background data are limited.

A ranking index for quality assessment of forensic DNA profiles forensic DNA profiles.

BACKGROUND: Assessment of DNA profile quality is vital in forensic DNA analysis, both in order to determine the evidentiary value of DNA results and to compare the performance of different DNA analysis protocols. Generally the quality assessment is performed through manual examination of the DNA profiles based on empirical knowledge, or by comparing the intensities (allelic peak heights) of the capillary electrophoresis electropherograms. RESULTS: We recently developed a ranking index for unbiased and quantitative quality assessment of forensic DNA profiles, the forensic DNA profile index (FI) (Hedman et al. Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modeling of DNA profiles, Biotechniques 47 (2009) 951-958). FI uses electropherogram data to combine the intensities of the allelic peaks with the balances within and between loci, using Principal Components Analysis. Here we present the construction of FI. We explain the mathematical and statistical methodologies used and present details about the applied data reduction method. Thereby we show how to adapt the ranking index for any Short Tandem Repeat-based forensic DNA typing system through validation against a manual grading scale and calibration against a specific set of DNA profiles. CONCLUSIONS: The developed tool provides unbiased quality assessment of forensic DNA profiles. It can be applied for any DNA profiling system based on Short Tandem Repeat markers. Apart from crime related DNA analysis, FI can therefore be used as a quality tool in paternal or familial testing as well as in disaster victim identification.

Synergy between DNA polymerases increases polymerase chain reaction inhibitor tolerance in forensic DNA analysis.

The success rate of diagnostic polymerase chain reaction (PCR) analysis is lowered by inhibitory substances present in the samples. Recently, we showed that tolerance to PCR inhibitors in crime scene saliva stains can be improved by replacing the standard DNA polymerase AmpliTaq Gold with alternative DNA polymerase-buffer systems (Hedman et al., BioTechniques 47 (2009) 951-958). Here we show that blending inhibitor-resistant DNA polymerase-buffer systems further increases the success rate of PCR for various types of real crime scene samples showing inhibition. For 34 of 42 "inhibited" crime scene stains, the DNA profile quality was significantly improved using a DNA polymerase blend of ExTaq Hot Start and PicoMaxx High Fidelity compared with AmpliTaq Gold. The significance of the results was confirmed by analysis of variance. The blend performed as well as, or better than, the alternative DNA polymerases used separately for all tested sample types. When used separately, the performance of the DNA polymerases varied depending on the nature of the sample. The superiority of the blend is discussed in terms of complementary effects and synergy between the DNA polymerase-buffer systems.

Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modeling of DNA profiles.

DNA evidence, linking perpetrators to crime scenes, is central to many legal proceedings. However, DNA samples from crime scenes often contain PCR-inhibitory substances, which may generate blank or incomplete DNA profiles. Extensive DNA purification can be required to rid the sample of these inhibitors, although these procedures increase the risk of DNA loss. Most forensic laboratories use commercial DNA amplification kits (e.g., AmpFlSTR SGM Plus) with the DNA polymerase AmpliTaq Gold as the gold standard. Here, we show that alternative DNA polymerase-buffer systems can improve the quality of forensic DNA analysis and efficiently circumvent PCR inhibition in crime scene samples, without additional sample preparation. DNA profiles from 20 of 32 totally or partially inhibited crime scene saliva samples were significantly improved using Bio-X-Act Short, ExTaq Hot Start, or PicoMaxx High Fidelity instead of AmpliTaq Gold. A statistical model for unbiased quality control of forensic DNA profiles was developed to quantify the results. Our study demonstrates the importance of adjusting the chemistry of the PCR to enhance forensic DNA analysis and diagnostic PCR, providing an alternative to laborious sample preparation protocols.