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A likelihood ratio-...
A likelihood ratio-based approach for improved source attribution in microbiological forensic investigations
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- Lindgren, Petter (författare)
- Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Uemå, Sweden
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- Myrtennäs, Kerstin (författare)
- Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden.
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- Forsman, Mats (författare)
- Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden
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- Johansson, Anders, 1966- (författare)
- Umeå universitet,Molekylär Infektionsmedicin, Sverige (MIMS),Department of Clinical Microbiology and Molecular Infection Medicine Sweden (MIMS), Umeå University, Sweden
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- Stenberg, Per, 1974- (författare)
- Umeå universitet,Institutionen för ekologi, miljö och geovetenskap,Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), SE-901 82 Umeå, Sweden,Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden; Department of Ecology and Environmental Science (EMG), Umeå University, Sweden
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- Nordgaard, Anders, 1962- (författare)
- Swedish Police Auhtority, National Forensic Centre (NFC)
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- Ahlinder, Jon (författare)
- Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden
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Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Uemå, Sweden Department of Biological Agents, Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden (creator_code:org_t)
- Elsevier, 2019
- 2019
- Engelska.
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Ingår i: Forensic Science International. - : Elsevier. - 0379-0738 .- 1872-6283. ; 302
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Annan medicin och hälsovetenskap -- Rättsmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Other Medical and Health Sciences -- Forensic Science (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
- NATURVETENSKAP -- Biologi -- Genetik (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Genetics (hsv//eng)
- SAMHÄLLSVETENSKAP -- Juridik -- Juridik och samhälle (hsv//swe)
- SOCIAL SCIENCES -- Law -- Law and Society (hsv//eng)
- NATURVETENSKAP -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)
Nyckelord
- Microbial source tracking
- Bayes factor
- Hypothesis assessment
- Listeria monocytogenes
- Francisella tularensis
- Likelihood ratio
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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