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Rapid assignment of bacterial pathogens into predefined populations is an important first step for epidemiological tracking. For clonal species, a single allele can theoretically define a population. For non-clonal species such as Burkholderia pseudomallei, however, shared allelic states between distantly related isolates make it more difficult to identify population defining characteristics. Two distinct B. pseudomallei populations have been previously identified using multilocus sequence typing (MLST). These populations correlate with the major foci of endemicity (Australia and Southeast Asia). Here, we use multiple Bayesian approaches to evaluate the compositional robustness of these populations, and provide assignment results for MLST sequence types (STs). Our goal was to provide a reference for assigning STs to an established population without the need for further computational analyses. We also provide allele frequency results for each population to enable estimation of population assignment even when novel STs are discovered. The ability for humans and potentially contaminated goods to move rapidly across the globe complicates the task of identifying the source of an infection or outbreak. Population genetic dynamics of B. pseudomallei are particularly complicated relative to other bacterial pathogens, but the work here provides the ability for broad scale population assignment. As there is currently no independent empirical measure of successful population assignment, we provide comprehensive analytical details of our comparisons to enable the reader to evaluate the robustness of population designations and assignments as they pertain to individual research questions. Finer scale subdivision and verification of current population compositions will likely be possible with genotyping data that more comprehensively samples the genome. The approach used here may be valuable for other non-clonal pathogens that lack simple group-defining genetic characteristics and provides a rapid reference for epidemiologists wishing to track the origin of infection without the need to compile population data and learn population assignment algorithms. Author Summary: Burkholderia pseudomallei is a soil-dwelling bacterium that can infect a large range of hosts. In humans, B. pseudomallei causes melioidosis, and typical routes of entry include open wounds, inhalation, or ingestion. Clinical features are diverse, although pneumonia and abscess formation are common. High rates of recombination within the genome of this bacterium have confounded attempts to match clinical samples to geographically defined populations. Here we provide a reference that simplifies source attribution issues. We applied population assignment software to previously generated sequence data from seven B. pseudomallei genes to define the major geographic populations within this species. We evaluated the robustness of our results by comparison with two additional population assignment programs. We present the likelihood that each variant is assigned to a particular geographic population. This information can be used to assign novel B. pseudomallei isolates to a geographic population without needing to learn and run cumbersome population assignment applications. This method can also be used for other bacteria that are difficult to source-attribute due to high levels of genomic variation and recombination. [ABSTRACT FROM AUTHOR]

Rapid assignment of bacterial pathogens into predefined populations is an important first step for epidemiological tracking. For clonal species, a single allele can theoretically define a population. For non-clonal species such as Burkholderia pseudomallei, however, shared allelic states between distantly related isolates make it more difficult to identify population defining characteristics. Two distinct B. pseudomallei populations have been previously identified using multilocus sequence typing (MLST). These populations correlate with the major foci of endemicity (Australia and Southeast Asia). Here, we use multiple Bayesian approaches to evaluate the compositional robustness of these populations, and provide assignment results for MLST sequence types (STs). Our goal was to provide a reference for assigning STs to an established population without the need for further computational analyses. We also provide allele frequency results for each population to enable estimation of population assignment even when novel STs are discovered. The ability for humans and potentially contaminated goods to move rapidly across the globe complicates the task of identifying the source of an infection or outbreak. Population genetic dynamics of B. pseudomallei are particularly complicated relative to other bacterial pathogens, but the work here provides the ability for broad scale population assignment. As there is currently no independent empirical measure of successful population assignment, we provide comprehensive analytical details of our comparisons to enable the reader to evaluate the robustness of population designations and assignments as they pertain to individual research questions. Finer scale subdivision and verification of current population compositions will likely be possible with genotyping data that more comprehensively samples the genome. The approach used here may be valuable for other nonclonal pathogens that lack simple group-defining genetic characteristics and provides a rapid reference for epidemiologists wishing to track the origin of infection without the need to compile population data and learn population assignment algorithms. [ABSTRACT FROM AUTHOR]

Melioidosis is caused by Burkholderia pseudomallei, a Gram-negative bacillus, primarily found in soils in Southeast Asia and northern Australia. A recent case of melioidosis in non-endemic Arizona was determined to be the result of locally acquired infection, as the patient had no travel history to endemic regions and no previous history of disease. Diagnosis of the case was confirmed through multiple microbiologic and molecular techniques. To enhance the epidemiological analysis, we conducted several molecular genotyping procedures, including multi-locus sequence typing, SNP-profiling, and whole genome sequence typing. Each technique has different molecular epidemiologic advantages, all of which provided evidence that the infecting strain was most similar to those found in Southeast Asia, possibly originating in, or around, Malaysia. Advancements in new typing technologies provide genotyping resolution not previously available to public health investigators, allowing for more accurate source identification. Author Summary: Melioidosis is a bacterial disease caused by percutaneous inoculation, aspiration or ingestion of the soil bacteria Burkholderia pseudomallei. Melioidosis is primarily found in Southeast Asia and Northern Australia, and, to a lesser degree, nearby regions. A recent case of melioidosis in Southwestern United States (Southern Arizona) prompted a detailed epidemiological and molecular investigation to discover the source of infection. The authors describe the use of multiple genomic analysis tools to aid in this investigation. The results of these analyses uniformly identified Southeast Asia as the source of the strain that infected the patient, however the epidemiological investigation had determined the patient had no international travel or known exposures to Southeast Asian products. New cutting edge technologies, such as next generation sequencing, are quickly being adapted into epidemiologic investigations, particularly for cases and outbreaks of unknown origin, although older, mature technologies with larger existing databases will still be needed for appropriate comparative analyses. [ABSTRACT FROM AUTHOR]

Melioidosis is caused by Burkholderia pseudomallei, a Gram-negative bacillus, primarily found in soils in Southeast Asia and northern Australia. A recent case of melioidosis in non-endemic Arizona was determined to be the result of locally acquired infection, as the patient had no travel history to endemic regions and no previous history of disease. Diagnosis of the case was confirmed through multiple microbiologic and molecular techniques. To enhance the epidemiological analysis, we conducted several molecular genotyping procedures, including multi-locus sequence typing, SNP-profiling, and whole genome sequence typing. Each technique has different molecular epidemiologic advantages, all of which provided evidence that the infecting strain was most similar to those found in Southeast Asia, possibly originating in, or around, Malaysia. Advancements in new typing technologies provide genotyping resolution not previously available to public health investigators, allowing for more accurate source identification. [ABSTRACT FROM AUTHOR]