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Burkholderia pseudomallei is frequently detected in groundwater that discharges to major watercourses in northern Australia
AL. Baker, JM. Warner,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
- MeSH
- bakteriologické techniky MeSH
- Burkholderia pseudomallei genetika izolace a purifikace MeSH
- DNA bakterií genetika izolace a purifikace MeSH
- počasí MeSH
- podzemní voda mikrobiologie MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Queensland MeSH
Burkholderia pseudomallei is the environmental bacterium that causes the serious disease melioidosis. Recently, a high prevalence of viable B. pseudomallei was reported from natural groundwater seeps around Castle Hill, a clinical focus of melioidosis in Townsville, Australia. This study sought to expand previous findings to determine the extent of B. pseudomallei in more diverse natural groundwater seeps in northern Queensland to ascertain if the presence of the organism in groundwater on Castle Hill was an isolated occurrence. Analysis of water samples (n = 26) obtained from natural groundwater seeps following an intensive rainfall event in the Townsville region determined the presence of B. pseudomallei DNA in duplicates of 18 samples (69.2 % [95 % CI, 51.5 to 87.0]). From 26 water samples, a single isolate of B. pseudomallei was recovered despite plating of both pre-enriched samples and original water samples onto selective media, indicating that the sensitivity of these molecular techniques far exceeds culture-based methods. Furthermore, the identification of new environments endemic for melioidosis may be more effectively determined by analysing surface groundwater seeps than by the analysis of random soil samples. This study suggests that a higher incidence of melioidosis following monsoonal rains may be partially the result of exposure to groundwater sources carrying B. pseudomallei, and that modifications to public health messages in endemic regions may be warranted. Moreover, these findings have implications for predictive models of melioidosis, effective models requiring consideration of topographical and surface hydrological data.
Citace poskytuje Crossref.org
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- $a Baker, Anthony L $u Environmental and Public Health Microbiology Research Group, School of Veterinary and Biomedical Sciences, James Cook University, Townsville, Queensland, Australia. anthony.baker@my.jcu.edu.au. Tasmanian Institute of Agriculture (TIA), University of Tasmania, Hobart, Tasmania, Australia. anthony.baker@my.jcu.edu.au.
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- $a Burkholderia pseudomallei is the environmental bacterium that causes the serious disease melioidosis. Recently, a high prevalence of viable B. pseudomallei was reported from natural groundwater seeps around Castle Hill, a clinical focus of melioidosis in Townsville, Australia. This study sought to expand previous findings to determine the extent of B. pseudomallei in more diverse natural groundwater seeps in northern Queensland to ascertain if the presence of the organism in groundwater on Castle Hill was an isolated occurrence. Analysis of water samples (n = 26) obtained from natural groundwater seeps following an intensive rainfall event in the Townsville region determined the presence of B. pseudomallei DNA in duplicates of 18 samples (69.2 % [95 % CI, 51.5 to 87.0]). From 26 water samples, a single isolate of B. pseudomallei was recovered despite plating of both pre-enriched samples and original water samples onto selective media, indicating that the sensitivity of these molecular techniques far exceeds culture-based methods. Furthermore, the identification of new environments endemic for melioidosis may be more effectively determined by analysing surface groundwater seeps than by the analysis of random soil samples. This study suggests that a higher incidence of melioidosis following monsoonal rains may be partially the result of exposure to groundwater sources carrying B. pseudomallei, and that modifications to public health messages in endemic regions may be warranted. Moreover, these findings have implications for predictive models of melioidosis, effective models requiring consideration of topographical and surface hydrological data.
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