Pseudomonas aeruginosa intensive care unit outbreak : winnowing of transmissions with molecular and genomic typing
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Background: Pseudomonas aeruginosa healthcare outbreaks can be time consuming and difficult to investigate. Guidance does not specify which typing technique is most practical to base decisions on. Aim: We explore the usefulness of whole genome sequencing (WGS) in the investigation of a Pseudomonas aeruginosa outbreak describing how it compares with pulsed-field gel electrophoresis (PFGE) and variable number tandem repeat (VNTR) analysis. Methods: Six patient isolates and six environmental samples from an Intensive Care Unit (ICU) positive for P. aeruginosa over two years underwent VNTR, PFGE and WGS. Findings: VNTR and PFGE were required to fully determine the potential source of infection and rule out others. WGS results unambiguously distinguished linked isolates giving greater assurance of the transmission route between wash hand basin (WHB) water and two patients supporting control measures employed. Conclusion: WGS provided detailed information without need for further typing. When allied to epidemiological information it can be used to understand outbreak situations rapidly and with certainty. Implementation of WGS in real-time would be a major advance in day-to-day practice. It could become a standard of care as it becomes more widespread due to its reproducibility and reduction in costs.
Parcell , B J , Oravcova , K , Pinheiro , M , Holden , M T G , Phillips , G , Turton , J F & Gillespie , S H 2018 , ' Pseudomonas aeruginosa intensive care unit outbreak : winnowing of transmissions with molecular and genomic typing ' , Journal of Hospital Infection , vol. 98 , no. 3 , pp. 282-288 . https://doi.org/10.1016/j.jhin.2017.12.005
Journal of Hospital Infection
© 2017 The Authors. Published by Elsevier Ltd on behalf of The Healthcare Infection Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
DescriptionBioinformatics and computational biology analyses were supported by the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award [grant 097831/Z/11/Z]. BJP, KO, MP, MTGH, GP and SHG are funded by the Chief Scientist Office through the Scottish Infection Research Network, a part of the SHAIPI consortium grant reference number SIRN/10.
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