Title
Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray
Author
Euser, S.M.
Nagelkerke, N.J.
Schuren, F.
Jansen, R.
den Boer, J.W.
Publication year
2012
Abstract
Background: Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Methods: Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in the Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Results: Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. Conclusions: The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment. © 2012 Euser et al.
Subject
EELS - Earth, Environmental and Life Sciences
Life
Healthy Living
Biomedical Innovation
bacterial genome
bacterial strain
bacterial virulence
bacterium identification
bacterium isolation
epidemic
genetic marker
genome analysis
genotype
infection control
Legionella pneumophila
microarray analysis
mixed genome microarray
Netherlands
nonhuman
predictive validity
strain difference
MSB - Microbiology and Systems Biology
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http://resolver.tudelft.nl/uuid:4e09f769-4116-43ba-a7e1-7f416c32ddd9
DOI
https://doi.org/10.1371/journal.pone.0047437
TNO identifier
465840
ISSN
1932-6203
Source
PLoS ONE, 7 (7)
Document type
article