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2010-10-21Zeitschriftenartikel DOI: 10.1186/1471-2164-11-591
High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis
dc.contributor.authorFriedrich, Torben
dc.contributor.authorRahmann, Sven
dc.contributor.authorWeigel, Wilfried
dc.contributor.authorRabsch, Wolfgang
dc.contributor.authorFruth, Angelika
dc.contributor.authorRon, Eliora
dc.contributor.authorGunzer, Florian
dc.contributor.authorDandekar, Thomas
dc.contributor.authorHacker, Jörg
dc.contributor.authorMüller, Tobias
dc.contributor.authorDobrindt, Ulrich
dc.date.accessioned2018-05-07T14:11:34Z
dc.date.available2018-05-07T14:11:34Z
dc.date.created2010-11-17
dc.date.issued2010-10-21none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/reB4yVztdhdY/PDF/29ndlbYxv29z.pdf
dc.identifier.urihttp://edoc.rki.de/176904/741
dc.description.abstractBackground: The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. Results: We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Conclusions: Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut, Infektionsepidemiologie
dc.subjectBacterial/geneticseng
dc.subjectRegression Analysiseng
dc.subjectDrug Resistanceeng
dc.subjectOligonucleotide Array Sequence Analysis/methodseng
dc.subjectBacterial Typing Techniqueseng
dc.subjectGenomeeng
dc.subjectBacterial/drug effectseng
dc.subjectAnti-Infective Agents/pharmacologyeng
dc.subjectDNA Probes/metabolismeng
dc.subjectDNA Bacterial/geneticseng
dc.subjectDecision Treeseng
dc.subjectDrug Resistance Bacterial/geneticseng
dc.subjectEnterobacteriaceae/classificationeng
dc.subjectEnterobacteriaceae/drug effectseng
dc.subjectEnterobacteriaceae/geneticseng
dc.subjectEnterobacteriaceae/isolation & purificationeng
dc.subjectHigh-Throughput Screening Assays/methodseng
dc.subjectMolecular Diagnostic Techniques/methodseng
dc.subjectNucleic Acid Hybridization/drug effectseng
dc.subject.ddc610 Medizin
dc.titleHigh-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10011384
dc.identifier.doi10.1186/1471-2164-11-591
dc.identifier.doihttp://dx.doi.org/10.25646/666
local.edoc.container-titleBMC Genomics
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://www.biomedcentral.com/1471-2164/11/591
local.edoc.container-publisher-nameBioMedCentral
local.edoc.container-volume11
local.edoc.container-issue591
local.edoc.container-year2010

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