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Identification of antibiotic-resistant staphylococci and epidemiological typing of methicillin-resistant Staphylococcus aureus by Fourier transform infrared spectroscopy

Staphylococci strains are among the most widespread multidrug-resistant nosocomial pathogens in Canada. Rapid and accurate identification and epidemiological typing of methicillin-resistant S. aureus (MRSA) and its discrimination from coagulase-negative staphylococci (CNS) and glycopeptide-intermediate S. aureus (GISA) are crucial for appropriate therapy and for monitoring and limiting intra- and inter-hospital spread of epidemic MRSA strains. Although pulsed-field gel electrophoresis and polymerase chain reaction methods for the identification of MRSA are reliable, they are technically demanding, time-consuming and inappropriate for routine clinical diagnosis. Moreover, no reliable method exists for discrimination of epidemic MRSA from sporadic MRSA and from GISA strains. The objective of the research described in this thesis was to investigate whether Fourier transform infrared (FTIR) spectroscopy could be used to distinguish MRSA from methicillin-susceptible S. aureus, borderline oxacillin-resistant S. aureus (BORSA), CNS, including methicillin-resistant CNS, and GISA. The application of FTIR spectroscopy for epidemiological typing of Canadian epidemic MRSA (CMRSA) strains as well as their discrimination from sporadic MRSA was also assessed. FTIR spectra were recorded from intact stationary-phase cells grown on Universal Medium (UM™) and deposited and dried on a ZnSe optical window, normalized, and converted to first-derivative spectra. Various chemometric approaches were employed to cluster the different phenotypes of staphylococci species and to subtype five CMRSA strains based on the similarity of their infrared spectral fingerprints in narrow spectral regions selected by visual inspection and by employing a singularvalue decomposition (SVD) algorithm. Pairwise separation of MRSA from MSSA, BORSA, CNS, MRCNS, and GISA was accomplished by using principal component analysis (PCA), self-organizing maps (SOM), and the K-nearest neighbors (KNN) algorithm. These chemometric techniques were also successfully employed for epidemiological typing of the five CMRSA strains and their discrimination from sporadic MRSA strains using a combination of different optimal spectral regions selected by SVD. These results demonstrate that FTIR spectroscopy has considerable potential as a rapid method for the identification of different phenotypes of staphylococci and epidemiological typing of MRSA.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.19525
Date January 2003
CreatorsAmiali, Mohamed Nassim
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageDoctor of Philosophy (Department of Food Science and Agricultural Chemistry)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 002021306, Theses scanned by McGill Library.

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