Characterization of a Staphylococcus aureus USA300 protein signature using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Boggs, Sarah R.; Cazares, Lisa H.; Drake, Richard

doi:10.1099/jmm.0.037978-0

Cited by 35 publications

(21 citation statements)

References 23 publications

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“…Among the three model generation algorithms available, models based on the genetic algorithm performed better for our study isolates than the other algorithms (Supervised Neural Network and QuickClassifier; data not shown). Two recent studies have used classification models generated using ClinProTools software for distinguishing between two Staphylococcus aureus strains (22) and between Streptococcus pneumoniae and S. mitis (23). The genetic algorithm was either the optimal algorithm for model generation or worked as well as the other options in both studies.…”

Section: Discussionmentioning

confidence: 99%

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

2013

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bShigella species are so closely related to Escherichia coli that routine matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) cannot reliably differentiate them. Biochemical and serological methods are typically used to distinguish these species; however, "inactive" isolates of E. coli are biochemically very similar to Shigella species and thus pose a greater diagnostic challenge. We used ClinProTools (Bruker Daltonics) software to discover MALDI-TOF MS biomarker peaks and to generate classification models based on the genetic algorithm to differentiate between Shigella species and E. coli. Sixtysix Shigella spp. and 72 E. coli isolates were used to generate and test classification models, and the optimal models contained 15 biomarker peaks for genus-level classification and 12 peaks for species-level classification. We were able to identify 90% of E. coli and Shigella clinical isolates correctly to the species level. Only 3% of tested isolates were misidentified. This novel MALDI-TOF MS approach allows laboratories to streamline the identification of E. coli and Shigella species.

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Section: Discussionmentioning

confidence: 99%

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

2013

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“…Another promising study using an UltraFlex III machine proposed three protein peaks as specific for 197 of 224 (88%) USA300 isolates (9). However, a previous study (7) identified one of the peaks, m/z 6,423, as species specific, while a second peak, m/z 6,592, was more generally associated with CC8, to which USA300 belongs.…”

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confidence: 91%

Microbial Typing by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry: Do We Need Guidance for Data Interpretation?

et al. 2015

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eThe integration of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology has revolutionized species identification of bacteria, yeasts, and molds. However, beyond straightforward identification, the method has also been suggested to have the potential for subspecies-level or even type-level epidemiological analyses. This minireview explores MALDI-TOF MS-based typing, which has already been performed on many clinically relevant species. We discuss the limits of the method's resolution and we suggest interpretative criteria allowing valid comparison of strain-specific data. We conclude that guidelines for MALDI-TOF MS-based typing can be developed along the same lines as those used for the interpretation of data from pulsed-field gel electrophoresis (PFGE). Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been integrated into the routine diagnostic workflow of many industrial, pharmaceutical, and medical microbiology laboratories. It has already been thoroughly evaluated for the identification of clinically relevant bacterial species, including anaerobes, Gram-positive rods and cocci, Enterobacteriaceae, and miscellaneous Gram-negative (including nonfermentative) rods, with adequate to excellent results (1, 2).Species identification, however, is only a first step in the diagnostic workflow. The ability to quickly and reliably distinguish or "type" related bacterial isolates is essential for bacterial transmission studies and larger-scale epidemiological surveillance projects. "Conventional" phenotyping methods, such as multiple-susceptibility testing, phage typing, serotyping, biochemical typing, and several others, have been important contributors to our understanding of the epidemiology of community-and health careassociated infections. However, these methods all have practical limitations which render them largely unsuitable for comprehensive bacterial population analyses as well as for scientifically less ambitious but critical infection surveillance. Furthermore, most phenotypic methods have been developed for individual bacterial taxa and are not transferable to other taxa without considerable adaptation.Hence, over the past 2 decades, phenotyping has been largely replaced by "molecular" genotyping. Clonal reproduction by binary fission imprints the evolutionary history of the organism in genotypic markers amenable to analysis by nucleic acid-mediated methods. However, in practice, the ease with which recombination, transfection, and transformation can take place in bacteria necessitates that data from multiple genetic markers are analyzed in defining a "precise" genotype and even then there is no guarantee that an adequate natural taxonomy will be derived. Polyphasic taxonomy currently uses combinations of different phenotypic and/or genotypic data sets to define genera, species, and entities at or below the subspecies level. Still, all these approaches remain time-consuming and relatively...

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“…Indeed, it is possible to identify Listeria monocytogenes serotypes, Yersinia enterocolitica biotypes and Salmonella enterica subspecies (Barbuddhe et al, 2008;Stephan et al, 2011;Dieckmann et al, 2008). MALDI-TOF MS also differentiates some M types of Streptococcus pyogenes (Wang et al, 2012) and clonal complexes of Staphylococcus aureus (Wolters et al, 2011;Boggs et al, 2012). Recently MALDI-TOF MS has been successfully used for the identification of some pathovars of E. coli (Clark et al, 2013).…”

Section: Introductionmentioning

confidence: 98%

Matrix-assisted laser desorption ionization-time of flight mass spectrometry assigns Escherichia coli to the phylogroups A, B1, B2 and D

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Nicolas–Chanoine

Cabrolier

et al. 2014

International Journal of Medical Microbiology

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Characterization of a Staphylococcus aureus USA300 protein signature using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Cited by 35 publications

References 23 publications

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Microbial Typing by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry: Do We Need Guidance for Data Interpretation?

Matrix-assisted laser desorption ionization-time of flight mass spectrometry assigns Escherichia coli to the phylogroups A, B1, B2 and D

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