Dataset Information

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry.

ABSTRACT: Mass spectrometry (MS) in Selected Reaction Monitoring (SRM) mode is proposed for in-depth characterisation of microorganisms in a multiplexed analysis. Within 60-80?minutes, the SRM method performs microbial identification (I), antibiotic-resistance detection (R), virulence assessment (V) and it provides epidemiological typing information (T). This SRM application is illustrated by the analysis of the human pathogen Staphylococcus aureus, demonstrating its promise for rapid characterisation of bacteria from positive blood cultures of sepsis patients.

SUBMITTER: Charretier Y

PROVIDER: S-EPMC4563557 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Publications

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry.

Charretier Yannick Y Dauwalder Olivier O Franceschi Christine C Degout-Charmette Elodie E Zambardi Gilles G Cecchini Tiphaine T Bardet Chloe C Lacoux Xavier X Dufour Philippe P Veron Laurent L Rostaing Hervé H Lanet Veronique V Fortin Tanguy T Beaulieu Corinne C Perrot Nadine N Dechaume Dominique D Pons Sylvie S Girard Victoria V Salvador Arnaud A Durand Géraldine G Mallard Frédéric F Theretz Alain A Broyer Patrick P Chatellier Sonia S Gervasi Gaspard G Van Nuenen Marc M Roitsch Carolyn Ann CA Van Belkum Alex A Lemoine Jérôme J Vandenesch François F Charrier Jean-Philippe JP

Scientific reports 20150909

Mass spectrometry (MS) in Selected Reaction Monitoring (SRM) mode is proposed for in-depth characterisation of microorganisms in a multiplexed analysis. Within 60-80 minutes, the SRM method performs microbial identification (I), antibiotic-resistance detection (R), virulence assessment (V) and it provides epidemiological typing information (T). This SRM application is illustrated by the analysis of the human pathogen Staphylococcus aureus, demonstrating its promise for rapid characterisation of ...[more]

PMID: 26350205

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Project description:For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the "best flyer" hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R(2) of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM, such as high sensitivity, selectivity, reproducibility, and dynamic range, and estimates absolute protein concentrations of selected proteins at minimized costs.

Dataset Information

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry.

Publications

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry.

Similar Datasets

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