Literature DB >> 22807025

Nonculture-based identification of bacteria in milk by protein fingerprinting.

Juliana Regina Barreiro1, Patricia Aparecida Campos Braga, Christina Ramires Ferreira, Markus Kostrzewa, Thomas Maier, Beatrix Wegemann, Viktoria Böettcher, Marcos N Eberlin, Marcos Veiga dos Santos.   

Abstract

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time-consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state-of-the-art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture-based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI Sepsityper(TM) Kit followed by MALDI-MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real-time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 10(3) -10(8) colony-forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (10(4) cfu mL(-1) ), bacterial identification could be performed after initial incubation at 37°C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture-based bacterial identification allows for high-throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.
© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2012        PMID: 22807025     DOI: 10.1002/pmic.201200053

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  5 in total

1.  Comparison of standard and on-plate extraction protocols for identification of mastitis-causing bacteria by MALDI-TOF MS.

Authors:  M M Barcelos; L Martins; R C Grenfell; L Juliano; K L Anderson; M V Dos Santos; J L Gonçalves
Journal:  Braz J Microbiol       Date:  2019-06-29       Impact factor: 2.476

2.  Characterization of Bacillus strains and hoax agents by protein profiling using automated microfluidic capillary electrophoresis.

Authors:  Jessica McLaughlin; Michelle Nelson; Dennis McNevin; Paul Roffey; Michelle E Gahan
Journal:  Forensic Sci Med Pathol       Date:  2014-06-19       Impact factor: 2.007

Review 3.  Recent advances in bacteria identification by matrix-assisted laser desorption/ionization mass spectrometry using nanomaterials as affinity probes.

Authors:  Tai-Chia Chiu
Journal:  Int J Mol Sci       Date:  2014-04-28       Impact factor: 5.923

4.  Direct identification of bovine mastitis pathogens by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in pre-incubated milk.

Authors:  Juliana R Barreiro; Juliano L Gonçalves; Rafaella Grenfell; Renata F Leite; Luiz Juliano; Marcos V Santos
Journal:  Braz J Microbiol       Date:  2018-08-16       Impact factor: 2.476

5.  Biomarker- and similarity coefficient-based approaches to bacterial mixture characterization using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).

Authors:  Lin Zhang; Sonja Smart; Todd R Sandrin
Journal:  Sci Rep       Date:  2015-11-05       Impact factor: 4.379

  5 in total

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