Non-culture-based identification of mastitis-causing bacteria by MALDI-TOF mass spectrometry.

The purpose of this study was to evaluate the detection limit of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for direct identification, without previous microbiological culture, of bovine mastitis-causing bacteria from milk samples. Milk samples (n = 15) were experimentally contaminated with Staphylococcus aureus, Streptococcus uberis, Streptococcus agalactiae, Streptococcus dysgalactiae, and Escherichia coli to have bacterial counts ranging from 103 to 109 cfu/mL. These contaminated milk samples were subjected to a preparation protocol for bacterial ribosomal protein extraction using the MALDI Sepsityper kit (Bruker Daltonik, Bremen, Germany), which allowed MALDI-TOF MS coupled with Biotyper software (Bruker Daltonik) to identify bacterial fingerprints based on intact ribosomal proteins. The ability of MALDI-TOF MS to correctly identify bacterial strains from experimentally contaminated milk (without previous microbiological culture) depended on the bacterial count of the samples and on the species of the bacteria evaluated. Adequate identification at the bacterial species level (score ≥2.0) directly from milk samples required bacterial counts in the following ranges: ≥106 cfu/mL of Staph. aureus, ≥107 cfu/mL of E. coli, and ≥108 cfu/mL of Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis. We concluded that direct identification of mastitis-causing pathogens is possible for Staph. aureus, E. coli, Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis, but correct identification depended on the bacterial count in the milk samples.

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

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.