Species-Level Discrimination of Psychrotrophic Pathogenic and Spoilage Gram-Negative Raw Milk Isolates Using a Combined MALDI-TOF MS Proteomics-Bioinformatics-based Approach.

Identification of psychrotrophic pathogenic and spoilage Gram-negative bacteria using rapid and reliable techniques is important in commercial milk processing, as these bacteria can produce heat-resistant proteases and act as postprocessing contaminants in pasteurized milk. Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is a proven technology for identification of bacteria in food, however, may require optimization for identification of pathogenic and spoilage bacteria in milk and dairy products. The current study evaluated the effects of various culture conditions and sample preparation methods on assigning of raw milk isolates to the species level by MALDI-TOF MS. The results indicated that culture media, incubation conditions (temperature and time), and sample preparation significantly affected the identification rates of bacteria to the species level. Nevertheless, the development of spectral libraries of isolates grown on different media using a web tool for hierarchical clustering of peptide mass spectra (SPECLUST) followed by a ribosomal protein based bioinformatics approach significantly enhanced the assigning of bacteria, with at least one unique candidate biomarker peak identified for each species. Phyloproteomic relationships based on spectral profiles were compared to phylogenetic analysis using 16S rRNA gene sequences and demonstrated similar clustering patterns with significant discriminatory power. Thus, with appropriate optimization, MALDI-TOF MS is a valuable tool for species-level discrimination of pathogenic and milk spoilage bacteria.

Microbiological quality of raw milk attributable to prolonged refrigeration conditions.

Refrigerated storage of raw milk is a prerequisite in dairy industry. However, temperature abused conditions in the farming and processing environments can significantly affect the microbiological quality of raw milk. Thus, the present study investigated the effect of different refrigeration conditions such as 2, 4, 6, 8, 10 and 12 °C on microbiological quality of raw milk from three different dairy farms with significantly different initial microbial counts. The bacterial counts (BC), protease activity (PA), proteolysis (PL) and microbial diversity in raw milk were determined during storage. The effect of combined heating (75 ± 0·5 °C for 15 s) and refrigeration on controlling those contaminating microorganisms was also investigated. Results of the present study indicated that all of the samples showed increasing BC, PA and PL as a function of temperature, time and initial BC with a significant increase in those criteria ≥6 °C. Similar trends in BC, PA and PL were observed during the extended storage of raw milk at 4 °C. Both PA and PL showed strong correlation with the psychrotrophic proteolytic count (PPrBC: at ≥4 °C) and thermoduric psychrotrophic count (TDPC: at ≥8 °C) compared to total plate count (TPC) and psychrotrophic bacterial count (PBC), that are often used as the industry standard. Significant increases in PA and PL were observed when PPrBC and TDPC reached 5 × 104 cfu/ml and 1 × 104 cfu/ml, and were defined as storage life for quality (S LQ), and storage life for safety (S LS) aspects, respectively. The storage conditions also significantly affected the microbial diversity, where Pseudomonas fluorescens and Bacillus cereus were found to be the most predominant isolates. However, deep cooling (2 °C) and combination of heating and refrigeration (≤4 °C) significantly extended the S LQ and S Ls of raw milk.

Comparison of identification systems for psychrotrophic bacteria isolated from raw bovine milk.

Psychrotrophic bacteria in raw milk produce heat-resistant extracellular proteases, resulting in spoilage and shelf-life reduction of ultrahigh temperature treated milk and milk products. Controlling of these spoilage microbes requires rapid and reliable identification systems for screening of raw milk. This study aimed to compare commercial bacterial identification systems with a genetic method (considered as the 'gold standard' method) for the identification of heat-resistant protease producing bacteria in raw milk. Five bacterial identification systems were compared based on typability, discrimination power (i.e. Simpson's Index of Diversity), reproducibility and speed of analysis. The accuracy of 16S rRNA gene sequencing, Biolog, MALDI-TOF MS, API, and Microbact for the identification of Gram negative bacilli at the species level was 100.0%, 86.8%, 63.2%, 60.5% and 57.9%, respectively. The Gram positive bacilli were identified by 16S rRNA gene sequencing, Biolog, MALDI-TOF MS, and API with accuracies at the species level of 100.0%, 85.0%, 95.0% and 90.0%, respectively. The 16S rRNA gene sequencing and phylogenetic analysis discriminated Pseudomonas fluorescens, Pseudomonas syringae, Hafnia alvei, Bacillus cereus, Bacillus pumilus and Bacillus licheniformis to the subspecies level. The Simpson's Index of Diversity scores were 0.966, 0.711, 0.496, 0.472, and 0.140, for 16S rRNA gene sequencing, Biolog, MALDI-TOF MS, API and Microbact, respectively. Limited reference profiles in the databases of Biolog, MALDI-TOF MS, API and Microbact systems reduced their accuracy in bacterial identification, compared to 16S rRNA gene sequencing. The rapidity of each assay is in the following order; MALDI-TOF MS>16S rRNA gene sequencing>Biolog>Microbact>API. The reproducibility of the assays is in the order of 16S rRNA gene sequencing>API>Microbact>MALDI-TOF MS>Biolog. Thus, 16S rRNA gene sequencing appears to be the most reliable and robust system for the identification of dairy spoilage bacteria. The Biolog system is suitable for the identification of Gram negative spoilage bacteria, while MALDI-TOF MS and API systems are suitable for the identification of Gram positive spoilage bacteria isolated from raw milk. The commercial systems used in this study have been developed and extensively used for the identification of clinical microbes but only a limited number of studies used those systems to identify the environmental microorganisms that often contaminate raw milk. Therefore, comparison of those systems for the identification of spoilage microbes in raw milk would provide better understanding of their suitability for routine dairy microbiology and more extensive dairy research.