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Season and location have previously been shown to be associated with differences in the microbiota of raw milk, especially in milk from pasture-based systems. Here, we further advance research in this area by examining differences in the raw milk microbiota from several locations across Ireland over 12 months, and by investigating microbiota associations with climatic variables and chemical composition. Shotgun metagenomic sequencing was used to investigate the microbiota of raw milk collected from nine locations ( n = 241). Concurrent chemical analysis of the protein, fat, lactose, total solids, nonprotein nitrogen contents, and titratable acidity (TA) of the same raw milk were performed. Although the raw milk microbiota was highly diverse, a core microbiota was found, with Pseudomonas_E , Lactococcus, Acinetobacter , and Leuconostoc present in all samples. Microbiota diversity significantly differed by season and location, with differences in seasonality and geography corresponding to 11.8% and 10.5% of the variation in the microbiota. Functional and antibiotic resistance profiles also varied across season and location. The analysis of other metadata revealed additional interactions, such as an association between mean daily air and grass temperatures with the abundance of spoilage taxa like Pseudomonas species. Correlations were identified between pathogenic, mastitis-related species, fat content, and the number of sun hours, suggesting a seasonal effect. Ultimately, this study expands our understanding of the interconnected nature of the microbiota, environment/climate variables, and chemical composition of raw milk and provides evidence of a season- and location-specific microbiota., Importance: The microbiota of raw milk is influenced by many factors that encourage or prevent the introduction and growth of both beneficial and undesirable microorganisms. The seasonal and geographical impacts on the microbial communities of raw milk have been previously seen, but the relationships with environmental factors and the chemical composition has yet to be investigated. In this year-long study, we found that while raw milk is highly diverse, a core microbiota was detected for Irish raw milk, with strong evidence of seasonal and geographical influence. We also found associations between groups of microorganisms, environmental factors, and milk composition, which expand current knowledge on the relationships between microbial and chemical composition and the climate. These results provide evidence for the development of a tool to allow for the prediction of raw milk quality and safety., Competing Interests: The authors declare no conflict of interest.

Cleaning of the production environment is vital to ensure the safety and quality of dairy products. Although cleaning with chlorine-based agents is widely adopted, it has been associated with detrimental effects on milk quality and safety, which has garnered increasing interest in chlorine-free cleaning. However, the influence of these methods on the milk microbiota is not well documented. This study investigated the factors that influence the raw milk microbiota, with a focus on the differences when chlorine-based and chlorine-free cleaning of milking equipment are used. Bulk tank raw milk was sampled during three sampling months (April, August, and November), from farms across Ireland selected to capture the use of different cleaning methods, i.e., exclusively chlorine-based ( n  = 51) and chlorine-free cleaning ( n  = 92) and farms that used chlorine-free agents for the bulk tank and chlorine-based cleaning agents for the rest of the equipment ( n  = 28). Shotgun metagenomic analysis revealed the significant influence of seasonal and geographic factors on the bulk tank milk microbiota, indicated by differences in diversity, taxonomic composition, and functional characteristics. Taxonomic and functional profiles of samples collected in November clustered separately from those of samples collected in other months. In contrast, cleaning methods only accounted for 1% of the variation in the bulk tank milk bacterial community, and samples collected from farms using chlorine-based versus chlorine-free cleaning did not differ significantly, suggesting that the chlorine-free approaches used did not negatively impact microbiological quality. This study shows the value of shotgun metagenomics in advancing our knowledge of the raw milk microbiota. IMPORTANCE The microbiota of raw milk is affected by many factors that can control or promote the introduction of undesirable microorganisms. Chlorine-based cleaning agents have been commonly used due to their effectiveness in controlling undesirable microorganisms, but they have been associated with the formation of chlorine residues that are detrimental to product quality and may impact consumer health. Chlorine-free alternatives have been recommended in some countries, but the influence of cleaning agents on the milk microbiota is unknown. Here, we investigated the influence of cleaning methods and other factors on bulk tank raw milk. Results showed that season and location had a greater influence on the milk microbiota than the cleaning agents used. Indeed, the similar microbiota compositions of raw milk from farms that used chlorine-based and those that used chlorine-free cleaning methods supports the further use of chlorine-free cleaning agents in dairy production.

Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.

The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products., (Copyright © 2017 American Society for Microbiology.)

Background: The aim of this study was to employ high-throughput DNA sequencing to assess the incidence of bacteria with biogenic amine (BA; histamine and tyramine) producing potential from among 10 different cheeses varieties. To facilitate this, a diagnostic approach using degenerate PCR primer pairs that were previously designed to amplify segments of the histidine (hdc) and tyrosine (tdc) decarboxylase gene clusters were employed. In contrast to previous studies in which the decarboxylase genes of specific isolates were studied, in this instance amplifications were performed using total metagenomic DNA extracts., Results: Amplicons were initially cloned to facilitate Sanger sequencing of individual gene fragments to ensure that a variety of hdc and tdc genes were present. Once this was established, high throughput DNA sequencing of these amplicons was performed to provide a more in-depth analysis of the histamine- and tyramine-producing bacteria present in the cheeses. High-throughput sequencing resulted in generation of a total of 1,563,764 sequencing reads and revealed that Lactobacillus curvatus, Enterococcus faecium and E. faecalis were the dominant species with tyramine producing potential, while Lb. buchneri was found to be the dominant species harbouring histaminogenic potential. Commonly used cheese starter bacteria, including Streptococcus thermophilus and Lb. delbreueckii, were also identified as having biogenic amine producing potential in the cheese studied. Molecular analysis of bacterial communities was then further complemented with HPLC quantification of histamine and tyramine in the sampled cheeses., Conclusions: In this study, high-throughput DNA sequencing successfully identified populations capable of amine production in a variety of cheeses. This approach also gave an insight into the broader hdc and tdc complement within the various cheeses. This approach can be used to detect amine producing communities not only in food matrices but also in the production environment itself.

Here, we review what is known about the microorganisms present in raw milk, including milk from cows, sheep, goats and humans. Milk, due to its high nutritional content, can support a rich microbiota. These microorganisms enter milk from a variety of sources and, once in milk, can play a number of roles, such as facilitating dairy fermentations (e.g. Lactococcus, Lactobacillus, Streptococcus, Propionibacterium and fungal populations), causing spoilage (e.g. Pseudomonas, Clostridium, Bacillus and other spore-forming or thermoduric microorganisms), promoting health (e.g. lactobacilli and bifidobacteria) or causing disease (e.g. Listeria, Salmonella, Escherichia coli, Campylobacter and mycotoxin-producing fungi). There is also concern that the presence of antibiotic residues in milk leads to the development of resistance, particularly among pathogenic bacteria. Here, we comprehensively review these topics, while comparing the approaches, both culture-dependent and culture-independent, which can be taken to investigate the microbial composition of milk., (© 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.)

The microbial composition of raw and pasteurized milk is assessed on a daily basis. However, many such tests are culture-dependent, and, thus, bacteria that are present at subdominant levels, or that cannot be easily grown in the laboratory, may be overlooked. To address this potential bias, we have used several culture-independent techniques, including flow cytometry, real-time quantitative PCR, and high-throughput DNA sequencing, to assess the microbial population of milk from a selection of commercial milk producers, pre- and postpasteurization. The combination of techniques employed reveals the presence of a previously unrecognized and diverse bacterial population in unpasteurized cow milk. Most notably, the use of high-throughput DNA sequencing resulted in several bacterial genera being identified in milk samples for the first time. These included Bacteroides, Faecalibacterium, Prevotella, and Catenibacterium. Our culture-independent analyses also indicate that the bacterial population of pasteurized milk is more diverse than previously appreciated, and that nonthermoduric bacteria within these populations are likely to be in a damaged, nonculturable form. It is thus apparent that the application of state-of-the-art approaches can provide a detailed insight into the bacterial composition of milk and could potentially be employed in the future to investigate the factors that influence the composition of these populations., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Kefir is a fermented milk-based beverage to which a number of health-promoting properties have been attributed. The microbes responsible for the fermentation of milk to produce kefir consist of a complex association of bacteria and yeasts, bound within a polysaccharide matrix, known as the kefir grain. The consistency of this microbial population, and that present in the resultant beverage, has been the subject of a number of previous, almost exclusively culture-based, studies which have indicated differences depending on geographical location and culture conditions. However, culture-based identification studies are limited by virtue of only detecting species with the ability to grow on the specific medium used and thus culture-independent, molecular-based techniques offer the potential for a more comprehensive analysis of such communities. Here we describe a detailed investigation of the microbial population, both bacterial and fungal, of kefir, using high-throughput sequencing to analyse 25 kefir milks and associated grains sourced from 8 geographically distinct regions. This is the first occasion that this technology has been employed to investigate the fungal component of these populations or to reveal the microbial composition of such an extensive number of kefir grains or milks. As a result several genera and species not previously identified in kefir were revealed. Our analysis shows that the bacterial populations in kefir are dominated by 2 phyla, the Firmicutes and the Proteobacteria. It was also established that the fungal populations of kefir were dominated by the genera Kazachstania, Kluyveromyces and Naumovozyma, but that a variable sub-dominant population also exists.

Aims:   In this study, we compare seven different methods which have been designed or modified to extract total DNA from raw milk and raw milk cheese with a view to its subsequent use for the PCR of bacterial DNA., Materials and Results:   Seven extraction methods were employed to extract total DNA from these foods, and their relative success with respect to the yield and purity of the DNA isolated, and its quality as a template for downstream PCR, was compared. Although all of the methods were successful with respect to the extraction of DNA naturally present in cheese, they varied in their relative ability to extract DNA from milk. However, when milk was spiked with a representative Gram-positive (Listeria monocytogenes EGDe) or Gram-negative (Salmonella enterica serovar Typhimurium LT2) bacterium, it was established that all methods successfully extracted DNA which was suitable for subsequent detection by PCR., Conclusions:   Of the seven approaches, the PowerFood™ Microbial DNA Isolation kit (MoBio Laboratories Inc.) was found to most consistently extract highly concentrated and pure DNA with a view to its subsequent use for PCR-based amplification and also facilitated accurate detection by real-time quantitative PCR., Significance and Impact of the Study:   Accurately assessing the bacterial composition of milk and cheese is of great importance to the dairy industry. Increasingly, DNA-based technologies are being employed to provide an accurate assessment of this microbiota. However, these approaches are dependent on our ability to extract DNA of sufficient yield and purity. This study compares a number of different options and highlights the relative success of these approaches. We also highlight the success of one method to extract DNA from different microbial populations as well as DNA which is suitable for real-time PCR of microbes of interest, a challenge often encountered by the food industry., (© 2012 The Authors. Journal of Applied Microbiology © 2012 The Society for Applied Microbiology.)

The availability and application of culture-independent tools that enable a detailed investigation of the microbiota and microbial biodiversity of food systems has had a major impact on food microbiology. This review focuses on the application of DNA-based technologies, such as denaturing gradient gel electrophoresis (DGGE), temporal temperature gradient gel electrophoresis (TTGE), single stranded conformation polymorphisms (SSCP), the polymerase chain reaction (PCR) and others, to investigate the diversity, dynamics and identity of microbes in dairy products from raw milk. Here, we will highlight the benefits associated with culture-independent methods which include enhanced sensitivity, rapidity and the detection of microorganisms not previously associated with such products., (Copyright © 2011 Elsevier B.V. All rights reserved.)