Gene sequencing was used to analyze the samples, the same method already being used to study the gut microbiome and soil, according to researcher Maria L. Marco, PhD, an associate professor in the department of food science and technology at UC Davis. “The method has been revolutionary in medicine, agriculture, and many other fields where microbes can be either beneficial or detrimental,” she says.
Using DNA sequencing, Dr. Marco and her team found that the communities of milk microbiomes are highly diverse, with a core microbiota showing distinct seasonal trends. Milk collected in the spring had the most diverse bacterial communities, with the highest total cell numbers and highest proportions of Actinobacteria. A core community of microbes was found in all the raw milk samples, with 29 different bacterial groups and high proportions of Streptococcus and Staphylococcus, as well as Costridiales. The bacterial composition of milk stored in some silos at processing plants was distinct from that in the tanker trucks.
According to Dr. Marco, the research, which was published in a 2016 issue of American Society for Microbiology’s mBio, demonstrated “how the built environment in processing plants can have significant but still unpredictable impacts on the microbial quality of foods.” There are three major ways that this research can impact the dairy industry, she notes. First, it can help identify probable contamination points in processing, such as the pieces of equipment or precise steps where contaminants enter. Second, it can shed light on effective cleaning protocols, such as when and how to clean and how much time should elapse before a piece of equipment should be cleaned again. “Contaminant bacteria can build up over time, so our work is focused on helping processors refine their cleaning procedures,” she says. And third, using DNA sequencing will help increase the ability to predict spoilage. Understanding how to predict which milk would most likely result in a defect in cheese or other dairy product can improve the treatment and handling of milk and thus ensure consistently high-quality products, Dr. Marco emphasizes.
This type of testing is not intended to replace the widely used diagnostic assays that effectively identify pathogens such as Listeria or Salmonella and Campylobacter in milk. Instead, it is an additional approach that can help identify a potential safety risk. “This has shown that we have to be mindful that frequent sampling is needed and that, by using methods we never had before, we can really monitor the equipment to keep the contaminants down,” Dr. Marco says.
Genomics Tools
Metagenomics and metatranscriptomics have moved food safety, including dairy safety, into the arena of nontargeted screening to give early warning signals of deviations that could indicate a safety issue. The use of genomics also provides a more precise method of detecting, characterizing, and identifying pathogens in foods such as milk, according to Martin Wiedmann, DVM, PhD, Gellert Family Professor in Food Safety at Cornell University. Sequencing DNA and RNA means that the microbiomes can be profiled all along the milk supply chain.
Cornell is collaborating with IBM Research as part of the Consortium for Sequencing the Food Supply Chain (the university is one of several members). The goal of the consortium is to categorize and understand microorganisms and the factors that influence their activity in a normal, safe environment, and to develop the science and the tools that can be used for analysis. Researchers at Cornell are using the university’s own approved and licensed dairy farm and processing facility as a “model system for how we can implement on a routine basis these types of tools,” Dr. Wiedmann says.
Another focus of the program is defining the baseline for “normal” raw milk, and then being able to define “abnormal” milk, he points out. “We have started developing the knowledge to detect some of these abnormalities earlier and trace them back to identifying the cause and, therefore, more effectively and more rapidly address or further characterize the abnormalities.”
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