Characterising 'normal' milk


Friday, 30 June, 2017

To minimise the chances of the global milk supply being impacted by safety breaches, IBM and Cornell University are using genetic sequencing and big data analytics to characterise milk.

With the onset of this dairy project, Cornell University has become the newest academic institution to join the Consortium for Sequencing the Food Supply Chain, a food safety initiative that includes IBM Research, Mars and Bio-Rad Laboratories.

Normally, raw milk samples are tested for a few specific groups of bacteria. However, the Consortium for Sequencing the Food Supply Chain is using the community of microbes or bacteria known as the microbiome to characterise the food samples at an unprecedented resolution. By sequencing and analysing the DNA and RNA (genetic code) of food microbiomes, researchers plan to create new tools that can help monitor raw milk to detect anomalies that represent food safety hazards and possible fraud.

Characterising what is ‘normal’ for a food ingredient can better allow the observation of when something goes awry. Detecting unknown anomalies is a challenge in food safety and serious repercussions may arise due to contaminants that may never have been seen in the food supply chain before.

While many food producers already have rigorous processes in place to ensure food safety hazards are managed appropriately, this pioneering application of genomics will be designed to enable a deeper understanding and characterisation of microorganisms on a much larger scale than has previously been possible. Consortium researchers will conduct several studies comparing the baseline data of raw milk with known anomalies to help create proven models that can be used for additional studies. They will continue to provide innovative solutions that can potentially minimise the chance that a food hazard will reach the final consumer and provide a tool to assist against food fraud.

The research project will collect genetic data from the microbiome of raw milk samples in a ‘real-world’ scenario at Cornell’s Dairy Processing Plant and farm in Ithaca, New York. The facility is unusual in that it represents the full dairy supply chain — from farm to processing to consumer. This initial data collection will form a raw milk baseline and be used to further expand existing Consortium bioinformatic analytical tools.

The Consortium for Sequencing the Food Supply Chain was officially launched in January 2015 by IBM Research and Mars, Incorporated. Bio-Rad Laboratories joined the Consortium in 2016. This collaborative food safety initiative will leverage advances in next-generation sequencing to further the understanding of what can help make food safe. The consortium is conducting the largest-ever metagenomics study to categorise and understand microorganisms and the factors that influence their activity in various food matrices. This work could eventually be extended into the larger context of the food supply chain — from farm to fork — and, using artificial intelligence and machine learning, may lead to new insights into how microorganisms interact within a particular environment.

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