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This is a first in a series of invited blogs from FAN's laboratory Centres of Expertise.  In this article, Christophe Noel from SGS's food analysis molecular biology team, discusses the likely challenges in authenticating lab-grown meat.

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The Infinite Animal: Mutation, Identity, and Authentication in Lab-Grown Meat

Lab-grown meat, or cultured meat, presents a new frontier in food production.  It introduces complex authentication challenges involving traceability, product integrity, and regulatory compliance.

With novelty and uncharted territory comes the need for new and emerging technological and regulatory strategies, as well as a combination of different methodological approaches to address these issues.

For example, the use of molecular and isotopic fingerprinting to distinguish lab-grown meat from conventional meat products—by analysing specific metabolic markers or isotopic ratios unique to cell culture processes—appears to be a promising option. DNA-based methods, including barcoding and genetic tracing, are also being proposed to verify cell line origins and production authenticity. Additionally, blockchain technology could offer transparent supply chain management, providing immutable records of production steps from cell culture to final product labelling, which would be extremely valuable.

Regulatory bodies are contributing by drafting frameworks that require rigorous documentation and verification at each stage of production, helping to establish standards for what legally constitutes "cultured meat."

Despite these advances, the field remains in its infancy, and ongoing research is crucial for validating these methods across different production platforms and global regulatory systems.

When considering the potential role of DNA/RNA analysis, its scope can include confirming the animal species present, detecting potential adulteration, identifying the nature of heterogeneous scaffolding, or even verifying the brand of the product if a unique genetic signature—either naturally occurring or engineered as a molecular label—is used.

An important aspect to consider in terms of authentication is the genetic stability of the product. A fundamental characteristic of cultured meat is that once cells are collected from the animal, this step is not repeated. The cell line must become immortal, ideally multiplying indefinitely and remaining genetically identical. However, cell culturing and propagation are, by nature, driving forces for potential mutations, raising the question of how we monitor these effects and their impact on the integrity of the final product.

Ultimately, an important question for authentication arises: are we destined to eat a definitive, unchanging version of one animal forever?

 

SGS Analytics United Kingdom Ltd is a UKAS (ISO17025) accredited analytical laboratory specialising in molecular and immunological detection of contaminants and adulterants in foodstuffs. With specific reference to authenticity testing our core area of expertise is the detection of meat, plant, fish and crustaceans using endpoint PCR; real time-PCR, PCR-sequencing and Next Generation Sequencing based technologies.  FAN has more information here.

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13208864101?profile=RESIZE_584xThe FAN annual call for new Centres of Expertise (CoEs) was launched in the last FAN Newsletter; the applications received were reviewed by FAN and recommendations for acknowledgement discussed and agreed with the UK Department for Environment, Food and Rural Affairs, the Food Standards Agency & Food Standards Scotland.  

We are delighted to announce that the following five organisations have been acknowledged as Food Authenticity CoEs:  

  • Edinburgh Scientific Services 
  • Glasgow Scientific Services 
  • Hampshire Scientific Services 
  • Isle of Man Government Laboratory 
  • Tayside Scientific Services.  

These organisations are all Public Analyst laboratories and have a wealth of experience in food authenticity analysis in the context of official controls. Two Public Analyst laboratories were already recognised as CoEs, and now all seven will be listed as food authenticity CoEs in a separate category called ‘Public Analysts’. 

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10951670268?profile=RESIZE_710xThe Food Authenticity Network has worked with Defra, FSA, FSS, NFCU, SFCIU and the Food Authenticity Centres of Expertise to agree a framework for a co-ordinated response from food authenticity Centres of Expertise to national / international food and feed fraud incidents / investigations.

Official controls of food and feed labelling and compositional standards involves the verification of labelled product information and requires a wide range of analytical and molecular biological techniques to be deployed, many with exacting instrumentation requirements and in-depth scientific interpretation of the datasets generated. In recognition that no single institution could field the complete range of such techniques with the required expertise in all of the food and feed commodity groups, a number of Food Authenticity Centres of Expertise (CoEs) have been acknowledged (see below for list and further information). 

It was envisaged that the virtual network of  CoEs would function in a similar way to a National Reference Laboratory by helping to ensure that authenticity testing methods employed are fit for purpose and offer expert advice to the food authenticity analytical community as required. 

A framework has been produced for collaboration of Food Authenticity Centres of Expertise to facilitate the formulation a collective technical view, in response to a request from UK Government, during an emergency food or feed fraud incident/investigation. A collective technical view will facilitate UK Government in making evidence-based decisions in a timely manner so as to minimise the impact on legitimate businesses and protect consumers.

The Framework is not a public document but the process flow diagram is presented above to illustrate the process agreed. An accessible version is available here.

The Framework flow chart and the accessible version have also been added to the CoE page on this network.

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