Rangées de graines.. © INRA, Elena Schweitzer © Fotolia

Our results

Contents
  1. Introduction
  2. Human milk digestion in the preterm infant: impact of technological treatments
  3. Research & Innovation 2017 - For Food and Biobased Products
  4. The way in which proteins aggregate when heated may change their sensitising potency
  5. Enhancing the viability of spray-dried probiotic bacteria by stimulating their stress tolerance
  6. To stick or not to stick? Pulling pili sheds new light on biofilm formation
  7. When biopolymers selfassemble: a balance between energy and entropy.
  8. Mimicking the gastrointestinal digestion in a lab-on-a-chip:the microdigester
  9. How a milk droplet becomes a powder grain
  10. Research & Innovation 2016 - For Food and Bioproducts
  11. A new process for the biorefining of plants
  12. Under the UV light : the bacterial membrane
  13. Reverse engineering or how to rebuild ... bread!
  14. Green Chemistry: a step towards lipid production in yeast
  15. Individually designed neo-enzymes for antibacterial vaccines
  16. Multi-scale mechanical modelling: from the nanometric scale to the macroscopic properties of bread crumb
  17. Minimill: 500 g to assess the milling value of soft wheats
  18. Microbial production of lipids for energy or chemical purposes
  19. The discrete role of ferulic acid in the assembly of lignified cell wall
  20. Eco-design of composites made from wood co-products
  21. Analysis of volatile compounds enables the authentication of a poultry production system
  22. Nanoparticles as capping agents for biopolymers microscopy
  23. Pasteurisation, UHT, microfiltration...All the processes don't affect the nutritional quality of milk in the same way
  24. Integration of expert knowledge applied to cheese ripening
  25. Controlling cheese mass loss during ripening
  26. The shape memory of starch
  27. Research & Innovation 2015 - For Food & Biobased Products
  28. Behaviour of casein micelles during milk filtering operations
  29. Overaccumulation of lipids by the yeast S. cerevisiae for the production of biokerosine
  30. Sequential ventilation in cheese ripening rooms: 50% electrical energy savings
  31. An innovative process to extract bioactive compounds from wheat
  32. Diffusion weighted MRI: a generic tool for the microimaging of lipids in food matrices
  33. Characterization of a major gene of anthocyanin biosynthesis in grape berry
  34. New enzyme activity detectors made from semi-reflective biopolymer nanolayers
  35. Improving our knowledge about the structure of the casein micelle
  36. Heating milk seems to favour the development of allergy in infants
  37. Fun with Shape
  38. Using volatile metabolites in meat products to detect livestock contamination by environmental micropollutants
  39. SensinMouth, when taste makes sense
  40. A decision support system for the fresh fruit and vegetable chain based on a knowledge engineering approach
  41. SOLEIL casts light on the 3D structure of proteins responsible for the stabilisation of storage lipids in oilseed plants
  42. A close-up view of the multi-scale protein assembly process
  43. Controlling the drying of infant dairy products by taking water-constituent interactions into account
  44. Polysccharide nanocrystals to stabilise pickering emulsions
  45. Discovery of new degradative enzymes of plant polysaccharides in the human intestinal microbiome
  46. A durum wheat flour adapted for the production of traditional baguettes
  47. Virtual modelling to guide the construction of « tailored-made » enzymes
  48. How far can we reduce the salt content of cooked meat products?
  49. Diffusion of organic substances in polymer materials: beyond existing scaling laws
  50. Smart Foams : various ways to destroy foams on demand !
  51. Dates, rich in tannins and yet neither bitter nor astringent
  52. Sodium content reduction in food
  53. Research & Innovation 2014

Using volatile metabolites in meat products to detect livestock contamination by environmental micropollutants

Environmental micropollutants such as dioxins (PCDD/Fs), polychlorobiphenyls (PCBs), brominated flame retardants (PBDEs, HBCD), polycyclic aromatic hydrocarbons (PAHs), pesticides and veterinary products are effectively transferred to animal tissue and eventually find their way to animal-based food products where they present a risk to human health. Detecting exposure of the food chain to these substances through the analysis of meat and dairy projects is a major challenge for ensuring the safety of these sectors. Scientists at INRA are studying the volatile metabolite signature in meat products to trace the exposure of animals to micropollutants during their production. This approach appears to be particularly promising in the case of contamination by micropollutants that are rapidly metabolised by the animal and, therefore, undetectable in the final product.

Poulets de train de rôtir.. © INRA, CAIN Anne-Hélène

Are volatile compounds proof of animal exposure to environmental micropollutants?

Revealing the exposure of livestock to micropollutants a posteriori through the analysis of meat and dairy products is one of the major challenges facing research today to guarantee food chain safety.  The typical approach that consists of directly quantifying micropollutant residues in contaminated animal tissue is only applicable to micropollutants that are slowly metabolised by the animal.  It is therefore necessary to develop alternative approaches for constituents whose toxicity is known but that are rapidly metabolised.  An effective solution consists of measuring the metabolic stress induced by the exposure of the animal to these micropollutants by characterising changes in the composition of compounds in animal tissue at the end of the metabolic chain, particularly volatile ones (Fig. 1).

Explanatory scheme of the two approaches that may be used to back-trace poultry exposure to micropollutants based on analyses of animal tissues. The “residue quantification” approach is suitable for slowly metabolized micropollutants whereas the “metabolic signature” is dedicated to reveal exposure to rapidly metabolized micropollutants  (© ACS).. © INRA
Explanatory scheme of the two approaches that may be used to back-trace poultry exposure to micropollutants based on analyses of animal tissues. The “residue quantification” approach is suitable for slowly metabolized micropollutants whereas the “metabolic signature” is dedicated to reveal exposure to rapidly metabolized micropollutants (© ACS). © INRA

Metabolic signatures reveal animal exposure to rapidly metabolised micropollutants

Researchers at INRA evaluated the validity of these "volatile compound metabolic signatures" for detecting animal exposure to different families of micropollutants.  The meat chicken was chosen as the model animal.  At the same time that a control group was fed with standard feed, five groups of chickens were fed with the same feed expressly contaminated with dioxins, PCBs, PAHs, brominated flame retardants (PBDEs) and coccidiostats, respectively.  After seven weeks, the tissues (liver, fatty tissue, muscle) were sampled and analysed using both residue quantification reference methods (GC-HRMS, GC-MS/MS, LC-MS/MS) and direct MS techniques to generate global volatile compound signatures.
The livers of animals contaminated with rapidly metabolised micropollutants such as PAHs or PBDEs reveal volatile compound signatures that are clearly different from those of the control (Fig. 2), whereas, for example, the concentrations of PAHs measured in the livers by the reference method (GC-MS/MS) are not different from those of the control animals.  Similar conclusions were reached in a second experiment carried out on laying hens contaminated and then "decontaminated" with a brominated flame retardant, hexabromocyclododecane, which has sparked an increasing interest on the part of health authorities and the scientific community. On the other hand, the quantification of residues such as dioxins and PCBs confirms the significant accumulation of these substances in the liver, whereas the absence of a distinctive volatile compound signature confirms their slow metabolisation. Confirmation of these findings on other tissues and more frequently consumed animal products such as meat and eggs will soon be published.

 

The first principle component analysis design carried out on data from direct-MS volatile compound signatures of chicken livers contaminated or not with PBDEs (A) or PAHs (B) reveals a distinctive metabolic activation in the case of exposure (© ACS).. © INRA
The first principle component analysis design carried out on data from direct-MS volatile compound signatures of chicken livers contaminated or not with PBDEs (A) or PAHs (B) reveals a distinctive metabolic activation in the case of exposure (© ACS). © INRA

A :
Principle component 2 (6%)
Principle component 1 (85%)
Chickens contaminated with PBDEs
Healthy chickens
B :
Principle component 2 (5%)
Principle component 1 (84%)
Chickens contaminated with PAHs
Healthy chickens

Towards a new generation of methods to trace contamination of the food chain

Research carried out in the past mainly focused on rough metabolic signatures of the volatile fraction of animal products.  Scientists today aim at using more detailed signatures to identify the specific biomarkers of different types of contamination.  This information is now available at the molecular scale thanks to the use of "high resolution" analytical techniques such as systematic two-dimensional chromatography, combined with "time-of-flight"-type mass spectrometry (GCxGC-MS/TOF), making it possible to purify, identify and quantify the volatile compounds of interest.  On the medium term, the monitoring of biomarkers revealed by these "omic" methods could lead to the broad-spectrum detection of exposure of the food chain to rapidly metabolised contaminants such as PAHs, brominated flame retardants, pesticides and veterinary products.  This research could open the way to a new generation of reference methods for detecting specific compounds that are difficult to access through the direct quantification of residues or of their identified degradation products.  As a result of their non-targeted character, these approaches could also prove interesting to reveal the activation of previously unimagined metabolic pathways.      

Partnership

ONIRIS,laboratory of residues and contaminants in food, (LABERCA), Nantes : Reference analysis of PCDD/Fs, PCBs, PBDEs, HBCDs, HAPs.
Laboratory of Veterinary Drugs (LERMVD), Fougères : reference analysis of coccidiostats
UR AFPA, USC 340 INRA, Equipe « micropolluants et résidus dans la chaîne alimentaire » Nancy Université : controlled contamination and production of chicken's flesh
URA-ITAVI, Nouzilly, France : production of laying hens.
Most of these experiments have been funded under the European project SIGMA-CHAIN (2005-2009) No. FP6-518451 (www.sigmachain.eu).

Références

See also

  • Berge P.,  Ratel J., Fournier A., Jondreville C., Feidt C., Roudaut B., Le Bizec B., Engel E. Use of Volatile Compound Metabolic Signatures in Poultry Liver to Back-Trace Dietary Exposure to Rapidly Metabolized Xenobiotics. Environ. Sci. Technol. 2011, 45, 6584–6591.
  • Ratel, J., Engel, E. 2012. Back-tracing poultry meat chain exposure to rapidly metabolized pollutants using volatile compound metabolic signatures in liver tissues. The Column. 8, 2-10.
  • Fournier A., & Feidt C., Marchand P., Vénisseau A., Le Bizec B., Sellier N., Engel E, Ratel J., Travel A., Jondreville C. Kinetic study of γ-hexabromocyclododecane orally given to laying hens (Gallus domesticus). Environ. Sci. Pollut. Res. 2012, 19, 440-44