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Metabolomics and the Detection of Unintended Effects in Genetically Modified Crops

  • Laetitia Shintu
  • Gwénaëlle Le Gall
  • Ian J. Colquhoun
Chapter

Abstract

The chapter describes current procedures for the safety assessment of genetically modified crops and foods. The concepts of substantial equivalence, the conventional comparator, and intended and unintended effects are introduced. Most published examples of substantial equivalence testing deal with crops that have been modified for insect resistance or herbicide tolerance. A standard procedure has developed based on broadly similar field trial designs, sampling schemes and targeted analyses of a consensus set of compounds for each crop. The main characteristics of the procedure are summarised with reference to published analyses of this type of crop and different statistical approaches to judging ‘equivalence’ are discussed.

There is a current trend towards development of crops with enhanced nutritional properties or health-related benefits through genetic modification of metabolic pathways. These more complex modifications have greater potential for introducing unpredictable unintended effects, and it may be advisable to supplement current targeted analysis procedures with metabolomics methods. The second part of the chapter discusses the application of metabolomics to substantial equivalence testing. As yet there is no standard procedure for this approach so individual studies, which differ greatly in size and scope, are discussed. The major analytical techniques (GC/MS, LC/MS and NMR) are briefly described and examples of their use are given: a few studies have shown how the massive amounts of data produced by non-targeted profiling methods may be treated to judge equivalence. Some limitations need to be overcome before metabolomics can be adopted as part of the official safety assessment procedure.

Keywords

High Performance Liquid Chromatography Linear Discriminant Analysis Metabolic Profile Unintended Effect Safety Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

2D

Two-dimensional

ANOVA

Analysis of Variance

AOAC

Association of Analytical Communities

COSY

Correlation Spectroscopy

DIMS

Direct Injection Mass Spectrometry

DP

Degree of Polymerisation

EFSA

European Food Safety Authority

ESI

Electrospray Ionisation

FAO/WHO

Food and Agriculture Organisation/ World Health Organisation

FIE-MS

Flow Injection Electrospray Mass Spectrometry

FT-ICR-MS

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

FTIR

Fourier Transform Infrared

GC/FID

Gas Chromatography/ Flame Ionisation Detector

GC/MS

Gas Chromatography/ Mass Spectrometry

GC-TOF-MS

Gas Chromatography-Time of Flight-Mass Spectrometry

GM

Genetically Modified

HMBC

Heteronuclear Multiple Bond Correlation

HPLC

High Performance Liquid Chromatography

HSQC

Heteronuclear Single Quantum Coherence

ILSI

International Life Sciences Institute

LC/MS

Liquid Chromatography/ Mass Spectrometry

LDA

Linear Discriminant Analysis

MAS

Magic Angle Spinning

NMR

Nuclear Magnetic Resonance

OECD

Organisation for Economic Cooperation and Development

PC

Principal Component

PCA

Principal Component Analysis

PLS

Partial Least Squares

PLS-DA

Partial Least Squares-Discriminant Analysis

RT

Retention Time

SD

Standard Deviation

SPE

Solid Phase Extraction

TOCSY

Total Correlation Spectroscopy

UV

Ultraviolet

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Laetitia Shintu
    • 1
  • Gwénaëlle Le Gall
    • 1
  • Ian J. Colquhoun
    • 1
  1. 1.Institute of Food ResearchNorwich Research ParkNorwichUK

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