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10/11/2013

Compositional Analysis in the Safety Assessment of Biotechnology Derived Maize Juan Manuel De la Fuente Mtz.

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Outline

Purpose for crop compositional analysis Sources of compositional variability SmartStax® compositional assessment Conclusions

Purpose Review the role of compositional analysis as part of the safety assessment of biotechnology-derived products. Present data demonstrating that gene insertion in maize, relative to other sources of natural variability, does not lead to biologically relevant changes in composition.

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Crop Composition is a Key Nutritional Attribute Through identification and cultivation of edible crops, diversification through human migration, breeding, and human selection, crop composition has been defined, determined, and modified by human activities throughout history Peanut

Sorghum

Pistachio

Corn

Domesticates

Progenitors

Hops

Rice

Soybean

Coffee 3

Compositional Analysis as part of the Safety Assessment • In 1997, the Organization of Economic Cooperation and Development (OECD) determined that “substantial equivalence provides equal or increased assurance of the safety of foods derived from GMO plants”. • Part of the safety assessment includes a composition analysis consistent with both OECD and Codex recommendations. • The compositional analysis can determine the compositional equivalence between a biotech product and a genetically similar conventional control.

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Compositional Analysis as part of the Safety Assessment • What components should be measured? – The OECD publishes a consensus document for each crop. The document for maize recommends the measurement of nutritionally significant components, including nutrients, anti-nutrients and secondary metabolites.

• The OECD emphasizes: – The analysis of differences between the biotech product and a genetically similar conventional control in the context of natural variability.

Sources of compositional variability • Environment – For any crop, the same variety/hybrid grown in different environments (geography, temperature, water-stress, field position) can express different compositions

• Germplasm – For any crop, different varieties/hybrids grown in the same environment can express different compositions – Many of these differences are correlated with phenotypic differences (e.g. yield)

• Targeted Biotech Modification – A targeted biotech modification offers a way to modify specific aspects of crop composition to develop nutritionally enhanced crops

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The variability of maize components is well characterized • Publicly available informational resources on natural variability include the ILSI-Crop Composition Database1 and published literature. % Protein in maize from ILSI database

% Protein

• In addition, in-study reference hybrids can also help describe natural variability. 1

International Life Sciences Institute

Example: Compositional Analysis of SmartStax®

• SmartStax® offers protection against lepidopteran and corn rootworm insect pests, while providing tolerance to glyphosate and glufosinateammonium herbicides.

• The compositional analysis involved the comparison of SmartStax® vs. a genetically similar conventional maize hybrid.

J. Agric. Food Chem. (2013) 61, 1991-1998

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Compositional Analysis based on OECD guidelines • The compositional evaluation of SmartStax ® was completed according to OECD recommendations. This included the analysis of the following components: Nutrients Proximates: Moisture, Ash, Fat and Protein, carbohydrates by calculation Total Dietary Fiber Amino Acids

Secondary metabolites Ferulic Acid and p-Coumaric Acid 2-Furaldehyde (furfural)

Anti-nutrients

Acid and Neutral Detergent Fiber

Raffinose

Minerals (Ca, Cu, Fe, K, Mg, Mg, Na, P, Zn) Fatty acid profile

Phytic Acid

Niacin, Vitamins B1, B2, B6 and E,  carotene, Folic Acid

• The obtained compositional data was then used to determine compositional equivalence.

How can we determine there is compositional equivalence? • First, the compositional data is statistically analyzed. The means of the biotech and conventional hybrid maize are compared for each composition component to determine the similarities and the statistically significant differences (α=0.05). • Next, the biological relevance of each statistically significant difference is assessed in the context of natural variability.

Statistical significance ≠ biological relevance

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SmartStax® vs. Conventional maize • 46 out of the 52 components measured were not different. • Six statistically significant differences were observed: 5 different fatty acids and thiamine. Component

Difference (Conventional Mean – SmartStax Mean)

Oleic Acid

0.84 %FA

Stearic Acid

-0.12 %FA

Arachidic Acid

-0.02 %FA

Eicosenoic Acid Linolenic Acid

0.01 %FA -0.04 %FA

Thiamine

0.30 mg/kg dwt %FA = % Total Fatty acid dwt = dry weight

As an example the results from oleic acid will be discussed: Oleic Acid

% Total Fatty Acid

• The difference between SmartStax® and the conventional maize is evaluated in the context of the variability observed within the conventional maize.

Difference : 0.84 3.07% FA%FA Difference : 0.84 3.07% FA %FA

Conv. Mean: 31.24 %FA

Conventional

SmartStax Mean: 30.24 %FA

SmartStax ®

• In this context the statistically significant difference between SmartStax® and the conventional maize is not biologically relevant.

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Example analyte – Oleic acid Oleic Acid

% Total Fatty Acid

• The 0.84% total fatty acid difference is small in relation to the variability in oleic acid levels as determined by the in-study references and published sources.

40.2 %FA

Conventional

References

SmartStax® 17.4 %FA ILSI range

Statistical significance ≠ biological relevance

SmartStax® is not different compositionally to a conventional maize hybrid After evaluating all statistically significant differences in the context of natural variability, the significant differences were all found not to be compositionally meaningful from a food and feed safety perspective.

Not different Compositionally

SmartStax ®

Conventional maize

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SmartStax® study is supported by many others • The SmartStax® study joins multiple studies supporting the compositional equivalence of biotech maize to conventional maize. •

For example: The amino acid levels of conventional vs biotech maize were compared for samples from eight seasons (Harrigan et. al 2010). The data demonstrates it is impossible to distinguish between conventional and biotech maize based upon amino acid composition. This observation extends to all other analytes.

Conventional Biotech

•Four different biotech traits: Insect and herbicide protection and drought tolerance •46 locations in 4 countries

•828 comparisons

Nature Biotech. (2010) 28, 404

Conclusion • The data demonstrates that gene insertion in maize does not lead to biologically relevant changes in composition; therefore downstream products would not be different.

Not different Compositionally

Biotech maize

Conventional maize

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Compositional analysis in the safety assessment of biotechnology derived maize