Enhancing the Nutritional Quality of Tomato Fruit

1. Enhancing the Nutritional Quality of Tomato Fruit Genny Enfissi Royal Holloway, University of London

2. Research Group & Interests • Peter Bramley & Paul Fraser: 20 post-docs, PhD students, MSc students and technicians. • Biosynthesis, regulation & genetic engineering of isoprenoid formation in plants & micro-organisms. • Non-GM approaches to enhancing health related consumer traits in tomato. • Food safety, particularly unintended effects in novel foods. • Metabolomics/Proteomics and Systems Biology.

3. Overview of Presentation • Introduction to bioactives and tomato. • Utilising natural diversity. • Screening for improved health-related traits. • Metabolomics and metabolomics-assisted breeding. • Enhancing multiple bioactive classes simultaneously in tomato.

4. Colour & Health Quality Traits • Carotenoid and flavonoid pigments are responsible for most of the colour of fruits and vegetables found in nature.

5. Health-Promoting Phytochemicals • Bioactives in fruits and vegetables have been linked to a reduced incidence of chronic disease states.

6. Health Benefits Associated with Diets Rich in Fruit & Vegetables • Flavonoids - hydrophilic antioxidants, prevent certain cancers and cadiovascular disease. • Carotenoids - lipophilic antioxidants, e.g. lycopene which prevent certain cancers, b-carotene (provitamin A) and xanthophylls (prevent eye disease, AMD). • WHO recommend 500 g per day of fruit and vegetables (5 servings per day).

7. Tomatoes • Tomatoes are the principal source of lycopene in the human diet, and also a major dietary source of b-carotene. • In addition, they contain synergistic bioactives such as flavonoids, phenylpropanoids, tocopherols & vitamin C.

8. Natural Diversity

9. Wild ancestors of domesticated tomato varieties have been used to re-introduce genetic diversity. By crossing a wild species with a domestic tomato large populations of introgressed lines (ILs) are developed. Diversity & Opportunity

10. Introgression Lines • Each line contains mapped genomic regions from the wild relative. • Screened for improved traits e.g. stress tolerance, improved yield or nutritional qualities. • To identify QTL and candidate genes. http://zamir.sgn.cornell.edu/Qtl/il_story.htm

11. Diversity of Tomato ILs Pictures taken from http://solgenomics.net

12. Screening of Tomato Collections • Targeted HPLC-PDA analyses performed on 4 different introgression collections: S. pennellii, S. neorickii, S. galapagense and S. habrochaites. • Carotenoids, tocopherols, phenylpropanoids and flavonoids quantified. • Identified a number of lines with elevated health-related bioactives. • Isolated dominant candidate genes which can be crossed into elite lines.

13. Identification of Health-Related Flavonoid QTL • 142 introgression lines. • 4 Biological replicates plus technical replicates, controls and QC samples. • Analysed by HPLC-PDA and 18 metabolites identified and quantified (~20k data points). • 10 lines with 5 fold to 60 fold increases in rutin. • Plus a series of lines with novel phenylpropanoid profiles with over 800 fold increases in some compounds.

14. Global Analysis • Multiple analytical platforms utilised to identify and quantify >150 metabolites. 2,500 compounds putatively identified (50% validated). • Provides greater understanding of metabolism as a whole. • Can be applied to any crop of interest. • Can be applied to post-harvest analysis or processed samples. (Currently analysing unique post-harvest QTL).

15. Metabolomic Approaches to Screening Introgression Collections Biological material Optimised extraction • Targeted analysis • carotenoids • tocopherols • phytosterols • water soluble B vitamins • flavonoids, phenylpropanoids • anthocyanins • glycoalkoids Non-targeted analysis DI-MS GC-MS known metabolites (primary metabolites) NMR Data analysis Mathematical interrogation Extraction PCA Pathway displays Integration of metabolomic and transcriptomic data Correlation analysis

16. sd sd Asc c si a TFM7 TFM7 st c Asp at Chl r ne lu gl A. T56 B. ma T56 lt 2A11 2A11 P119 b-c lu P119 mt gl mt Principal component-2 Principal component-2 gl fa Principal component-1 Principal component-1 va C. 2A11 D. ma gl va lu P119 ma Principal component-2 (36%) r T56 fr Principal component-2 ci at fr L dasc b-c 2A11 P119 si TFM7 sd a st T56 c TFM7 Principal component-1 Principal component-1 Principal Component Analysis- ~150 Metabolites from Multiple Analytical Platforms • Mature green- targeted • and non-targeted analysis. • B. Mature green-non-targeted • analysis. • C. Ripe- targeted and • non-targeted analysis. • D. Ripe-non-targeted • analysis.

17. Biological material Optimised extraction • Targeted analysis • carotenoids • tocopherols • phytosterols • water soluble B vitamins • flavonoids, phenylpropanoids • anthocyanins • glycoalkoids Extraction Metabolomic Approaches to Screening Introgression Collections Non-targeted analysis DI-MS GC-MS known metabolites (primary metabolites) NMR Data analysis Mathematical interrogation PCA Pathway displays Integration of metabolomic and transcriptomic data Correlation analysis

18. Global Overview of Metabolism Green is significant elevated levels Red is significant decreased levels Not present but detectable by the analytical platform Red ripe stage P119 • Simultaneous increases in all antioxidants

19. Biological material Optimised extraction • Targeted analysis • carotenoids • tocopherols • phytosterols • water soluble B vitamins • flavonoids, phenylpropanoids • anthocyanins • glycoalkoids Extraction Metabolomic Approaches to Screening Introgression Collections Non-targeted analysis DI-MS GC-MS known metabolites (primary metabolites) NMR Data analysis Mathematical interrogation PCA Pathway displays Integration of metabolomic and transcriptomic data Correlation analysis

20. Relative change compared to wild type Log scale Metabolite QTL Identified Within the S. pennellii Population 3 million data points. 2,600 mQTL identified to date

21. Metabolomics Summary • Wide range of genetic resources available. • Identified many thousands of metabolite changes. • Integration of metabolite data sets with other profiling methods e.g. transcriptomics. • Elucidate the underlying mechanisms behind traits and identify candidate genes for breeding. • Potential to predict metabolite response to perturbations in metabolism.

22. Limitations • Robust QTL identified through analysis of repeat crops and crops grown in different environmental locations/conditions. • Time consuming, expensive and yet to identify robust lines with simultaneously enhanced levels of multiple bioactives. • Development of elite lines even utilising the latest “omic” technologies is estimated to take 6 or 7 years.

23. Enhancing Multiple Bioactives Simultaneously • No proof that carotenoids or flavonoids when extracted and given as supplements have anti-cancer properties. • BUT a diet high in fruits and vegetables rich in these bioactives might due to the synergistic action of the vitamins, minerals and bioactives they contain.

24. Tomato high pigment Mutants wild type hp2(DET-1)

25. Cis-genic Approach • Down regulating the endogenous gene in a fruit specific manner over comes the negative effects of the mutation seen in the hp plants i.e. loss of plant vigour and poor fruit yield. • Cis-genic modification does not include any transgenes. Enfissi et. al., Plant Cell (2010), 22:1-26

26. DET1 Phenotype T56 P119 T56 2A11 TFM7 P119 TFM7 2A11

27. Enhanced Bioactive Content • Carotenoids and tocopherol:2.5 to 10-fold increases, no change in composition. • Phenylpropanoids and flavonoids: 4 to 14-fold increase in quercetin derivatives (rutin), 10-fold increase in chlorogenic acid, 3-fold increase in anthocyanidins. • Vitamin C:5 to 10-fold increases.

28. A. B. Total Antioxidant Activity in DET1 Fruit A: Polar (flavonoids) B: Non-Polar (carotenoids) • Significant increases in activity in all lines. • Up to 4-fold in polar extracts & 2-fold in non-polar extracts.

29. Cis-genic Approach Summary • Simultaneous elevation of both polar and non-polar health-promoting bioactives, increasing antioxidant capacity. • No loss of plant vigour or yield. • A single DET1 fruit provides 3x the RDA pro-vitamin A and elevated levels of multiple synergistic bioactives.

30. Conclusions • The combination of advanced “omics” technologies now available for tomato is allowing exploitation of the natural genetic diversity and the discovery of new traits. • Metabolomics methods and screening protocols can be applied to any crop or trait of interest including post-harvest or processed products.

31. Conclusions • Metabolomics-assisted breeding will result in production of crops with improved nutritional traits (amongst others). • Cis-genic approaches are a viable option although still subject to GMO regulations.

32. Acknowledgements RHUL Peter Bramley Paul Fraser Tom Wells Mike Goodfellow Dan Rickett Chris Gerrish Seminis Ltd. Henk Pennings Hebrew University Jerusalem Dani Zamir Nottingham University Graham Seymour Naples and CNRS/ENS Chris Bowler Syngenta Ltd. Charles Baxter Funding- European Commision (EU-Sol Project PI016214), BBSRC (#C19322), Syngenta and Seminis Ltd.

33. H C O 3 - O R - R O O C H 3 PARTNERS P1-RHUL : Dr Paul D. Fraser (Coordinator) & Dr Genny Enfissi P2-Max Planck, Golm, Prof. Ralph Bock METAPRO P3-ENEA, Prof. Giovanni Giuliano P4 P4-SCRI, Dr Mark Taylor P1 P2 P8 O O H H P6-Freiburg University, Prof. Peter Beyer P6 H H O O P7- Metapontum Agrobios, Dr Giovanni Giorio O O P3 P8- Proplanta, Prof. Carmen Socaciu P7 P5 Budget: 4.1 million EUR www.isoprenoid.com The development of tools and effective strategies for the optimisation of useful secondary METAbolite PROduction in planta (METAPRO) P5-Hebrew University, Prof. Yossi Hirschberg