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Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
Yeast Genomics: Medium and Long Term Goals
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Yeast Genomics: Medium and Long Term Goals

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Wine microbiology, particular the yeast(s) responsible for the conversion of grape juice to wine, has a significant impact on wine composition and thus the quality and saleablilty of wine. …

Wine microbiology, particular the yeast(s) responsible for the conversion of grape juice to wine, has a significant impact on wine composition and thus the quality and saleablilty of wine. Understanding the manner in which yeast genetic constitution influences these processes can shed light on ways a winemaker might be able to manipulate winemaking conditions, and therefore yeast performance. In addition, such knowledge will provide researchers with approaches to isolate or produce strains with superior performance. This presentation outlines the medium and long term goals of research activities in this area.

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  • 1. Wine 2030 Conference Research to transform the wine industry Yeast Genomics: Medium and Long Term Goals Assoc Prof Vladimir Jiranek School of Agriculture, Food and Wine The University of Adelaide, Waite Campus. The University of Adelaide is a partner in the Wine Innovation Cluster
  • 2. Winemaking is easy But hard to predict exact outcome (composition) + = A particular composition is important to sell wine (i.e. one specifically sought after by consumers)
  • 3. Winemaking is easy But hard to predict exact outcome (composition) + = A particular composition is important to sell wine (i.e. one specifically sought after by consumers)
  • 4. • Must know what consumers (producers) want (from a compositional point of view) • Need to understand process so that can achieve this – per se i.e. in a „typical‟ year but also – against increasing variability (of inputs and consumer desires) Long term goal: To achieve a precise (tailored) compositional outcome (i.e. „dial-up a wine‟)
  • 5. What does the outcome of reaching the long term goal look like? Complete compositional Influence of profile of winemaking grapes/juice fully defined Reconcile & integrate inputs, control the process Wine of specified composition
  • 6. Can’t tackle all aspects toward long term goal What are some key medium term goals? Defining the Yeast and „Wine‟ Metabolomes Defining Wine Yeast Genomics Integrating these datasets Developing models and thus strategies or strains Moving to include more winemaking parameters
  • 7. The Wine Yeast and ‘Wine’ Metabolomes: Progress & Challenges  Development of protocols for exo- & endo- metabolomes of yeast in „wine‟ media (merit of each?)  Definition of the Wine Metabolome Metabolites from yeast and bacteria, grapes, additives, chemical reactions, enzymatic modification, etc. • Definition of above is a large but „pedestrian‟ task • Analytical systems exist but not a single platform • Can detect but not identify all – need reference libraries • Need to integrate multiple datasets – data management
  • 8. Wine Yeast Genomics: Progress & Challenges  Lab yeast genome has been sequenced (1996)  Genomes of wine yeasts recently sequenced (2008) FEMS Yeast Res. (2008) Interpretation – lost, added, modified, new genes  Functional Genomics to understand function of genes in winemaking Can look at all genes OR just the vital genes i.e. the “(Minimal) Wine Genome” Use libraries – deletion, over-expression, etc. Need to look at interactions of genes
  • 9. Genome-Metabolome Integration, Predictive Models, Strategies and Strains: Progress & Challenges  Integration of information from two(+) data sets leading to a predictive model of fermentation and metabolism.  Development of strategies for tailoring wine Juice:strain matching Ferment management protocols
  • 10. Genome-Metabolome Integration, Predictive Models, Strategies and Strains: Progress & Challenges ►Minimal Genome used to yield a „skeletal‟ yeast as a basis for constructing tailored yeasts Strains used: as is (i.e. GM) as proof-of-concept for selecting natural variants (non-GM) Data + data + data = bioinformatics will be essential!
  • 11. Long Term Goal Move towards a systems approach by way of: • Rapid and comprehensive analytical capabilities. • Completely integrated model(s) of viticultural and oenological parameters. To give protocols for the ready modification of winemaking (i.e. process and yeast) for a given outcome even if inputs are variable. This ability to will need to able to rapidly respond to changing consumer preferences or market forces.

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