1. Farhana R Pinu Richard C Gardner Silas G Villas-Boas
Sauvignon blanc metabolomics: Influence of juice manipulations on wine aroma compounds
Farhana R Pinu Richard C Gardner Silas G Villas-Boas
School of Biological Sciences, University of Auckland

2. Volatile thiols are key aroma compounds of SB wine
Volatile thiols are absent in juice
Yeasts convert odourless precursors
Volatile thiol
Structure
Olfactory description/threshold
3-mercaptohexan- 1-ol (3MH)
Grapefruit, passion fruit (60 ng/L)
3-mercaptohexyl acetate (3MHA)
Box tree, passion fruit
(4 ng/L)
4-mercapto-4-methylpentan-2-one (4MMP)
Box tree, broom, cat’s pee (0.8 ng/L)
volatile thiols in wine

3. Existing hypotheses regarding biosynthesis and transformation of volatile thiols
Very low conversion rate of precursors to respective volatile thiols
Cys-3MH MH
0.1% (Dubourdieu et al. 2006) up to 7% (Subileau et al. 2008).
GSH-3MH MH
4.5% ( Roland et al. 2010a)
GSH-4MMP MMP
0.3% ( Roland et al. 2010b)

4. Poor correlation of putative precursors with 3MH and 3MHA in 55 juices
Pinu et al. 2012; AJEV 63: 3
3MHA
0.78
0.27
0.22
3MH
0.017
0.026
Cys-3MH
0.78
GSH-3MH

5. Sauvignon blanc metabolomics
Aim:
Correlate metabolite profile of Sauvignon grape juice with thiol levels of fermented wine
Objectives:
To establish methods for comprehensive metabolite profiling of grape juice and wines
To determine metabolites in juice that influence the production of volatile thiols in wines
To provide a biochemical basis for improved selection of juices for different styles and batches of wine based on the metabolite profile of the juice

6. Experimental approach
2006 ,2007 and 2008 MB=20
2009 MB=20
2010 MB=13
2010 HB and CO=10
Total= 63 juices

7. GC-MS metabolite profile generated using Metab, a new R package (developed in our Lab)

8. Correlation network of GC-MS peaks with varietal thiols
3MHA
3MH
4MMP

9. Metabolite profile of grape juices from NMR (software: Amix)
Peak area
Peak areas
Bucket=compound
Juices

10. Correlation networks with 3MH and 3MHA with different NMR buckets/compounds

11. Juice metabolites showed better correlation with volatile thiols than the precursors  
4MMP
3MH
Acetylation ratio
3MHA fa
aa6
ca7
aa9
aa4
aa7
aa5
aa8
ca5
ca6
aa1
ca1
ca2
ca4
aa2
aa3
aa11
ca8
aa12
aa10
aa13
aa14
GSH-3MH
Cys-3MH
Tripeptide
Cys-gly-3MH

12. Does direct manipulation of juice alter thiol production?

13. Only one group of compounds “ca” affected the rate of fermentation (longer lag)

14. 35x more 4MMP was produced when 1000 µg/L cys-4MMP was added
a= p-value<0.05
b= p-value<0.005
c= p-value<0.0005
d= p-value<
0.045%
No influence on 4MMP production when DAP and carboxylic acids were added to the juice
More than 2-fold increase was found when aa1, aa2, fa, all aa and cys-3MH had been added.

15. aa1 and ca1 increased the production of 3MH to 150%
a= p-value<0.05
b= p-value<0.005
c= p-value<0.0005
no difference found in the production of 3MH when DAP(YAN300, YAN600),Cys-4MMP,Cys-3MH (putative precursor for 3MH) were added in the juice.
4x ca decreased the concentration of 3MH.

16. 100% increase of 3MHA concentration when aa1, aa2, s-ethyl-cys, Glut-3MH and DAP (YAN400) were added to juice
a= p-value<0.05
b= p-value<0.005
c= p-value<0.0005
3MHA concentration did nt change when 2x all metabolites and 2x ca were added.
‘fa’ decreased the production of 3MHA by 43%

17. OAV> 1 is perceived by human nose
Contribution of volatile thiols in manipulated wines by Odor Active Values (OAV)
OAV= (concentration of an aroma compound in wine)/ perception threshold
OAV> 1 is perceived by human nose
Aroma compound
Aroma descriptor
OAV in control wine
Maximum OAV
Minimum OAV
3MH
Grapefruit, passion fruit 19
29 (aa2)
15 (4xca)
3MHA
Box tree, passion fruit 59
127 (aa2 and GSH-3MH)
34 (fa)
4MMP
Box tree, cats’ pee 15
526 (Cys-4MMP)
14 (DAP 300)

18. Influence of juice manipulation on other wine aroma compounds

19. Contribution of esters in manipulated wines by OAV
Aroma compound
Aroma descriptor
OAV in control wine
Maximum OAV
Minimum OAV
Isoamyl acetate
Banana, apple, pear
106
175 (aa1)
23 (fa)
Ethyl hexanoate
Pineapple 53
72 (DAP 300)
24 (fa)
Ethyl butanoate
Apple, fruity 23
32 (2xaa)
7 (fa)
ß-phenylethyl acetate
Fruity, olive 2
3 (aa1)
0.60 (fa)
Ethyl decanoate
Fruity
1.59
2.4 (all meta)
0.65 (2xca)
Ethyl octanoate
Ripe banana
1.26
2.3 (all meta)
0.63 (4x ca)
Ethyl isovalerate
Fruity, cheese
1.08
3 (DAP 300)
0.75 (Cys-4MMP)

20. Contribution of other aroma compounds in manipulated wines by OAV
Aroma descriptor
OAV in control wine
Maximum OAV
Minimum OAV
Decanoic acid
Woody, fatty 20
21 (ca1)
8 (4xca)
Isovaleric acid
Sweet, cheese 14
18 (DAP 600)
4 (1xaa)
Hexanoic acid
Sweet, spicy 12
16 (DAP 400)
8 (4x ca)
β-ionone
Floral
6.6
6.7 (aa1)
5.5 (s-ethyl-cys)
Isoamyl alcohol
Burnt, whisky 4
7 (2x aa)
3 (Cys-3MH)
Octanoic acid
Fatty, dry, dairy 3
No change
Cis-3-hexen-1-ol
Green, cut grass
2.27
2.7 (aa1)
1.6 (Cys-3MH)
Hexanol
Resin, cut grass
2.25
4 (4xca)
1.4 (Cys-3MH)
Methionol
Cooked cabbage 2
9 (2xaa)
0.46 (2xallmeta)
β-damascenone
Rose
1.5
2.6 (fa)
0.47 (s-ethyl-cys)

21. Key findings and outcomes
Identification of juice metabolites that correlate with production of volatile thiols
24 juice metabolites
Not precursors
Addition of juice metabolites affect the formation of thiols and other wine aroma compounds
Juice metabolites, DAP, S-compounds, precursors
Identification of metabolites that can predict the thiol production in wine by looking at juice composition
New direction to produce different styles of Sauvignon blanc wines according to consumers’ choice

22. Conclusions
The results from juice addition experiment validated the metabolomics hypothesis
New insight in Sauvignon blanc research:
Some non-sulfur, even some non-nitrogenous metabolites have impact on the production of volatile thiols
unsuspected connection between regulation of central metabolism of the yeast cell and the production of volatile thiols

23. Acknowledgements
Supervisors: Dr. Silas G. Villas-Boas and Professor Richard Gardner
Data analysis: Raphael Aggio (SBS), Dr Marlon dos Reis (AgResearch), Dr Kim-Anh Lee (University of Queensland, AUS) and Dr Katya Ruggiero (SBS)
NMR Analysis: Dr. Patrick Edwards, Massey University
WineScan: Villa Maria Lab
Juice collection: Andy Frost (Pernod Ricard), Saint Clair Family Estate, Soon Lee (Wine Sci), Sara Jouanneau (Wine Sci), Jody Hasty (VinPro, Otago), Vidal wines, Trinity Hills, C.J. Pask winery and Pernod Ricard for supplying grape juices
Scholarship: Education New Zealand (NZIDRS) and University of Auckland Doctoral Scholarship
Project funding: MSI, School of Biological Sciences and NZ Winegrowers
All the members of Metabolomics group and Wine Science, specially Soon, Zum and Mandy