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

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

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

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

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

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

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

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

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

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

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

Does direct manipulation of juice alter thiol production?

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

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<0.000005 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.

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.

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%

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)

Influence of juice manipulation on other wine aroma compounds

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)

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)

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

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

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