The amino acid consumption pattern is broadly consistent for both strains, especially for the preferred amino acids, with the exception of arginine. There was no significant difference in the final biomass accumulation between the strains as is shown in Figure 1 except for fermentation driven by arginine, leucine, isoleucine, tyrosine and threonine which had strain B producing more cells at the end of fermentation. From this it can deduced that strain B is a better fermenter than strain A given that they had similar media to begin with.
These data highlight the fact that total YAN only has limited potential to predict the fermentation performance of yeast. Indeed, two musts with the same YAN, but very different amino acid composition, and in particular a different ratio of preferred vs. non-preferred amino acids, will lead to different fermentation dynamics.
Aroma production was determined by using gas chromatography coupled with a flame ionisation detector. The aroma compounds were extracted using ethyl acetate and a total of 32 compounds were analysed. The volatile compound production was more driven by the amino acids used as nitrogen source than by the yeast strain. With the exception of acetic acid and ethyl acetate, aroma compounds were positively correlated to their related amino acid. For instance the two related amino acids, leucine and isoleucine resulted in aroma profiles dominated by isoamyl alcohol (banana), isoamyl acetate (fruity) and isovaleric acid (cheese), compounds whose formation is directly linked to leucine and isoleucine metabolism. A similar trend is observed for phenylalanine and its corresponding volatiles; 2-phenylethanol (floral) and 2-phenylethyl acetate (rose), and valine which increased the synthesis of isobutanol (solvent) and isobutyric acid (rancid). Acetic acid (vinegar) and ethyl acetate (sweet, nail polish remover) appeared positively correlated across for all amino acids and both strains showed no pronounced difference.
Further experiments were conducted with only strain A to investigate the effect of increasing branched chain and aromatic amino acid (BCAA) concentration of the quantity of the resultant aroma metabolites. In these studies SGM contained 100 mg N L-1, 200 mg N L-1 and 300 mg N L-1 YAN provided by individual amino acids. The total YAN was always 300 mg N L-1 and in cases where amino acids were used at lower rates, the YAN was supplemented with ammonium.
Taking 2-phenylethanol, isobutanol, isoamyl acetate (banana) and isoamyl alcohol (banana) to represent volatiles from metabolism of phenylalanine, valine, leucine and isoleucine respectively, Figure 3 shows the strong and positive relationship (R2 is greater than 0.99 for all compounds) between the amino acids and resultant volatiles. Similar relationships were also observed for the other related compound and lead to the development of the theory that if all the BCAAs are added simultaneously to the SGM, all compounds associated with the amino acids included will be positively altered.
To validate the predictability of the linear relationship between BCAAs and aroma compound, another experiment was designed to test the model. Four classes of amino acids (preferred, BCAAs, non-utilised and non-preferred) were used as nitrogen source at a concentration of 200 mg N L-1 and the rate of volatile compound production was compared with the predicted values for BCAAs (Figure 3). Of all the volatiles analysed, only isobutanol and 2-phenylethanol had high predictability. For all other compounds (isobutyric acid, propionoic acid, butanol, 2-phenylethyl acetate, decanoic acid, and valeric acid) there were no similarities between the observed and the predicted concentration.
Thus, predictability of aroma production is possible when individual amino acids are used for the provision of YAN. On the contrary, the predictability is reduced the more complex the nitrogen source. The reason lies with the nature of the metabolic networks involved in aroma production, since many of the amino acids share metabolic enzymes and precursors. In a complex mix, the competition between substrates, the variable preferences of enzymes and the many indirect drivers such as the need to maintain a healthy redox balance result in a more “chaotic” output. However, this study provides baseline data from which to extend further analysis to link amino acid nutrition to yeast aroma production. A better understanding of this relationship is indeed necessary to optimise the use of nitrogen addition to grape must.
Generally, yeast utilisation of amino acid classes is similar across the two strains used in this experiment. The type of nitrogen source played a major role in fermentation kinetic and aroma production, and it would clearly be in the interest of winemakers to be able to monitor levels and types of amino acids in the must before fermentation in order to adjust nitrogen not only with regard to total YAN, but also with regard to potential aromatic impact. The BCAAs are particularly important as they have direct bearing on the production of many major aroma compounds that can either add character or render the wine unpalatable. This study provides a good baseline investigation from which to further explore the effect of more complex nitrogen treatments. Since cultivar and regional differences have been shown to also lead to differences in amino acid present in grape must, this study also contributes to the body of knowledge attempting to explain the basis of varietal and regional wine characteristics.
The researchers are grateful to Winetech, NRF and THRIP for the funding provided to conduct this study.
– For more information, contact Florian Bauer at firstname.lastname@example.org.
Bell, S.J. & Henschke, P., 2005. Implications of nitrogen nutrition for grapes, fermentation and wine. Australian Journal of Grape and Wine Research 11(3), pp. 242 – 295. Available at: <Go to ISI>://WOS:000233851200001.
Jackson, R.S., 2014. Wine Science 4th ed., Amsterdam: Elsevier Inc.
Ljungdahl, P.O. & Daignan-Fornier, B., 2012. Regulation of amino acid, nucleotide, and phosphate metabolism in Saccharomyces cerevisiae. Genetics, 190(3), pp. 885 – 929.
Styger, G., Jacobson, D. & Bauer, F.F., 2011. Identifying genes that impact on aroma profiles produced by Saccharomyces cerevisiae and the production of higher alcohols. Applied Microbiology & Biotechnology 91(3), pp. 713 – 730.