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Machine Learning Techniques Disclose the Combined Effect of Fermentation Conditions on Yeast Mixed-Culture Dynamics and Wine Quality.

ABSTRACT: The use of yeast starter cultures consisting of a blend of Saccharomyces cerevisiae and non-Saccharomyces yeasts has increased in recent years as a mean to address consumers' demands for diversified wines. However, this strategy is currently limited by the lack of a comprehensive knowledge regarding the factors that determine the balance between the yeast-yeast interactions and their responses triggered in complex environments. Our previous studies demonstrated that the strain Hanseniaspora guilliermondii UTAD222 has potential to be used as an adjunct of S. cerevisiae in the wine industry due to its positive impact on the fruity and floral character of wines. To rationalize the use of this yeast consortium, this study aims to understand the influence of production factors such as sugar and nitrogen levels, fermentation temperature, and the level of co-inoculation of H. guilliermondii UTAD222 in shaping fermentation and wine composition. For that purpose, a Central Composite experimental Design was applied to investigate the combined effects of the four factors on fermentation parameters and metabolites produced. The patterns of variation of the response variables were analyzed using machine learning methods, to describe their clustered behavior and model the evolution of each cluster depending on the experimental conditions. The innovative data analysis methodology adopted goes beyond the traditional univariate approach, being able to incorporate the modularity, heterogeneity, and hierarchy inherent to metabolic systems. In this line, this study provides preliminary data and insights, enabling the development of innovative strategies to increase the aromatic and fermentative potential of H. guilliermondii UTAD222 by modulating temperature and the availability of nitrogen and/or sugars in the medium. Furthermore, the strategy followed gathered knowledge to guide the rational development of mixed blends that can be used to obtain a particular wine style, as a function of fermentation conditions.

SUBMITTER: Barbosa C

PROVIDER: S-EPMC8781278 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe introduction of yeast starter cultures consisting in a blend of Saccharomyces cerevisiae and non-Saccharomyces yeast strains is emerging for production of wines with improved complexity of flavor. The rational use of this approach is, however, dependent on knowing the impact that co-inoculation has in the physiology of S. cerevisiae. In this work the transcriptome of S. cerevisiae was monitored throughout a wine fermentation, carried out in single culture or in a consortium with Hanseniaspora guilliermondii, this being the first time that this relevant yeast-yeast interaction is examined at a genomic scale.ResultsCo-inoculation with H. guilliermondii reduced the overall genome-wide transcriptional response of S. cerevisiae throughout the fermentation, which was attributable to a lower fermentative activity of S. cerevisiae while in the mixed-fermentation. Approximately 350 genes S. cerevisiae genes were found to be differently expressed (FDR < 0.05) in response to the presence of H. guilliermondii in the fermentation medium. Genes involved in biosynthesis of vitamins were enriched among those up-regulated in the mixed-culture fermentation, while genes related with the uptake and biosynthesis of amino acids were enriched among those more expressed in the single-culture. The differences in the aromatic profiles of wines obtained in the single and in the mixed-fermentations correlated with the differential expression of S. cerevisiae genes encoding enzymes required for formation of aroma compounds.ConclusionsBy integrating results obtained in the transcriptomic analysis performed with physiological data our study provided, for the first time, an integrated view into the adaptive responses of S. cerevisiae to the challenging environment of mixed culture fermentation. The availability of nutrients, in particular, of nitrogen and vitamins, stands out as a factor that may determine population dynamics, fermentative activity and by-product formation.

Project description:BACKGROUND: Variation of gene expression can lead to phenotypic variation and have therefore been assumed to contribute the diversity of wine yeast (Saccharomyces cerevisiae) properties. However, the molecular bases of this variation of gene expression are unknown. We addressed these questions by carrying out an integrated genetical-genomic study in fermentation conditions. We report here quantitative trait loci (QTL) mapping based on expression profiling in a segregating population generated by a cross between a derivative of the popular wine strain EC1118 and the laboratory strain S288c. RESULTS: Most of the fermentation traits studied appeared to be under multi-allelic control. We mapped five phenotypic QTLs and 1465 expression QTLs. Several expression QTLs overlapped in hotspots. Among the linkages unraveled here, several were associated with metabolic processes essential for wine fermentation such as glucose sensing or nitrogen and vitamin metabolism. Variations affecting the regulation of drug detoxification and export (TPO1, PDR12 or QDR2) were linked to variation in four genes encoding transcription factors (PDR8, WAR1, YRR1 and HAP1). We demonstrated that the allelic variation of WAR1 and TPO1 affected sorbic and octanoic acid resistance, respectively. Moreover, analysis of the transcription factors phylogeny suggests they evolved with a specific adaptation of the strains to wine fermentation conditions. Unexpectedly, we found that the variation of fermentation rates was associated with a partial disomy of chromosome 16. This disomy resulted from the well known 8-16 translocation. CONCLUSIONS: This large data set made it possible to decipher the effects of genetic variation on gene expression during fermentation and certain wine fermentation properties. Our findings shed a new light on the adaptation mechanisms required by yeast to cope with the multiple stresses generated by wine fermentation. In this context, the detoxification and export systems appear to be of particular importance, probably due to nitrogen starvation. Furthermore, we show that the well characterized 8-16 translocation located in SSU1, which is associated with sulfite resistance, can lead to a partial chromosomic amplification in the progeny of strains that carry it, greatly improving fermentation kinetics. This amplification has been detected among other wine yeasts.

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Machine Learning Techniques Disclose the Combined Effect of Fermentation Conditions on Yeast Mixed-Culture Dynamics and Wine Quality.

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