Modelling the physiological status of yeast during wine fermentation enables the prediction of secondary metabolism

Abstract

Saccharomyces non‐cerevisiae yeasts are gaining momentum in wine fermentation due to their potential to reduce ethanol content and achieve attractive aroma profiles. However, the design of the fermentation process for new species requires intensive experimentation. The use of mechanistic models could automate process design, yet to date, most fermentation models have focused on primary metabolism. Therefore, these models do not provide insight into the production of secondary metabolites essential for wine quality, such as aromas. In this work, we formulate a continuous model that accounts for the physiological status of yeast, that is, exponential growth, growth under nitrogen starvation and transition to stationary or decay phases. To do so, we assumed that nitrogen starvation is associated with carbohydrate accumulation and the induction of a set of transcriptional changes associated with the stationary phase. The model accurately described the dynamics of time series data for biomass and primary and secondary metabolites obtained for various yeast species in single culture fermentations. We also used the proposed model to explore different process designs, showing how the addition of nitrogen could affect the aromatic profile of wine. This study underlines the potential of incorporating yeast physiology into batch fermentation modelling and provides a new means of automating process design.

A continuous dynamic genome-scale model explains batch fermentations led by species of theSaccharomycesgenus

“…Our study builds on a previous model proposed by Moimenta et al [2023] and suggests a continuous model that links different fermentation phases through regulation. Compared to the discontinuous model for the same species and data , results are in good agreement, and the continuous model offers several computational advantages in parameter estimation and simulation.…”

“…The model builds upon a previously developed model by Moimenta et al [2023] The model accounts for assimilable nitrogen (YAN) (g N /L) including ammonia (NH4) (g NH4 /L) and the different amino acids measured in (g/L) present in the medium: alanine (Ala), arginine (Arg), aspartate (Asp), cysteine (Cys), glutamate (Glu), glutamine (Gln), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Meth), phenylalanine (Phe), serine (Ser), threonine (Thr), tyrosine (Tyr), tryptophan (Try) and valine (Val). Note that yeasts do not metabolize proline under anaerobic conditions; therefore, we do not include it as an assimilable nitrogen source.…”

“…In this study, we formulated a model that builds on a previous one by Moimenta et al [2023]. The model describes the role of amino acids and introduces several adaptations to account for experimental observations and to automatically transition between the different batch fermentation phases (lag, exponential, growth-non-growth and stationary phase).…”

“…To overcome these limitations, we propose combining a continuous extracellular model that can automatically describe the different phases of batch fermentation with a dynamic genome-scale model to predict the distribution of intracellular fluxes. To do so, we extend the model proposed by Moimenta et al [2023] to predict secondary metabolism during batch fermentation, incorporating the role of transport of amino acids from the extracellular medium into the cell. The model incorporates a regulatory mechanism that can automatically detect fermentation phases.…”

Differences in metabolism among Saccharomyces species and their hybrids during wine fermentation

“…In recent years, different studies have used a metabolomic or modelling approach to better understand the specificities of central carbon and nitrogen metabolism in S. uvarum and S. kudriavzevii species (Coral‐Medina et al., 2022 ; Henriques et al., 2021 ; Minebois et al., 2020a , 2021 ; Moimenta et al., 2023 ), but this approach has not been applied to their hybrids yet. Given the relevance of the interspecific hybrids of S. cerevisiae × S. kudriavzevii and S. cerevisiae × S. uvarum for the wine industry, this study is the first of its kind aiming to provide a comprehensive picture of their metabolomes in wine fermentation.…”