Temperature-dependent kinetic model for nitrogen-limited wine fermentations

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

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

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.

Development and Analysis of an Intensified Batch-Fed Wine Fermentation Process

White wine fermentations are typically performed in an entirely batchwise manner, with yeast nutrients only added at the beginning of fermentation. This leads to slow (2+ weeks) fermentation cycle times, with large capital expenditures required to increase winery processing capacity. Prior attempts to speed fermentations via increasing temperature have resulted in unpalatable wine, and continuous fermentation processing is uneconomical and impractical in the winery setting. In this work, we measured yeast nutrient consumption as a function of fermentation progression at the 300 mL scale, and from this derived an equation to optimize yeast nutrient concentration as a function of fermentation progression. These findings were applied at the pilot scale in 150 L fermentors, which resulted in a 60% cycle time reduction versus “best practices” control fermentations. The resultant wines were compared via GC-MS as well as by a trained sensory panel. Organoleptic analysis found statistically significant, but overall, small differences in sensory characteristics between the control and process intensified wines. This intensified fermentation process shows great promise for fermented beverage producers wishing to maximize equipment utilization and debottleneck wineries or other beverage fermentation facilities.

Wine Microbiology and Predictive Microbiology: A Short Overview on Application, and Perspectives

Predictive microbiology (PM) is an essential element in food microbiology; its aims are the determination of the responses of a given microorganism combining mathematical models with experimental data under certain environmental conditions, and the simulation a priori of the growth/inactivation of a population based on the known traits of a food matrix. Today, a great variety of models exist to describe the behaviour of several pathogenic and spoilage microorganisms in foods. In winemaking, many mathematical models have been used for monitoring yeast growth in alcoholic fermentation as well as to predict the risk of contamination of grapes and grape products by mycotoxin producing fungi over the last years, but the potentialities of PM in wine microbiology are underestimated. Thus, the goals of this review are to show some applications and perspectives in the following fields: (1) kinetics of alcoholic and malolactic fermentation; (2) models and approaches for yeasts and bacteria growth/inactivation; (3) toxin production and removal.

Effects of Yeast Product Addition and Fermentation Temperature on Lipid Composition, Taste and Mouthfeel Characteristics of Pinot Noir Wine

Lipids have important impacts on wine sensory. By targeting the lipid sources in wine, mainly from grape tissues and yeast cell walls, it was possible to alter the wine lipid profile thus potentially changing the final product quality. This research examined the changes of wine total lipids, lipid composition and sensory characteristics of Pinot noir wines in response to the winemaking factors, fermentation temperature and yeast product addition. Pinot noir grapes were fermented at 16 °C and 27 °C. After fermentation, Oenolees® yeast product was added to the wines at three levels (0 g/L, 0.5 g/L and 1.0 g/L). The six wine treatments were subjected to chemical analyses measuring total lipids and an untargeted lipidomic approach analyzing lipid composition. High temperature fermentation wines had significantly higher total lipid content. Random forest analysis distinguished the wine groups based on the 25 main lipids, including free fatty acids, acylcarnitines, diglycerides, triglycerides and phospholipids. Taste and mouthfeel characteristics of each treatment were assessed using descriptive analysis and check-all-that-apply (CATA) techniques. Multivariate analyses showed that changing fermentation temperature significantly impacted sweetness and drying perception in Pinot noir wines. Yeast product addition had nuanced effects on wine lipid profiles and sensory perception.

Nitrogenous Compound Utilization and Production of Volatile Organic Compounds among Commercial Wine Yeasts Highlight Strain-Specific Metabolic Diversity

Genetic background and environmental conditions affect the production of sensory impact compounds by Saccharomyces cerevisiae. The relative importance of the strain-specific metabolic capabilities for the production of volatile organic compounds (VOCs) remains unclear. We investigated which amino acids contribute to VOC production and whether amino acid-VOC relations are conserved among yeast strains. Amino acid consumption and production of VOCs during grape juice fermentation was investigated using four commercial wine yeast strains: Elixir, Opale, R2, and Uvaferm. Principal component analysis of the VOC data demonstrated that Uvaferm correlated with ethyl acetate and ethyl hexanoate production, R2 negatively correlated with the acetate esters, and Opale positively correlated with fusel alcohols. Biomass formation was similar for all strains, pointing to metabolic differences in the utilization of nutrients to form VOCs. Partial least-squares linear regression showed that total aroma production is a function of nitrogen utilization (R2 = 0.87). We found that glycine, tyrosine, leucine, and lysine utilization were positively correlated with fusel alcohols and acetate esters. Mechanistic modeling of the yeast metabolic network via parsimonious flux balance analysis and flux enrichment analysis revealed enzymes with crucial roles, such as transaminases and decarboxylases. Our work provides insights in VOC production in wine yeasts. IMPORTANCE Saccharomyces cerevisiae is widely used in grape juice fermentation to produce wines. Along with the genetic background, the nitrogen in the environment in which S. cerevisiae grows impacts its regulation of metabolism. Also, commercial S. cerevisiae strains exhibit immense diversity in their formation of aromas, and a desirable aroma bouquet is an essential characteristic for wines. Since nitrogen affects aroma formation in wines, it is essential to know the extent of this connection and how it leads to strain-dependent aroma profiles in wines. We evaluated the differences in the production of key aroma compounds among four commercial wine strains. Moreover, we analyzed the role of nitrogen utilization on the formation of various aroma compounds. This work illustrates the unique aroma-producing differences among industrial yeast strains and suggests more intricate, nitrogen-associated routes influencing those aroma-producing differences.

Deletion of the MBP1 Gene, Involved in the Cell Cycle, Affects Respiration and Pseudohyphal Differentiation in Saccharomyces cerevisiae

Mbp1p is a component of MBF (MluI cell cycle box binding factor, Mbp1p-Swi6p) and is well known to regulate the G1-S transition of the cell cycle. However, few studies have provided clues regarding its role in fermentation. This work aimed to recognize the function of the MBP1 gene in ethanol fermentation in a wild-type industrial Saccharomyces cerevisiae strain. MBP1 deletion caused an obvious decrease in the final ethanol concentration under oxygen-limited (without agitation), but not under aerobic, conditions (130 rpm). Furthermore, the mbp1Δ strain showed 84% and 35% decreases in respiration intensity under aerobic and oxygen-limited conditions, respectively. These findings indicate that MBP1 plays an important role in responding to variations in oxygen content and is involved in the regulation of respiration and fermentation. Unexpectedly, mbp1Δ also showed pseudohyphal growth, in which cells elongated and remained connected in a multicellular arrangement on yeast extract-peptone-dextrose (YPD) plates. In addition, mbp1Δ showed an increase in cell volume, associated with a decrease in the fraction of budded cells. These results provide more detailed information about the function of MBP1 and suggest some clues to efficiently improve ethanol production by industrially engineered yeast strains. IMPORTANCE Saccharomyces cerevisiae is an especially favorable organism used for ethanol production. However, inhibitors and high osmolarity conferred by fermentation broth, and high concentrations of ethanol as fermentation runs to completion, affect cell growth and ethanol production. Therefore, yeast strains with high performance, such as rapid growth, high tolerance, and high ethanol productivity, are highly desirable. Great efforts have been made to improve their performance by evolutionary engineering, and industrial strains may be a better start than laboratory ones for industrial-scale ethanol production. The significance of our research is uncovering the function of MBP1 in ethanol fermentation in a wild-type industrial S. cerevisiae strain, which may provide clues to engineer better-performance yeast in producing ethanol. Furthermore, the results that lacking MBP1 caused pseudohyphal growth on YPD plates could shed light on the development of xylose-fermenting S. cerevisiae, as using xylose as the sole carbon source also caused pseudohyphal growth.

Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation

The yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae. The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations. Importance: Problematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod equation does not suffice to explain biomass formation.

Optimal Control Applied to Oenological Management of Red Wine Fermentative Macerations

The management of wineries for industrial red winemaking is limited by the capacity and availability of fermentation tanks over the harvest season. The winemakers aim to optimize the wine quality, the fermentative maceration length, and the fermentation tank’s productive cycle simultaneously. Maceration in varietal wine production is carried out until a specific sugar content (digging-out point) is attained, finishing before alcoholic fermentation. Winemakers have found that by trial and error handling of the digging-out point, they can improve the winery capacity and production cost. In this work, we develop an optimal control problem for managing the digging-out point considering two objectives associated with process efficiency and costs. A good compromise between these objectives was found by applying multi-criteria decision-making (MCDM) techniques and the knee point. Two control strategies were compared: free nutrition and traditional nutrition. TOPSIS and LINMAP algorithms were used to choose the most suitable strategy that coincided with the knee point. The preferred option was nitrogen addition only at the beginning of fermentation (6.6–10.6 g/hL of DAP) and a high fermentation temperature (30 °C), yielding the desired digging-out point with a small error (6–9 g/L).

Mild Pretreatments to Increase Fructose Consumption in Saccharomyces cerevisiae Wine Yeast Strains

The present research investigates the effect of different pretreatments on glucose and fructose consumption and ethanol production by four Saccharomyces cerevisiae wine strains, three isolated and identified from different wine regions in Turkey and one reference strain. A mild stress temperature (45 °C, 1 h) and the presence of ethanol (14% v/v) were selected as pretreatments applied to cell cultures prior to the fermentation step in synthetic must. The goodness fit of the mathematical models was estimated: linear, exponential decay function and sigmoidal model were evaluated with the model parameters R² (regression coefficient), RMSE (root mean square error), MBE (mean bias error) and χ² (reduced Chi-square). Sigmoidal function was determined as the most suitable model with the highest R² and lower RMSE values. Temperature pretreatment allowed for an increase in fructose consumption rate by two strains, evidenced by a t90 value 10% lower than the control. One of the indigenous strains showed particular promise for mild temperature treatment (45 °C, 1 h) prior to the fermentation step to reduce residual glucose and fructose in wine. The described procedure may be effective for indigenous yeasts in preventing undesirable sweetness in wines.

Lifestyle, Lineage, and Geographical Origin Influence Temperature-Dependent Phenotypic Variation across Yeast Strains during Wine Fermentation

Saccharomyces cerevisiae yeasts are a diverse group of single-celled eukaryotes with tremendous phenotypic variation in fermentation efficiency, particularly at different temperatures. Yeast can be categorized into subsets based on lifestyle (Clinical, Fermentation, Laboratory, and Wild), genetic lineage (Malaysian, Mosaic, North American, Sake, West African, and Wine), and geographical origin (Africa, Americas, Asia, Europe, and Oceania) to start to understand their ecology; however, little is known regarding the extent to which these groupings drive S. cerevisiae fermentative ability in grape juice at different fermentation temperatures. To investigate the response of yeast within the different subsets, we quantified fermentation performance in grape juice by measuring the lag time, maximal fermentation rate (V_max), and fermentation finishing efficiency of 34 genetically diverse S. cerevisiae strains in grape juice at five environmentally and industrially relevant temperatures (10, 15, 20, 25, and 30 °C). Extensive multivariate analysis was applied to determine the effects of lifestyle, lineage, geographical origin, strain, and temperature on yeast fermentation phenotypes. We show that fermentation capability is inherent to S. cerevisiae and that all factors are important in shaping strain fermentative ability, with temperature having the greatest impact, and geographical origin playing a lesser role than lifestyle or genetic lineage.

A predictive dynamic yeast model based on component, energy, and electron carrier balances

The present study describes a novel yeast model for the prediction of yeast fermentation. The proposed model considers the possible metabolic pathways of yeast. For each pathway, the time evolution of components, energy (ATP/ADP), and electron carriers (NAD⁺ /NADH) are expressed with limitation factors for all quantities consumed by each respective pathway. In this manner, the model can predict the partition of these pathways based on the growth conditions and their evolution over time. Several biological pathways and their stoichiometric coefficients are well known from literature. It is important to note that most of the kinetic parameters have no effect as the actual kinetics are controlled by the balance of limiting factors. The few remaining parameters were adjusted and compared with the literature when the data set was available. The model fits our experimental data from yeast fermentation on glucose in a nonaerated batch system. The predictive ability of the model and its capacity to represent the intensity of each pathway over time facilitate an improved understanding of the interactions between the pathways. The key role of energy (ATP) and electron carrier (NAD⁺ ) to trigger the different metabolic pathways during yeast growth is highlighted, whereas the involvement of mitochondrial respiration not being associated with the TCA cycle is also shown.

Improvement of Thermotolerance of Zymomonas mobilis by Genes for Reactive Oxygen Species-Scavenging Enzymes and Heat Shock Proteins

Thermotolerant genes, which are essential for survival at a high temperature, have been identified in three mesophilic microbes, including Zymomonas mobilis. Contrary to expectation, they include only a few genes for reactive oxygen species (ROS)-scavenging enzymes and heat shock proteins, which are assumed to play key roles at a critical high temperature (CHT) as an upper limit of survival. We thus examined the effects of increased expression of these genes on the cell growth of Z. mobilis strains at its CHT. When overexpressed, most of the genes increased the CHT by about one degree, and some of them enhanced tolerance against acetic acid. These findings suggest that ROS-damaged molecules or unfolded proteins that prevent cell growth are accumulated in cells at the CHT.

A combined phenolic extraction and fermentation reactor engineering model for multiphase red wine fermentation

Red wine production begins with a simultaneous fermentation and solid-phase extraction process. Red wine color and mouthfeel is the result of the extraction of phenolics from grape skins and seeds during fermentation, where extraction is a strong function of temperature and ethanol concentration. During fermentation, grape solids form a porous "cap" at the top of the fermentor, resulting in a heterogeneous fermentation system with significant temperature and concentration gradients. In this work, we present a spatial, time-variant reactor engineering model for phenolic extraction during red wine fermentation, incorporating fermentation kinetics, mass transfer, heat transfer, compressible fluid flow, and phenolic extraction kinetics. The temperature and ethanol concentration profiles predicted by this model allow for the calculation of phenolic extraction rates over the course of fermentation. Phenolic extraction predictions were validated against prior experimental data to good agreement and compared to a well-mixed model's predictions to show the utility of a spatial model over well-mixed models.

Influence of nitrogen status in wine alcoholic fermentation

Nitrogen is an essential nutrient for yeast during alcoholic fermentation. Nitrogen is involved in the biosynthesis of protein, amino acids, nucleotides, and other metabolites, including volatile compounds. However, recent studies have called several mechanisms that regulate its role in biosynthesis into question. An initial focus on S. cerevisiae has highlighted that the concept of "preferred" versus "non-preferred" nitrogen sources is extremely variable and strain-dependent. Then, the direct involvement of amino acids consumed in the formation of proteins and volatile compounds has recently been reevaluated. Indeed, studies have highlighted the key role of lipids in nitrogen regulation in S. cerevisiae and their involvement in the mechanism of cell death. New winemaking strategies using non-Saccharomyces yeast strains in co- or sequential fermentation improve nitrogen management. Indeed, recent studies show that non-Saccharomyces yeasts have significant and specific needs for nitrogen. Moreover, sluggish fermentation can occur when they are associated with S. cerevisiae, necessitating nitrogen addition. In this context, we will present the consequences of nitrogen addition, discussing the sources, time of addition, transcriptome changes, and effect on volatile compound composition.

Mass Transfer of Anthocyanins during Extraction from Pre-Fermentative Grape Solids under Simulated Fermentation Conditions: Effect of Convective Conditions

The colour of red wine is largely determined by the concentration of anthocyanins that are extracted from grape skins during fermentation. Because colour is a key parameter in determining the overall quality of the finished product, understanding the effect of processing variables on anthocyanin extraction is critical for producing a red wine with the desired sensorial characteristics. In this study, the effect of convective conditions (natural and forced) on the mass transfer properties of malvidin-3-glucoside (M3G) from pre-fermentative grape solids was explored at various liquid phase conditions representing stages of fermentation. A mathematical model that separates solid and liquid phase mass transfer parameters was applied to experimental extraction curves, and in all cases, provided a coefficient of determination exceeding 0.97. Calculated mass transfer coefficients indicated that under forced convective conditions, the extraction process was controlled by internal diffusion whereas under natural convection, both internal diffusion and liquid-phase mass transfer were relevant in determining the overall extraction rate. Predictive simulations of M3G extraction during active fermentation were accomplished by incorporating the current results with a previously developed fermentation model, providing insight into the effect of a dynamic liquid phase on anthocyanin extraction.

Creation and validation of a reactor engineering model for multiphase red wine fermentations

Red wine fermentations are performed in the presence of grape skins and seeds to ensure the extraction of color and other phenolics. The presence of these solids results in two distinct phases in the fermentor, as the solids float to the top to form a "cap." Modeling of red wine fermentation is, therefore, complex and must consider spatial heterogeneity to predict fermentation kinetics. We have developed a reactor-engineering model for red wine fermentations that includes the fundamentals of fermentation kinetics, heat transfer, diffusion, and compressible fluid flow. To develop the heat transfer component of the model, the heat transfer properties of grapes were experimentally determined as a function of fermentation progression. COMSOL was used to solve all components of the model simultaneously utilizing a finite element analysis approach. Predictions from this model were validated using prior experimental work. Model prediction and experimental data showed excellent agreement. The model was then used to predict spatial profiles of active yeast cell concentration and ethanol productivity, as well as liquid velocity profiles. Finally, the model was used to predict how these gradients would change with differences in initial bioavailable nitrogen concentration, a key parameter in predicting fermentation outcome in nitrogen-limited wine fermentations.

Saccharomyces cerevisiae and S. kudriavzevii Synthetic Wine Fermentation Performance Dissected by Predictive Modeling

Wineries face unprecedented challenges due to new market demands and climate change effects on wine quality. New yeast starters including non-conventional Saccharomyces species, such as S. kudriavzevii, may contribute to deal with some of these challenges. The design of new fermentations using non-conventional yeasts requires an improved understanding of the physiology and metabolism of these cells. Dynamic modeling brings the potential of exploring the most relevant mechanisms and designing optimal processes more systematically. In this work we explore mechanisms by means of a model selection, reduction and cross-validation pipeline which enables to dissect the most relevant fermentation features for the species under consideration, Saccharomyces cerevisiae T73 and Saccharomyces kudriavzevii CR85. The pipeline involved the comparison of a collection of models which incorporate several alternative mechanisms with emphasis on the inhibitory effects due to temperature and ethanol. We focused on defining a minimal model with the minimum number of parameters, to maximize the identifiability and the quality of cross-validation. The selected model was then used to highlight differences in behavior between species. The analysis of model parameters would indicate that the specific growth rate and the transport of hexoses at initial times are higher for S. cervisiae T73 while S. kudriavzevii CR85 diverts more flux for glycerol production and cellular maintenance. As a result, the fermentations with S. kudriavzevii CR85 are typically slower; produce less ethanol but higher glycerol. Finally, we also explored optimal initial inoculation and process temperature to find the best compromise between final product characteristics and fermentation duration. Results reveal that the production of glycerol is distinctive in S. kudriavzevii CR85, it was not possible to achieve the same production of glycerol with S. cervisiae T73 in any of the conditions tested. This result brings the idea that the optimal design of mixed cultures may have an enormous potential for the improvement of final wine quality.

Physiology, ecology and industrial applications of aroma formation in yeast

Yeast cells are often employed in industrial fermentation processes for their ability to efficiently convert relatively high concentrations of sugars into ethanol and carbon dioxide. Additionally, fermenting yeast cells produce a wide range of other compounds, including various higher alcohols, carbonyl compounds, phenolic compounds, fatty acid derivatives and sulfur compounds. Interestingly, many of these secondary metabolites are volatile and have pungent aromas that are often vital for product quality. In this review, we summarize the different biochemical pathways underlying aroma production in yeast as well as the relevance of these compounds for industrial applications and the factors that influence their production during fermentation. Additionally, we discuss the different physiological and ecological roles of aroma-active metabolites, including recent findings that point at their role as signaling molecules and attractants for insect vectors.

Saccharomyces cerevisiae FLO1 Gene Demonstrates Genetic Linkage to Increased Fermentation Rate at Low Temperatures

Low fermentation temperatures are of importance to food and beverage industries working with Saccharomyces cerevisiae Therefore, the identification of genes demonstrating a positive impact on fermentation kinetics is of significant interest. A set of 121 mapped F1 progeny, derived from a cross between haploid strains BY4716 (a derivative of the laboratory yeast S288C) and wine yeast RM11-1a, were fermented in New Zealand Sauvignon Blanc grape juice at 12.5°. Analyses of five key fermentation kinetic parameters among the F1 progeny identified a quantitative trait locus (QTL) on chromosome I with a significant degree of linkage to maximal fermentation rate (Vmax) at low temperature. Independent deletions of two candidate genes within the region, FLO1 and SWH1, were constructed in the parental strains (with S288C representing BY4716). Fermentation of wild-type and deletion strains at 12.5 and 25° confirmed that the genetic linkage to Vmax corresponds to the S288C version of the FLO1 allele, as the absence of this allele reduced Vmax by ∼50% at 12.5°, but not at 25°. Reciprocal hemizygosity analysis (RHA) between S288C and RM11-1a FLO1 alleles did not confirm the prediction that the S288C version of FLO1 was promoting more rapid fermentation in the opposing strain background, suggesting that the positive effect on Vmax derived from S288C FLO1 may only provide an advantage in haploids, or is dependent on strain-specific cis or trans effects. This research adds to the growing body of evidence demonstrating the role of FLO1 in providing stress tolerance to S. cerevisiae during fermentation.

Thermotolerant genes essential for survival at a critical high temperature in thermotolerant ethanologenic Zymomonas mobilis TISTR 548

BACKGROUND

High-temperature fermentation (HTF) technology is expected to reduce the cost of bioconversion of biomass to fuels or chemicals. For stable HTF, the development of a thermotolerant microbe is indispensable. Elucidation of the molecular mechanism of thermotolerance would enable the thermal stability of microbes to be improved.

RESULTS

Thermotolerant genes that are essential for survival at a critical high temperature (CHT) were identified via transposon mutagenesis in ethanologenic, thermotolerant Zymomonas mobilis TISTR 548. Surprisingly, no genes for general heat shock proteins except for degP were included. Cells with transposon insertion in these genes showed a defect in growth at around 39 °C but grew normally at 30 °C. Of those, more than 60% were found to be sensitive to ethanol at 30 °C, indicating that the mechanism of thermotolerance partially overlaps with that of ethanol tolerance in the organism. Products of these genes were classified into nine categories of metabolism, membrane stabilization, transporter, DNA repair, tRNA modification, protein quality control, translation control, cell division, and transcriptional regulation.

CONCLUSIONS

The thermotolerant genes of Escherichia coli and Acetobacter tropicalis that had been identified can be functionally classified into 9 categories according to the classification of those of Z. mobilis, and the ratio of thermotolerant genes to total genomic genes in Z. mobilis is nearly the same as that in E. coli, though the ratio in A. tropicalis is relatively low. There are 7 conserved thermotolerant genes that are shared by these three or two microbes. These findings suggest that Z. mobilis possesses molecular mechanisms for its survival at a CHT that are similar to those in E. coli and A. tropicalis. The mechanisms may mainly contribute to membrane stabilization, protection and repair of damage of macromolecules and maintenance of cellular metabolism at a CHT. Notably, the contribution of heat shock proteins to such survival seems to be very low.

Modeling acclimatization by hybrid systems: condition changes alter biological system behavior models

In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass.

Examining the role of membrane lipid composition in determining the ethanol tolerance of Saccharomyces cerevisiae

Yeast (Saccharomyces cerevisiae) has an innate ability to withstand high levels of ethanol that would prove lethal to or severely impair the physiology of other organisms. Significant efforts have been undertaken to elucidate the biochemical and biophysical mechanisms of how ethanol interacts with lipid bilayers and cellular membranes. This research has implicated the yeast cellular membrane as the primary target of the toxic effects of ethanol. Analysis of model membrane systems exposed to ethanol has demonstrated ethanol's perturbing effect on lipid bilayers, and altering the lipid composition of these model bilayers can mitigate the effect of ethanol. In addition, cell membrane composition has been correlated with the ethanol tolerance of yeast cells. However, the physical phenomena behind this correlation are likely to be complex. Previous work based on often divergent experimental conditions and time-consuming low-resolution methodologies that limit large-scale analysis of yeast fermentations has fallen short of revealing shared mechanisms of alcohol tolerance in Saccharomyces cerevisiae. Lipidomics, a modern mass spectrometry-based approach to analyze the complex physiological regulation of lipid composition in yeast and other organisms, has helped to uncover potential mechanisms for alcohol tolerance in yeast. Recent experimental work utilizing lipidomics methodologies has provided a more detailed molecular picture of the relationship between lipid composition and ethanol tolerance. While it has become clear that the yeast cell membrane composition affects its ability to tolerate ethanol, the molecular mechanisms of yeast alcohol tolerance remain to be elucidated.

Fermentation temperature modulates phosphatidylethanolamine and phosphatidylinositol levels in the cell membrane of Saccharomyces cerevisiae

During alcoholic fermentation, Saccharomyces cerevisiae is exposed to a host of environmental and physiological stresses. Extremes of fermentation temperature have previously been demonstrated to induce fermentation arrest under growth conditions that would otherwise result in complete sugar utilization at "normal" temperatures and nutrient levels. Fermentations were carried out at 15°C, 25°C, and 35°C in a defined high-sugar medium using three Saccharomyces cerevisiae strains with diverse fermentation characteristics. The lipid composition of these strains was analyzed at two fermentation stages, when ethanol levels were low early in stationary phase and in late stationary phase at high ethanol concentrations. Several lipids exhibited dramatic differences in membrane concentration in a temperature-dependent manner. Principal component analysis (PCA) was used as a tool to elucidate correlations between specific lipid species and fermentation temperature for each yeast strain. Fermentations carried out at 35°C exhibited very high concentrations of several phosphatidylinositol species, whereas at 15°C these yeast strains exhibited higher levels of phosphatidylethanolamine and phosphatidylcholine species with medium-chain fatty acids. Furthermore, membrane concentrations of ergosterol were highest in the yeast strain that experienced stuck fermentations at all three temperatures. Fluorescence anisotropy measurements of yeast cell membrane fluidity during fermentation were carried out using the lipophilic fluorophore diphenylhexatriene. These measurements demonstrate that the changes in the lipid composition of these yeast strains across the range of fermentation temperatures used in this study did not significantly affect cell membrane fluidity. However, the results from this study indicate that fermenting S. cerevisiae modulates its membrane lipid composition in a temperature-dependent manner.

Recurrent rearrangement during adaptive evolution in an interspecific yeast hybrid suggests a model for rapid introgression

Genome rearrangements are associated with eukaryotic evolutionary processes ranging from tumorigenesis to speciation. Rearrangements are especially common following interspecific hybridization, and some of these could be expected to have strong selective value. To test this expectation we created de novo interspecific yeast hybrids between two diverged but largely syntenic Saccharomyces species, S. cerevisiae and S. uvarum, then experimentally evolved them under continuous ammonium limitation. We discovered that a characteristic interspecific genome rearrangement arose multiple times in independently evolved populations. We uncovered nine different breakpoints, all occurring in a narrow ~1-kb region of chromosome 14, and all producing an "interspecific fusion junction" within the MEP2 gene coding sequence, such that the 5' portion derives from S. cerevisiae and the 3' portion derives from S. uvarum. In most cases the rearrangements altered both chromosomes, resulting in what can be considered to be an introgression of a several-kb region of S. uvarum into an otherwise intact S. cerevisiae chromosome 14, while the homeologous S. uvarum chromosome 14 experienced an interspecific reciprocal translocation at the same breakpoint within MEP2, yielding a chimaeric chromosome; these events result in the presence in the cell of two MEP2 fusion genes having identical breakpoints. Given that MEP2 encodes for a high-affinity ammonium permease, that MEP2 fusion genes arise repeatedly under ammonium-limitation, and that three independent evolved isolates carrying MEP2 fusion genes are each more fit than their common ancestor, the novel MEP2 fusion genes are very likely adaptive under ammonium limitation. Our results suggest that, when homoploid hybrids form, the admixture of two genomes enables swift and otherwise unavailable evolutionary innovations. Furthermore, the architecture of the MEP2 rearrangement suggests a model for rapid introgression, a phenomenon seen in numerous eukaryotic phyla, that does not require repeated backcrossing to one of the parental species.

Ethanol production and maximum cell growth are highly correlated with membrane lipid composition during fermentation as determined by lipidomic analysis of 22 Saccharomyces cerevisiae strains

Optimizing ethanol yield during fermentation is important for efficient production of fuel alcohol, as well as wine and other alcoholic beverages. However, increasing ethanol concentrations during fermentation can create problems that result in arrested or sluggish sugar-to-ethanol conversion. The fundamental cellular basis for these problem fermentations, however, is not well understood. Small-scale fermentations were performed in a synthetic grape must using 22 industrial Saccharomyces cerevisiae strains (primarily wine strains) with various degrees of ethanol tolerance to assess the correlation between lipid composition and fermentation kinetic parameters. Lipids were extracted at several fermentation time points representing different growth phases of the yeast to quantitatively analyze phospholipids and ergosterol utilizing atmospheric pressure ionization-mass spectrometry methods. Lipid profiling of individual fermentations indicated that yeast lipid class profiles do not shift dramatically in composition over the course of fermentation. Multivariate statistical analysis of the data was performed using partial least-squares linear regression modeling to correlate lipid composition data with fermentation kinetic data. The results indicate a strong correlation (R(2) = 0.91) between the overall lipid composition and the final ethanol concentration (wt/wt), an indicator of strain ethanol tolerance. One potential component of ethanol tolerance, the maximum yeast cell concentration, was also found to be a strong function of lipid composition (R(2) = 0.97). Specifically, strains unable to complete fermentation were associated with high phosphatidylinositol levels early in fermentation. Yeast strains that achieved the highest cell densities and ethanol concentrations were positively correlated with phosphatidylcholine species similar to those known to decrease the perturbing effects of ethanol in model membrane systems.

Use of sequential-batch fermentations to characterize the impact of mild hypothermic temperatures on the anaerobic stoichiometry and kinetics of Saccharomyces cerevisiae

This work presents a characterization of the stoichiometry and kinetics of anaerobic batch growth of Saccharomyces cerevisiae at cultivation temperatures between 12 and 30°C. To minimize the influence of the inoculum condition and ensure full adaptation to the cultivation temperature, the experiments were carried out in sequencing batch reactors. It was observed that the growth rate obtained in the first batch performed after each temperature shift was 10-30% different compared with the subsequent batches at the same temperature, which were much more reproducible. This indicates that the sequencing batch approach provides accurate and reproducible growth rate data. Data reconciliation was applied to the measured time patterns of substrate, biomass, carbon dioxide and byproducts with the constraint that the elemental conservation relations were satisfied, allowing to obtain consistent best estimates of all uptake and secretion rates. Subsequently, it was attempted to obtain an appropriate model description of the temperature dependency of these rates. It was found that the Ratkowsky model provided a better description of the temperature dependency of growth, uptake and secretion rates than the Arrhenius law. Most interesting was to find that most of the biomass-specific rates have the same temperature dependency, leading to a near temperature independent batch stoichiometry.

Genetic improvement of thermo-tolerance in wine Saccharomyces cerevisiae strains by a backcross approach

During red wine fermentation, high temperatures may cause stuck fermentation by affecting the physiology of fermenting yeast. This deleterious effect is the result of the complex interaction of temperature with other physicochemical parameters of grape juice, such as sugar and lipid content. The genetic background of fermenting yeast also interacts with this complex matrix and some strains are more resistant to high temperatures than others. Here, the temperature tolerance of nine commercial starters was evaluated, demonstrating that, at high sugar concentrations, half of them are sensitive to temperature. Using a classical backcross approach, one thermo-sensitive commercial starter was genetically improved by introducing quantitative trait loci conferring resistance to temperature. With this breeding program it is possible to obtain a thermo-resistant strain sharing most of its genome with the initial commercial starter. The parental and improved strains were compared for population growth and fermentation ability in various conditions. Despite their common genetic background, these two strains showed slight physiological differences in response to environmental changes that enable identification of the key physiological parameters influencing stuck fermentation.

Effects of temperature, pH and sugar concentration on the growth parameters of Saccharomyces cerevisiae, S. kudriavzevii and their interspecific hybrid

The effects of temperature, pH and sugar concentration (50% glucose+50% fructose) on the growth parameters of Saccharomyces cerevisiae T73, S. kudriavzevii IFO 1802(T) and the hybrid strain S. cerevisiae x S. kudriavzevii W27 were studied by means of response surface methodology based in a central composite circumscribed design. Lag phase could not be properly modelled in the wine model system, where yeasts started the fermentation in few hours after inoculation. In the case of the maximum specific growth rate (micro(max)), the temperature was the most important variable for three yeasts, although the effects of sugar concentration (in T73 and W27) and pH (W27 and 1802) were also significant (p<0.05). The only retained interaction was between the variables temperature and pH for yeast 1802. The polynomial equations built for micro(max) were used both to assess the behaviour of yeasts as a function of the factors and to predict their growth. In the case of temperature, the profiles obtained by the equations showed that response of the hybrid W27 was similar to T73 and different to 1802. When pH was the factor under study, the response of the hybrid W27 was closer to 1802 than yeast T73. For sugar concentration, the response of the hybrid W27 was similar to T73 but different to 1802. To the best of our knowledge, this is the first time that predictive models are used to assess and compare the response of a hybrid strain with respect to its parental species. The information obtained could also be useful to estimate the possible effect of climatic change on yeast growth.