Computational approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection

Exploring wine yeast natural biodiversity to select strains with enological traits adapted to climate change

Wine is widely consumed throughout the world and represents a significant financial market, but production faces increasing challenges. While consumers progressively value more complex flavor profiles, regional authenticity, and decreased use of additives, winemakers strive for consistency among climate change, characterized by rising environmental temperatures and sun burn events. This often leads to grapes reaching phenolic maturity with higher sugar levels, and increased microbial spoilage risk. Herein, we addressed these dual concerns by investigating the use of autochthonous Saccharomyces cerevisiae strains for fermentations of grape musts resulting from these altered conditions. We characterized underexplored repositories of naturally-occurring strains isolated from different environments and geographical regions, regarding adequate enological properties (e.g., high cell growth, reduced production of H2S, ethanol and acetic acid, increased SO2 resistance, killer activity), and other less frequently investigated properties (resistance to osmotic stress, potassium and aluminium silicates and fungicides). The phenotypic data were organized in a biobank, and bioinformatic analysis grouped the strains according to their characteristics. Furthermore, we analyzed the potential of four Portuguese isolates to be used in fermentations of grape musts with high sugar levels, uncovering promising candidates. This research therefore contributes to ongoing efforts to increase sustainability and quality of wine production.

Torulaspora delbrueckii Phenotypic and Metabolic Profiling towards Its Biotechnological Exploitation

Wine is a particularly complex beverage resulting from the combination of several factors, with yeasts being highlighted due to their fundamental role in its development. For many years, non-Saccharomyces yeasts were believed to be sources of spoilage and contamination, but this idea was challenged, and many of these yeasts are starting to be explored for their beneficial input to wine character. Among this group, Torulaspora delbrueckii is gaining relevance within the wine industry, owing to its low volatile acidity production, increased release of aromatic compounds and enhanced color intensity. In addition, this yeast was also attracting interest in other biotechnological areas, such as bread and beer fermentation. In this work, a set of 40 T. delbrueckii strains, of varied geographical and technological origins, was gathered in order to characterize the phenotypic behavior of this species, focusing on different parameters of biotechnological interest. The fermentative performance of the strains was also evaluated through individual fermentations in synthetic grape must with the isolates’ metabolic profile being assessed by HPLC. Data analysis revealed that T. delbrueckii growth is significantly affected by high temperature (37 °C) and ethanol concentrations (up to 18%), alongside 1.5 mM SO₂, showing variable fermentative power and yields. Our computation models suggest that the technological origin of the strains seems to prevail over the geographical origin as regards the influence on yeast properties. The inter-strain variability and profile of the products through the fermentative processes reinforce the potential of T. delbrueckii from a biotechnological point of view.

Whole-Genome Sequencing and Annotation of the Yeast Clavispora santaluciae Reveals Important Insights about Its Adaptation to the Vineyard Environment

Clavispora santaluciae was recently described as a novel non-Saccharomyces yeast species, isolated from grapes of Azores vineyards, a Portuguese archipelago with particular environmental conditions, and from Italian grapes infected with Drosophila suzukii. In the present work, the genome of five Clavispora santaluciae strains was sequenced, assembled, and annotated for the first time, using robust pipelines, and a combination of both long- and short-read sequencing platforms. Genome comparisons revealed specific differences between strains of Clavispora santaluciae reflecting their isolation in two separate ecological niches—Azorean and Italian vineyards—as well as mechanisms of adaptation to the intricate and arduous environmental features of the geographical location from which they were isolated. In particular, relevant differences were detected in the number of coding genes (shared and unique) and transposable elements, the amount and diversity of non-coding RNAs, and the enzymatic potential of each strain through the analysis of their CAZyome. A comparative study was also conducted between the Clavispora santaluciae genome and those of the remaining species of the Metschnikowiaceae family. Our phylogenetic and genomic analysis, comprising 126 yeast strains (alignment of 2362 common proteins) allowed the establishment of a robust phylogram of Metschnikowiaceae and detailed incongruencies to be clarified in the future.

The influence of growth conditions on MALDI-TOF MS spectra of winemaking yeast: implications for industry applications

Previous studies have shown MALDI-TOF MS to be a powerful tool in wine yeast identification and potential prediction of application. However, it is also established that substrate composition influences protein expression, but the degree to which this may affect MALDI-TOF spectra (and analytical results thereof) has not been fully explored. To further inform assay optimisation, the influence on MALDI-TOF spectra was determined using eight Saccharomyces strains of diverse origins cultivated on grape juices from Pinot Noir and Chardonnay varieties, synthetic grape juice, and laboratory-grade artificial culture media (YPD broth and agar). Our results demonstrated significant influences of culture media on strain MALDI-TOF spectra. Yeast culture on YPD agar is recommended for taxonomic studies, with YPD broth culture of S. cerevisiae offering improved intra-subspecific differentiation Furthermore, our data supported a correlation between MALDI spectra and the potential industrial application of individual yeast strains.

Molecular Diagnosis of Brettanomyces bruxellensis' Sulfur Dioxide Sensitivity Through Genotype Specific Method

The yeast species Brettanomyces bruxellensis is associated with important economic losses due to red wine spoilage. The most common method to prevent and/or control B. bruxellensis spoilage in winemaking is the addition of sulfur dioxide into must and wine. However, recently, it was reported that some B. bruxellensis strains could be tolerant to commonly used doses of SO₂. In this work, B. bruxellensis response to SO₂ was assessed in order to explore the relationship between SO₂ tolerance and genotype. We selected 145 isolates representative of the genetic diversity of the species, and from different fermentation niches (roughly 70% from grape wine fermentation environment, and 30% from beer, ethanol, tequila, kombucha, etc.). These isolates were grown in media harboring increasing sulfite concentrations, from 0 to 0.6 mg.L^-1 of molecular SO₂. Three behaviors were defined: sensitive strains showed longer lag phase and slower growth rate and/or lower maximum population size in presence of increasing concentrations of SO₂. Tolerant strains displayed increased lag phase, but maximal growth rate and maximal population size remained unchanged. Finally, resistant strains showed no growth variation whatever the SO₂ concentrations. 36% (52/145) of B. bruxellensis isolates were resistant or tolerant to sulfite, and up to 43% (46/107) when considering only wine isolates. Moreover, most of the resistant/tolerant strains belonged to two specific genetic groups, allowing the use of microsatellite genotyping to predict the risk of sulfur dioxide resistance/tolerance with high reliability (>90%). Such molecular diagnosis could help the winemakers to adjust antimicrobial techniques and efficient spoilage prevention with minimal intervention.

Genomic and transcriptomic analysis of Saccharomyces cerevisiae isolates with focus in succinic acid production

Succinic acid is a platform chemical that plays an important role as precursor for the synthesis of many valuable bio-based chemicals. Its microbial production from renewable resources has seen great developments, specially exploring the use of yeasts to overcome the limitations of using bacteria. The objective of the present work was to screen for succinate-producing isolates, using a yeast collection with different origins and characteristics. Four strains were chosen, two as promising succinic acid producers, in comparison with two low producers. Genome of these isolates was analysed, and differences were found mainly in genes SDH1, SDH3, MDH1 and the transcription factor HAP4, regarding the number of single nucleotide polymorphisms and the gene copy-number profile. Real-time PCR was used to study gene expression of 10 selected genes involved in the metabolic pathway of succinic acid production. Results show that for the non-producing strain, higher expression of genes SDH1, SDH2, ADH1, ADH3, IDH1 and HAP4 was detected, together with lower expression of ADR1 transcription factor, in comparison with the best producer strain. This is the first study showing the capacity of natural yeast isolates to produce high amounts of succinic acid, together with the understanding of the key factors associated, giving clues for strain improvement.

Comparative studies on the fermentation performance of autochthonous Saccharomyces cerevisiae strains in Chinese light-fragrant liquor during solid-state or submerged fermentation

AIM

To explore the metabolic characteristic of autochthonous Saccharomyces cerevisiae strains in Chinese light-fragrant liquor fermentation.

METHODS AND RESULTS

Inter-delta amplification analysis was used to differentiate the S. cerevisiae strains at strain level. Twelve biotypes (I-XII) were identified among the 72 S. cerevisiae strains preselected. A comparison was conducted between solid-state fermentation (SSF) and submerged fermentation (SmF) with S. cerevisiae strains had different genotype, with a focus on the production of ethanol and the volatile compounds. The degree of ethanol ranged from 28·0 to 45·2 g l^-1 in SmF and from 14·8 to 25·6 g kg^-1 in SSF, and SSF was found to be more suitable for the production of ethanol with higher yield coefficient of all the S. cerevisiae strains. The metabolite profiles of each yeast strain showed obvious distinction in the two fermentations. The highest amounts of ethyl acetate in SmF and SSF were found in genotype VII (328·2 μg l^-1 ) and genotype V (672 μg kg^-1 ), respectively. In addition, the generation of some volatile compounds could be strictly related to the strain used. Compound β-damascenone was only detected in genotypes I, II, X and XII in the two fermentation processes. Furthermore, laboratory scale fermentations were clearly divided into SSF and SmF in hierarchical cluster analysis regardless of the inoculated yeast strains, indicating that the mode of fermentation was more important than the yeast strains inoculated.

CONCLUSION

The autochthonous S. cerevisiae strains in Chinese light-fragrant liquor vary considerably in terms of their volatiles profiles during SSF and SmF.

SIGNIFICANCE AND IMPACT OF THE STUDY

This work facilitates a better understanding of the fermentative mechanism in the SSF process for light-fragrant liquor production.

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Computational models reveal genotype-phenotype associations in Saccharomyces cerevisiae

Genome sequencing is essential to understand individual variation and to study the mechanisms that explain relations between genotype and phenotype. The accumulated knowledge from large-scale genome sequencing projects of Saccharomyces cerevisiae isolates is being used to study the mechanisms that explain such relations. Our objective was to undertake genetic characterization of 172 S. cerevisiae strains from different geographical origins and technological groups, using 11 polymorphic microsatellites, and computationally relate these data with the results of 30 phenotypic tests. Genetic characterization revealed 280 alleles, with the microsatellite ScAAT1 contributing most to intrastrain variability, together with alleles 20, 9 and 16 from the microsatellites ScAAT4, ScAAT5 and ScAAT6. These microsatellite allelic profiles are characteristic for both the phenotype and origin of yeast strains. We confirm the strength of these associations by construction and cross-validation of computational models that can predict the technological application and origin of a strain from the microsatellite allelic profile. Associations between microsatellites and specific phenotypes were scored using information gain ratios, and significant findings were confirmed by permutation tests and estimation of false discovery rates. The phenotypes associated with higher number of alleles were the capacity to resist to sulphur dioxide (tested by the capacity to grow in the presence of potassium bisulphite) and the presence of galactosidase activity. Our study demonstrates the utility of computational modelling to estimate a strain technological group and phenotype from microsatellite allelic combinations as tools for preliminary yeast strain selection.

Phenotypic and metabolic traits of commercial Saccharomyces cerevisiae yeasts

Currently, pursuing yeast strains that display both a high potential fitness for alcoholic fermentation and a favorable impact on quality is a major goal in the alcoholic beverage industry. This considerable industrial interest has led to many studies characterizing the phenotypic and metabolic traits of commercial yeast populations. In this study, 20 Saccharomyces cerevisiae strains from different geographical origins exhibited high phenotypic diversity when their response to nine biotechnologically relevant conditions was examined. Next, the fermentation fitness and metabolic traits of eight selected strains with a unique phenotypic profile were evaluated in a high-sugar synthetic medium under two nitrogen regimes. Although the strains exhibited significant differences in nitrogen requirements and utilization rates, a direct relationship between nitrogen consumption, specific growth rate, cell biomass, cell viability, acetic acid and glycerol formation was only observed under high-nitrogen conditions. In contrast, the strains produced more succinic acid under the low-nitrogen regime, and a direct relationship with the final cell biomass was established. Glucose and fructose utilization patterns depended on both yeast strain and nitrogen availability. For low-nitrogen fermentation, three strains did not fully degrade the fructose. This study validates phenotypic and metabolic diversity among commercial wine yeasts and contributes new findings on the relationship between nitrogen availability, yeast cell growth and sugar utilization. We suggest that measuring nitrogen during the stationary growth phase is important because yeast cells fermentative activity is not exclusively related to population size, as previously assumed, but it is also related to the quantity of nitrogen consumed during this growth phase.

Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40°C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures.

Influence of red wine fermentation oenological additives on inoculated strain implantation

Pure selected cultures of Saccharomyces cerevisiae starters are regularly used in the wine industry. A survey of S. cerevisiae populations during red wine fermentations was performed in order to evaluate the influence of oenological additives on the implantation of the inoculated strain. Pilot scale fermentations (500 L) were conducted with active dry yeast (ADY) and other commercial oenological additives, namely two commercial fermentation activators and two commercial tannins. Six microsatellite markers were used to type S. cerevisiae strains. The methodology proved to be very discriminating as a great diversity of wild strains (48 genotypes) was detected. Statistical analysis confirmed a high detection of the inoculated commercial strain, and for half the samples an effective implantation of ADY (over 80 %) was achieved. At late fermentation time, ADY strain implantation in fermentations conducted with commercial additives was lower than in the control. These results question the efficacy of ADY addition in the presence of other additives, indicating that further studies are needed to improve knowledge on oenological additives' use.

Analysis of the Saccharomyces cerevisiae pan-genome reveals a pool of copy number variants distributed in diverse yeast strains from differing industrial environments

Although the budding yeast Saccharomyces cerevisiae is arguably one of the most well-studied organisms on earth, the genome-wide variation within this species--i.e., its "pan-genome"--has been less explored. We created a multispecies microarray platform containing probes covering the genomes of several Saccharomyces species: S. cerevisiae, including regions not found in the standard laboratory S288c strain, as well as the mitochondrial and 2-μm circle genomes-plus S. paradoxus, S. mikatae, S. kudriavzevii, S. uvarum, S. kluyveri, and S. castellii. We performed array-Comparative Genomic Hybridization (aCGH) on 83 different S. cerevisiae strains collected across a wide range of habitats; of these, 69 were commercial wine strains, while the remaining 14 were from a diverse set of other industrial and natural environments. We observed interspecific hybridization events, introgression events, and pervasive copy number variation (CNV) in all but a few of the strains. These CNVs were distributed throughout the strains such that they did not produce any clear phylogeny, suggesting extensive mating in both industrial and wild strains. To validate our results and to determine whether apparently similar introgressions and CNVs were identical by descent or recurrent, we also performed whole-genome sequencing on nine of these strains. These data may help pinpoint genomic regions involved in adaptation to different industrial milieus, as well as shed light on the course of domestication of S. cerevisiae.

Expression variability of co-regulated genes differentiates Saccharomyces cerevisiae strains

BACKGROUND

Saccharomyces cerevisiae (Baker's yeast) is found in diverse ecological niches and is characterized by high adaptive potential under challenging environments. In spite of recent advances on the study of yeast genome diversity, little is known about the underlying gene expression plasticity. In order to shed new light onto this biological question, we have compared transcriptome profiles of five environmental isolates, clinical and laboratorial strains at different time points of fermentation in synthetic must medium, during exponential and stationary growth phases.

RESULTS

Our data unveiled diversity in both intensity and timing of gene expression. Genes involved in glucose metabolism and in the stress response elicited during fermentation were among the most variable. This gene expression diversity increased at the onset of stationary phase (diauxic shift). Environmental isolates showed lower average transcript abundance of genes involved in the stress response, assimilation of nitrogen and vitamins, and sulphur metabolism, than other strains. Nitrogen metabolism genes showed significant variation in expression among the environmental isolates.

CONCLUSIONS

Wild type yeast strains respond differentially to the stress imposed by nutrient depletion, ethanol accumulation and cell density increase, during fermentation of glucose in synthetic must medium. Our results support previous data showing that gene expression variability is a source of phenotypic diversity among closely related organisms.

PGM2 overexpression improves anaerobic galactose fermentation in Saccharomyces cerevisiae

Background

In Saccharomyces cerevisiae galactose is initially metabolized through the Leloir pathway after which glucose 6-phosphate enters glycolysis. Galactose is controlled both by glucose repression and by galactose induction. The gene PGM2 encodes the last enzyme of the Leloir pathway, phosphoglucomutase 2 (Pgm2p), which catalyses the reversible conversion of glucose 1-phosphate to glucose 6-phosphate. Overexpression of PGM2 has previously been shown to enhance aerobic growth of S. cerevisiae in galactose medium.

Results

In the present study we show that overexpression of PGM2 under control of the HXT7'promoter from an integrative plasmid increased the PGM activity 5 to 6 times, which significantly reduced the lag phase of glucose-pregrown cells in an anaerobic galactose culture. PGM2 overexpression also increased the anaerobic specific growth rate whereas ethanol production was less influenced. When PGM2 was overexpressed from a multicopy plasmid instead, the PGM activity increased almost 32 times. However, this increase of PGM activity did not further improve aerobic galactose fermentation as compared to the strain carrying PGM2 on the integrative plasmid.

Conclusion

PGM2 overexpression in S. cerevisiae from an integrative plasmid is sufficient to reduce the lag phase and to enhance the growth rate in anaerobic galactose fermentation, which results in an overall decrease in fermentation duration. This observation is of particular importance for the future development of stable industrial strains with enhanced PGM activity.