Debra Rossouw

Comparative Transcriptomic Approach To Investigate Differences in Wine Yeast Physiology and Metabolism during Fermentation

ABSTRACT Commercial wine yeast strains of the species Saccharomyces cerevisiae have been selected to satisfy many different, and sometimes highly specific, oenological requirements. As a consequence, more than 200 different strains with significantly diverging phenotypic traits are produced globally. This genetic resource has been rather neglected by the scientific community because industrial strains are less easily manipulated than the limited number of laboratory strains that have been successfully employed to investigate fundamental aspects of cellular biology. However, laboratory strains are unsuitable for the study of many phenotypes that are of significant scientific and industrial interest. Here, we investigate whether a comparative transcriptomics and phenomics approach, based on the analysis of five phenotypically diverging industrial wine yeast strains, can provide insights into the molecular networks that are responsible for the expression of such phenotypes. For this purpose, some oenologically relevant phenotypes, including resistance to various stresses, cell wall properties, and metabolite production of these strains were evaluated and aligned with transcriptomic data collected during alcoholic fermentation. The data reveal significant differences in gene regulation between the five strains. While the genetic complexity underlying the various successive stress responses in a dynamic system such as wine fermentation reveals the limits of the approach, many of the relevant differences in gene expression can be linked to specific phenotypic differences between the strains. This is, in particular, the case for many aspects of metabolic regulation. The comparative approach therefore opens new possibilities to investigate complex phenotypic traits on a molecular level.

Reduced neutral invertase activity in the culm tissues of transgenic sugarcane plants results in a decrease in respiration and sucrose cycling and an increase in the sucrose to hexose ratio

Transgenic sugarcane plants (Saccharum officinarum L. interspecific hybrids) were regenerated from previously described cell lines with reduced neutral invertase (NI) activity. The effects that were observed in the differentiated culm tissues at different stages of maturity paralleled those observed across the growth cycle of the suspension cultures. Reduced NI activity correlated with an increase in sucrose and a decrease in hexose levels. However, the magnitude of the reduction in enzyme activity and the accompanying changes in carbohydrate metabolism were not as pronounced as in the suspension cultures. Feeding experiments with radio-labelled fructose provided evidence that the cycling of sucrose as well as the total respiration rate correlated directly with NI activity. Sucrose synthase activity was upregulated in the transgenic plants, possibly to compensate for the reduction in invertase activity. Despite this partial compensation, the respiratory rates of the transgenic lines were still significantly lower than those of the untransformed control lines. This study clearly demonstrates the importance of NI in directing carbon towards respiratory processes in the sugarcane culm. In addition, this is the first report in which data obtained from genetically modified sugarcane suspension cell cultures and their regenerated, whole-plant counterparts are compared. The observed correlations support the use of cell cultures as a model system for sugarcane internodes, which could significantly accelerate reverse genetic studies on sugarcane carbohydrate metabolism in the future.

The impact of co-inoculation with Oenococcus oeni on the trancriptome of Saccharomyces cerevisiae and on the flavour-active metabolite profiles during fermentation in synthetic must.

Co-inoculation of commercial yeast strains with a bacterial starter culture at the beginning of fermentation of certain varietal grape juices is rapidly becoming a preferred option in the global wine industry, and frequently replaces the previously dominant sequential inoculation strategy where bacterial strains, responsible for malolactic fermentation, are inoculated after alcoholic fermentation has been completed. However, while several studies have highlighted potential advantages of co-inoculation, such studies have mainly focused on broad fermentation properties of the mixed cultures, and no data exist regarding the impact of this strategy on many oenologically relevant attributes of specific wine yeast strains such as aroma production. Here we investigate the impact of co-inoculation on a commercial yeast strain during alcoholic fermentation by comparing the transcriptome of this strain in yeast-only and in co-inoculated fermentations of synthetic must. The data show that a significant number of genes are differentially expressed in this strain in these two conditions. Some of the differentially expressed genes appear to respond to chemical changes in the fermenting must that are linked to bacterial metabolic activities, whereas others might represent a direct response of the yeast to the presence of a competing organism.

Comparative transcriptomic and proteomic profiling of industrial wine yeast strains.

ABSTRACT The geno- and phenotypic diversity of commercial Saccharomyces cerevisiae wine yeast strains provides an opportunity to apply the system-wide approaches that are reasonably well established for laboratory strains to generate insight into the functioning of complex cellular networks in industrial environments. We have previously analyzed the transcriptomes of five industrial wine yeast strains at three time points during alcoholic fermentation. Here, we extend the comparative approach to include an isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis of two of the previously analyzed wine yeast strains at the same three time points during fermentation in synthetic wine must. The data show that differences in the transcriptomes of the two strains at a given time point rather accurately reflect differences in the corresponding proteomes independently of the gene ontology (GO) category, providing strong support for the biological relevance of comparative transcriptomic data sets in yeast. In line with previous observations, the alignment proves to be less accurate when assessing intrastrain changes at different time points. In this case, differences between the transcriptome and proteome appear to be strongly dependent on the GO category of the corresponding genes. The data in particular suggest that metabolic enzymes and the corresponding genes appear to be strongly correlated over time and between strains, suggesting a strong transcriptional control of such enzymes. The data also allow the generation of hypotheses regarding the molecular origin of significant differences in phenotypic traits between the two strains.

Comparing the transcriptomes of wine yeast strains: toward understanding the interaction between environment and transcriptome during fermentation

System-wide “omics” approaches have been widely applied to study a limited number of laboratory strains of Saccharomyces cerevisiae. More recently, industrial S. cerevisiae strains have become the target of such analyses, mainly to improve our understanding of biotechnologically relevant phenotypes that cannot be adequately studied in laboratory strains. Most of these studies have investigated single strains in a single medium. This experimental layout cannot differentiate between generally relevant molecular responses and strain- or media-specific features. Here we analyzed the transcriptomes of two phenotypically diverging wine yeast strains in two different fermentation media at three stages of wine fermentation. The data show that the intersection of transcriptome datasets from fermentations using either synthetic MS300 (simulated wine must) or real grape must (Colombard) can help to delineate relevant from “noisy” changes in gene expression in response to experimental factors such as fermentation stage and strain identity. The differences in the expression profiles of strains in the different environments also provide relevant insights into the transcriptional responses toward specific compositional features of the media. The data also suggest that MS300 is a representative environment for conducting research on wine fermentation and industrially relevant properties of wine yeast strains.

Transcriptional Regulation and the Diversification of Metabolism in Wine Yeast Strains

Transcription factors and their binding sites have been proposed as primary targets of evolutionary adaptation because changes to single transcription factors can lead to far-reaching changes in gene expression patterns. Nevertheless, there is very little concrete evidence for such evolutionary changes. Industrial wine yeast strains, of the species Saccharomyces cerevisiae, are a geno- and phenotypically diverse group of organisms that have adapted to the ecological niches of industrial winemaking environments and have been selected to produce specific styles of wine. Variation in transcriptional regulation among wine yeast strains may be responsible for many of the observed differences and specific adaptations to different fermentative conditions in the context of commercial winemaking. We analyzed gene expression profiles of wine yeast strains to assess the impact of transcription factor expression on metabolic networks. The data provide new insights into the molecular basis of variations in gene expression in industrial strains and their consequent effects on metabolic networks important to wine fermentation. We show that the metabolic phenotype of a strain can be shifted in a relatively predictable manner by changing expression levels of individual transcription factors, opening opportunities to modify transcription networks to achieve desirable outcomes.

Adjustment of trehalose metabolism in wine Saccharomyces cerevisiae strains to modify ethanol yields.

ABSTRACT The ability of Saccharomyces cerevisiae to efficiently produce high levels of ethanol through glycolysis has been the focus of much scientific and industrial activity. Despite the accumulated knowledge regarding glycolysis, the modification of flux through this pathway to modify ethanol yields has proved difficult. Here, we report on the systematic screening of 66 strains with deletion mutations of genes encoding enzymes involved in central carbohydrate metabolism for altered ethanol yields. Five of these strains showing the most prominent changes in carbon flux were selected for further investigation. The genes were representative of trehalose biosynthesis (TPS1, encoding trehalose-6-phosphate synthase), central glycolysis (TDH3, encoding glyceraldehyde-3-phosphate dehydrogenase), the oxidative pentose phosphate pathway (ZWF1, encoding glucose-6-phosphate dehydrogenase), and the tricarboxylic acid (TCA) cycle (ACO1 and ACO2, encoding aconitase isoforms 1 and 2). Two strains exhibited lower ethanol yields than the wild type (tps1Δ and tdh3Δ), while the remaining three showed higher ethanol yields. To validate these findings in an industrial yeast strain, the TPS1 gene was selected as a good candidate for genetic modification to alter flux to ethanol during alcoholic fermentation in wine. Using low-strength promoters active at different stages of fermentation, the expression of the TPS1 gene was slightly upregulated, resulting in a decrease in ethanol production and an increase in trehalose biosynthesis during fermentation. Thus, the mutant screening approach was successful in terms of identifying target genes for genetic modification in commercial yeast strains with the aim of producing lower-ethanol wines.

Co-Flocculation of Yeast Species, a New Mechanism to Govern Population Dynamics in Microbial Ecosystems

Flocculation has primarily been studied as an important technological property of Saccharomyces cerevisiae yeast strains in fermentation processes such as brewing and winemaking. These studies have led to the identification of a group of closely related genes, referred to as the FLO gene family, which controls the flocculation phenotype. All naturally occurring S. cerevisiae strains assessed thus far possess at least four independent copies of structurally similar FLO genes, namely FLO1, FLO5, FLO9 and FLO10. The genes appear to differ primarily by the degree of flocculation induced by their expression. However, the reason for the existence of a large family of very similar genes, all involved in the same phenotype, has remained unclear. In natural ecosystems, and in wine production, S. cerevisiae growth together and competes with a large number of other Saccharomyces and many more non-Saccharomyces yeast species. Our data show that many strains of such wine-related non-Saccharomyces species, some of which have recently attracted significant biotechnological interest as they contribute positively to fermentation and wine character, were able to flocculate efficiently. The data also show that both flocculent and non-flocculent S. cerevisiae strains formed mixed species flocs (a process hereafter referred to as co-flocculation) with some of these non-Saccharomyces yeasts. This ability of yeast strains to impact flocculation behaviour of other species in mixed inocula has not been described previously. Further investigation into the genetic regulation of co-flocculation revealed that different FLO genes impact differently on such adhesion phenotypes, favouring adhesion with some species while excluding other species from such mixed flocs. The data therefore strongly suggest that FLO genes govern the selective association of S. cerevisiae with specific species of non-Saccharomyces yeasts, and may therefore be drivers of ecosystem organisational patterns. Our data provide, for the first time, insights into the role of the FLO gene family beyond intraspecies cellular association, and suggest a wider evolutionary role for the FLO genes. Such a role would explain the evolutionary persistence of a large multigene family of genes with apparently similar function.

The effect of scale on gene expression: Commercial versus laboratory wine fermentations

Molecular and cellular processes that are responsible for industrially relevant phenotypes of fermenting microorganisms are a central focus of biotechnological research. Such research intends to generate insights and solutions for fermentation-based industries with regards to issues such as improving product yield or the quality of the final fermentation product. For logistical reasons, and to ensure data reproducibility, such research is mostly carried out in defined or synthetic media and in small-scale fermentation vessels. Two questions are frequently raised regarding the applicability of this approach to solve problems experienced in industrial fermentations: (1) Is synthetic medium a sufficiently accurate approximation of the generally more complex natural (and frequently highly variable) substrates that are employed in most fermentation-based industries, and (2) can results obtained in small-scale laboratory fermentations be extrapolated to large-scale industrial environments? Here, we address the second question through a comparative transcriptomic approach by assessing the response of an industrial wine yeast strain fermenting a natural grape juice in small-scale laboratory and large-scale industrial conditions. In yeast, transcriptome analysis is arguably the best available tool to holistically assess the physiological state of a population and its response to changing environmental conditions. The data suggest that scale does indeed impact on some environmental parameters such as oxygen availability. However, the data show that small-scale fermentations nevertheless accurately reflect general molecular processes and adaptations during large-scale fermentation and that extrapolation of laboratory datasets to real industrial processes can be justified.

Wine science in the omics era: the impact of systems biology on the future of wine research.

Industrial wine making confronts viticulturalists, wine makers, process engineers and scientists alike with a bewildering array of independent and semi-independent parameters that can in many cases only be optimized by trial and error. Furthermore, as most parameters are outside of individual control, predictability and consistency of the end product remain difficult to achieve. The traditional wine sciences of viticulture and oenology have been accumulating data sets and generating knowledge and know-how that has resulted in a significant optimization of the vine growing and wine making processes. However, much of these processes remain based on empirical and even anecdotal evidence, and only a small part of all the interactions and cause-effect relationships between individual input and output parameters is scientifically well understood. Indeed, the complexity of the process has prevented a deeper understanding of such interactions and causal relationships. New technologies and methods in the biological and chemical sciences, combined with improved tools of multivariate data analysis, open new opportunities to assess the entire vine growing and wine making process from a more holistic perspective. This review outlines the current efforts to use the tools of systems biology in particular to better understand complex industrial processes such as wine making.