Development of bottom-fermenting saccharomyces strains that produce high SO2 levels, using integrated metabolome and transcriptome analysis

Lager-brewing yeasts in the era of modern genetics

The yeast Saccharomyces pastorianus is responsible for the annual worldwide production of almost 200 billion liters of lager-type beer. S. pastorianus is a hybrid of Saccharomyces cerevisiae and Saccharomyces eubayanus that has been studied for well over a century. Scientific interest in S. pastorianus intensified upon the discovery, in 2011, of its S. eubayanus ancestor. Moreover, advances in whole-genome sequencing and genome editing now enable deeper exploration of the complex hybrid and aneuploid genome architectures of S. pastorianus strains. These developments not only provide novel insights into the emergence and domestication of S. pastorianus but also generate new opportunities for its industrial application. This review paper combines historical, technical and socioeconomic perspectives to analyze the evolutionary origin and genetics of S. pastorianus. In addition, it provides an overview of available methods for industrial strain improvement and an outlook on future industrial application of lager-brewing yeasts. Particular attention is given to the ongoing debate on whether current S. pastorianus originates from a single or multiple hybridization events and to the potential role of genome editing in developing industrial brewing yeast strains.

Reverse metabolic engineering in lager yeast: impact of the NADH/NAD+ ratio on acetaldehyde production during the brewing process

Acetaldehyde is synthesized by yeast during the main fermentation period of beer production, which causes an unpleasant off-flavor. Therefore, there has been extensive effort toward reducing acetaldehyde to obtain a beer product with better flavor and anti-staling ability. In this study, we discovered that acetaldehyde production in beer brewing is closely related with the intracellular NADH equivalent regulated by the citric acid cycle. However, there was no significant relationship between acetaldehyde production and amino acid metabolism. A reverse engineering strategy to increase the intracellular NADH/NAD⁺ ratio reduced the final acetaldehyde production level, and vice versa. This work offers new insight into acetaldehyde metabolism and further provides efficient strategies for reducing acetaldehyde production by the regulating the intracellular NADH/NAD⁺ ratio through cofactor engineering.

Identification of new Saccharomyces cerevisiae variants of the MET2 and SKP2 genes controlling the sulfur assimilation pathway and the production of undesirable sulfur compounds during alcoholic fermentation

Background

Wine yeasts can produce undesirable sulfur compounds during alcoholic fermentation, such as SO₂ and H₂S, in variable amounts depending mostly on the yeast strain but also on the conditions. However, although sulfur metabolism has been widely studied, some of the genetic determinants of differences in sulfite and/or sulfide production between wine yeast strains remain to be identified. In this study, we used an integrated approach to decipher the genetic determinants of variation in the production of undesirable sulfur compounds.

Results

We examined the kinetics of SO₂ production by two parental strains, one high and one low sulfite producer. These strains displayed similar production profiles but only the high-sulfite producer strain continued to produce SO₂ in the stationary phase. Transcriptomic analysis revealed that the low-sulfite producer strain overexpressed genes of the sulfur assimilation pathway, which is the mark of a lower flux through the pathway consistent with a lower intracellular concentration in cysteine. A QTL mapping strategy then enabled us to identify MET2 and SKP2 as the genes responsible for these phenotypic differences between strains and we identified new variants of these genes in the low-sulfite producer strain. MET2 influences the availability of a metabolic intermediate, O-acetylhomoserine, whereas SKP2 affects the activity of a key enzyme of the sulfur assimilation branch of the pathway, the APS kinase, encoded by MET14. Furthermore, these genes also affected the production of propanol and acetaldehyde. These pleiotropic effects are probably linked to the influence of these genes on interconnected pathways and to the chemical reactivity of sulfite with other metabolites.

Conclusions

This study provides new insight into the regulation of sulfur metabolism in wine yeasts and identifies variants of MET2 and SKP2 genes, that control the activity of both branches of the sulfur amino acid synthesis pathway and modulate sulfite/sulfide production and other related phenotypes. These results provide novel targets for the improvement of wine yeast strains.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-015-0245-1) contains supplementary material, which is available to authorized users.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.

Secretion expression of SOD1 and its overlapping function with GSH in brewing yeast strain for better flavor and anti-aging ability

Superoxide dismutase (SOD) is a significant antioxidant, but unlike glutathione (GSH), SOD cannot be secreted into beer by yeast cells during fermentation, this directly leads to the limited application of SOD in beer anti-aging. In this investigation, we constructed the SOD1 secretion cassette in which strong promoter PGK1p and the sequence of secreting signal factor from Saccharomyces cerevisiae were both harbored to the upstream of coding sequence of SOD1 gene, as a result, the obtained strains carrying this cassette successfully realized the secretion of SOD1. In order to overcome the limitation of previous genetic modification on yeast strains, one new comprehensive strategy was adopted targeting the suitable homologous sites by gene deletion and SOD1 + GSH1 co-overexpression, and the new strain ST31 (Δadh2::SOD1 + Δilv2::GSH1) was constructed. The results of the pilot-scale fermentation showed that the diacetyl content of ST31 was lower by 42 % than that of the host, and the acetaldehyde content decreased by 29 %, the GSH content in the fermenting liquor of ST31 increased by 29 % compared with the host. Both SOD activity test and the positive and negative staining assay after native PAGE indicated that the secreted active SOD in the fermenting liquor of ST31 was mainly a dimer with the size of 32,500 Da. The anti-aging indexes such as the thiobarbituric acid and the resistance staling value further proved that the flavor stability of the beer brewed with strain ST31 was not only better than that of the original strain, but also better than that of the previous engineering strains. The multi-modification and comprehensive improvement of the beer yeast strain would greatly enhance beer quality than ever, and the self-cloning strain would be attractive to the public due to its bio-safety.

Improving industrial yeast strains: exploiting natural and artificial diversity

Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.

Sterol side chain reductase 2 is a key enzyme in the biosynthesis of cholesterol, the common precursor of toxic steroidal glycoalkaloids in potato

Potatoes (Solanum tuberosum) contain α-solanine and α-chaconine, two well-known toxic steroidal glycoalkaloids (SGAs). Sprouts and green tubers accumulate especially high levels of SGAs. Although SGAs were proposed to be biosynthesized from cholesterol, the biosynthetic pathway for plant cholesterol is poorly understood. Here, we identify sterol side chain reductase 2 (SSR2) from potato as a key enzyme in the biosynthesis of cholesterol and related SGAs. Using in vitro enzyme activity assays, we determined that potato SSR2 (St SSR2) reduces desmosterol and cycloartenol to cholesterol and cycloartanol, respectively. These reduction steps are branch points in the biosynthetic pathways between C-24 alkylsterols and cholesterol in potato. Similar enzymatic results were also obtained from tomato SSR2. St SSR2-silenced potatoes or St SSR2-disrupted potato generated by targeted genome editing had significantly lower levels of cholesterol and SGAs without affecting plant growth. Our results suggest that St SSR2 is a promising target gene for breeding potatoes with low SGA levels.

Intracellular proteins of ethanol-treated yeast cells involved in iron sorption

Iron is essential for human health, but it sometimes causes an unpleasant taste, rusty colour and a decrease in the stability of food products. Previously, we found that ethanol-treated yeast (ETY) cells could remove iron from wine and juice, and reduce the fishy aftertaste induced by iron in wine-seafood pairings. However, the mechanism of iron sorption by ETY cells is undefined; thus, there is no indicator that can be used to estimate the iron sorption capacity of these cells. In this study, we showed that cell wall components are not mainly associated with iron sorption by investigating ETY cells with the cell wall removed. Moreover, plasma membrane permeability was correlated with the iron sorbing capacity of the cells. Microscopic analysis showed that iron accumulated within ETY cells. Proteinase-treated ETY cells had no iron sorbing capacity. On the basis of these results, we conclude that intracellular proteins are involved in iron sorption by ETY cells.

Dynamic changes in brewing yeast cells in culture revealed by statistical analyses of yeast morphological data

The vitality of brewing yeasts has been used to monitor their physiological state during fermentation. To investigate the fermentation process, we used the image processing software, CalMorph, which generates morphological data on yeast mother cells and bud shape, nuclear shape and location, and actin distribution. We found that 248 parameters changed significantly during fermentation. Successive use of principal component analysis (PCA) revealed several important features of yeast, providing insight into the dynamic changes in the yeast population. First, PCA indicated that much of the observed variability in the experiment was summarized in just two components: a change with a peak and a change over time. Second, PCA indicated the independent and important morphological features responsible for dynamic changes: budding ratio, nucleus position, neck position, and actin organization. Thus, the large amount of data provided by imaging analysis can be used to monitor the fermentation processes involved in beer and bioethanol production.

Dynamic metabolic profiling of cyanobacterial glycogen biosynthesis under conditions of nitrate depletion

Cyanobacteria represent a globally important biomass because they are responsible for a substantial proportion of primary production in the hydrosphere. Arthrospira platensis is a fast-growing halophilic cyanobacterium capable of accumulating glycogen and has the potential to serve as a feedstock in the fermentative production of third-generation biofuels. Accordingly, enhancing cyanobacterial glycogen production is a promising biofuel production strategy. However, the regulatory mechanism of glycogen metabolism in cyanobacteria is poorly understood. The aim of the present study was to determine the metabolic flux of glycogen biosynthesis using a dynamic metabolomic approach. Time-course profiling of widely targeted cyanobacterial metabolic intermediates demonstrated a global metabolic reprogramming that involves transient increases in the levels of some amino acids during the glycogen production phase induced by nitrate depletion. Also, in vivo labelling with NaH(13)CO3 enabled direct measurement of metabolic intermediate turnover in A. platensis, revealing that under conditions of nitrate depletion glycogen is biosynthesized with carbon derived from amino acids released from proteins via gluconeogenesis. This dynamic metabolic profiling approach provided conclusive evidence of temporal alterations in the metabolic profile in cyanobacterial cells.

Capillary electrophoresis-mass spectrometry reveals the distribution of carbon metabolites during nitrogen starvation in Synechocystis sp. PCC 6803

Nitrogen availability is one of the most important factors for the survival of cyanobacteria. Previous studies on Synechocystis revealed a contradictory situation with regard to metabolism during nitrogen starvation; that is, glycogen accumulated even though the expressions of sugar catabolic genes were widely upregulated. Here, we conducted transcript and metabolomic analyses using capillary electrophoresis-mass spectrometry on Synechocystis sp. PCC 6803 under nitrogen starvation. The levels of some tricarboxylic acid cycle intermediates (succinate, malate and fumarate) were greatly increased by nitrogen deprivation. Purine and pyrimidine nucleotides were markedly downregulated under nitrogen depletion. The levels of 19 amino acids changed under nitrogen deprivation, especially those of amino acids synthesized from pyruvate and phosphoenolpyruvate, which showed marked increases. Liquid chromatography-mass spectrometry analysis demonstrated that the amount of NADPH and the NADPH/NADH ratio decreased under nitrogen depletion. These data demonstrate that there are increases in not only glycogen but also in metabolites downstream of sugar catabolism in Synechocystis sp. PCC 6803 under nitrogen starvation, resolving the contradiction between glycogen accumulation and induction of sugar catabolic gene expression in this unicellular cyanobacterium.

Current metabolomics: practical applications

The field of metabolomics continues to grow rapidly over the last decade and has been proven to be a powerful technology in predicting and explaining complex phenotypes in diverse biological systems. Metabolomics complements other omics, such as transcriptomics and proteomics and since it is a 'downstream' result of gene expression, changes in the metabolome is considered to best reflect the activities of the cell at a functional level. Thus far, metabolomics might be the sole technology capable of detecting complex, biologically essential changes. As one of the omics technology, metabolomics has exciting applications in varied fields, including medical science, synthetic biology, medicine, and predictive modeling of plant, animal and microbial systems. In addition, integrated applications with genomics, transcriptomics, and proteomics provide greater understanding of global system biology. In this review, we discuss recent applications of metabolomics in microbiology, plant, animal, food, and medical science.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Evaluation of control mechanisms for Saccharomyces cerevisiae central metabolic reactions using metabolome data of eight single-gene deletion mutants

We performed metabolome and metabolite-metabolite correlation analyses for eight single-gene deletion mutants of Saccharomyces cerevisiae to evaluate the physiology of glucose metabolism. The irreversible enzyme reactions can become bottlenecks when intracellular metabolism is perturbed by direct interference from the central metabolic pathway by gene deletions or by a deletion of transcriptional regulator. Metabolome data reveal that transcriptional factor, gcr2, regulates the reaction that converts 3-phosphoglycerate into phosphoenolpyruvate. Metabolome data also suggest that the reaction catalyzed by pyruvate kinase makes one of the rate-limiting reactions throughout the glycolytic pathway.

Novel method to reduce fishy aftertaste in wine and seafood pairing using alcohol-treated yeast cells

"Fishy aftertaste" is sometimes perceived in wine consumed with seafood. Iron in wine has been reported to be a key compound that produces fishy aftertaste. However, cost-effective methods to remove iron from wine have not been developed. Here, we describe a cost-effective and safe iron adsorbent consisting of alcohol-treated yeast (ATY) cells based on the observation that nonviable cells adsorbed iron after completion of fermentation. Treatment of cells with more than 40% (v/v) ethanol killed them without compromising their ability to adsorb iron. Drying the ATY cells did not reduce iron adsorption. Use of ATY cells together with phytic acid had a synergistic effect on iron removal. We term this means of removing iron the "ATY-PA" method. Sensory analysis indicated that fishy aftertaste in wine-seafood pairings was not perceived if the wine had been pretreated with both ATY cells and phytic acid.

Improvements in ethanol production from xylose by mating recombinant xylose-fermenting Saccharomyces cerevisiae strains

To improve the ability of recombinant Saccharomyces cerevisiae strains to utilize the hemicellulose components of lignocellulosic feedstocks, the efficiency of xylose conversion to ethanol needs to be increased. In the present study, xylose-fermenting, haploid, yeast cells of the opposite mating type were hybridized to produce a diploid strain harboring two sets of xylose-assimilating genes encoding xylose reductase, xylitol dehydrogenase, and xylulokinase. The hybrid strain MN8140XX showed a 1.3- and 1.9-fold improvement in ethanol production compared to its parent strains MT8-1X405 and NBRC1440X, respectively. The rate of xylose consumption and ethanol production was also improved by the hybridization. This study revealed that the resulting improvements in fermentation ability arose due to chromosome doubling as well as the increase in the copy number of xylose assimilation genes. Moreover, compared to the parent strain, the MN8140XX strain exhibited higher ethanol production under elevated temperatures (38 °C) and acidic conditions (pH 3.8). Thus, the simple hybridization technique facilitated an increase in the xylose fermentation activity.

Metabolic pathway engineering based on metabolomics confers acetic and formic acid tolerance to a recombinant xylose-fermenting strain of Saccharomyces cerevisiae

Background

The development of novel yeast strains with increased tolerance toward inhibitors in lignocellulosic hydrolysates is highly desirable for the production of bio-ethanol. Weak organic acids such as acetic and formic acids are necessarily released during the pretreatment (i.e. solubilization and hydrolysis) of lignocelluloses, which negatively affect microbial growth and ethanol production. However, since the mode of toxicity is complicated, genetic engineering strategies addressing yeast tolerance to weak organic acids have been rare. Thus, enhanced basic research is expected to identify target genes for improved weak acid tolerance.

Results

In this study, the effect of acetic acid on xylose fermentation was analyzed by examining metabolite profiles in a recombinant xylose-fermenting strain of Saccharomyces cerevisiae. Metabolome analysis revealed that metabolites involved in the non-oxidative pentose phosphate pathway (PPP) [e.g. sedoheptulose-7-phosphate, ribulose-5-phosphate, ribose-5-phosphate and erythrose-4-phosphate] were significantly accumulated by the addition of acetate, indicating the possibility that acetic acid slows down the flux of the pathway. Accordingly, a gene encoding a PPP-related enzyme, transaldolase or transketolase, was overexpressed in the xylose-fermenting yeast, which successfully conferred increased ethanol productivity in the presence of acetic and formic acid.

Conclusions

Our metabolomic approach revealed one of the molecular events underlying the response to acetic acid and focuses attention on the non-oxidative PPP as a target for metabolic engineering. An important challenge for metabolic engineering is identification of gene targets that have material importance. This study has demonstrated that metabolomics is a powerful tool to develop rational strategies to confer tolerance to stress through genetic engineering.

Metabolomics-based systematic prediction of yeast lifespan and its application for semi-rational screening of ageing-related mutants

Metabolomics - the comprehensive analysis of metabolites - was recently used to classify yeast mutants with no overt phenotype using raw data as metabolic fingerprints or footprints. In this study, we demonstrate the estimation of a complicated phenotype, longevity, and semi-rational screening for relevant mutants using metabolic profiles as strain-specific fingerprints. The fingerprints used in our experiments are profiled data consisting of individually identified and quantified metabolites rather than raw spectrum data. We chose yeast replicative lifespan as a model phenotype. Several yeast mutants that affect lifespan were selected for analysis, and they were subjected to metabolic profiling using mass spectrometry. Fingerprinting based on the profiles revealed a correlation between lifespan and metabolic profile. Amino acids and nucleotide derivatives were the main contributors to this correlation. Furthermore, we established a multivariate model to predict lifespan from a metabolic profile. The model facilitated the identification of putative longevity mutants. This work represents a novel approach to evaluate and screen complicated and quantitative phenotype by means of metabolomics.

Metabolomic profiling of anionic metabolites by capillary electrophoresis mass spectrometry

We describe a sheath flow capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) method in the negative mode using a platinum electrospray ionization (ESI) spray needle, which allows the comprehensive analysis of anionic metabolites. The material of the spray needle had significant effect on the measurement of anions. A stainless steel spray needle was oxidized and corroded at the anodic electrode due to electrolysis. The precipitation of iron oxides (rust) plugged the capillary outlet, resulting in shortened capillary lifetime. Many anionic metabolites also formed complexes with the iron oxides or migrating nickel ion, which was also generated by electrolysis and moved toward the cathode (the capillary inlet). The metal-anion complex formation significantly reduced detection sensitivity of the anionic compounds. The use of a platinum ESI needle prevented both oxidation of the metals and needle corrosion. Sensitivity using the platinum needle increased from several- to 63-fold, with the largest improvements for anions exhibiting high metal chelating properties such as carboxylic acids, nucleotides, and coenzyme A compounds. The detection limits for most anions were between 0.03 and 0.87 micromol/L (0.8 and 24 fmol) at a signal-to-noise ratio of 3. This method is quantitative, sensitive, and robust, and its utility was demonstrated by the analysis of the metabolites in the central metabolic pathways extracted from mouse liver.

Genome-wide expression analysis of Saccharomyces pastorianus orthologous genes using oligonucleotide microarrays

The lager brewing yeast, Saccharomyces pastorianus, an allopolyploid species hybrid, contains 2 diverged sub-genomes; one derived from Saccharomyces cerevisiae (Sc-type) and the other from Saccharomyces bayanus (Sb-type). We analyzed the functional roles of these orthologous genes in determining the phenotypic features of S. pastorianus. We used a custom-made oligonucleotide microarray containing probes designed for both Sc-type and Sb-type ORFs for a comprehensive expression analysis of S. pastorianus in a pilot-scale fermentation. We showed a high degree of correlation between the expression levels and the expression changes for a majority of orthologous gene sets during the fermentation process. We screened the functional categories and metabolic pathways where Sc- or Sb-type genes have higher expression levels than the corresponding orthologous genes. Our data showed that, for example, pathways for sulfur metabolism, cellular import, and production of branched amino acids are dominated by Sb-type genes. This comprehensive expression analysis of orthologous genes can provide valuable insights on understanding the phenotype of S. pastorianus.

Efficient production of L-lactic acid by Crabtree-negative yeast Candida boidinii

Industrial production of L-lactic acid, which in polymerized form as poly-lactic acid is widely used as a biodegradable plastic, has been attracting world-wide attention. By genetic engineering we constructed a strain of the Crabtree-negative yeast Candida boidinii that efficiently produced a large amount of L-lactic acid. The alcohol fermentation pathway of C. boidinii was altered by disruption of the PDC1 gene encoding pyruvate decarboxylase, resulting in an ethanol production that was reduced to 17% of the wild-type strain. The alcohol fermentation pathway of the PDC1 deletion strain was then successfully utilized for the synthesis of L-lactic acid by placing the bovine L-lactate dehydrogenase-encoding gene under the control of the PDC1 promoter by targeted integration. Optimizing the conditions for batch culture in a 5 l jar-fermenter resulted in an L-lactic acid production reaching 85.9 g/l within 48 h. This productivity (1.79 g/l/h) is the highest thus far reported for L-lactic acid-producing yeasts.