An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry

A method for the global analysis of yeast intracellular metabolites, based on electrospray mass spectrometry (ES-MS), has been developed. This has involved the optimization of methods for quenching metabolism in Saccharomyces cerevisiae and extracting the metabolites for analysis by positive-ion electrospray mass spectrometry. The influence of cultivation conditions, sampling, quenching and extraction conditions, concentration step, and storage have all been studied and adapted to allow direct infusion of samples into the mass spectrometer and the acquisition of metabolic profiles with simultaneous detection of more than 25 intracellular metabolites. The method, which can be applied to other micro-organisms and biological systems, may be used for comparative analysis and screening of metabolite profiles of yeast strains and mutants under controlled conditions in order to elucidate gene function via metabolomics. Examples of the application of this analytical strategy to specific yeast strains and single-ORF yeast deletion mutants generated through the EUROFAN programme are presented.     

A systems-level approach for metabolic engineering of yeast cell factories

The generation of novel yeast cell factories for production of high-value industrial biotechnological products relies on three metabolic engineering principles: design, construction, and analysis. In the last two decades, strong efforts have been put on developing faster and more efficient strategies and/or technologies for each one of these principles. For design and construction, three major strategies are described in this review: (1) rational metabolic engineering; (2) inverse metabolic engineering; and (3) evolutionary strategies. Independent of the selected strategy, the process of designing yeast strains involves five decision points: (1) choice of product, (2) choice of chassis, (3) identification of target genes, (4) regulating the expression level of target genes, and (5) network balancing of the target genes. At the construction level, several molecular biology tools have been developed through the concept of synthetic biology and applied for the generation of novel, engineered yeast strains. For comprehensive and quantitative analysis of constructed strains, systems biology tools are commonly used and using a multi-omics approach. Key information about the biological system can be revealed, for example, identification of genetic regulatory mechanisms and competitive pathways, thereby assisting the in silico design of metabolic engineering strategies for improving strain performance. Examples on how systems and synthetic biology brought yeast metabolic engineering closer to industrial biotechnology are described in this review, and these examples should demonstrate the potential of a systems-level approach for fast and efficient generation of yeast cell factories.     

Differentiation of industrial wine yeast strains using microsatellite markers

AIMS: To differentiate nine industrial wine strains of Saccharomyces cerevisiae using microsatellite (simple sequence repeats, SSR) markers. METHODS AND RESULTS: Six of the strains were indigenous yeasts currently used as high-density starter monocultures by the Uruguayan wine industry. Unequivocal differentiation of these six native strains and three commercial S. cerevisiae wine strains was achieved by PCR amplification and polymorphism analysis of loci containing microsatellite markers. CONCLUSION: We recommend the use of this reproducible and simple molecular method to routinely discriminate wine yeast strains. SIGNIFICANCE AND IMPACT OF THE STUDY: Microsatellites are superior to other methods for typing yeasts because the results can be exchanged as quantitative data. Knowledge of the frequencies of the alleles for different SSR markers will eventually lead to an accurate typing method to identify industrial wine yeast strains.     

Inferring Metabolic States in Uncharacterized Environments Using Gene-Expression Measurements

The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of biotechnological processes that use complex, largely uncharacterized media, such as biofuel production.     

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in (1)H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.     

Genomic characterization of Saccharomyces cerevisiae strains isolated from wine-producing areas in South America

AIMS: The wide use of yeast inoculum for wine fermentations permit the spreading of commercial Saccharomyces strains in wine areas all over the world. To study the impact of this practice on the autochthonous yeast populations it is necessary to have tools that permit the evaluation of the geographical origin of native isolates and differentiate them from commercial strains. METHODS AND RESULTS: Electrophoretic karyotyping and mitochondrial DNA restriction analysis were used to characterize the genome of native S. cerevisiae isolates associated to wine from three countries in South America. Both methods revealed differences in the genomic structure between these populations, in addition to differences between sub-populations collected in wine-producing areas in Chile. CONCLUSIONS: Our data support that molecular polymorphism analysis may be useful to evaluate the geographical origin of native isolates of yeast strains for industrial use. Furthermore, these findings are in agreement with the idea of a clonal mode of reproduction of wine yeasts in natural environments. SIGNIFICANCE AND IMPACT OF THE STUDY: This study permits the characterization of native yeast isolates in relation to their geographical origin. This procedure could be used as a tool for evaluating if a native isolate derives from the region were it was collected or if it is a strain derived from a commercial strain by microevolution.     

酵母生物多样性开发及工业应用

酵母是一类包括酿酒酵母和非常规酵母在内的多种单细胞真菌的总称,其中酿酒酵母是应用较多的重要工业微生物,广泛应用于生物医药、食品、轻工和生物燃料生产等不同生物制造领域.近年来,研究者从不同生态环境中分离了大量的酵母菌株,鉴定了多个新种,也发现了抗逆性不同以及具有多种活性产物合成能力的菌株,证明天然酵母资源具有丰富的生物多...     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.     

Exploring industrial and natural Saccharomyces cerevisiae strains for the bio-based economy from biomass: the case of bioethanol

Saccharomyces cerevisiae is the preferred microorganism for the production of bioethanol from biomass. Industrial strain development for first-generation ethanol from sugar cane and corn mostly relies on the historical know-how from high gravity beer brewing and alcohol distilleries. However, the recent design of yeast platforms for the production of second–generation biofuels and green chemicals from lignocellulose exposes yeast to different environments and stress challenges. The industrial need for increased productivity, wider substrate range utilization, and the production of novel compounds leads to renewed interest in further extending the use of current industrial strains by exploiting the immense, and still unknown, potential of natural yeast strains. This review describes key metabolic engineering strategies tailored to develop efficient industrial and novel natural yeast strains towards bioethanol production from biomass. Furthermore, it shapes how proof-of-concept studies, often advanced in academic settings on natural yeast, can be upgraded to meet the requirements for industrial applications. Academic and industrial research should continue to cooperate on both improving existing industrial strains and developing novel phenotypes by exploring the vast biodiversity available in nature on the road to establish yeast biorefineries where a range of biomass substrates are converted into valuable compounds.     

Advancing secondary metabolite biosynthesis in yeast with synthetic biology tools

Secondary metabolites are an important source of high-value chemicals, many of which exhibit important pharmacological properties. These valuable natural products are often difficult to synthesize chemically and are commonly isolated through inefficient extractions from natural biological sources. As such, they are increasingly targeted for production by biosynthesis from engineered microorganisms. The budding yeast species Saccharomyces cerevisiae has proven to be a powerful microorganism for heterologous expression of biosynthetic pathways. S. cerevisiae's usefulness as a host organism is owed in large part to the wealth of knowledge accumulated over more than a century of intense scientific study. Yet many challenges are currently faced in engineering yeast strains for the biosynthesis of complex secondary metabolite production. However, synthetic biology is advancing the development of new tools for constructing, controlling, and optimizing complex metabolic pathways in yeast. Here, we review how the coupling between yeast biology and synthetic biology is advancing the use of S. cerevisiae as a microbial host for the construction of secondary metabolic pathways.     

The value of electrophoretic fingerprinting and karyotyping in wine yeast breeding programmes

Electrophoretic banding pattens of total soluble cell proteins, DNA restriction fragments and chromosomal DNA were used to characterise ten strains ofSaccharomyces cerevisiae used for commercial production of wine. These fingerprinting procedures provided unique profiles for all the different yeast strains and can therefore be used to identify and control industrial strains. Furthermore, the protein profiles, restriction fragments banding patterns and electrophoretic karyotyping by contour clamped homogeneous electric field electrophoresis (CHEF), were valuable to differentiate hybrid and parental strains in yeast breeding programmes. Hybrid strains, with desirable oenological properties, were obtained by mass spore-cell mating between a heterothallic killer yeast and two homothallic sensitive strains and all were shown to have unique DNA fingerprints and electrophoretic karyotypes.     

Review: Ethanol production at elevated temperatures and alcohol concentrations: Part II – Use of Kluyveromyces marxianus IMB3

It is clear that only a small proportion of all micro-organisms have been isolated and identified. The simple technique of seeking a thermotolerant fermentative yeast from a suitable hot environment has yielded a number of strains. These organisms, identified as strains of Kluyveromyces marxianus var. marxianus, have been shown to have a wide range of metabolic capabilities that could be used in industrial applications. Not only have the metabolic capabilities been elucidated but possible bioreactor configurations and process application options have been investigated. It appears that there are a number of specific situations where this thermotolerant yeast could find industrial applications. A full-scale industrial ethanol production trial using this yeast was successfully carried out in India. K. marxianus IMB3's performance in terms of the ethanol concentrations achieved was comparable to that obtained using the distillery's own yeast strain with an added advantage of eliminating cooling.     

Metabolic profiling of Escherichia coli cultivations: evaluation of extraction and metabolite analysis procedures

The quantitative estimation of intracellular metabolite concentrations (metabolic profiling) is a prerequisite for a better understanding of biological processes and thus inevitable for the rational improvement of microbial production strains and process design. Since pool sizes of substrates regulate flux through different enzymes, the accurate determination of intracellular metabolite concentrations is necessary to understand in vivo reaction kinetics. Quantification of intracellular concentrations of glycolytic intermediates in Escherichia coli K12 was achieved by using a novel in situ rapid sampling and quenching procedure. A new extraction procedure using buffered hot water was established. By use of simultaneous multi-substrate feeding with various ratios of glucose, fructose and acetate during continuous cultivations several metabolic states were induced. Metabolic flux analysis and the newly developed metabolic profiling procedure were used to determine in vivo enzyme kinetics as exemplified for fructose 1,6-bisphosphate aldolase and citrate synthase.     

Different life strategies in genetic backgrounds of the Saccharomyces cerevisiae yeast cells

Changes in the natural environment require an organism to make constant adaptations enabling efficient use of environmental resources and ensuring its success in competition with other organisms. Such adaptations are expressed through various life strategies, largely determined by the rate of consumption and use of available resources, affecting the life-history traits and the related trade-offs. Allocation of available resources must take into consideration the costs of cell maintenance as well as reproduction. Given that carbon metabolism plays a crucial role in resource allocation, yeast living in different ecological niches show various life-history traits. There are a lot of data about life-history strategies in yeast living in various ecological niches; however, the question is whether different life strategies will be noted for yeast strains growing under strictly controlled conditions. Our studies based on three laboratory yeast strains representing different genetic backgrounds show that each of these strains has specified life strategies which are mainly determined by the glucose uptake rate and its intracellular usage. These results suggest that specific life strategies and related differences in the physiological and metabolic parameters of the cell are the key aspects that may explain various features of cells from different yeast strains, either industrial or laboratory.     

Rapid detection and quantification of yeast species during spontaneous wine fermentation by PCR-RFLP analysis of the rDNA ITS region

L. GRANCHI, M. BOSCO, A. MESSINI and M. VINCENZINI.1999.PCR–RFLP analysis of the rDNA–ITS (internal transcribed spacer) region was applied to 174 yeast strains belonging to 30 species of oenological significance and including 27 type strains in order to define a rapid identification protocol for yeast colonies. Dra I-or Hae III-PCR–RFLP patterns were species-specific with the exception of teleomorphic and anamorphic forms. An improved protocol taking about 30 h was used for the detection and quantification of yeast species occurring in the course of a spontaneous wine fermentation at industrial level. Wine samples were taken and plated daily on an agar medium and the developed colonies were analysed by PCR–RFLP after 24 h of incubation. A representative sample of these colonies was also identified by traditional methods. Both procedures gave identical results. However, PCR–RFLP analysis allowed a more precise enumeration of the yeast populations, proving to be a reliable and simple method for monitoring the development of the yeast community throughout wine fermentation.     

APJ1 and GRE3 homologs work in concert to allow growth in xylose in a natural Saccharomyces sensu stricto hybrid yeast

Creating Saccharomyces yeasts capable of efficient fermentation of pentoses such as xylose remains a key challenge in the production of ethanol from lignocellulosic biomass. Metabolic engineering of industrial Saccharomyces cerevisiae strains has yielded xylose-fermenting strains, but these strains have not yet achieved industrial viability due largely to xylose fermentation being prohibitively slower than that of glucose. Recently, it has been shown that naturally occurring xylose-utilizing Saccharomyces species exist. Uncovering the genetic architecture of such strains will shed further light on xylose metabolism, suggesting additional engineering approaches or possibly even enabling the development of xylose-fermenting yeasts that are not genetically modified. We previously identified a hybrid yeast strain, the genome of which is largely Saccharomyces uvarum, which has the ability to grow on xylose as the sole carbon source. To circumvent the sterility of this hybrid strain, we developed a novel method to genetically characterize its xylose-utilization phenotype, using a tetraploid intermediate, followed by bulk segregant analysis in conjunction with high-throughput sequencing. We found that this strain's growth in xylose is governed by at least two genetic loci, within which we identified the responsible genes: one locus contains a known xylose-pathway gene, a novel homolog of the aldo-keto reductase gene GRE3, while a second locus contains a homolog of APJ1, which encodes a putative chaperone not previously connected to xylose metabolism. Our work demonstrates that the power of sequencing combined with bulk segregant analysis can also be applied to a nongenetically tractable hybrid strain that contains a complex, polygenic trait, and identifies new avenues for metabolic engineering as well as for construction of nongenetically modified xylose-fermenting strains.