Strategies for the Genetic Manipulation of Saccharomyces cerevisiae

Abstract

The budding yeast Saccharomyces cerevisiae is now widely used as a model organism in the study of gene structure, function, and regulation in addition to its more traditional use as a workhorse of the brewing and baking industries. In this article the plethora of methods available for manipulating the genome of S. cerevisiae are reviewed. This will include a discussion of methods for manipulating individual genes and whole chromosomes, and will address both classic genetic and recombinant DNA-based methods. Furthermore, a critical evaluation of the various genetic strategies for genetically manipulating this simple eukaryote will be included, highlighting the requirements of both the new and the more traditional biotechnology industries.     

酿酒酵母生产羧酸的代谢工程策略

羧酸广泛地应用于食品、医药和化工等行业,具有广阔的市场前景.作为真核模式微生物,酿酒酵母作为代谢工程平台用来生产有机酸具有明显优势.本文论述了酿酒酵母生产重要羧酸的策略:首先构建一条能够和糖酵解途径相连接的高效的重要羧酸积累途径,进而探讨如何将碳代谢流由乙醇转向目的产物,在此基础上研究有机酸的转运及涉及到的能量问题.最后,对当前研究存在的问题进行了分析,并对未来研究方向进行了展望.     

Yeast as factory and factotum

After centuries of vigorous activity in making fine wines, beers and breads, Saccharomyces cerevisiae is now acquiring a rich new portfolio of skills, bestowed by genetic manipulation. As shown in a recent shop-window of research supported by the European Commission, yeasts will soon be benefiting industries as diverse as fish farming, pharmaceuticals and laundering.     

植物脂肪酸代谢途径遗传调控的研究进展

目前,利用传统育种方法改良油料作物脂肪酸组分已取得巨大成功,通过有性杂交、X-射线或EMS处理等方法都可用来修饰存在于油菜中脂肪酸的性质。国外已培育出高棕榈酸、高或低亚油酸、高油酸和无芥酸的油菜品种。但由于油料作物基因池(Gene Pool)的局限性使得育种学家不得不寻找其他种质资源。随着基因克隆和遗传转化技术的进步,通过基因工程改良油料作物品质已成可能。本文主要介绍了植物脂肪酸的代谢途径以及通过操纵TAG的生物合成来改变油的成分等研究,其中主要包括脂肪酸链长度的改良、饱和度改良、增加脂肪酸含量以及新的不饱和脂肪酸的改良等方面。不久的将来,转基因油料作物中将会产生更有价值的脂肪酸造福于人类。     

Genetic Dissection of Histone Function

Mutational analysis is an essential tool for understanding the functions of genes within a living organism. The budding yeastSaccharomyces cerevisiaeprovides an excellent model system for dissecting the genetics of histone function at the molecular and cellular levels. A simple gene organization, plus a wide variety of genetic strategies, makes it possible to directly manipulate a specific histone genein vitroand then examine the expression of mutant allelesin vivo.Recent methods for manipulating the yeast histone genes have been designed to facilitate both site-directed analysis of structure/function relationships and unbiased screens targeted at specific functional pathways. The conservation of histone and nucleosome structure throughout evolution means that the principles discovered through genetic studies in yeast will be broadly applicable to the chromatin of more complex eukaryotes.     

Transformation of Saccharomyces cerevisiae and other fungi: methods and possible underlying mechanism

Transformation (i.e., genetic modification of a cell by the incorporation of exogenous DNA) is indispensable for manipulating fungi. Here, we review the transformation methods for Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans, Pichia pastoris and Aspergillus species and discuss some common modifications to improve transformation efficiency. We also present a model of the mechanism underlying S. cerevisiae transformation, based on recent reports and the mechanism of transfection in mammalian systems. This model predicts that DNA attaches to the cell wall and enters the cell via endocytotic membrane invagination, although how DNA reaches the nucleus is unknown. Polyethylene glycol is indispensable for successful transformation of intact cells and the attachment of DNA and also possibly acts on the membrane to increase the transformation efficiency. Both lithium acetate and heat shock, which enhance the transformation efficiency of intact cells but not that of spheroplasts, probably help DNA to pass through the cell wall.     

Genetic conservation: our evolutionary responsibility

The conservation of the crop varieties of traditional agriculture in the centers of genetic diversity is essential to provide genetic resources for plant improvement. These resources are acutely threatened by rapid agricultural development which is essential for the welfare of millions. Methodologies for genetic conservation have been worked out which are both effective and economical. Urgent action is needed to collect and preserve irreplaceable genetic resources.

Wild species, increasingly endangered by loss of habitats, will depend on organized protection for their survival. On a long term basis this is feasible only within natural communities in a state of continuing evolution, hence there is an urgent need for exploration and clarification of the genetic principles of conservation. Gene pools of wild species are increasingly needed for various uses, from old and new industries to recreation. But the possibility of a virtual end to the evolution of species of no direct use to man raises questions of responsibility and ethics.

     

代谢改造酿酒酵母合成萜类化合物的研究进展

萜类化合物是一类种类繁多、功能多样的化合物,部分具有抗癌、增强免疫力等作用,具有良好的生物活性,在食品、保健品以及医疗等领域应用广泛。近年来,随着对萜类化合物生物合成途径研究的深入,研究人员采用代谢工程手段构建了多种萜类产物的高产酿酒酵母工程菌株,部分已经达到或者接近工业化生产水平。因此,采用合成生物学相关技术手段合成萜类化合物,有望取代化学合成或者传统的提取模式,成为天然萜类产物的新型生产方法。文中以常见的几种萜类产物为例,介绍并探讨萜类产物的生物合成策略以及合成生物学方面的研究进展。     

Whole-genome comparison reveals novel genetic elements that characterize the genome of industrial strains of Saccharomyces cerevisiae

Human intervention has subjected the yeast Saccharomyces cerevisiae to multiple rounds of independent domestication and thousands of generations of artificial selection. As a result, this species comprises a genetically diverse collection of natural isolates as well as domesticated strains that are used in specific industrial applications. However the scope of genetic diversity that was captured during the domesticated evolution of the industrial representatives of this important organism remains to be determined. To begin to address this, we have produced whole-genome assemblies of six commercial strains of S. cerevisiae (four wine and two brewing strains). These represent the first genome assemblies produced from S. cerevisiae strains in their industrially-used forms and the first high-quality assemblies for S. cerevisiae strains used in brewing. By comparing these sequences to six existing high-coverage S. cerevisiae genome assemblies, clear signatures were found that defined each industrial class of yeast. This genetic variation was comprised of both single nucleotide polymorphisms and large-scale insertions and deletions, with the latter often being associated with ORF heterogeneity between strains. This included the discovery of more than twenty probable genes that had not been identified previously in the S. cerevisiae genome. Comparison of this large number of S. cerevisiae strains also enabled the characterization of a cluster of five ORFs that have integrated into the genomes of the wine and bioethanol strains on multiple occasions and at diverse genomic locations via what appears to involve the resolution of a circular DNA intermediate. This work suggests that, despite the scrutiny that has been directed at the yeast genome, there remains a significant reservoir of ORFs and novel modes of genetic transmission that may have significant phenotypic impact in this important model and industrial species.     

Discovering relational-based association rules with multiple minimum supports on microarray datasets

MOTIVATION: Association rule analysis methods are important techniques applied to gene expression data for finding expression relationships between genes. However, previous methods implicitly assume that all genes have similar importance, or they ignore the individual importance of each gene. The relation intensity between any two items has never been taken into consideration. Therefore, we proposed a technique named REMMAR (RElational-based Multiple Minimum supports Association Rules) algorithm to tackle this problem. This method adjusts the minimum relation support (MRS) for each gene pair depending on the regulatory relation intensity to discover more important association rules with stronger biological meaning. RESULTS: In the actual case study of this research, REMMAR utilized the shortest distance between any two genes in the Saccharomyces cerevisiae gene regulatory network (GRN) as the relation intensity to discover the association rules from two S.cerevisiae gene expression datasets. Under experimental evaluation, REMMAR can generate more rules with stronger relation intensity, and filter out rules without biological meaning in the protein-protein interaction network (PPIN). Furthermore, the proposed method has a higher precision (100%) than the precision of reference Apriori method (87.5%) for the discovered rules use a literature survey. Therefore, the proposed REMMAR algorithm can discover stronger association rules in biological relationships dissimilated by traditional methods to assist biologists in complicated genetic exploration.     

Conserved rules govern genetic interaction degree across species

ABSTRACT: BACKGROUND: Synthetic genetic interactions have recently been mapped on a genome scale in the budding yeast Saccharomyces cerevisiae, providing a functional view of the central processes of eukaryotic life. Currently, comprehensive genetic interaction networks have not been determined for other species, and we therefore sought to model conserved aspects of genetic interaction networks in order to enable the transfer of knowledge between species. RESULTS: Using a combination of physiological and evolutionary properties of genes, we built models that successfully predicted the genetic interaction degree of S. cerevisiae genes. Importantly, a model trained on S. cerevisiae gene features and degree also accurately predicted interaction degree in the fission yeast Schizosaccharomyces pombe, suggesting that many of the predictive relationships discovered in S. cerevisiae also hold in this evolutionarily distant yeast. In both species, high single mutant fitness defect, protein disorder, pleiotropy, protein-protein interaction network degree, and low expression variation were significantly predictive of genetic interaction degree. A comparison of the predicted genetic interaction degrees of S. pombe genes to the degrees of S. cerevisiae orthologs revealed functional rewiring of specific biological processes that distinguish these two species. Finally, predicted differences in genetic interaction degree were independently supported by differences in co-expression relationships of the two species. CONCLUSIONS: Our findings show that there are common relationships between gene properties and genetic interaction network topology in two evolutionarily distant species. This conservation allows use of the extensively mapped S. cerevisiae genetic interaction network as an orthology-independent reference to guide the study of more complex species.     

Genetic Characterization of Pathogenic Saccharomyces Cerevisiae Isolates

Saccharomyces cerevisiae isolates from human patients have been genetically analyzed. Some of the characteristics of these isolates are very different from laboratory and industrial strains of S. cerevisiae and, for this reason, stringent genetic tests have been used to confirm their identity as S. cerevisiae. Most of these clinical isolates are able to grow at 42°, a temperature that completely inhibits the growth of most other S. cerevisiae strains. This property can be considered a virulence trait and may help explain the presence of these isolates in human hosts. The ability to grow at 42° is shown to be polygenic with primarily additive effects between loci. S. cerevisiae will be a useful model for the evolution and genetic analysis of fungal virulence and the study of polygenic traits.     

Protein complexes are central in the yeast genetic landscape

If perturbing two genes together has a stronger or weaker effect than expected, they are said to genetically interact. Genetic interactions are important because they help map gene function, and functionally related genes have similar genetic interaction patterns. Mapping quantitative (positive and negative) genetic interactions on a global scale has recently become possible. This data clearly shows groups of genes connected by predominantly positive or negative interactions, termed monochromatic groups. These groups often correspond to functional modules, like biological processes or complexes, or connections between modules. However it is not yet known how these patterns globally relate to known functional modules. Here we systematically study the monochromatic nature of known biological processes using the largest quantitative genetic interaction data set available, which includes fitness measurements for ～5.4 million gene pairs in the yeast Saccharomyces cerevisiae. We find that only 10% of biological processes, as defined by Gene Ontology annotations, and less than 1% of inter-process connections are monochromatic. Further, we show that protein complexes are responsible for a surprisingly large fraction of these patterns. This suggests that complexes play a central role in shaping the monochromatic landscape of biological processes. Altogether this work shows that both positive and negative monochromatic patterns are found in known biological processes and in their connections and that protein complexes play an important role in these patterns. The monochromatic processes, complexes and connections we find chart a hierarchical and modular map of sensitive and redundant biological systems in the yeast cell that will be useful for gene function prediction and comparison across phenotypes and organisms. Furthermore the analysis methods we develop are applicable to other species for which genetic interactions will progressively become more available.     

Replicative and chronological aging in Saccharomyces cerevisiae

Saccharomyces cerevisiae has directly or indirectly contributed to the identification of arguably more mammalian genes that affect aging than any other model organism. Aging in yeast is assayed primarily by measurement of replicative or chronological life span. Here, we review the genes and mechanisms implicated in these two aging model systems and key remaining issues that need to be addressed for their optimization. Because of its well-characterized genome that is remarkably amenable to genetic manipulation and high-throughput screening procedures, S. cerevisiae will continue to serve as a leading model organism for studying pathways relevant to human aging and disease.     

Genetic programming of polynomial harmonic networks using the discrete Fourier transform

This paper presents a genetic programming system that evolves polynomial harmonic networks. These are multilayer feed-forward neural networks with polynomial activation functions. The novel hybrids assume that harmonics with non-multiple frequencies may enter as inputs the activation polynomials. The harmonics with non-multiple, irregular frequencies are derived analytically using the discrete Fourier transform. The polynomial harmonic networks have tree-structured topology which makes them especially suitable for evolutionary structural search. Empirical results show that this hybrid genetic programming system outperforms an evolutionary system manipulating polynomials, the traditional Koza-style genetic programming, and the harmonic GMDH network algorithm on processing time series.     

The early bird catches the worm: new technologies for the Caenorhabditis elegans toolkit

The inherent simplicity of Caenorhabditis elegans and its extensive genetic toolkit make it ideal for studying complex biological processes. Recent developments further increase the usefulness of the worm, including new methods for: altering gene expression, altering physiology using optogenetics, manipulating large numbers of worms, automating laborious processes and processing high-resolution images. These developments both enhance the worm as a model for studying processes such as development and ageing and make it an attractive model in areas such as neurobiology and behaviour.     

Cloning and expression of the 3-isopropylmalate dehydrogenase gene from Candida albicans

Abstract A variety of Saccharomyces cerevisiae genes e.g. HIS3, LEU2, TRP1, URA3 , are expressed in Escherichia coli and have been isolated by complementation of mutations in the corresponding E. coli genes [1]. The LEU2 gene was one of the first S. cerevisiae genes to be isolated in this way [2], and its isolation led to the development of transformation systems for S. cerevisiae [3,4]. The leuB gene in E. coli [5] and the LEU2 gene in S. cerevisiae [6] both code for 3-isopropylmalate dehydrogenase (3-IMDH; EC 1.1.1.85) which is essential for the biosynthesis of leucine in both organisms. This paper describes the cloning of a fragment of C. albicans DNA carrying the gene for 3-IMDH which will be useful in the development of transformation methods in C. albicans .     

Emerging technologies for gene manipulation in Drosophila melanogaster

The popularity of Drosophila melanogaster as a model for understanding eukaryotic biology over the past 100 years has been accompanied by the development of numerous tools for manipulating the fruitfly genome. Here we review some recent technologies that will allow Drosophila melanogaster to be manipulated more easily than any other multicellular organism. These developments include the ability to create molecularly designed deletions, improved genetic mapping technologies, strategies for creating targeted mutations, new transgenic approaches and the means to clone and modify large fragments of DNA.     

The spatial scale of genetic differentiation in a model organism: the wild yeast Saccharomyces paradoxus

Little information is presently available on the factors promoting genetic divergence in eukaryotic microbes. We studied the spatial distribution of genetic variation in Saccharomyces paradoxus, the wild relative of Saccharomyces cerevisiae, from the scale of a few centimetres on individual oak trees to thousands of kilometers across different continents. Genealogical analysis of six loci shows that isolates from Europe form a single recombining population, and within this population genetic differentiation increases with physical distance. Between different continents, strains are more divergent and genealogically independent, indicating well-differentiated lineages that may be in the process of speciation. Such replicated populations will be useful for studies in population genomics.