代谢基因工程提高作物产量的分子靶标

应用基因工程技术对植物细胞内的代谢途径进行遗传修饰,已成功地使细胞代谢发生改变或合成新的化合物。光合作用,淀粉合成,氮素同化和水分利用等是形成作物产量的基础代谢。对这些代谢途径中的关键步骤和靶分子进行基因修饰以提高作物产量的研究已取得长足的进展,并正在发展成为提高作物产量的新途径。本文着重论述应用代谢基因工程提高作物产量的技术策略,研究现状,存在的问题,所面临的挑战和应用前景。     

Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies

For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (13)CO(2) dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.     

A metabolic network stoichiometry analysis of microbial growth and product formation

Using available biochemical information, metabolic networks have been constructed to describe the biochemistry of growth of Saccharomyces cerevisiae and Candida utilis on a wide variety of carbon substrates. All networks contained only two fitted parameters, the P/O ratio and a maintenance coefficient. It is shown that with a growth-associated maintenance coefficient, K, of 1.37 mol ATP/ C-mol protein for both yeasts and P/O ratios of 1.20 and 1.53 for S. cerevisiae and C. utilis, respectively, measured biomass yields could be described accurately. A metabolic flux analysis of aerobic growth of S. cerevisiae on glucose/ethanol mixtures predicted five different metabolic flux regimes upon transition from 100% glucose to 100% ethanol. The metabolic network constructed for growth of S. cerevisiae on glucose was applied to perform a theoretical exercise on the overproduction of amino acids. It is shown that theoretical operational product yield values can be substantially lower than calculated maximum product yields. A practical case of lysine production was analyzed with respect to theoretical bottlenecks limiting product formation. Predictions of network-derived irreversibility limits for Y(sp) (mu) functions were compared with literature data. The comparisons show that in real systems such irreversibility constraints may be of relevance. It is concluded that analysis of metabolic network stoichiometry is a useful tool to detect metabolic limits and to guide process intensification studies. (c) 1995 John Wiley & Sons, Inc.     

Future research directions in plant signal transduction mechanisms

Photosynthesis is the ultimate driving force behind world food production. Modern agricultural practices have done much to maximize the benefits of photosynthesis through better land management and intensive crop breeding. However, enhancement in grain production is becoming increasingly dependent on biotechnology with every improvement becoming more difficult to achieve. With several crop species nearing the physical limits of grain production, more attention will be given to methods that enable farmers to consistently attain maximum yields. These efforts focus in part on how plants respond to the biotic and abiotic stresses that can significantly reduce potential yields, including the study of plant signal transduction pathways related to stress responses. Strong evidence is emerging that these pathways share many similarities to classical mammalian receptor systems including tyrosine-kinase receptors and G protein-coupled receptors. Several putative receptor-like proteins have been identified in maize and provide vast opportunities for studying plant signal transduction mechanisms. The elucidation of plant signaling pathways combined with modern technologies will not only serve to push harvest yields closer to the maximum theoretical levels but may also provide opportunities for actually increasing the theoretical maximum.     

Metabolic engineering of plant secondary metabolite pathways for the production of fine chemicals

The technology of large-scale plant cell culture is feasible for the industrial production of plant-derived fine chemicals. Due to low or no productivity of the desired compounds the economy is only in a few cases favorable. Various approaches are studied to increase yields, these encompass screening and selection of high producing cell lines, media optimization, elicitation, culturing of differentiated cells (organ cultures), immobilization. In recent years metabolic engineering has opened a new promising perspectives for improved production in a plant or plant cell culture.     

Biogeochemistry of selenium and its impact on food chain quality and human health

In areas where soils are low in bioavailable selenium (Se), potential Se deficiencies cause health risks for humans. Though higher plants have been considered not to require this element, the experience with low-Se soils in Finland has provided evidence that the supplementation of commercial fertilizers with sodium selenate affects positively not only the nutritive value of the whole food chain from soil to plants, animals and humans but also the quantity of plant yields. The level of Se addition has been optimal, and no abnormally high concentrations in plants or in foods of animal origin have been observed. Se levels in serum and human milk indicate that the average daily intake has been within limits considered to be safe and adequate. In fact, plants act as effective buffers, because their growth is reduced at high Se levels. They also tend to synthesize volatile compounds in order to reduce excess Se. On the other hand, when added at low concentrations, Se exerts a beneficial effect on plant growth via several mechanisms. As in humans and animals, Se strengthens the capacity of plants to counteract oxidative stress caused by oxygen radicals produced by internal metabolic or external factors. At proper levels it also delays some of the effects of senescence and may improve the utilization of short-wavelength light by plants. High additions are toxic and may trigger pro-oxidative reactions. Thus, the present supplementation of fertilizers with Se can be considered a very effective and readily controlled way to increase the average daily Se intake nationwide.     

Simple and fast alignment of metabolic pathways by exploiting local diversity

MOTIVATION: An important tool for analyzing biological networks is the ability to perform homology searches, i.e. given a pattern network one would like to be able to search for occurrences of similar (sub)networks within a set of host networks. In the context of metabolic pathways, Pinter et al. [Bioinformatics, 2005] proposed to solve this computationally hard problem by restricting it to the case where both the pattern and host networks are trees. This restriction, however, severely limits the applicability of their algorithm. RESULTS: We propose a very fast and simple algorithm for the alignment of metabolic pathways that does not restrict the topology of the host or pattern network in any way; instead, our algorithm exploits a natural property of metabolic networks that we call 'local diversity property'. Experiments on a test bed of metabolic pathways from the BioCyc database indicate that our algorithm is much faster than the restricted algorithm of Pinter et al.-the metabolic pathways of two organisms can be aligned in mere seconds-and yet has a wider range of applicability and yields new biological insights. Our ideas can likely be extended to work for the alignment of various types of biological networks other than metabolic pathways. AVAILABILITY: Our algorithm has been implemented in C++ as a user-friendly metabolic pathway alignment tool called METAPAT. The tool runs under Linux or Windows and can be downloaded at http://theinf1.informatik.uni-jena.de/metapat/     

Metabolic capabilities of Escherichia coli: I. synthesis of biosynthetic precursors and cofactors

Metabolism of living cells converts substrates into metabolic energy, redox potential and metabolic end products that are essential to maintain cellular function. The flux distribution among the various biochemical pathways is determined by the kinetic properties of enzymes which are subject to strict regulatory control. Simulation of metabolic behavior therefore requires the complete knowledge of biochemical pathways, enzyme kinetics as well as their regulation. Unfortunately, complete kinetic and regulatory information is not available for microbial cells, thus preventing accurate dynamic simulation of their metabolic behavior. However, it is possible to define wider limits on metabolic behavior based solely on flux balances of biochemical pathways. We present here comprehensive information about the catabolic pathways of the bacterium Escherichia coli. Using this biochemical database, we formulate a stoichiometric model of the bacterial network of fueling reactions. After logical structural reduction, the network consists of 53 metabolic fluxes and 30 metabolites. The solution space of this under-determined system of equations presents the bounds of metabolic flux distribution that the bacterial cell can achieve. We use specific objective functions and linear optimization to investigate the capability of E. coli catabolism to maximally produce the 12 biosynthetic precursors and three key cofactors within this solution space. For the three cofactors, the maximum yields are calculated to be 18.67 ATP, 11.6 NADH and 11 NADPH per glucose molecule, respectively. The yields of NADH and NADPH are less than 12 owing to the energy costs of importing glucose. These constraints are made explicit by the interpretation of shadow prices. The optimal yields of the 12 biosynthetic precursors are computed. Four of the 12 precursors (3-phosphoglycerate, phosphoenolpyruvate, pyruvate and oxaloacetate) can be made by E. coli with complete carbon conversion. Conversely, none of the sugar monophosphates can be made with 100% carbon conversion and analysis of the shadow prices reveals that this conversion is constrained by the energy cost of importing glucose. Three of the 12 precursors (acetyl-coA, α-ketoglutarate, and succinyl-coA) cannot be made with full carbon conversion owing to stoichiometric constraints; there is no route to these compounds without carrying out a decarboxylation reaction. Metabolite flux balances and linear optimization have thus been used to determine the catabolic capabilities of E. coli .     

Amino acid stabilization for cell-free protein synthesis by modification of the Escherichia coli genome

Cell-free biology provides a unique opportunity to assess and to manipulate microbial systems by inverse metabolic engineering. We have applied this approach to amino acid metabolism, one of the systems in cell-free biology that limits protein synthesis reactions. Four amino acids (arginine, tryptophan, serine and cysteine) are depleted during a 3-h batch cell-free protein synthesis reaction under various conditions. By modifying the genome of the Escherichia coli strain used to make the cell extract, we see significant stabilization of arginine, tryptophan and serine. Cysteine, however, continues to be degraded. Cell-free protein synthesis with the modified cell extract produces increased yields of the cysteine-free protein Outer Membrane Protein T (OmpT).     

Biogeochemistry of selenium and its impact on food chain quality and human health

In areas where soils are low in bioavailable selenium (Se), potential Se deficiencies cause health risks for humans. Though higher plants have been considered not to require this element, the experience with low-Se soils in Finland has provided evidence that the supplementation of commercial fertilizers with sodium selenate affects positively not only the nutritive value of the whole food chain from soil to plants, animals and humans but also the quantity of plant yields. The level of Se addition has been optimal, and no abnormally high concentrations in plants or in foods of animal origin have been observed. Se levels in serum and human milk indicate that the average daily intake has been within limits considered to be safe and adequate. In fact, plants act as effective buffers, because their growth is reduced at high Se levels. They also tend to synthesize volatile compounds in order to reduce excess Se. On the other hand, when added at low concentrations, Se exerts a beneficial effect on plant growth via several mechanisms. As in humans and animals, Se strengthens the capacity of plants to counteract oxidative stress caused by oxygen radicals produced by internal metabolic or external factors. At proper levels it also delays some of the effects of senescence and may improve the utilization of short-wavelength light by plants. High additions are toxic and may trigger pro-oxidative reactions. Thus, the present supplementation of fertilizers with Se can be considered a very effective and readily controlled way to increase the average daily Se intake nationwide.     

Complex physiology and compound stress responses during fermentation of alkali-pretreated corn stover hydrolysate by an Escherichia coli ethanologen

The physiology of ethanologenic Escherichia coli grown anaerobically in alkali-pretreated plant hydrolysates is complex and not well studied. To gain insight into how E. coli responds to such hydrolysates, we studied an E. coli K-12 ethanologen fermenting a hydrolysate prepared from corn stover pretreated by ammonia fiber expansion. Despite the high sugar content (～6% glucose, 3% xylose) and relatively low toxicity of this hydrolysate, E. coli ceased growth long before glucose was depleted. Nevertheless, the cells remained metabolically active and continued conversion of glucose to ethanol until all glucose was consumed. Gene expression profiling revealed complex and changing patterns of metabolic physiology and cellular stress responses during an exponential growth phase, a transition phase, and the glycolytically active stationary phase. During the exponential and transition phases, high cell maintenance and stress response costs were mitigated, in part, by free amino acids available in the hydrolysate. However, after the majority of amino acids were depleted, the cells entered stationary phase, and ATP derived from glucose fermentation was consumed entirely by the demands of cell maintenance in the hydrolysate. Comparative gene expression profiling and metabolic modeling of the ethanologen suggested that the high energetic cost of mitigating osmotic, lignotoxin, and ethanol stress collectively limits growth, sugar utilization rates, and ethanol yields in alkali-pretreated lignocellulosic hydrolysates.     

代谢工程改造解脂耶氏酵母合成植物萜类化合物的研究进展

萜类化合物是一类广泛存在于植物中的天然产物,其在食品、药品和化工等多个领域中均有广泛的用途,市场潜力巨大.因此,开发生产萜类化合物等植物天然产物可再生的微生物资源来补充甚至代替原有稀少和珍贵的植物资源,具有重要的理论意义和潜在的应用价值.解脂耶氏酵母是目前使用最广泛的非常规酵母底盘细胞之一.近年来,利用代谢工程及合成生...     

植物磷酸烯醇式丙酮酸羧化酶的功能及其在基因工程中的应用

植物磷酸烯醇式丙酮酸羧化酶(Phosphoenolpyruvate carboxylase,PEPC,EC 4.1.1.31)是广泛存在的一种细胞质酶,催化磷酸烯醇式丙酮酸(PEP)和HCO3-生成草酰乙酸(OAA),后者可转化生成三羧酸循环的多种中间产物.PEPC在植物细胞中参与植物的光合碳同化等重要代谢途径,并且在不同组织中具有多种生理功能.PEPC同时也参与调控植物种子的营养物质合成与代谢过程,控制糖类物质流向脂肪酸合成或蛋白质合成途径.以下介绍了植物PEPC的种类、蛋白质结构特点及其在植物组织中的调控方式,并重点论述了PEPC在生物基因工程中的应用方面的进展,随着对其功能机制和应用研究的深入,将有助于植物PEPC在高产优质农作物育种、能源植物和工业微生物等的开发利用等方面得到更好的发展与应用.     

不同小麦品种氮效率和产量性状的研究

对29个冬小麦品种进行子粒产量和氮效率的研究,结果表明,在氮胁迫条件下,供试小麦品种的子粒产量具有明显差异。缺氮条件下子粒产量的聚类分析结果表明,供试品种可划分为氮高效、中效和低效三类,氮高效品种在其中所占比例较少。在缺氮条件（N-）下,不同氮效率品种成熟期植株全氮含量差异不大,植株氮素积累量、氮效率（NUE）、吸收效率（UPE）和利用效率（UTE）均以氮高效品种最高,中效品种次之,低效品种最低。缺氮条件下较强的氮索吸收和利用能力是氮高效小麦品种氮胁迫条件下高氮效率的主要原因。     

Plant Interactions Alter the Predictions of Metabolic Scaling Theory

Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of −4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms’ internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than −4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.     

Exploitation of the molecular potential of plants:Equisetum arvense (EQUISETACEAE)

After a search of the literature including computerized data bases on the economic potential of various plants, experiments designed to improve the extraction of silica from the horsetailEquisetum arvense L. were carried out. Improved yields of colloidal silica were obtained by sonication in a shorter time than by conventional extraction with boiling distilled water. However we conclude that commercial exploitation of silica (colloidal or solid) fromEquisetum arvense is not feasible at present because: growing conditions of this plant species are not yet well defined; the disappearance of the plant during the winter months limits its period of exploitation; the silica content of the plant can vary over a six-fold range depending on weather and soil conditions, and so its economic potential is unpredictable.     

Omics of root-to-shoot signaling under salt stress and water deficit

Maximizing crop yield depends on the leaves receiving an optimal supply of water, mineral nutrients, small organic molecules, proteins, and hormones from the root system via the xylem. Soil drying and salinization alter these xylem fluxes, and modern omics techniques offer unparalleled opportunities to understand the complexity of these responses. Although absolute xylem concentrations of any constituent depend on the genotype and xylem sap sampling methodology, analysis of the relative changes in concentrations has revealed some conserved behavior. Typically, these stresses increase xylem concentrations of the plant hormone abscisic acid (ABA) that limits crop water loss, but decrease the concentrations of certain cytokinins that stimulate expansive growth and prevent premature leaf senescence. Further understanding of the ionic and biophysical alterations in the rhizosphere environment that cause increased xylem concentrations of the ethylene precursor (ACC) is needed. Interactions of these plant hormones with plant nutrient status and xylem nutrient delivery may be important in tuning plant responses to their environment. Xylem proteomics is an emerging area that will help understand mechanisms of plant stress adaptation. Using omics techniques to underpin rootstock-mediate plant improvement is likely to improve crop yields in dry or saline soil.     

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.