Flux balance analysis of barley seeds: a computational approach to study systemic properties of central metabolism

The accumulation of storage compounds is an important aspect of cereal seed metabolism. Due to the agronomical importance of the storage reserves of starch, protein, and oil, the understanding of storage metabolism is of scientific interest, with practical applications in agronomy and plant breeding. To get insight into storage patterning in developing cereal seed in response to environmental and genetic perturbation, a computational analysis of seed metabolism was performed. A metabolic network of primary metabolism in the developing endosperm of barley (Hordeum vulgare), a model plant for temperate cereals, was constructed that includes 257 biochemical and transport reactions across four different compartments. The model was subjected to flux balance analysis to study grain yield and metabolic flux distributions in response to oxygen depletion and enzyme deletion. In general, the simulation results were found to be in good agreement with the main biochemical properties of barley seed storage metabolism. The predicted growth rate and the active metabolic pathway patterns under anoxic, hypoxic, and aerobic conditions predicted by the model were in accordance with published experimental results. In addition, the model predictions gave insight into the potential role of inorganic pyrophosphate metabolism to maintain seed metabolism under oxygen deprivation.     

Systems rebalancing of metabolism in response to sulfur deprivation, as revealed by metabolome analysis of Arabidopsis plants

Sulfur is an essential macro-element in plant and animal nutrition. Plants assimilate inorganic sulfate into two sulfur-containing amino acids, cysteine and methionine. Low supply of sulfate leads to decreased sulfur pools within plant tissues. As sulfur-related metabolites represent an integral part of plant metabolism with multiple interactions, sulfur deficiency stress induces a number of adaptive responses, which must be coordinated. To reveal the coordinating network of adaptations to sulfur deficiency, metabolite profiling of Arabidopsis has been undertaken. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry techniques revealed the response patterns of 6,023 peaks of nonredundant ion traces and relative concentration levels of 134 nonredundant compounds of known chemical structure. Here, we provide a catalogue of the detected metabolic changes and reconstruct the coordinating network of their mutual influences. The observed decrease in biomass, as well as in levels of proteins, chlorophylls, and total RNA, gives evidence for a general reduction of metabolic activity under conditions of depleted sulfur supply. This is achieved by a systemic adjustment of metabolism involving the major metabolic pathways. Sulfur/carbon/nitrogen are partitioned by accumulation of metabolites along the pathway O-acetylserine to serine to glycine, and are further channeled together with the nitrogen-rich compound glutamine into allantoin. Mutual influences between sulfur assimilation, nitrogen imbalance, lipid breakdown, purine metabolism, and enhanced photorespiration associated with sulfur-deficiency stress are revealed in this study. These responses may be assembled into a global scheme of metabolic regulation induced by sulfur nutritional stress, which optimizes resources for seed production.     

Metabolic profiling of a mapping population exposes new insights in the regulation of seed metabolism and seed, fruit, and plant relations

To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping.     

Modification of starch metabolism in transgenic Arabidopsis thaliana increases plant biomass and triples oilseed production

We have identified a novel means to achieve substantially increased vegetative biomass and oilseed production in the model plant Arabidopsis thaliana. Endogenous isoforms of starch branching enzyme (SBE) were substituted by either one of the endosperm‐expressed maize (Zea mays L.) branching isozymes, ZmSBEI or ZmSBEIIb. Transformants were compared with the starch‐free background and with the wild‐type plants. Each of the maize‐derived SBEs restored starch biosynthesis but both morphology and structure of starch particles were altered. Altered starch metabolism in the transformants is associated with enhanced biomass formation and more‐than‐trebled oilseed production while maintaining seed oil quality. Enhanced oilseed production is primarily due to an increased number of siliques per plant whereas oil content and seed number per silique are essentially unchanged or even modestly decreased. Introduction of cereal starch branching isozymes into oilseed plants represents a potentially useful strategy to increase biomass and oilseed production in related crops and manipulate the structure and properties of leaf starch.     

The biochemistry of headgroup exchange during triacylglycerol synthesis in canola

Many pathways of primary metabolism are substantially conserved within and across plant families. However, significant differences in organization and fluxes through a reaction network may occur, even between plants in closely related genera. Assessing and understanding these differences is key to appreciating metabolic diversity, and to attempts to engineer plant metabolism for higher crop yields and desired product profiles. To better understand lipid metabolism and seed oil synthesis in canola (Brassica napus), we have characterized four canola homologues of the Arabidopsis (Arabidopsis thaliana) ROD1 gene. AtROD1 encodes phosphatidylcholine:diacylglycerol cholinephosphotransferase (PDCT), the enzyme that catalyzes a major flux of polyunsaturated fatty acids (PUFAs) in oil synthesis. Assays in yeast indicated that only two of the canola genes, BnROD1.A3 and BnROD1.C3, encode active isozymes of PDCT, and these genes are strongly expressed during the period of seed oil synthesis. Loss of expression of BnROD1.A3 and BnROD1.C3 in a double mutant, or by RNA interference, reduced the PUFA content of the oil to 26.6% compared with 32.5% in the wild type. These results indicate that ROD1 isozymes in canola are responsible for less than 20% of the PUFAs that accumulate in the seed oil compared with 40% in Arabidopsis. Our results demonstrate the care needed when translating results from a model species to crop plants.     

WBE 模型及其在生态学中的应用：研究概述

介绍了WBE模型,综述了该模型在生态学中的应用进展。WBE模型,以及以该模型为基础的MTE模型,假设生物体为自相似分形网络结构,提出代谢速率和个体大小之间存在3/4指数关系,分别预测了从个体到生物圈多个尺度上的生物属性之间的异速生长关系,而且部分得到了验证。WBE模型的应用涵盖了个体组织生物量、年生长率,种群密度和生态系统单位面积产量、能量流动率等多个方面;即使在生物圈大尺度上,WBE模型也可用来预测试验中无法直接测量的特征变量的属性,如全球碳储量的估算等。至今,关于WBE和MTE模型仍然存在各种褒贬争论,讨论焦点主要集中于模型建立的前提假设以及权度指数的预测。今后的研究工作应规范试验技术和方法,考虑物种多样性和环境等因素的影响,提出符合各类生物的模型结构体系,使其具有更广泛的应用性和预测性。     

Genotype networks,innovation, and robustness in sulfur metabolism

Background  

A metabolism is a complex network of chemical reactions. This network synthesizes multiple small precursor molecules of biomass from chemicals that occur in the environment. The metabolic network of any one organism is encoded by a metabolic genotype, defined as the set of enzyme-coding genes whose products catalyze the network's reactions. Each metabolic genotype has a metabolic phenotype. We define this metabolic phenotype as the spectrum of different sources of a chemical element that a metabolism can use to synthesize biomass. We here focus on the element sulfur. We study properties of the space of all possible metabolic genotypes in sulfur metabolism by analyzing random metabolic genotypes that are viable on different numbers of sulfur sources.     

Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism

The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species.     

Cytosolic Phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenases Affect Arabidopsis Cellular Metabolism and Promote Seed Oil Accumulation

The cytosolic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPC) catalyzes a key reaction in glycolysis, but its contribution to plant metabolism and growth are not well defined. Here, we show that two cytosolic GAPCs play important roles in cellular metabolism and seed oil accumulation. Knockout or overexpression of GAPCs caused significant changes in the level of intermediates in the glycolytic pathway and the ratios of ATP/ADP and NAD(P)H/NAD(P). Two double knockout seeds had ∼3% of dry weight decrease in oil content compared with that of the wild type. In transgenic seeds under the constitutive 35S promoter, oil content was increased up to 42% of dry weight compared with 36% in the wild type and the fatty acid composition was altered; however, these transgenic lines exhibited decreased fertility. Seed-specific overexpression lines had >3% increase in seed oil without compromised seed yield or fecundity. The results demonstrate that GAPC levels play important roles in the overall cellular production of reductants, energy, and carbohydrate metabolites and that GAPC levels are directly correlated with seed oil accumulation. Changes in cellular metabolites and cofactor levels highlight the complexity and tolerance of Arabidopsis thaliana cells to the metabolic perturbation. Further implications for metabolic engineering of seed oil production are discussed.     

Suppression of the SUGAR‐DEPENDENT1 triacylglycerol lipase family during seed development enhances oil yield in oilseed rape (Brassica napus L.)

Increasing the productivity of oilseed crops is an important challenge for plant breeders and biotechnologists. To date, attempts to increase oil production in seeds via metabolic pathway engineering have focused on boosting synthetic capacity. However, in the tissues of many organisms, it is well established that oil levels are determined by both anabolism and catabolism. Indeed, the oil content of rapeseed (Brassica napus L.) has been reported to decline by approximately 10% in the final stage of development, as the seeds desiccate. Here, we show that RNAi suppression of the SUGAR‐DEPENDENT1 triacylglycerol lipase gene family during seed development results in up to an 8% gain in oil yield on either a seed, plant or unit area basis in the greenhouse, with very little adverse impact on seed vigour. Suppression of lipolysis could therefore constitute a new method for enhancing oil yield in oilseed crops.     

On the vegetative biomass partitioning of seed plant leaves, stems, and roots

A central goal of comparative life-history theory is to derive the general rules governing growth, metabolic allocation, and biomass partitioning. Here, we use allometric theory to predict the relationships among annual leaf, stem, and root growth rates (GL, GS, and GR, respectively) across a broad spectrum of seed plant species. Our model predicts isometric scaling relationships among all three organ growth rates: GL is proportional to GS is proportional to GR. It also provides a conceptual basis for understanding the differences in the absolute amounts of biomass allocated to construct the three organ types. Analyses of a large compendium of biomass production rates across diverse seed plant species provide strong statistical support for the predictions of the theory and indicate that reproductive investments may scale isometrically with respect to vegetative organ growth rates. The general rules governing biomass allocation as indexed by the scaling exponents for organ growth rates are remarkably indifferent to plant size and taxonomic affiliation. However, the allometric "constants" for these relationships differ numerically as a function of phenotypic features and local environmental conditions. Nonetheless, at the level of both inter- and intraspecific comparisons, the same proportional biomass allocation pattern holds across extant seed plant species.     

Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber

MOTIVATION: Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood. RESULTS: We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.     

Plant acyl-CoA-binding proteins: An emerging family involved in plant development and stress responses

Acyl-CoA-binding protein (ACBP) was first identified in mammals as a neuropeptide, and was demonstrated to belong to an important house-keeping protein family that extends across eukaryotes and some prokaryotes. In plants, the Arabidopsis ACBP family consists of six AtACBPs (AtACBP1 to AtACBP6), and has been investigated using gene knock-out mutants and overexpression lines. Herein, recent findings on the AtACBPs are examined to provide an insight on their functions in various plant developmental processes, such as embryo and seed development, seed dormancy and germination, seedling development and cuticle formation, as well as their roles under various environmental stresses. The significance of the AtACBPs in acyl-CoA/lipid metabolism, with focus on their interaction with long to very-long-chain (VLC) acyl-CoA esters and their potential role in the formation of lipid droplets in seeds and vegetative tissues are discussed. In addition, recent findings on the rice ACBP family are presented. The similarities and differences between ACBPs from Arabidopsis and rice, that represent eudicot and monocot model plants, respectively, are analyzed and the evolution of plant ACBPs by phylogenetic analysis reviewed. Finally, we propose potential uses of plant ACBPs in phytoremediation and in agriculture related to the improvement of environmental stress tolerance and seed oil production.     

Evolutionary changes of metabolic networks and their biosynthetic capacities

The metabolic networks of different species show a large variety in their structural design. In this work, the evolution of functional properties of metabolism in relation with metabolic network structure is investigated. The metabolism of ancestral species is inferred from the metabolism of contemporary species using a Bayesian network model for metabolism evolution. Subsequently, these networks are analysed with the recently developed method of network expansion. This method allows for a structural analysis of metabolic networks as well as a quantification of network functions in terms of their synthesising capacities when they are provided with certain external resources. The evolutionary dynamics of one particular network function: the metabolic expansion of glucose is investigated.     

Structure and dynamics of the isoprenoid pathway network

Isoprenoids are functionally and structurally the most diverse group of plant metabolites reported to date. They can function as primary metabolites, participating in essential plant cellular processes, and as secondary metabolites, of which many have substantial commercial, pharmacological, and agricultural value. Isoprenoid end products participate in plants in a wide range of physiological processes acting in them both synergistically, such as chlorophyll and carotenoids during photosynthesis, or antagonistically, such as gibberellic acid and abscisic acid during seed germination. It is therefore expected that fluxes via isoprenoid metabolic network are tightly controlled both temporally and spatially, and that this control occurs at different levels of regulation and in an orchestrated manner over the entire isoprenoid metabolic network. In this review, we summarize our current knowledge of the topology of the plant isoprenoid pathway network and its regulation at the gene expression level following diverse stimuli. We conclude by discussing agronomical and biotechnological applications emerging from the plant isoprenoid metabolism and provide an outlook on future directions in the systems analysis of the plant isoprenoid pathway network.     

Identification of a metabolic network structure representative of Arthrospira (spirulina) platensis metabolism

A comprehensive network structure for the autotrophic growth of Arthrospira platensis is proposed. The metabolic network was built up with 121 reactions and 134 metabolites including biomass synthesis, production of a growth-associated exopolysaccharide, and energy aspects. The model supports the existence of a metabolic shunt of PEP to pyruvate through PEP carboxylase, NAD(+)-dependent malate dehydrogenase and malic enzyme to convert NADH,H(+) into NADPH,H(+). A limit in Arthrospira growth metabolism due to NADH,H(+) balancing is evidenced, explaining why the maximal light-dependent mass yield of the growth-associated exopolysaccharide was 0.51 kg EPS kg(-1) biomass, consistent with experimental results.     

Components of complex lipid biosynthetic pathways in developing castor (Ricinus communis) seeds identified by MudPIT analysis of enriched endoplasmic reticulum

Ricinoleic acid is a feedstock for nylon-11 (N11) synthesis which is currently obtained from castor (Ricinus communis) oil. Production of this fatty acid in a temperate oilseed crop is of great commercial interest, but the highest reported level in transgenic plant oils is 30%, below the 90% observed in castor and insufficient for commercial exploitation. To identify castor oil-biosynthetic enzymes and inform strategies to improve ricinoleic acid yields, we performed MudPIT analysis on endoplasmic reticulum (ER) purified from developing castor bean endosperm. Candidate enzymes for all steps of triacylglycerol synthesis were identified among 72 proteins in the data set related to complex-lipid metabolism. Previous reported proteomic data from oilseeds had not included any membrane-bound enzyme that might incorporate ricinoleic acid into oil. Analysis of enriched ER enabled determination of which protein isoforms for these enzymes were in developing castor seed. To complement this data, quantitative RT-PCR experiments with castor seed and leaf RNA were performed for orthologues of Arabidopsis oil-synthetic enzymes, determining which were highly expressed in the seed. These data provide important information for further manipulation of ricinoleic acid content in oilseeds and peptide data for future quantification strategies.     

Model‐assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom‐up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint‐based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.