Computational identification of altered metabolism using gene expression and metabolic pathways

Understanding altered metabolism is an important issue because altered metabolism is often revealed as a cause or an effect in pathogenesis. It has also been shown to be an important factor in the manipulation of an organism's metabolism in metabolic engineering. Unfortunately, it is not yet possible to measure the concentration levels of all metabolites in the genome‐wide scale of a metabolic network; consequently, a method that infers the alteration of metabolism is beneficial. The present study proposes a computational method that identifies genome‐wide altered metabolism by analyzing functional units of KEGG pathways. As control of a metabolic pathway is accomplished by altering the activity of at least one rate‐determining step enzyme, not all gene expressions of enzymes in the pathway demonstrate significant changes even if the pathway is altered. Therefore, we measure the alteration levels of a metabolic pathway by selectively observing expression levels of significantly changed genes in a pathway. The proposed method was applied to two strains of Saccharomyces cerevisiae gene expression profiles measured in very high‐gravity (VHG) fermentation. The method identified altered metabolic pathways whose properties are related to ethanol and osmotic stress responses which had been known to be observed in VHG fermentation because of the high sugar concentration in growth media and high ethanol concentration in fermentation products. With the identified altered pathways, the proposed method achieved best accuracy and sensitivity rates for the Red Star (RS) strain compared to other three related studies (gene‐set enrichment analysis (GSEA), significance analysis of microarray to gene set (SAM‐GS), reporter metabolite), and for the CEN.PK 113‐7D (CEN) strain, the proposed method and the GSEA method showed comparably similar performances. Biotechnol. Bioeng. 2009;103: 835–843. © 2009 Wiley Periodicals, Inc.     

Malate synthase expression is deregulated in the Pseudomonas aeruginosa cystic fibrosis isolate FRD1

Pseudomonas aeruginosa causes chronic pulmonary infections, which can persist for decades, in patients with cystic fibrosis (CF). Current evidence suggests that the glyoxylate pathway is an important metabolic pathway for P. aeruginosa growing within the CF lung. In this study, we identified glcB, which encodes for the second key enzyme of the glyoxylate pathway, malate synthase, as a requirement for virulence of P.?aeruginosa on alfalfa seedlings. While expression of glcB in PAO1, an acute isolate of P. aeruginosa, responds to some carbon sources that use the glyoxylate pathway, expression of glcB in FRD1, a CF isolate, is constitutively upregulated. Malate synthase activity is moderately affected by glcB expression and is nearly constitutive in both backgrounds, with slightly higher activity in FRD1 than in PAO1. In addition, RpoN negatively regulates glcB in PAO1 but not in FRD1. In summary, the genes encoding for the glyoxylate-specific enzymes appear to be coordinately regulated, even though they are not located within the same operon on the P.?aeruginosa genome. Furthermore, both genes encoding for the glyoxylate enzymes can become deregulated during adaptation of the bacterium to the CF lung.     

Endogenous enzyme activities and polyamine levels in diverse rice cultivars depend on the genetic background and are not affected by the presence of the hygromycin phosphotransferase selectable marker

We used the polyamine biosynthetic pathway and rice as a relevant model to understand the genetic basis of variation in endogenous levels of metabolites and key enzymes involved in the pathway. Wild-type tissues and also tissues containing a commonly used selectable marker gene were employed. We detected a wide variation in levels of arginine decarboxylase activity and in the three polyamines, putrescine, spermidine and spermine, in different tissues and varieties, but this was not dependent on the presence of the selectable marker. A more-extensive profile of enzyme activities (ADC, ODC, SAMDC, DAO and PAO) and polyamine levels in different tissues was generated in two different varieties. Our results indicate that genetic background is important in terms of the basal levels of metabolites and enzyme activity, particularly in situations in which we aim to engineer metabolic pathways that are also encoded by homologous endogenous genes. We did not find any evidence that the presence of a selectable marker in any way influences enzyme activity or metabolite levels.     

GENETIC VARIATION IN HIF SIGNALING UNDERLIES QUANTITATIVE VARIATION IN PHYSIOLOGICAL AND LIFE‐HISTORY TRAITS WITHIN LOWLAND BUTTERFLY POPULATIONS

Oxygen conductance to the tissues determines aerobic metabolic performance in most eukaryotes but has cost/benefit tradeoffs. Here we examine in lowland populations of a butterfly a genetic polymorphism affecting oxygen conductance via the hypoxia‐inducible factor (HIF) pathway, which senses intracellular oxygen and controls the development of oxygen delivery networks. Genetically distinct clades of Glanville fritillary (Melitaea cinxia) across a continental scale maintain, at intermediate frequencies, alleles in a metabolic enzyme (succinate dehydrogenase, SDH) that regulates HIF‐1α. One Sdhd allele was associated with reduced SDH activity rate, twofold greater cross‐sectional area of tracheoles in flight muscle, and better flight performance. Butterflies with less tracheal development had greater post‐flight hypoxia signaling, swollen & disrupted mitochondria, and accelerated aging of flight metabolic performance. Allelic associations with metabolic and aging phenotypes were replicated in samples from different clades. Experimentally elevated succinate in pupae increased the abundance of HIF‐1α and expression of genes responsive to HIF activation, including tracheal morphogenesis genes. These results indicate that the hypoxia inducible pathway, even in lowland populations, can be an important axis for genetic variation underlying intraspecific differences in oxygen delivery, physiological performance, and life history.     

Profiling the metabolic proteome of bovine mammary tissue

2-DE and MALDI mass fingerprinting were used to analyse mammary tissue from lactating Friesian cows. The goal was detection of enzymes in metabolic pathways for synthesis of milk molecules including fatty acids and lactose. Of 418 protein spots analysed by PMF, 328 were matched to database sequences, resulting in 215 unique proteins. We detected 11 out of the 15 enzymes in the direct pathways for conversion of glucose to fatty acids, two of the pentose phosphate pathway enzymes and two of the enzymes for lactose synthesis from glucose. We did not detect enzymes that catalyse the first three reactions of glycolysis. Our results are typical of enzyme detection using 2-DE of mammalian tissues. We therefore advocate caution when relating enzyme abundances measured by 2-DE to metabolic output as not all relevant proteins are detected. 2-D DIGE was used to measure interindividual variation in enzyme abundance from eight animals. We extracted relative protein abundances from 2-D DIGE data and used a logratio transformation that is appropriate for compositional data of the kind represented in many proteomics experiments. Coefficients of variation for abundances of detected enzymes were 3-8%. We recommend use of this transformation for DIGE and other compositional data.     

Genetic variation and correlations between genotype and locomotor physiology in outbred laboratory house mice (Mus domesticus).

Laboratory strains of house mice (Mus domesticus) are increasingly used as model organisms in evolutionary physiology, so information on levels of genetic variation is important. For example, are levels of genetic variation comparable to those found in populations of wild house mice? We studied allozymes to estimate genetic variation in outbred Hsd:ICR mice, which have been used in several studies with evolutionary emphasis. The physiological significance of allozyme variation remains obscure. Several workers have reported relationships between multi-locus heterozygosity and metabolic traits, but endotherms have not been studied. Therefore, we also measured mice for basal metabolic rate (BMR), maximal oxygen consumption during forced treadmill exercise (VO2max), and 12 other traits related to locomotor physiology, before genotyping them for 10 allozyme loci. Four of these loci were polymorphic, all were in Hardy-Weinberg equilibrium, and inbreeding coefficients were not significantly different from zero. Average heterozygosities were 11%, similar to values reported for wild populations of house mice. Fourteen percent of the associations between single-locus genotype and physiological traits were statistically significant. Multi-locus heterozygosity was not significantly related to VO2max, but was positively correlated with BMR, a result opposite to the negative correlation between standard metabolic rate and heterozygosity reported in many ectotherms. Therefore, the proposed mechanisms for the effect of multi-locus heterozygosity on metabolic rate in ectotherms may not apply to endotherms.     

Total cell protein concentration as an evolutionary constraint on the metabolic control distribution in cells.

Cell protein occupies 15-35% of cell volume. This level is argued to be the maximum compatible with cell function. Because of this constraint, selection pressure during evolution is likely to have maximized pathway fluxes for minimum total protein level. Pathways optimized in this way are shown to have the following characteristics: (1) the "simple" flux control coefficients of all enzymes are equal, (2) the normal flux control coefficients depend on the relative kinetic constants of the enzymes, such that enzymes with low specific activity are present at relatively high levels and have high flux control, (3) the normal flux control coefficients are proportional to enzyme levels. A single rate limiting step located at the first step in a pathway is likely to be inefficient in terms of protein levels, and the major metabolic pathways are therefore expected to have control distributed throughout the pathway. This has important implications for metabolic control.     

Mapping determinants of variation in energy metabolism, respiration and flight in Drosophila

We employed quantitative trait locus (QTL) mapping to dissect the genetic architecture of a hierarchy of functionally related physiological traits, including metabolic enzyme activity, metabolite storage, metabolic rate, and free-flight performance in recombinant inbred lines of Drosophila melanogaster. We identified QTL underlying variation in glycogen synthase, hexokinase, phosphoglucomutase, and trehalase activity. In each case variation mapped away from the enzyme-encoding loci, indicating that trans-acting regions of the genome are important sources of variation within the metabolic network. Individual QTL associated with variation in metabolic rate and flight performance explained between 9 and 35% of the phenotypic variance. Bayesian QTL analysis identified epistatic effects underlying variation in flight velocity, metabolic rate, glycogen content, and several metabolic enzyme activities. A region on the third chromosome was associated with expression of the glucose-6-phosphate branchpoint enzymes and with metabolic rate and flight performance. These genomic regions are of special interest as they may coordinately regulate components of energy metabolism with effects on whole-organism physiological performance. The complex biochemical network is encoded by an equally complex network of interacting genetic elements with potentially pleiotropic effects. This has important consequences for the evolution of performance traits that depend upon these metabolic networks.     

Prediction of missing enzyme genes in a bacterial metabolic network. Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa

The metabolic network is an important biological network which consists of enzymes and chemical compounds. However, a large number of metabolic pathways remains unknown, and most organism-specific metabolic pathways contain many missing enzymes. We present a novel method to identify the genes coding for missing enzymes using available genomic and chemical information from bacterial genomes. The proposed method consists of two steps: (a) estimation of the functional association between the genes with respect to chromosomal proximity and evolutionary association, using supervised network inference; and (b) selection of gene candidates for missing enzymes based on the original candidate score and the chemical reaction information encoded in the EC number. We applied the proposed methods to infer the metabolic network for the bacteria Pseudomonas aeruginosa from two genomic datasets: gene position and phylogenetic profiles. Next, we predicted several missing enzyme genes to reconstruct the lysine-degradation pathway in P. aeruginosa using EC number information. As a result, we identified PA0266 as a putative 5-aminovalerate aminotransferase (EC 2.6.1.48) and PA0265 as a putative glutarate semialdehyde dehydrogenase (EC 1.2.1.20). To verify our prediction, we conducted biochemical assays and examined the activity of the products of the predicted genes, PA0265 and PA0266, in a coupled reaction. We observed that the predicted gene products catalyzed the expected reactions; no activity was seen when both gene products were omitted from the reaction.     

Muscle fibres: applications for the study of the metabolic consequences of enzyme deficiencies in skeletal muscle

Mitochondrial function in saponin-permeabilized muscle fibres can be studied by high-resolution respirometry, laser-excited fluorescence spectroscopy and fluorescence microscopy. We applied these techniques to study metabolic effects of changes in the pattern of mitochondrial enzymes in skeletal muscle of patients with chronic progressive external ophthalmoplegia or Kearns-Sayre syndrome harbouring large-scale deletions of mitchondrial DNA (mtDNA). In all patients combined deficiencies of respiratory chain enzymes containing mitochondrially encoded subunits were observed. The citrate synthase-normalized activity ratios of these enzymes decreased linearly with increasing mtDNA heteroplasmy. This indicates the absence of any well-defined mutation thresholds for mitochondrial enzyme activities in the entire skeletal muscle. We applied metabolic control analysis to perform a quantitative estimation of the metabolic influence of the observed enzyme deficiencies. For patients with degrees of mtDNA heteroplasmy below about 60% we observed at almost normal maximal rates of respiration an increase in flux control coefficients of complexes I and IV. Permeabilized skeletal-muscle fibres of patients with higher degrees of mtDNA heteroplasmy and severe enzyme deficiencies exhibited additionally decreased maximal rates of respiration. This finding indicates the presence of a 'metabolic threshold' which can be assessed by functional studies of muscle fibres providing the link to the phenotypic expression of the mtDNA mutation in skeletal muscle.     

Predicting the adaptive evolution of Thermoanaerobacterium saccharolyticum

A fully evolved metabolic network can be described as a weighted sum of elementary modes where the usage probabilities of modes are distributed according to the Boltzmann distribution law (Srienc and Unrean, 2010). An organism presumably achieves the fully evolved state through adaptive changes in the kinetics of rate-controlling enzymes. Metabolic control analysis identifies reactions catalyzed by such enzymes. Comparison of the experimentally determined metabolic flux distributions of Thermoanaerobacterium saccharolyticum AS411 with the predicted flux distribution of a fully evolved metabolic network identified phosphoglucose isomerase (PGI) as the enzyme with the greatest flux control, the rate-controlling enzyme. The analysis predicts that an increased activity of PGI would enable the metabolic network to approach the fully evolved state and result in a faster specific growth rate. The prediction was confirmed by experimental results that showed an increased specific activity of PGI in a culture of strain AS411 that adaptively evolved over 280 generations. Sequencing of the gene confirmed the occurrence of a group of mutations clustered in the subunit binding domain of the dimeric enzyme. The results indicate that the evolutionary path is predictable as the strain AS411 adapted toward the fully evolved state by increasing the PGI activity. This experimental finding confirms that enzymes with predicted highest metabolic flux control are the targets of adaptive metabolic pathway evolution.     

Control of the flux in the arginine pathway of Neurospora crassa. Modulations of enzyme activity and concentration.

The influence of particular enzyme activities on the flux of metabolites in a pathway can be estimated by 'modulating' enzymes (i.e. changing turnover or concentration) and measuring the response in various parts of the system. By controlling the nuclear ration of two genetically different nuclear types in heterokaryons, the enzyme concentrations at four different steps in the arginine pathway were decreased over a range. This range was extended by the use of bradytrophs, mutant strains specifying enzymes with greatly diminished enzyme activities. Strains altered simultaneously at more than one step were also constructed by genetic recombination. By measuring the outputs of the pathway and the steady-state concentrations of intermediate pools, the fluxes in different parts of the pathway were calculated. This allowed the construction of flux/enzyme relationships, the slope of which is a measure of the sensitivity of a flux to the change in enzyme activity at that step. All fluxes were found to be considerably buffered for quite substantial decreases in the activities of all enzymes. Mass action plays an important part in this phenomenon, as do inhibition and repression. Because of the existence of expansion fluxes in growing systems, we find quantitatively different fluxes in different parts of the single pathway. For the same reason some enzyme modulations given decreased fluxes in one part and increased fluxes in another. The understanding of control in the pathway thus involves consideration of many mechanisms operating simultaneously and the estimation of changes in the whole system. The concept of a 'rate-limiting step' is found to be inadequate and is replaced by a quantitative measure, the Sensitivity Coefficient, which takes account of all the interactions. It is shown that control of the flux is shared among all the enzymes of the pathway. The results are discussed in terms of the theory of flux control.     

Genes encoding hub and bottleneck enzymes of the Arabidopsis metabolic network preferentially retain homeologs through whole genome duplication

Background

Whole genome duplication (WGD) occurs widely in angiosperm evolution. It raises the intriguing question of how interacting networks of genes cope with this dramatic evolutionary event.

Results

In study of the Arabidopsis metabolic network, we assigned each enzyme (node) with topological centralities (in-degree, out-degree and between-ness) to measure quantitatively their centralities in the network. The Arabidopsis metabolic network is highly modular and separated into 11 interconnected modules, which correspond well to the functional metabolic pathways. The enzymes with higher in-out degree and between-ness (defined as hub and bottleneck enzymes, respectively) tend to be more conserved and preferentially retain homeologs after WGD. Moreover, the simultaneous retention of homeologs encoding enzymes which catalyze consecutive steps in a pathway is highly favored and easily achieved, and enzyme-enzyme interactions contribute to the retention of one-third of WGD enzymes.

Conclusions

Our analyses indicate that the hub and bottleneck enzymes of metabolic network obtain great benefits from WGD, and this event grants clear evolutionary advantages in adaptation to different environments.     

Heritability,Environmental Effects,and Genetic and Phenotypic Correlations of Oxidative Stress Resistance-Related Enzyme Activities During Early Life Stages in Atlantic Salmon

Oxidative stress (OS) may pose important physiological constraints on individuals, affecting trade-offs between growth and reproduction or ageing and survival. Despite such evolutionary and ecological importance, the results from studies on the magnitude of individual variation in OS resistance and the underlying causes of this variation such as genetic, environmental, and maternal origins, remain inconclusive. Using a high throughput methodology, we investigated the activity levels in three OS resistance-related enzymes (superoxide dismutase, SOD; glutathione reductase, GR; glutathione S-transferase, GST) during the early life stages of 1000 individuals from 50 paternal half-sib families in two populations of Atlantic salmon. Using animal mixed models, we detected the presence of narrow-sense heritability for SOD and GST; that for GST differed between populations due to differences in environmental variance. We found support for the presence of common environmental variation, including maternal effects, for only GR. Using a bivariate animal model, we detected a positive environmental correlation between activity levels of SOD and GST but were unable to detect an additive genetic correlation. Our results complement previous heritability findings for levels of reactive oxygen species or OS resistance by demonstrating the presence of heritability for OS-related enzyme activities. Our findings provide a foundation for future work, such as investigations on the evolutionary importance of variation in enzyme activities. In addition, our findings emphasise the importance of accounting for developmental stage, environmental variance, and kin relationships when investigating the OS-response at the enzyme activity level.     

Maltose metabolism in the hyperthermophilic archaeon Thermococcus litoralis: purification and characterization of key enzymes.

Maltose metabolism was investigated in the hyperthermophilic archaeon Thermococcus litoralis. Maltose was degraded by the concerted action of 4-alpha-glucanotransferase and maltodextrin phosphorylase (MalP). The first enzyme produced glucose and a series of maltodextrins that could be acted upon by MalP when the chain length of glucose residues was equal or higher than four, to produce glucose-1-phosphate. Phosphoglucomutase activity was also detected in T. litoralis cell extracts. Glucose derived from the action of 4-alpha-glucanotransferase was subsequently metabolized via an Embden-Meyerhof pathway. The closely related organism Pyrococcus furiosus used a different metabolic strategy in which maltose was cleaved primarily by the action of an alpha-glucosidase, a p-nitrophenyl-alpha-D-glucopyranoside (PNPG)-hydrolyzing enzyme, producing glucose from maltose. A PNPG-hydrolyzing activity was also detected in T. litoralis, but maltose was not a substrate for this enzyme. The two key enzymes in the pathway for maltose catabolism in T. litoralis were purified to homogeneity and characterized; they were constitutively synthesized, although phosphorylase expression was twofold induced by maltodextrins or maltose. The gene encoding MalP was obtained by complementation in Escherichia coli and sequenced (calculated molecular mass, 96,622 Da). The enzyme purified from the organism had a specific activity for maltoheptaose, at the temperature for maximal activity (98 degrees C), of 66 U/mg. A Km of 0.46 mM was determined with heptaose as the substrate at 60 degrees C. The deduced amino acid sequence had a high degree of identity with that of the putative enzyme from the hyperthermophilic archaeon Pyrococcus horikoshii OT3 (66%) and with sequences of the enzymes from the hyperthermophilic bacterium Thermotoga maritima (60%) and Mycobacterium tuberculosis (31%) but not with that of the enzyme from E. coli (13%). The consensus binding site for pyridoxal 5'-phosphate is conserved in the T. litoralis enzyme.