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Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. alpha-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC.
The objective of this study was to investigate the effect of dietary citric acid (CA) on the performance and mineral metabolism of broiler chicks. A total of 1720 Ross PM3 broiler chicks (days old) were randomly assigned to four groups (430 in each) and reared for a period of 35 days. The diets of groups 1, 2, 3 and 4 were supplemented with 0%, 0.25%, 0.75% or 1.25% CA by weight respectively. Feed and faeces samples were collected weekly and analysed for acid insoluble ash, calcium (Ca), phosphorus (P) and magnesium (Mg). The pH was measured in feed and faeces. At the age of 28 days, 10 birds from each group were slaughtered; tibiae were collected from each bird for the determination of bone mineral density, total ash, Ca, P, Mg and bone-breaking strength, and blood was collected for the measurement of osteocalcin, serum CrossLaps (R), Ca, P, Mg and 1,25(OH)(2)Vit-D in serum. After finishing the trial on day 37, all chicks were slaughtered by using the approved procedure. Birds that were fed CA diets were heavier (average body weights of 2030, 2079 and 2086 g in the 0.25%, 0.75% and 1.25% CA groups, respectively, relative to the control birds (1986 g). Feed conversion efficiency (weight gain in g per kg of feed intake) was also higher in birds of the CA-fed groups (582, 595 and 587 g/kg feed intake for 0.25%, 0.75% and 1.25% CA respectively), relative to the control birds (565 g/kg feed intake). The digestibility of Ca, P and Mg increased in the CA-fed groups, especially for the diets supplemented with 0.25% and 0.75% CA. Support for finding was also indicated in the results of the analysis of the tibia. At slaughter, the birds had higher carcass weights and higher graded carcasses in the groups that were fed the CA diets. The estimated profit margin was highest for birds fed the diet containing 0.25% CA. Birds of the 0.75% CA group were found to have the second highest estimated profit margin. Addition of CA up to a level of 1.25% of the diet increased performance, feed conversion efficiency, carcass weight and carcass quality, but only in numerical terms. The addition of CA up to 0.75% significantly increased the digestibility of macro minerals, bone ash content, bone mineral density and bone strength of the broiler chicks. It may, therefore, be concluded that the addition of 0.75% CA in a standard diet is suitable for growth, carcass traits, macromineral digestibility and bone mineral density of broiler chicks.
The nutrition of animal consumers is an important regulator of ecological processes due to its effects on their physiology, life-history and behaviour. Understanding the ecological effects of poor nutrition depends on correctly diagnosing the nature and strength of nutritional limitation. Despite the need to assess nutritional limitation, current approaches to delineating nutritional constraints can be non-specific and imprecise. Here, we consider the need and potential to develop new complementary approaches to the study of nutritional constraints on animal consumers by studying and using a suite of established and emerging biochemical and molecular responses. These nutritional indicators include gene expression, transcript regulators, protein profiling and activity, and gross biochemical and elemental composition. The potential applications of nutritional indicators to ecological studies are highlighted to demonstrate the value that this approach would have to future studies in community and ecosystem ecology.
Ecological regime shifts and carbon cycling in aquatic systems have both been subject to increasing attention in recent years, yet the direct connection between these topics has remained poorly understood. A four-fold increase in sedimentation rates was observed within the past 50 years in a shallow eutrophic lake with no surface in-or outflows. This change coincided with an ecological regime shift involving the complete loss of submerged macrophytes, leading to a more turbid, phytoplankton-dominated state. To determine whether the increase in carbon (C) burial resulted from a comprehensive transformation of C cycling pathways in parallel to this regime shift, we compared the annual C balances (mass balance and ecosystem budget) of this turbid lake to a similar nearby lake with submerged macrophytes, a higher transparency, and similar nutrient concentrations. C balances indicated that roughly 80% of the C input was permanently buried in the turbid lake sediments, compared to 40% in the clearer macrophyte-dominated lake. This was due to a higher measured C burial efficiency in the turbid lake, which could be explained by lower benthic C mineralization rates. These lower mineralization rates were associated with a decrease in benthic oxygen availability coinciding with the loss of submerged macrophytes. In contrast to previous assumptions that a regime shift to phytoplankton dominance decreases lake heterotrophy by boosting whole-lake primary production, our results suggest that an equivalent net metabolic shift may also result from lower C mineralization rates in a shallow, turbid lake. The widespread occurrence of such shifts may thus fundamentally alter the role of shallow lakes in the global C cycle, away from channeling terrestrial C to the atmosphere and towards burying an increasing amount of C.
Maternal environmental factors can impact on the phenotype of the offspring via the induction of epigenetic adaptive mechanisms. The advanced fetal programming hypothesis proposes that maternal genetic variants may influence the offspring's phenotype indirectly via epigenetic modification, despite the absence of a primary genetic defect. To test this hypothesis, heterozygous female eNOS knockout mice and wild type mice were bred with male wild type mice. We then assessed the impact of maternal eNOS deficiency on the liver phenotype of wild type offspring. Birth weight of male wild type offspring born to female heterozygous eNOS knockout mice was reduced compared to offspring of wild type mice. Moreover, the offspring displayed a sex specific liver phenotype, with an increased liver weight, due to steatosis. This was accompanied by sex specific differences in expression and DNA methylation of distinct genes. Liver global DNA methylation was significantly enhanced in both male and female offspring. Also, hepatic parameters of carbohydrate metabolism were reduced in male and female offspring. In addition, male mice displayed reductions in various amino acids in the liver. Maternal genetic alterations, such as partial deletion of the eNOS gene, can affect liver metabolism of wild type offspring without transmission of the intrinsic defect. This occurs in a sex specific way, with more detrimental effects in females. This finding demonstrates that a maternal genetic defect can epigenetically alter the phenotype of the offspring, without inheritance of the defect itself. Importantly, these acquired epigenetic phenotypic changes can persist into adulthood.
Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data
(2017)
Recent advances in metabolomics technologies have resulted in high-quality (time-resolved) metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA) based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higherorder dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.
The highly conserved protein complex containing the Target of Rapamycin (TOR) kinase is known to integrate intra- and extra-cellular stimuli controlling nutrient allocation and cellular growth. This thesis describes three studies aimed to understand how TOR signaling pathway influences carbon and nitrogen metabolism in Chlamydomonas reinhardtii. The first study presents a time-resolved analysis of the molecular and physiological features across the diurnal cycle. The inhibition of TOR leads to 50% reduction in growth followed by nonlinear delays in the cell cycle progression. The metabolomics analysis showed that the growth repression is mainly driven by differential carbon partitioning between anabolic and catabolic processes. Furthermore, the high accumulation of nitrogen-containing compounds indicated that TOR kinase controls the carbon to nitrogen balance of the cell, which is responsible for biomass accumulation, growth and cell cycle progression. In the second study the cause of the high accumulation of amino acids is explained. For this purpose, the effect of TOR inhibition on Chlamydomonas was examined under different growth regimes using stable 13C- and 15N-isotope labeling. The data clearly showed that an increased nitrogen uptake is induced within minutes after the inhibition of TOR. Interestingly, this increased N-influx is accompanied by increased activities of nitrogen assimilating enzymes. Accordingly, it was concluded that TOR inhibition induces de-novo amino acid synthesis in Chlamydomonas. The recognition of this novel process opened an array of questions regarding potential links between central metabolism and TOR signaling. Therefore a detailed phosphoproteomics study was conducted to identify the potential substrates of TOR pathway regulating central metabolism. Interestingly, some of the key enzymes involved in carbon metabolism as well as amino acid synthesis exhibited significant changes in the phosphosite intensities immediately after TOR inhibition. Altogether, these studies provide a) detailed insights to metabolic response of Chlamydomonas to TOR inhibition, b) identification of a novel process causing rapid upshifts in amino acid levels upon TOR inhibition and c) finally highlight potential targets of TOR signaling regulating changes in central metabolism. Further biochemical and molecular investigations could confirm these observations and advance the understanding of growth signaling in microalgae.
Tre6P synthesis by TPS1 is essential for embryogenesis and postembryonic growth in Arabidopsis, and appropriate Suc signaling by Tre6P is dependent on the noncatalytic domains of TPS1. In Arabidopsis (Arabidopsis thaliana), TREHALOSE-6-PHOSPHATE SYNTHASE1 (TPS1) catalyzes the synthesis of the sucrose-signaling metabolite trehalose 6-phosphate (Tre6P) and is essential for embryogenesis and normal postembryonic growth and development. To understand its molecular functions, we transformed the embryo-lethal tps1-1 null mutant with various forms of TPS1 and with a heterologous TPS (OtsA) from Escherichia coli, under the control of the TPS1 promoter, and tested for complementation. TPS1 protein localized predominantly in the phloem-loading zone and guard cells in leaves, root vasculature, and shoot apical meristem, implicating it in both local and systemic signaling of Suc status. The protein is targeted mainly to the nucleus. Restoring Tre6P synthesis was both necessary and sufficient to rescue the tps1-1 mutant through embryogenesis. However, postembryonic growth and the sucrose-Tre6P relationship were disrupted in some complementation lines. A point mutation (A119W) in the catalytic domain or truncating the C-terminal domain of TPS1 severely compromised growth. Despite having high Tre6P levels, these plants never flowered, possibly because Tre6P signaling was disrupted by two unidentified disaccharide-monophosphates that appeared in these plants. The noncatalytic domains of TPS1 ensure its targeting to the correct subcellular compartment and its catalytic fidelity and are required for appropriate signaling of Suc status by Tre6P.
The metabolic state of an organism reflects the entire phenotype that is jointly affected by genetic and environmental changes. Due to the complexity of metabolism, system-level modelling approaches have become indispensable tools to obtain new insights into biological functions. In particular, simulation and analysis of metabolic networks using constraint-based modelling approaches have helped the analysis of metabolic fluxes. However, despite ongoing improvements in prediction of reaction flux through a system, approaches to directly predict metabolite concentrations from large-scale metabolic networks remain elusive. In this thesis, we present a computational approach for inferring concentration ranges from genome-scale metabolic models endowed with mass action kinetics. The findings specify a molecular mechanism underling facile control of concentration ranges for components in large-scale metabolic networks. Most importantly, an extended version of the approach can be used to predict concentration ranges without knowledge of kinetic parameters, provided measurements of concentrations in a reference state. We show that the approach is applicable with large-scale kinetic and stoichiometric metabolic models of organisms from different kingdoms of life. By challenging the predictions of concentration ranges in the genome-scale metabolic network of Escherichia coli with real-world data sets, we further demonstrate the prediction power and limitations of the approach. To predict concentration ranges in other species, e.g. model plant species Arabidopsis thaliana, we would rely on estimates of kinetic parameters (i.e. enzyme catalytic rates) since plant-specific enzyme catalytic rates are poorly documented. Using the constraint-based approach of Davidi et al. for estimation of enzyme catalytic rates, we obtain values for 168 plant enzymes. The approach depends on quantitative proteomics data and flux estimates obtained from constraint-based model of plant leaf metabolism integrating maximal rates of selected enzymes, plant-specific constraints on fluxes through canonical pathways, and growth measurements from Arabidopsis thaliana rosette under ten conditions. We demonstrate a low degree of plant enzyme saturation, supported by the agreement between concentrations of nicotinamide adenine dinucleotide, adenosine triphosphate, and glyceraldehyde 3-phosphate, based on our maximal in vivo catalytic rates, and available quantitative metabolomics data. Hence, our results show genome-wide estimation for plant-specific enzyme catalytic rates is feasible. These can now be readily employed to study resource allocation, to predict enzyme and metabolite concentrations using recent constrained-based modelling approaches. Constraint-based methods do not directly account for kinetic mechanisms and corresponding parameters. Therefore, a number of workflows have already been proposed to approximate reaction kinetics and to parameterize genome-scale kinetic models. We present a systems biology strategy to build a fully parameterized large-scale model of Chlamydomonas reinhardtii accounting for microcompartmentalization in the chloroplast stroma. Eukaryotic algae comprise a microcompartment, the pyrenoid, essential for the carbon concentrating mechanism (CCM) that improves their photosynthetic performance. Since the experimental study of the effects of microcompartmentation on metabolic pathways is challenging, we employ our model to investigate compartmentation of fluxes through the Calvin-Benson cycle between pyrenoid and stroma. Our model predicts that ribulose-1,5-bisphosphate, the substrate of Rubisco, and 3-phosphoglycerate, its product, diffuse in and out of the pyrenoid. We also find that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Therefore, our computational approach represents a stepping stone towards understanding of microcompartmentalized CCM in other organisms. This thesis provides novel strategies to use genome-scale metabolic networks to predict and integrate metabolite concentrations. Therefore, the presented approaches represent an important step in broadening the applicability of large-scale metabolic models to a range of biotechnological and medical applications.
Food intake is driven by the need for energy but also by the demand for essential nutrients such as protein. Whereas it was well known how diets high in protein mediate satiety, it remained unclear how diets low in protein induce appetite. Therefore, this thesis aims to contribute to the research area of the detection of restricted dietary protein and adaptive responses.
This thesis provides clear evidence that the liver-derived hormone fibroblast growth factor 21 (FGF21) is an endocrine signal of a dietary protein restriction, with the cellular amino acid sensor general control nonderepressible 2 (GCN2) kinase acting as an upstream regulator of FGF21 during protein restriction. In the brain, FGF21 is mediating the protein-restricted metabolic responses, e.g. increased energy expenditure, food intake, insulin sensitivity, and improved glucose homeostasis. Furthermore, endogenous FGF21 induced by dietary protein or methionine restriction is preventing the onset of type 2 diabetes in the New Zealand Obese mouse.
Overall, FGF21 plays an important role in the detection of protein restriction and macronutrient imbalance in rodents and humans, and mediates both the behavioral and metabolic responses to dietary protein restriction. This makes FGF21 a critical physiological signal of dietary protein restriction, highlighting the important but often overlooked impact of dietary protein on metabolism and eating behavior, independent of dietary energy content.