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Plant growth and survival depend on photosynthesis in the leaves. This involves the uptake of carbon dioxide from the atmosphere and the simultaneous capture of light energy to produce organic molecules, which enter metabolism and are converted to many other compounds which then serve as building blocks for biomass growth. Leaves are organs specialised for photosynthetic carbon dioxide fixation. The function of leaves involves many trade-offs which must be optimised in order to achieve effective use of resources and maximum photosynthesis. It is known that the morphology of leaves adjusts to the growth environment of plants and this is important for optimising their function for photosynthesis. However, it is unclear how this adjustment is regulated. The general aim of the work presented in this thesis is to understand how leaf growth and morphology are regulated in the model species Arabidopsis thaliana. Special attention was dedicated to the possibility that there might be internal metabolic signals within the plant which affect the growth and development of leaves. In order to investigate this question, leaf growth and development must be considered beyond the level of the single organ and in the context of the whole plant because leaves do not grow autonomously but depend on resources and regulatory influences delivered by the rest of the plant. Due to the complexity of this question, three complementary approaches were taken. In the first and most specific approach it was asked whether a proposed down-stream component of sucrose signalling, trehalose-6-phosphate (Tre-6-P), might influence leaf development and growth. To investigate this question, transgenic Arabidopsis lines with perturbed levels of Tre-6-P were generated using the constitutive 35S promoter to express bacterial enzymes involved in trehalose metabolism. These experiments also led to an unanticipated project concerning a possible role for Tre-6-P in stomatal function, which is another very important function in leaves. In a second and more general approach it was investigated whether changes in sugar levels in plants affect the morphogenesis of leaves in response to light. For this, a series of metabolic mutants impaired in central metabolism were grown in one light environment and their leaf morphology was analysed. In a third and even more general approach the natural variation in leaf and rosette morphological traits was investigated in a panel of wild Arabidopsis accessions with the aim of understanding how leaf morphology affects leaf function and whole plant growth and how different traits relate to each other. The analysis included measurements of leaf morphological traits as well as the number of leaves in the plant to put leaf morphology in a whole plant context. The variance in plant growth could not be explained by variation in photosynthetic rates and only to a small degree by variation in rates of dark respiration. There were four key axes of variation in rosette and leaf morphology – leaf area growth, leaf thickness, cell expansion and leaf number. These four processes were integrated in the context of whole plant growth by models that employed a multiple linear regression approach. This then led to a theoretical approach in which a simple allometric mathematical model was constructed, linking leaf number, leaf size and plant growth rate together in a whole plant context in Arabidopsis.
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.
Leaf senescence is an essential physiological process in plants that supports the recycling of nitrogen and other nutrients to support the growth of developing organs, including young leaves, seeds, and fruits. Thus, the regulation of senescence is crucial for evolutionary success in wild populations and for increasing yield in crops. Here, we describe the influence of a NAC transcription factor, SlNAP2 (Solanum lycopersicum NAC-like, activated by Apetala3/Pistillata), that controls both leaf senescence and fruit yield in tomato (S. lycopersicum). SlNAP2 expression increases during age-dependent and dark-induced leaf senescence. We demonstrate that SlNAP2 activates SlSAG113 (S. lycopersicum SENESCENCE-ASSOCIATED GENE113), a homolog of Arabidopsis (Arabidopsis thaliana) SAG113, chlorophyll degradation genes such as SlSGR1 (S. lycopersicum senescence-inducible chloroplast stay-green protein 1) and SlPAO (S. lycopersicum pheide a oxygenase), and other downstream targets by directly binding to their promoters, thereby promoting leaf senescence. Furthermore, SlNAP2 directly controls the expression of genes important for abscisic acid (ABA) biosynthesis, S. lycopersicum 9-cis-epoxycarotenoid dioxygenase 1 (SlNCED1); transport, S. lycopersicum ABC transporter G family member 40 (SlABCG40); and degradation, S. lycopersicum ABA 8'-hydroxylase (SlCYP707A2), indicating that SlNAP2 has a complex role in establishing ABA homeostasis during leaf senescence. Inhibiting SlNAP2 expression in transgenic tomato plants impedes leaf senescence but enhances fruit yield and sugar content likely due to prolonged leaf photosynthesis in aging tomato plants. Our data indicate that SlNAP2 has a central role in controlling leaf senescence and fruit yield in tomato.
Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, thereby allowing mammals to maintain a constant body temperature in a cold environment. Thermogenic capacity of this tissue is due to a high mitochondrial density and expression of uncoupling protein 1 (UCP1), a unique brown adipocyte marker which dissipates the mitochondrial proton gradient to produce heat instead of ATP. BAT is actively involved in whole-body metabolic homeostasis and during aging there is a loss of classical brown adipose tissue with concomitantly reduced browning capacity of white adipose tissue. Therefore, an age-dependent decrease of BAT-related energy expenditure capacity may exacerbate the development of metabolic diseases, including obesity and type 2 diabetes mellitus. Given that direct effects of age-related changes of BAT-metabolic flux have yet to be unraveled, the aim of the current thesis is to investigate potential metabolic mechanisms involved in BAT-dysfunction during aging and to identify suitable metabolic candidates as functional biomarkers of BAT-aging. To this aim, integration of transcriptomic, metabolomic and proteomic data analyses of BAT from young and aged mice was performed, and a group of candidates with age-related changes was revealed. Metabolomic analysis showed age-dependent alterations of metabolic intermediates involved in energy, nucleotide and vitamin metabolism, with major alterations regarding the purine nucleotide pool. These data suggest a potential role of nucleotide intermediates in age-related BAT defects. In addition, the screening of transcriptomic and proteomic data sets from BAT of young and aged mice allowed identification of a 60-kDa lysophospholipase, also known as L-asparaginase (Aspg), whose expression declines during BAT-aging. Involvement of Aspg in brown adipocyte thermogenic function was subsequently analyzed at the molecular level using in vitro approaches and animal models. The findings revealed sensitivity of Aspg expression to β3-adrenergic activation via different metabolic cues, including cold exposure and treatment with β3-adrenergic agonist CL. To further examine ASPG function in BAT, an over-expression model of Aspg in a brown adipocyte cell line was established and showed that these cells were metabolically more active compared to controls, revealing increased expression of the main brown-adipocyte specific marker UCP1, as well as higher lipolysis rates. An in vitro loss-of-function model of Aspg was also functionally analyzed, revealing reduced brown adipogenic characteristics and an impaired lipolysis, thus confirming physiological relevance of Aspg in brown adipocyte function. Characterization of a transgenic mouse model with whole-body inactivation of the Aspg gene (Aspg-KO) allowed investigation of the role of ASPG under in vivo conditions, indicating a mild obesogenic phenotype, hypertrophic white adipocytes, impairment of the early thermogenic response upon cold-stimulation and dysfunctional insulin sensitivity. Taken together, these data show that ASPG may represent a new functional biomarker of BAT-aging that regulates thermogenesis and therefore a potential target for the treatment of age-related metabolic disease.
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.
Plants are unable to move away from unwanted environments and therefore have to locally adapt to changing conditions. Arabidopsis thaliana (Arabidopsis), a model organism in plant biology, has been able to rapidly colonize a wide spectrum of environments with different biotic and abiotic challenges. In recent years, natural variation in Arabidopsis has shown to be an excellent resource to study genes underlying adaptive traits and hybridization’s impact on natural diversity. Studies on Arabidopsis hybrids have provided information on the genetic basis of hybrid incompatibilities and heterosis, as well as inheritance patterns in hybrids. However, previous studies have focused mainly on global accessions and yet much remains to be known about variation happening within a local growth habitat. In my PhD, I investigated the impact of heterozygosity at a local collection site of Arabidopsis and its role in local adaptation. I focused on two different projects, both including hybrids among Arabidopsis individuals collected around Tübingen in Southern Germany. The first project sought to understand the impact of hybridization on metabolism and growth within a local Arabidopsis collection site. For this, the inheritance patterns in primary and secondary metabolism, together with rosette size of full diallel crosses among seven parents originating from Southern Germany were analyzed. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed pronounced non-additive inheritance patterns. In addition, defense metabolites, mainly glucosinolates, displayed the highest degree of variation from the midparent values and were positively correlated with a proxy for plant size.
In the second project, the role of ACCELERATED CELL DEATH 6 (ACD6) in the defense response pathway of Arabidopsis necrotic hybrids was further characterized. Allelic interactions of ACD6 have been previously linked to hybrid necrosis, both among global and local Arabidopsis accessions. Hence, I characterized the early metabolic and ionic changes induced by ACD6, together with marker gene expression assays of physiological responses linked to its activation. An upregulation of simple sugars and metabolites linked to non-enzymatic antioxidants and the TCA cycle were detected, together with putrescine and acids linked to abiotic stress responses. Senescence was found to be induced earlier in necrotic hybrids and cytoplasmic calcium signaling was unaffected in response to temperature. In parallel, GFP-tagged constructs of ACD6 were developed.
This work therefore gave novel insights on the role of heterozygosity in natural variation and adaptation and expanded our current knowledge on the physiological and molecular responses associated with ACD6 activation.
Stable isotopes represent a unique approach to provide insights into the ecology of organisms. δ13C and δ15N have specifically been used to obtain information on the trophic ecology and food-web interactions. Trophic discrimination factors (TDF, Δ13C and Δ15N) describe the isotopic fractionation occurring from diet to consumer tissue, and these factors are critical for obtaining precise estimates within any application of δ13C and δ15N values. It is widely acknowledged that metabolism influences TDF, being responsible for different TDF between tissues of variable metabolic activity (e.g., liver vs. muscle tissue) or species body size (small vs. large). However, the connection between the variation of metabolism occurring within a single species during its ontogeny and TDF has rarely been considered. Here, we conducted a 9-month feeding experiment to report Δ13C and Δ15N of muscle and liver tissues for several weight classes of Eurasian perch (Perca fluviatilis), a widespread teleost often studied using stable isotopes, but without established TDF for feeding on a natural diet. In addition, we assessed the relationship between the standard metabolic rate (SMR) and TDF by measuring the oxygen consumption of the individuals. Our results showed a significant negative relationship of SMR with Δ13C, and a significant positive relationship of SMR with Δ15N of muscle tissue, but not with TDF of liver tissue. SMR varies inversely with size, which translated into a significantly different TDF of muscle tissue between size classes. In summary, our results emphasize the role of metabolism in shaping-specific TDF (i.e., Δ13C and Δ15N of muscle tissue) and especially highlight the substantial differences between individuals of different ontogenetic stages within a species. Our findings thus have direct implications for the use of stable isotope data and the applications of stable isotopes in food-web studies.
Stable isotopes represent a unique approach to provide insights into the ecology of organisms. δ13C and δ15N have specifically been used to obtain information on the trophic ecology and food-web interactions. Trophic discrimination factors (TDF, Δ13C and Δ15N) describe the isotopic fractionation occurring from diet to consumer tissue, and these factors are critical for obtaining precise estimates within any application of δ13C and δ15N values. It is widely acknowledged that metabolism influences TDF, being responsible for different TDF between tissues of variable metabolic activity (e.g., liver vs. muscle tissue) or species body size (small vs. large). However, the connection between the variation of metabolism occurring within a single species during its ontogeny and TDF has rarely been considered. Here, we conducted a 9-month feeding experiment to report Δ13C and Δ15N of muscle and liver tissues for several weight classes of Eurasian perch (Perca fluviatilis), a widespread teleost often studied using stable isotopes, but without established TDF for feeding on a natural diet. In addition, we assessed the relationship between the standard metabolic rate (SMR) and TDF by measuring the oxygen consumption of the individuals. Our results showed a significant negative relationship of SMR with Δ13C, and a significant positive relationship of SMR with Δ15N of muscle tissue, but not with TDF of liver tissue. SMR varies inversely with size, which translated into a significantly different TDF of muscle tissue between size classes. In summary, our results emphasize the role of metabolism in shaping-specific TDF (i.e., Δ13C and Δ15N of muscle tissue) and especially highlight the substantial differences between individuals of different ontogenetic stages within a species. Our findings thus have direct implications for the use of stable isotope data and the applications of stable isotopes in food-web studies.
The regulation of energy homeostasis is controlled by the brain and, besides requiring high amounts of energy, it relies on functional insulin/insulin-like growth factor (IGF)-1 signalling in the central nervous system. This energy is mainly provided by mitochondria in form of ATP. Thus, there is an intricate interplay between mitochondrial function and insulin/IGF-1 action to enable functional brain signalling and, accordingly, propagate a healthy metabolism. To adapt to different nutritional conditions, the brain is able to sense the current energy status via mitochondrial and insulin signalling-dependent pathways and exerts an appropriate metabolic response. However, regional, cell type and receptor-specific consequences of this interaction occur and are linked to diverse outcomes such as altered nutrient sensing, body weight regulation or even cognitive function. Impairments of this cross-talk can lead to obesity and glucose intolerance and are linked to neurodegenerative diseases, yet they also induce a self-sustainable, dysfunctional 'metabolic triangle' characterised by insulin resistance, mitochondrial dysfunction and inflammation in the brain. The identification of causal factors deteriorating insulin action, mitochondrial function and concomitantly a signature of metabolic stress in the brain is of utter importance to offer novel mechanistic insights into development of the continuously rising prevalence of non-communicable diseases such as type 2 diabetes and neurodegeneration. This review aims to determine the effect of insulin action on brain mitochondrial function and energy metabolism. It precisely outlines the interaction and differences between insulin action, insulin-like growth factor (IGF)-1 signalling and mitochondrial function; distinguishes between causality and association; and reveals its consequences for metabolism and cognition. We hypothesise that an improvement of at least one signalling pathway can overcome the vicious cycle of a self-perpetuating metabolic dysfunction in the brain present in metabolic and neurodegenerative diseases.