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Die vorliegende Dissertation behandelt die Ökologie von Cnidium dubium (Schkuhr) Thell. (Sumpf-Brenndolde), Gratiola officinalis L. (Gottes-Gnadenkraut) und Juncus atratus Krocker (Schwarze Binse), drei gefährdeten Arten, die als sogenannte Stromtalpflanzen in Mitteleuropa in ihrem Vorkommen eng an die Flussauen gebunden sind. Die Arbeit basiert auf verschiedenen Simulationsexperimenten und Feldstudien in der Unteren Havelniederung, einem „Feuchtgebiet von internationaler Bedeutung“. Sie behandelt Themenkomplexe wie das Samenbankverhalten, die Samenkeimung, die Stickstofflimitierung, die Konkurrenzkraft, das Verhalten der Pflanzen nach einer Sommertrockenheit und nach einer Winter/Frühjahrsüberflutung. Ferner widmet sie sich der Populationsbiologie der Arten und dem Verhalten der Pflanzen nach besonderen Störungsereignissen wie Mahd, Herbivorie und der Sommerflut 2002. Der Leser erfährt, wie die Pflanzen in verschiedenen Lebensphasen auf die auentypische Umwelt reagieren und erhält umfassende Einblicke in physiologische Mechanismen, die der Anpassung an die typischen Bedingungen einer mitteleuropäischen Flussaue dienen. Eine Interpretation der Ergebnisse zeigt auf, welche der spezifischen Eigenschaften zur Gefährdung der drei Stromtalarten beitragen. Die Arbeit ist für den Arten-, Biotop- und Landschaftsschutz interessant. Darüber hinaus bietet sie zahlreiche Anknüpfungspunkte zur ökophysiologischen Grundlagenforschung. Die verstärkte Nutzung physiologischer Methoden bei der Klärung ökologischer Fragestellungen wird angeregt.
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 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.
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.
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.
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.
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.