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Institute
- Institut für Biochemie und Biologie (14) (remove)
To meet the demands of a growing world population while reducing carbon dioxide (CO2) emissions, it is necessary to capture CO2 and convert it into value-added compounds. In recent years, metabolic engineering of microbes has gained strong momentum as a strategy for the production of valuable chemicals. As common microbial feedstocks like glucose directly compete with human consumption, the one carbon (C1) compound formate was suggested as an alternative feedstock. Formate can be easily produced by various means including electrochemical reduction of CO2 and could serve as a feedstock for microbial production, hence presenting a novel entry point for CO2 to the biosphere and a storage option for excess electricity. Compared to the gaseous molecule CO2, formate is a highly soluble compound that can be easily handled and stored. It can serve as a carbon and energy source for natural formatotrophs, but these microbes are difficult to cultivate and engineer. In this work, I present the results of several projects that aim to establish efficient formatotrophic growth of E. coli – which cannot naturally grow on formate – via synthetic formate assimilation pathways. In the first study, I establish a workflow for growth-coupled metabolic engineering of E. coli. I demonstrate this approach by presenting an engineering scheme for the PFL-threonine cycle, a synthetic pathway for anaerobic formate assimilation in E. coli. The described methods are intended to create a standardized toolbox for engineers that aim to establish novel metabolic routes in E. coli and related organisms. The second chapter presents a study on the catalytic efficiency of C1-oxidizing enzymes in vivo. As formatotrophic growth requires generation of both energy and biomass from formate, the engineered E. coli strains need to be equipped with a highly efficient formate dehydrogenase, which provides reduction equivalents and ATP for formate assimilation. I engineered a strain that cannot generate reducing power and energy for cellular growth, when fed on acetate. Under this condition, the strain depends on the introduction of an enzymatic system for NADH regeneration, which could further produce ATP via oxidative phosphorylation. I show that the strain presents a valuable testing platform for C1-oxidizing enzymes by testing different NAD-dependent formate and methanol dehydrogenases in the energy auxotroph strain. Using this platform, several candidate enzymes with high in vivo activity, were identified and characterized as potential energy-generating systems for synthetic formatotrophic or methylotrophic growth in E. coli. In the third chapter, I present the establishment of the serine threonine cycle (STC) – a synthetic formate assimilation pathway – in E. coli. In this pathway, formate is assimilated via formate tetrahydrofolate ligase (FtfL) from Methylobacterium extorquens (M. extorquens). The carbon from formate is attached to glycine to produce serine, which is converted into pyruvate entering central metabolism. Via the natural threonine synthesis and cleavage route, glycine is regenerated and acetyl-CoA is produced as the pathway product. I engineered several selection strains that depend on different STC modules for growth and determined key enzymes that enable high flux through threonine synthesis and cleavage. I could show that expression of an auxiliary formate dehydrogenase was required to achieve growth via threonine synthesis and cleavage on pyruvate. By overexpressing most of the pathway enzymes from the genome, and applying adaptive laboratory evolution, growth on glycine and formate was achieved, indicating the activity of the complete cycle. The fourth chapter shows the establishment of the reductive glycine pathway (rGP) – a short, linear formate assimilation route – in E. coli. As in the STC, formate is assimilated via M. extorquens FtfL. The C1 from formate is condensed with CO2 via the reverse reaction of the glycine cleavage system to produce glycine. Another carbon from formate is attached to glycine to form serine, which is assimilated into central metabolism via pyruvate. The engineered E. coli strain, expressing most of the pathway genes from the genome, can grow via the rGP with formate or methanol as a sole carbon and energy source.
The earth’s ecosystems undergo considerable changes characterized by human-induced alterations of environmental factors. In order to develop conservation goals for vulnerable ecosystems, research on ecosystem functioning is required.. Therefore, it is crucial to explore organismal interactions, such as trophic interaction or competition, which are decisive for key processes in ecosystems. These interactions are determined by the performance responses of organisms to environmental changes, which in turn, are shaped by the organism’s functional traits. Exploring traits, their variation, and the environmental factors that act on them may provide insights on how ecological interactions affect
populations, community structures and dynamics, and thus ecosystem
functioning. In aquatic ecosystems, global warming intensifies
phytoplankton blooms, which are more frequently dominated by
cyanobacteria. As cyanobacteria are poor in polyunsaturated fatty acids
(PUFA) and sterols, this compositional change alters the biochemical
food quality of phytoplankton for consumer species with potential
effects on ecological interactions. Within this thesis, I studied the
effects of biochemical food quality on consumer traits and performance responses at the phytoplankton-zooplankton interface using different strains of two closely related generalist rotifer species Brachionus calyciflorus and Brachionus fernandoi and three phytoplankton species that differ in their biochemical food quality, i.e. in their content and composition of PUFA and sterols. In a series of laboratory feeding experiments I found that biochemical food quality affected rotifer’s performance, i.e. fecundity, survival, and population growth, across a broad range of food quantities. Biochemical food quality constraints,
which are often underestimated as influencing environmental factors, had strong impacts on performance responses. I further explored the potential of biochemical food quality in mediating consumer response variation between species and among strains of one species. Co-limitation by food quantity and biochemical food quality resulted in differences in performance responses, which were more pronounced within than between rotifer species. Furthermore, I demonstrated that the body PUFA compositions of rotifer species and strains were differently affected by the dietary PUFA supply, which indicates inter- and intraspecific differences in physiological traits, such as PUFA retention, allocation, and/or bioconversion capacity, within the genus Brachionus. This indicates that dietary PUFA are involved in shaping traits and performance responses of rotifers. This thesis reveals that biochemical food quality is an environmental factor with strong effects on individual traits and performance responses of consumers. Biochemical food quality constraints can further mediate trait and response variation among species or strains. Consequently, they carry the potential to shape ecological interactions and evolutionary processes with effects on community structures and dynamics. Trait-based approaches, which include food quality research, thus may provide further insights into the linkage between functional diversity and the maintenance of crucial ecosystem functions.
Escaping the plant cell
(2020)
Recent advances in microscopy have led to an improved visualization of different cell processes. Yet, this also leads to a higher demand of tools which can process images in an automated and quantitative fashion. Here, we present two applications that were developed to quantify different processes in eukaryotic cells which rely on the organization and dynamics of the cytoskeleton.. In plant cells, microtubules and actin filaments form the backbone of the cytoskeleton. These structures support cytoplasmic streaming, cell wall organization and tracking of cellular material to and from the plasma membrane. To better understand the underlying mechanisms of cytoskeletal organization, dynamics and coordination, frameworks for the quantification are needed. While this is fairly well established for the microtubules, the actin cytoskeleton has remained difficult to study due to its highly dynamic behaviour. One aim of this thesis was therefore to provide an automated framework to quantify and describe actin organization and dynamics. We used the framework to represent actin structures as networks and examined the transport efficiency in Arabidopsis thaliana hypocotyl cells. Furthermore, we applied the framework to determine the growth mode of cotton fibers and compared the actin organization in wild-type and mutant cells of rice. Finally, we developed a graphical user interface for easy usage. Microtubules and the actin cytoskeleton also play a major role in the morphogenesis of epidermal leaf pavement cells. These cells have highly complex and interdigitated shapes which are hard to describe in a quantitative way. While the relationship between microtubules, the actin cytoskeleton and shape formation is the object of many studies, it is still not clear how and if the cytoskeletal components predefine indentations and protrusions in pavement cell shapes. To understand the underlying cell processes which coordinate cell morphogenesis, a quantitative shape descriptor is needed. Therefore, the second aim of this thesis was the development of a network-based shape descriptor which captures global and local shape features, facilitates shape comparison and can be used to evaluate shape complexity. We demonstrated that our framework can be used to describe and compare shapes from various domains. In addition, we showed that the framework accurately detects local shape features of pavement cells and outperform contending approaches. In the third part of the thesis, we extended the shape description framework to describe pavement cell shape features on tissue-level by proposing different network representations of the underlying imaging data.
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.
With populations growing worldwide and climate change threatening food production there is an urgent need to find ways to ensure food security. Increasing carbon fixation rate in plants is a promising approach to boost crop yields. The carbon-fixing enzyme Rubisco catalyzes, beside the carboxylation reaction, also an oxygenation reaction that generates glycolate-2P, which needs to be recycled via a metabolic route termed photorespiration. Photorespiration dissipates energy and most importantly releases previously fixed CO2, thus significantly lowering carbon fixation rate and yield. Engineering plants to omit photorespiratory CO2 release is the goal of the FutureAgriculture consortium and this thesis is part of this collaboration. The consortium aims to establish alternative glycolate-2P recycling routes that do not release CO2. Ultimately, they are expected to increase carbon fixation rates and crop yields. Natural and novel reactions, which require enzyme engineering, were considered in the pathway design process. Here I describe the engineering of two pathways, the arabinose-5P and the erythrulose shunt. They were designed to recycle glycolate-2P via glycolaldehyde into a sugar phosphate and thereby reassimilate glycolate-2P to the Calvin cycle. I used Escherichia coli gene deletion strains to validate and characterize the activity of both synthetic shunts. The strains’ auxotrophies can be alleviated by the activity of the synthetic route, thus providing a direct way to select for pathway activity. I introduced all pathway components to these dedicated selection strains and discovered inhibitions, limitations and metabolic cross talk interfering with pathway activity. After resolving these issues, I was able to show the in vivo activity of all pathway components and combine them into functional modules.. Specifically, I demonstrate the activity of a new-to-nature module of glycolate reduction to glycolaldehyde. Also, I successfully show a new glycolaldehyde assimilation route via arabinose-5P to ribulose-5P. In addition, all necessary enzymes for glycolaldehyde assimilation via L-erythrulose were shown to be active and an L-threitol assimilation route via L-erythrulose was established in E. coli. On their own, these findings demonstrate the power of using an easily engineerable microbe to test novel pathways; combined, they will form the basis for implementing photorespiration bypasses in plants.