570 Biowissenschaften; Biologie
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Institute
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.
Since the golden era of antibiotics natural products are of ever growing interest to both basic research and applied sciences as they are the main source of new bioactive compounds delivering lead structures for new pharmaceuticals with potent antibiotic, anti-inflammatory or anti-cancer activities. Alongside the technological advances in high-throughput genome sequencing and the better understanding of the general organization of those modular biosynthetic assembly lines of secondary metabolites, there was also a shift from wet-lab screening of active cell extracts towards algorithm-based in silico screening for new natural product biosynthesis gene clusters (BGCs). Although the increasing availability of full genome sequences revealed that such non-ribosomal peptide synthetases (NRPS), polyketide synthases (PKS) and ribosomally synthesized and post-translationally modified peptides (RiPPs) can be found in all three kingdoms of life, certain phyla like actinobacteria and cyanobacteria show a very high density of these secondary metabolite BGCs.
The facultative symbiotic, N2-fixing model organism N. punctiforme PCC73102 is a terrestrial type IV cyanobacterium that not only dedicates are very large fraction of its genome to secondary metabolite production but is also amenable to genetic modification. AntiSMASH analysis of the genome showed that there are sixteen potential secondary metabolite BGCs encoded in N. punctiforme, but until now there were only two compounds assigned to their respective BGC leaving the remaining fourteen orphan. This makes the organism a perfect subject for the establishment of a novel combinatorial genomic mining approach for the detection of new natural products.
In the course of this study a combinatorial approach of genomic mining, independent monitoring techniques and alteration of cultivation conditions lead to new insights in cyanobacterial natural product biosynthesis and ultimately to the description of a novel compound produced by N. punctiforme. With the generation and investigation of a reporter strain library consisting of CFP-producing transcriptional reporter mutants for every predicted secondary metabolite BGC of N. punctiforme, it could be shown that natural product expression is in fact not silent for all those BGCs where no compound can be detected. Instead several distinct expression patterns could be described highlighting that secondary metabolite production is under tight regulation and only a minor fraction of these BGCs is in fact silent under standard laboratory conditions. Furthermore, increasing light intensity and carbon dioxide availability and cultivating N. punctiforme to very high cell densities had a tremendous impact on the overall metabolic activity of the organism. Investigation of high density cultivated cell extracts ultimately lead to the detection of a so far undescribed set of microviridins with unusual extended peptide sequences named Microviridin N3 – N9. Both cultivation of the transcriptional reporter mutants as well as RTqPCR-based detection of secondary metabolite BGC transcription levels revealed that in fact 50% of N. punctiforme’s natural product BGCs are upregulated under high cell density conditions. In contrast to this very broad response, co-cultivation of N. punctiforme in chemical or physical contact with a N-deprived host plant (Blasia pusilla) lead to a very specific upregulation of two natural product BGCs, namely RIPP3 and RIPP4. Although this response could be confirmed by various independent monitoring techniques and heavy analytical efforts were spent, no compound could be assigned to either of these BGCs.
This study is the first in-depth systematic investigation of a cyanobacterial secondary metabolome by a combinatorial approach of genome mining and independent monitoring techniques that can serve as a new strategic approach to gain further insight into natural product synthesis of various organisms. Although there are single well described examples of secondary metabolites like the cell differentiation factor PatS in Anabaena sp. strain PCC 7120, the level and extent of regulation observed in this study is unprecedented and understanding of these mechanisms might be the key to streamline natural product discovery. However, the results of this study also highlight that induction of secondary metabolite BGCs is not the real challenge. Instead the new insights point towards analytical issues being a severe hurdle and finding reliable strategies to overcome these problems might as well drive natural product discovery.
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.
Methane is an important greenhouse gas contributing to global climate change. Natural environments and restored wetlands contribute a large proportion to the global methane budget. Methanogenic archaea (methanogens) and methane oxidizing bacteria (methanotrophs), the biogenic producers and consumers of methane, play key roles in the methane cycle in those environments. A large number of studies revealed the distribution, diversity and composition of these microorganisms in individual habitats. However, uncertainties exist in predicting the response and feedback of methane-cycling microorganisms to future climate changes and related environmental changes due to the limited spatial scales considered so far, and due to a poor recognition of the biogeography of these important microorganisms combining global and local scales.
With the aim of improving our understanding about whether and how methane-cycling microbial communities will be affected by a series of dynamic environmental factors in response to climate change, this PhD thesis investigates the biogeographic patterns of methane-cycling communities, and the driving factors which define these patterns at different spatial scales. At the global scale, a meta-analysis was performed by implementing 94 globally distributed public datasets together with environmental data from various natural environments including soils, lake sediments, estuaries, marine sediments, hydrothermal sediments and mud volcanos. In combination with a global biogeographic map of methanogenic archaea from multiple natural environments, this thesis revealed that biogeographic patterns of methanogens exist. The terrestrial habitats showed higher alpha diversities than marine environments. Methanoculleus and Methanosaeta (Methanothrix) are the most frequently detected taxa in marine habitats, while Methanoregula prevails in terrestrial habitats. Estuary ecosystems, the transition zones between marine and terrestrial/limnic ecosystems, have the highest methanogenic richness but comparably low methane emission rates. At the local scale, this study compared two rewetted fens with known high methane emissions in northeastern Germany, a coastal brackish fen (Hütelmoor) and a freshwater riparian fen (Polder Zarnekow). Consistent with different geochemical conditions and land-use history, the two rewetted fens exhibit dissimilar methanogenic and, especially, methanotrophic community compositions. The methanotrophic community was generally under-represented among the prokaryotic communities and both fens show similarly low ratios of methanotrophic to methanogenic abundances. Since few studies have characterized methane-cycling microorganisms in rewetted fens, this study provides first evidence that the rapid and well re-established methanogenic community in combination with the low and incomplete re-establishment of the methanotrophic community after rewetting contributes to elevated sustained methane fluxes following rewetting.
Finally, this thesis demonstrates that dispersal limitation only slightly regulates the biogeographic distribution patterns of methanogenic microorganisms in natural environments and restored wetlands. Instead, their existence, adaption and establishment are more associated with the selective pressures under different environmental conditions. Salinity, pH and temperature are identified as the most important factors in shaping microbial community structure at different spatial scales (global versus terrestrial environments). Predicted changes in climate, such as increasing temperature, changes in precipitation patterns and increasing frequency of flooding events, are likely to induce a series of environmental alterations, which will either directly or indirectly affect the driving environmental forces of methanogenic communities, leading to changes in their community composition and thus potentially also in methane emission patterns in the future.
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.
NADPH is an essential cofactor that drives biosynthetic reactions in all living organisms. It is a reducing agent and thus electron donor of anabolic reactions that produce major cellular components as well as many products in biotechnology. Indeed, the engineering of metabolic pathways for the production of many products is often limited by the availability of NADPH. One common strategy to address this issue is to swap cofactor specificity from NADH to NADPH of enzymes. However, this process is time consuming and challenging because multiple parameters need to be engineered in parallel. Therefore, the first aim of this project is to establish an efficient metabolic biosensor to select enzymes that can reduce NADP+. An NADPH auxotroph strain was constructed by deleting major reactions involved in NADPH biosynthesis in E. coli’s central carbon metabolism with the exception of 6-phosphogluconate dehydrogenase. To validate this strain, two enzymes were tested in the presence of several carbon sources: a dihydrolipoamide dehydrogenase variant of E. coli harboring seven mutations and a formate dehydrogenase (FDH) from Mycobacterium vaccae N10 harboring four mutations were found to support NADPH biosynthesis and growth. The strain was subjected to adaptive laboratory evolution with the goal of testing its robustness under different carbon sources. Our evolution experiment resulted in the random mutagenesis of the malic enzyme (maeA), enabling it to produce NADPH. The additional deletion of maeA rendered a more robust second-generation biosensor strain for NADP+ reduction. We devised a structure-guided directed evolution approach to change cofactor specificity in Pseudomonas sp. 101 FDH. To this end, a library of >106 variants was tested using in vivo selection. Compared to the best engineered enzymes reported, our best variant carrying five mutations shows 5-fold higher catalytic efficiency and 13-fold higher specificity towards NADP+, as well as 2-fold higher affinity towards formate. In conclusion, we demonstrate the potential of in vivo selection and evolution-guided approaches to develop better NADPH biosensors and to engineer cofactor specificity by the simultaneous improvement of multiple parameters (kinetic efficiency with NADP+, specificity towards NADP+, and affinity towards formate), which is a major challenge in protein engineering due to the existence of tradeoffs and epistasis.
In nature, bacteria are found to reside in multicellular communities encased in self-produced extracellular matrices. Indeed, biofilms are the default lifestyle of the bacteria which cause persistent infections in humans. The biofilm assembly protects bacterial cells from desiccation and limits the effectiveness of antimicrobial treatments. A myriad of biomolecules in the extracellular matrix, including proteins, exopolysaccharides, lipids, extracellular DNA and other, form a dense and viscoelastic three dimensional network. Many studies emphasized that a destabilization of the mechanical integrity of biofilm architectures potentially eliminates the protective shield and renders bacteria more susceptible to the immune system and antibiotics. Pantoea stewartii is a plant pathogen which infects monocotyledons such as maize and sweet corn. These bacteria produce dense biofilms in the xylem of infected plants which cause wilting of plants and crops. Stewartan is an exopolysaccharide which is produced by Pantoea stewartii and secreted as the major component to the extracellular matrix. It consists of heptasaccharide repeating units with a high degree of polymerization (2-4 MDa). In this work, the physicochemical properties of stewartan were investigated to understand the contributions of this exopolysaccharide to the mechanical integrity and cohesiveness of Pantoea stewartii biofilms. Therefore, a coarse-grained model of stewartan was developed with computational techniques to obtain a model for its three dimensional structural features. Here, coarse-grained molecular dynamic simulations revealed that the exopolysaccharide forms a hydrogel in which the exopolysaccharide chains arrange into a three dimensional mesh-like network. Simulations at different concentrations were used to investigate the influence of the water content on the network formation. Stewartan was further purified from 72 h grown Pantoea stewartii biofilms and the diffusion of bacteriophage and differently-sized nanoparticles (which ranged from 1.1 to 193 nm diameter) was analyzed in reconstituted stewartan solutions. Fluorescence correlation spectroscopy and single-particle tracking revealed that the stewartan network impeded the mobility of a set of differently-sized fluorescent particles in a size-dependent manner. Diffusion of these particles became more anomalous, as characterized by fitting the diffusion data to an anomalous diffusion model, with increasing stewartan concentrations. Further bulk and microrheological experiments were used to analyze the transitions in stewartan fluid behavior and stewartan chain entanglements were described. Moreover, it was noticed, that a small fraction of bacteriophage particles was trapped in small-sized pores deviating from classical random walks which highlighted the structural heterogeneity of the stewartan network. Additionally, the mobility of fluorescent particles
also depended on the charge of the stewartan exopolysaccharide and a model of a molecular sieve for the stewartan network was proposed. The here reported structural features of the stewartan polymers were used to provide a detailed description of the mechanical properties of typically glycan-based biofilms such as the one from Pantoea stewartii.
In addition, the mechanical properties of the biofilm architecture are permanently sensed by the embedded bacteria and enzymatic modifications of the extracellular matrix take place to address environmental cues. Hence, in this work the influence of enzymatic degradation of the stewartan exopolysaccharides on the overall exopolysaccharide network structure was analyzed to describe relevant physiological processes in Pantoea stewartii biofilms. Here, the stewartan hydrolysis kinetics of the tailspike protein from the ΦEa1h bacteriophage, which is naturally found to infect Pantoea stewartii cells, was compared to WceF. The latter protein is expressed from the Pantoea stewartii stewartan biosynthesis gene cluster wce I-III. The degradation of stewartan by the ΦEa1h tailspike protein was shown to be much faster than the hydrolysis kinetics of WceF, although both enzymes cleaved the β D GalIII(1→3)-α-D-GalI glycosidic linkage from the stewartan backbone. Oligosaccharide fragments which were produced during the stewartan cleavage, were analyzed in size-exclusion chromatography and capillary electrophoresis. Bioinformatic studies and the analysis of a WceF crystal structure revealed a remarkably high structural similarity of both proteins thus unveiling WceF as a bacterial tailspike-like protein. As a consequence, WceF might play a role in stewartan chain length control in Pantoea stewartii biofilms.
The Arctic region is especially impacted by global warming as temperatures in high latitude regions have increased and are predicted to further rise at levels above the global average. This is crucial to Arctic soils and the shallow shelves of the Arctic Ocean as they are underlain by permafrost. Perennially frozen ground is a habitat for a large number and great diversity of viable microorganisms, which can remain active even under freezing conditions. Warming and thawing of permafrost makes trapped soil organic carbon more accessible to microorganisms. They can transform it to the greenhouse gases carbon dioxide, methane and nitrous oxide. On the other hand, it is assumed that thawing of the frozen ground stimulates microbial activity and carbon turnover. This can lead to a positive feedback loop of warming and greenhouse gas release.
Submarine permafrost covers most areas of the Siberian Arctic Shelf and contains a large though unquantified carbon pool. However, submarine permafrost is not only affected by changes in the thermal regime but by drastic changes in the geochemical composition as it formed under terrestrial conditions and was inundated by Holocene sea level rise and coastal erosion. Seawater infiltration into permafrost sediments resulted in an increase of the pore water salinity and, thus, in thawing of permafrost in the upper sediment layers even at subzero temperatures. The permafrost below, which was not affected by seawater, remained ice-bonded, but warmed through seawater heat fluxes.
The objective of this thesis was to study microbial communities in submarine permafrost with a focus on their response to seawater influence and long-term warming using a combined approach of molecular biological and physicochemical analyses. The microbial abundance, community composition and structure as well as the diversity were investigated in drill cores from two locations in the Laptev Sea, which were subjected to submarine conditions for centuries to millennia. The microbial abundance was measured through total cell counts and copy numbers of the 16S rRNA gene and of functional genes. The latter comprised genes which are indicative for methane production (mcrA) and sulfate reduction (dsrB). The microbial community was characterized by high-throughput-sequencing of the 16S rRNA gene. Physicochemical analyses included the determination of the pore water geochemical and stable isotopic composition, which were used to describe the degree of seawater influence. One major outcome of the thesis is that the submarine permafrost stratified into different so-called pore water units centuries as well as millennia after inundation: (i) sediments that were mixed with seafloor sediments, (ii) sediments that were infiltrated with seawater, and (iii) sediments that were unaffected by seawater. This stratification was reflected in the submarine permafrost microbial community composition only millennia after inundation but not on time-scales of centuries.
Changes in the community composition as well as abundance were used as a measure for microbial activity and the microbial response to changing thermal and geochemical conditions. The results were discussed in the context of permafrost temperature, pore water composition, paleo-climatic proxies and sediment age. The combination of permafrost warming and increasing salinity as well as permafrost warming alone resulted in a disturbance of the microbial communities at least on time-scales of centuries. This was expressed by a loss of microbial abundance and bacterial diversity. At the same time, the bacterial community of seawater unaffected but warmed permafrost was mainly determined by environmental and climatic conditions at the time of sediment deposition. A stimulating effect of warming was observed only in seawater unaffected permafrost after millennia-scale inundation, visible through increased microbial abundance and reduced amounts of substrate.
Despite submarine exposure for centuries to millennia, the community of bacteria in submarine permafrost still generally resembled the community of terrestrial permafrost. It was dominated by phyla like Actinobacteria, Chloroflexi, Firmicutes, Gemmatimonadetes and Proteobacteria, which can be active under freezing conditions.
Moreover, the archaeal communities of both study sites were found to harbor high abundances of marine and terrestrial anaerobic methane oxidizing archaea (ANME). Results also suggested ANME populations to be active under in situ conditions at subzero temperatures. Modeling showed that potential anaerobic oxidation of methane (AOM) could mitigate the release of almost all stored or microbially produced methane from thawing submarine permafrost.
Based on the findings presented in this thesis, permafrost warming and thawing under submarine conditions as well as permafrost warming without thaw are supposed to have marginal effects on the microbial abundance and community composition, and therefore likely also on carbon mobilization and the formation of methane. Thawing under submarine conditions even stimulates AOM and thus mitigates the release of methane.
Research on novel and advanced biomaterials is an indispensable step towards their applications in desirable fields such as tissue engineering, regenerative medicine, cell culture, or biotechnology. The work presented here focuses on such a promising material: polyelectrolyte multilayer (PEM) composed of hyaluronic acid (HA) and poly(L-lysine) (PLL). This gel-like polymer surface coating is able to accumulate (bio-)molecules such as proteins or drugs and release them in a controlled manner. It serves as a mimic of the extracellular matrix (ECM) in composition and intrinsic properties. These qualities make the HA/PLL multilayers a promising candidate for multiple bio-applications such as those mentioned above. The work presented aims at the development of a straightforward approach for assessment of multi-fractional diffusion in multilayers (first part) and at control of local molecular transport into or from the multilayers by laser light trigger (second part).
The mechanism of the loading and release is governed by the interaction of bioactives with the multilayer constituents and by the diffusion phenomenon overall. The diffusion of a molecule in HA/PLL multilayers shows multiple fractions of different diffusion rate. Approaches, that are able to assess the mobility of molecules in such a complex system, are limited. This shortcoming motivated the design of a novel evaluation tool presented here.
The tool employs a simulation-based approach for evaluation of the data acquired by fluorescence recovery after photobleaching (FRAP) method. In this approach, possible fluorescence recovery scenarios are primarily simulated and afterwards compared with the data acquired while optimizing parameters of a model until a sufficient match is achieved. Fluorescent latex particles of different sizes and fluorescein in an aqueous medium are utilized as test samples validating the analysis results. The diffusion of protein cytochrome c in HA/PLL multilayers is evaluated as well.
This tool significantly broadens the possibilities of analysis of spatiotemporal FRAP data, which originate from multi-fractional diffusion, while striving to be widely applicable. This tool has the potential to elucidate the mechanisms of molecular transport and empower rational engineering of the drug release systems.
The second part of the work focuses on the fabrication of such a spatiotemporarily-controlled drug release system employing the HA/PLL multilayer. This release system comprises different layers of various functionalities that together form a sandwich structure. The bottom layer, which serves as a reservoir, is formed by HA/PLL PEM deposited on a planar glass substrate. On top of the PEM, a layer of so-called hybrids is deposited. The hybrids consist of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) -based hydrogel microparticles with surface-attached gold nanorods. The layer of hybrids is intended to serve as a gate that controls the local molecular transport through the PEM–solution-interface. The possibility of stimulating the molecular transport by near-infrared (NIR) laser irradiation is being explored.
From several tested approaches for the deposition of hybrids onto the PEM surface, the drying-based approach was identified as optimal. Experiments, that examine the functionality of the fabricated sandwich at elevated temperature, document the reversible volume phase transition of the PEM-attached hybrids while sustaining the sandwich stability. Further, the gold nanorods were shown to effectively absorb light radiation in the tissue- and cell-friendly NIR spectral region while transducing the energy of light into heat. The rapid and reversible shrinkage of the PEM-attached hybrids was thereby achieved. Finally, dextran was employed as a model transport molecule. It loads into the PEM reservoir in a few seconds with the partition constant of 2.4, while it spontaneously releases in a slower, sustained manner. The local laser irradiation of the sandwich, which contains the fluorescein isothiocyanate tagged dextran, leads to a gradual reduction of fluorescence intensity in the irradiated region.
The release system fabricated employs renowned photoresponsivity of the hybrids in an innovative setting. The results of the research are a step towards a spatially-controlled on-demand drug release system that paves the way to spatiotemporally controlled drug release.
The approaches developed in this work have the potential to elucidate the molecular dynamics in ECM and to foster engineering of multilayers with properties tuned to mimic the ECM. The work aims at spatiotemporal control over the diffusion of bioactives and their presentation to the cells.
Giant unilamellar vesicles are an important tool in todays experimental efforts to understand the structure and behaviour of biological cells. Their simple structure allows the isolation of the physical elastic properties of the lipid membrane. A central physical
property is the bending energy of the membrane, since the many different shapes of giant vesicles can be obtained by finding the minimum of the bending energy. In the spontaneous curvature model the bending energy is a function of the bending rigidity as well as the mean curvature and an additional parameter called the spontaneous curvature, which describes an internal preference of the lipid-bilayer to bend towards one side or the other. The spontaneous and mean curvature are local properties of the membrane.
Additional constraints arise from the conservation of the membrane surface area and the enclosed volume, which are global properties.
In this thesis the spontaneous curvature model is used to explain the experimental observation of a periodic shape oscillation of a giant unilamellar vesicle that was filled with a protein complex that periodically binds to and unbinds from the membrane.
By assuming that the binding of the proteins to the membrane induces a change in the spontaneous curvature the experimentally observed shapes could successfully be explained. This involves the numerical solution of the differential equations as obtained from the minimization of the bending energy respecting the area and volume constraints, the so called shape equations. Vice versa this approach can be used to estimate the spontaneous curvature from experimentally measurable quantities.
The second topic of this thesis is the analysis of concentration gradients in rigid conic membrane compartments. Gradients of an ideal gas due to gravity and gradients generated by the directed stochastic movement of molecular motors along a microtubulus were considered. It was possible to calculate the free energy and the bending energy analytically for the ideal gas. In the case of the non-equilibrium system with molecular motors, the characteristic length of the density profile, the jam-length, and its dependency on the opening angle of the conic compartment have been calculated in the mean-field limit.
The mean field results agree qualitatively with stochastic particle simulations.
Due to continuously intensifying human usage of the marine environment worldwide ranging cetaceans face an increasing number of threats. Besides whaling, overfishing and by-catch, new technical developments increase the water and noise pollution, which can negatively affect marine species. Cetaceans are especially prone to these influences, being at the top of the food chain and therefore accumulating toxins and contaminants. Furthermore, they are extremely noise sensitive due to their highly developed hearing sense and echolocation ability. As a result, several cetacean species were brought to extinction during the last century or are now classified as critically endangered. This work focuses on two odontocetes. It applies and compares different molecular methods for inference of population status and adaptation, with implications for conservation. The worldwide distributed sperm whale (Physeter macrocephalus) shows a matrilineal population structure with predominant male dispersal. A recently stranded group of male sperm whales provided a unique opportunity to investigate male grouping for the first time. Based on the mitochondrial control region, I was able to infer that male bachelor groups comprise multiple matrilines, hence derive from different social groups, and that they represent the genetic variability of the entire North Atlantic. The harbor porpoise (Phocoena phocoena) occurs only in the northern hemisphere. By being small and occurring mostly in coastal habitats it is especially prone to human disturbance. Since some subspecies and subpopulations are critically endangered, it is important to generate and provide genetic markers with high resolution to facilitate population assignment and subsequent protection measurements. Here, I provide the first harbour porpoise whole genome, in high quality and including a draft annotation. Using it for mapping ddRAD seq data, I identify genome wide SNPs and, together with a fragment of the mitochondrial control region, inferred the population structure of its North Atlantic distribution range. The Belt Sea harbors a distinct subpopulation oppose to the North Atlantic, with a transition zone in the Kattegat. Within the North Atlantic I could detect subtle genetic differentiation between western (Canada-Iceland) and eastern (North Sea) regions, with support for a German North Sea breading ground around the Isle of Sylt. Further, I was able to detect six outlier loci which show isolation by distance across the investigated sampling areas. In employing different markers, I could show that single maker systems as well as genome wide data can unravel new information about population affinities of odontocetes. Genome wide data can facilitate investigation of adaptations and evolutionary history of the species and its populations. Moreover, they facilitate population genetic investigations, providing a high resolution, and hence allowing for detection of subtle population structuring especially important for highly mobile cetaceans.
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.
Plants are an attractive platform for the production of medicinal compounds because of their potential to generate large amounts of biomass cheaply. The use of chloroplast transformation is an attractive way to achieve the recombinant production of proteins in plants, because of the chloroplasts’ high capacity to produce foreign proteins in comparison to nuclear transformed plants. In this thesis, the production of two different types of antimicrobial polypeptides in chloroplasts is explored.
The first example is the production of the potent HIV entry inhibitor griffithsin. Griffithsin has the potential to prevent HIV infections by blocking the entry of the virus into human cells. Here the use of transplastomic plants as an inexpensive production method for griffithsin was explored. Transplastomic plants grew healthily and were able to accumulate griffithsin to up to 5% of the total soluble protein. Griffithsin could easily be purified from tobacco leaf tissue and had a similarly high neutralization activity as griffithsin recombinantly produced in bacteria. Griffithsin could be purified from dried tobacco leaves, demonstrating that dried leaves could be used as a storable starting material for griffithsin purification, circumventing the need for immediate purification after harvest.
The second example is the production of antimicrobial peptides (AMPs) that have the capacity to kill bacteria and are an attractive alternative to currently used antibiotics that are increasingly becoming ineffective. The production of antimicrobial peptides was considerably more challenging than the production of griffithsin. Small AMPs are prone to degradation in plastids. This problem was overcome by fusing AMPs to generate larger polypeptides. In one approach, AMPs were fused to each other to increase size and combine the mode of action of multiple AMPs. This improved the accumulation of AMPs but also resulted in impaired plant growth. This was solved by the use of two different inducible systems, which could largely restore plant growth. Fusions of multiple AMPs were insoluble and could not be purified.
In addition to fusing AMPs to each other, the fusion of AMPs to small ubiquitin-like modifier (SUMO), was tested as an approach to improve the accumulation, facilitate purification, and reduce the toxicity of AMPs to chloroplasts. Fusion of AMPs to SUMO indeed increased accumulation while reducing the toxicity to the plants. SUMO fusions produced inside chloroplasts could be purified, and SUMO could be efficiently cleaved off with the SUMO protease. Such fusions therefore provide a promising strategy for the production of AMPs and other small polypeptides inside chloroplasts.
Using individual-based modeling to understand grassland diversity and resilience in the Anthropocene
(2020)
The world’s grassland systems are increasingly threatened by anthropogenic change. Susceptible to a variety of different stressors, from land-use intensification to climate change, understanding the mechanisms driving the maintenance of these systems’ biodiversity and stability, and how these mechanisms may shift under human-mediated disturbance, is thus critical for successfully navigating the next century. Within this dissertation, I use an individual-based and spatially-explicit model of grassland community assembly (IBC-grass) to examine several processes, thought key to understanding their biodiversity and stability and how it changes under stress. In the first chapter of my thesis, I examine the conditions under which intraspecific trait variation influences the diversity of simulated grassland communities. In the second and third chapters of my thesis, I shift focus towards understanding how belowground herbivores influence the stability of these grassland systems to either a disturbance that results in increased, stochastic, plant mortality, or eutrophication.
Intraspecific trait variation (ITV), or variation in trait values between individuals of the same species, is fundamental to the structure of ecological communities. However, because it has historically been difficult to incorporate into theoretical and statistical models, it has remained largely overlooked in community-level analyses. This reality is quickly shifting, however, as a consensus of research suggests that it may compose a sizeable proportion of the total variation within an ecological community and that it may play a critical role in determining if species coexist. Despite this increasing awareness that ITV matters, there is little consensus of the magnitude and direction of its influence. Therefore, to better understand how ITV changes the assembly of grassland communities, in the first chapter of my thesis, I incorporate it into an established, individual-based grassland community model, simulating both pairwise invasion experiments as well as the assembly of communities with varying initial diversities. By varying the amount of ITV in these species’ functional traits, I examine the magnitude and direction of ITV’s influence on pairwise invasibility and community coexistence. During pairwise invasion, ITV enables the weakest species to more frequently invade the competitively superior species, however, this influence does not generally scale to the community level. Indeed, unless the community has low alpha- and beta- diversity, there will be little effect of ITV in bolstering diversity. In these situations, since the trait axis is sparsely filled, the competitively inferior may suffer less competition and therefore ITV may buffer the persistence and abundance of these species for some time.
In the second and third chapters of my thesis, I model how one of the most ubiquitous trophic interactions within grasslands, herbivory belowground, influences their diversity and stability. Until recently, the fundamental difficulty in studying a process within the soil has left belowground herbivory “out of sight, out of mind.” This dilemma presents an opportunity for simulation models to explore how this understudied process may alter community dynamics. In the second chapter of my thesis, I implement belowground herbivory – represented by the weekly removal of plant biomass – into IBC-grass. Then, by introducing a pulse disturbance, modelled as the stochastic mortality of some percentage of the plant community, I observe how the presence of belowground herbivores influences the resistance and recovery of Shannon diversity in these communities. I find that high resource, low diversity, communities are significantly more destabilized by the presence of belowground herbivores after disturbance. Depending on the timing of the disturbance and whether the grassland’s seed bank persists for more than one season, the impact of the disturbance – and subsequently the influence of the herbivores – can be greatly reduced. However, because human-mediated eutrophication increases the amount of resources in the soil, thus pressuring grassland systems, our results suggest that the influence of these herbivores may become more important over time.
In the third chapter of my thesis, I delve further into understanding the mechanistic underpinnings of belowground herbivores on the diversity of grasslands by replicating an empirical mesocosm experiment that crosses the presence of herbivores above- and below-ground with eutrophication. I show that while aboveground herbivory, as predicted by theory and frequently observed in experiments, mitigates the impact of eutrophication on species diversity, belowground herbivores counterintuitively reduce biodiversity. Indeed, this influence positively interacts with the eutrophication process, amplifying its negative impact on diversity. I discovered the mechanism underlying this surprising pattern to be that, as the herbivores consume roots, they increase the proportion of root resources to root biomass. Because root competition is often symmetric, herbivory fails to mitigate any asymmetries in the plants’ competitive dynamics. However, since the remaining roots have more abundant access to resources, the plants’ competition shifts aboveground, towards asymmetric competition for light. This leads the community towards a low-diversity state, composed of mostly high-performance, large plant species. We further argue that this pattern will emerge unless the plants’ root competition is asymmetric, in which case, like its counterpart aboveground, belowground herbivory may buffer diversity by reducing this asymmetry between the competitively superior and inferior plants.
I conclude my dissertation by discussing the implications of my research on the state of the art in intraspecific trait variation and belowground herbivory, with emphasis on the necessity of more diverse theory development in the study of these fundamental interactions. My results suggest that the influence of these processes on the biodiversity and stability of grassland systems is underappreciated and multidimensional, and must be thoroughly explored if researchers wish to predict how the world’s grasslands will respond to anthropogenic change. Further, should researchers myopically focus on understanding central ecological interactions through only mathematically tractable analyses, they may miss entire suites of potential coexistence mechanisms that can increase the coviability of species, potentially leading to coexistence over ecologically-significant timespans. Individual-based modelling, therefore, with its focus on individual interactions, will prove a critical tool in the coming decades for understanding how local interactions scale to larger contexts, and how these interactions shape ecological communities and further predicting how these systems will change under human-mediated stress.