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Increasing concerns regarding the environmental impact of our chemical production have shifted attention towards possibilities for sustainable biotechnology. One-carbon (C1) compounds, including methane, methanol, formate and CO, are promising feedstocks for future bioindustry. CO2 is another interesting feedstock, as it can also be transformed using renewable energy to other C1 feedstocks for use. While formaldehyde is not suitable as a feedstock due to its high toxicity, it is a central intermediate in the process of C1 assimilation. This thesis explores formaldehyde metabolism and aims to engineer formaldehyde assimilation in the model organism Escherichia coli for the future C1-based bioindustry.
The first chapter of the thesis aims to establish growth of E. coli on formaldehyde via the most efficient naturally occurring route, the ribulose monophosphate pathway. Linear variants of the pathway were constructed in multiple-gene knockouts strains, coupling E. coli growth to the activities of the key enzymes of the pathway. Formaldehyde-dependent growth was achieved in rationally designed strains. In the final strain, the synthetic pathway provides the cell with almost all biomass and energy requirements.
In the second chapter, taking advantage of the unique feature of its reactivity, formaldehyde assimilation via condensation with glycine and pyruvate by two promiscuous aldolases was explored. Facilitated by these two reactions, the newly designed homoserine cycle is expected to support higher yields of a wide array of products than its counterparts. By dividing the pathway into segments and coupling them to the growth of dedicated strains, all pathway reactions were demonstrated to be sufficiently active. The work paves a way for future implementation of a highly efficient route for C1 feedstocks into commodity chemicals.
In the third chapter, the in vivo rate of the spontaneous formaldehyde tetrahydrofolate condensation to methylene-tetrahydrofolate was assessed in order to evaluate its applicability as a biotechnological process. Tested within an E. coli strain deleted in essential genes for native methylene-tetrahydrofolate biosynthesis, the reaction was shown to support the production of this essential intermediate. However, only low growth rates were observed and only at high formaldehyde concentrations. Computational analysis dependent on in vivo evidence from this strain deduced the slow rate of this spontaneous reaction, thus ruling out its substantial contribution to growth on C1 feedstocks.
The reactivity of formaldehyde makes it highly toxic. In the last chapter, the formation of thioproline, the condensation product of cysteine and formaldehyde, was confirmed to contribute this toxicity effect. Xaa-Pro aminopeptidase (PepP), which genetically links with folate metabolism, was shown to hydrolyze thioproline-containing peptides. Deleting pepP increased strain sensitivity to formaldehyde, pointing towards the toxicity of thioproline-containing peptides and the importance of their removal. The characterization in this study could be useful in handling this toxic intermediate.
Overall, this thesis identified challenges related to formaldehyde metabolism and provided novel solutions towards a future bioindustry based on sustainable C1 feedstocks in which formaldehyde serves as a key intermediate.
Meta‐communities of habitat islands may be essential to maintain biodiversity in anthropogenic landscapes allowing rescue effects in local habitat patches. To understand the species‐assembly mechanisms and dynamics of such ecosystems, it is important to test how local plant‐community diversity and composition is affected by spatial isolation and hence by dispersal limitation and local environmental conditions acting as filters for local species sorting. We used a system of 46 small wetlands (kettle holes)—natural small‐scale freshwater habitats rarely considered in nature conservation policies—embedded in an intensively managed agricultural matrix in northern Germany. We compared two types of kettle holes with distinct topographies (flatsloped, ephemeral, frequently plowed kettle holes vs. steep‐sloped, more permanent ones) and determined 254 vascular plant species within these ecosystems, as well as plant functional traits and nearest neighbor distances to other kettle holes. Differences in alpha and beta diversity between steep permanent compared with ephemeral flat kettle holes were mainly explained by species sorting and niche processes and mass effect processes in ephemeral flat kettle holes. The plant‐community composition as well as the community trait distribution in terms of life span, breeding system, dispersal ability, and longevity of seed banks significantly differed between the two habitat types. Flat ephemeral kettle holes held a higher percentage of non‐perennial plants with a more persistent seed bank, less obligate outbreeders and more species with seed dispersal abilities via animal vectors compared with steep‐sloped, more permanent kettle holes that had a higher percentage of wind‐dispersed species. In the flat kettle holes, plant‐species richness was negatively correlated with the degree of isolation, whereas no such pattern was found for the permanent kettle holes. Synthesis: Environment acts as filter shaping plant diversity (alpha and beta) and plant‐community trait distribution between steep permanent compared with ephemeral flat kettle holes supporting species sorting and niche mechanisms as expected, but we identified a mass effect in ephemeral kettle holes only. Flat ephemeral kettle holes can be regarded as meta‐ecosystems that strongly depend on seed dispersal and recruitment from a seed bank, whereas neighboring permanent kettle holes have a more stable local species diversity.
Background
Organisms are expected to respond to changing environmental conditions through local adaptation, range shift or local extinction. The process of local adaptation can occur by genetic changes or phenotypic plasticity, and becomes especially relevant when dispersal abilities or possibilities are somehow constrained. For genetic changes to occur, mutations are the ultimate source of variation and the mutation rate in terms of a mutator locus can be subject to evolutionary change. Recent findings suggest that the evolution of the mutation rate in a sexual species can advance invasion speed and promote adaptation to novel environmental conditions. Following this idea, this work uses an individual-based model approach to investigate if the mutation rate can also evolve in a sexual species experiencing different conditions of directional climate change, under different scenarios of colored stochastic environmental noise, probability of recombination and of beneficial mutations. The color of the noise mimicked investigating the evolutionary dynamics of the mutation rate in different habitats.
Results
The results suggest that the mutation rate in a sexual species experiencing directional climate change scenarios can evolve and reach relatively high values mainly under conditions of complete linkage of the mutator locus and the adaptation locus. In contrast, when they are unlinked, the mutation rate can slightly increase only under scenarios where at least 50% of arising mutations are beneficial and the rate of environmental change is relatively fast. This result is robust under different scenarios of stochastic environmental noise, which supports the observation of no systematic variation in the mutation rate among organisms experiencing different habitats.
Conclusions
Given that 50% beneficial mutations may be an unrealistic assumption, and that recombination is ubiquitous in sexual species, the evolution of an elevated mutation rate in a sexual species experiencing directional climate change might be rather unlikely. Furthermore, when the percentage of beneficial mutations and the population size are small, sexual species (especially multicellular ones) producing few offspring may be expected to react to changing environments not by adaptive genetic change, but mainly through plasticity. Without the ability for a plastic response, such species may become – at least locally – extinct.
Molecularly imprinted polymers (MIPs) mimic the binding sites of antibodies by substituting the amino acid-scaffold of proteins by synthetic polymers. In this work, the first MIP for the recognition of the diagnostically relevant enzyme butyrylcholinesterase (BuChE) is presented. The MIP was prepared using electropolymerization of the functional monomer o-phenylenediamine and was deposited as a thin film on a glassy carbon electrode by oxidative potentiodynamic polymerization. Rebinding and removal of the template were detected by cyclic voltammetry using ferricyanide as a redox marker. Furthermore, the enzymatic activity of BuChE rebound to the MIP was measured via the anodic oxidation of thiocholine, the reaction product of butyrylthiocholine. The response was linear between 50 pM and 2 nM concentrations of BuChE with a detection limit of 14.7 pM. In addition to the high sensitivity for BuChE, the sensor responded towards pseudo-irreversible inhibitors in the lower mM range.
A contemporary challenge in Ecology and Evolutionary Biology is to anticipate the fate of populations of organisms in the context of a changing world. Climate change and landscape changes due to anthropic activities have been of major concern in the contemporary history. Organisms facing these threats are expected to respond by local adaptation (i.e., genetic changes or phenotypic plasticity) or by shifting their distributional range (migration). However, there are limits to their responses. For example, isolated populations will have more difficulties in developing adaptive innovations by means of genetic changes than interconnected metapopulations. Similarly, the topography of the environment can limit dispersal opportunities for crawling organisms as compared to those that rely on wind. Thus, populations of species with different life history strategy may differ in their ability to cope with changing environmental conditions. However, depending on the taxon, empirical studies investigating organisms’ responses to environmental change may become too complex, long and expensive; plus, complications arising from dealing with endangered species. In consequence, eco-evolutionary modeling offers an opportunity to overcome these limitations and complement empirical studies, understand the action and limitations of underlying mechanisms, and project into possible future scenarios. In this work I take a modeling approach and investigate the effect and relative importance of evolutionary mechanisms (including phenotypic plasticity) on the ability for local adaptation of populations with different life strategy experiencing climate change scenarios. For this, I performed a review on the state of the art of eco-evolutionary Individual-Based Models (IBMs) and identify gaps for future research. Then, I used the results from the review to develop an eco-evolutionary individual-based modeling tool to study the role of genetic and plastic mechanisms in promoting local adaption of populations of organisms with different life strategies experiencing scenarios of climate change and environmental stochasticity. The environment was simulated through a climate variable (e.g., temperature) defining a phenotypic optimum moving at a given rate of change. The rate of change was changed to simulate different scenarios of climate change (no change, slow, medium, rapid climate change). Several scenarios of stochastic noise color resembling different climatic conditions were explored. Results show that populations of sexual species will rely mainly on standing genetic variation and phenotypic plasticity for local adaptation. Population of species with relatively slow growth rate (e.g., large mammals) – especially those of small size – are the most vulnerable, particularly if their plasticity is limited (i.e., specialist species). In addition, whenever organisms from these populations are capable of adaptive plasticity, they can buffer fitness losses in reddish climatic conditions. Likewise, whenever they can adjust their plastic response (e.g., bed-hedging strategy) they will cope with bluish environmental conditions as well. In contrast, life strategies of high fecundity can rely on non-adaptive plasticity for their local adaptation to novel environmental conditions, unless the rate of change is too rapid. A recommended management measure is to guarantee interconnection of isolated populations into metapopulations, such that the supply of useful genetic variation can be increased, and, at the same time, provide them with movement opportunities to follow their preferred niche, when local adaptation becomes problematic. This is particularly important for bluish and reddish climatic conditions, when the rate of change is slow, or for any climatic condition when the level of stress (rate of change) is relatively high.
Phytoplankton growth depends not only on the mean intensity but also on the dynamics of the light supply. The nonlinear light-dependency of growth is characterized by a small number of basic parameters: the compensation light intensity PARcompμ, where production and losses are balanced, the growth efficiency at sub-saturating light αµ, and the maximum growth rate at saturating light µmax. In surface mixed layers, phytoplankton may rapidly move between high light intensities and almost darkness. Because of the different frequency distribution of light and/or acclimation processes, the light-dependency of growth may differ between constant and fluctuating light. Very few studies measured growth under fluctuating light at a sufficient number of mean light intensities to estimate the parameters of the growth-irradiance relationship. Hence, the influence of light dynamics on µmax, αµ and PARcompμ are still largely unknown. By extension, accurate modelling predictions of phytoplankton development under fluctuating light exposure remain difficult to make. This PhD thesis does not intend to directly extrapolate few experimental results to aquatic systems – but rather improving the mechanistic understanding of the variation of the light-dependency of growth under light fluctuations and effects on phytoplankton development.
In Lake TaiHu and at the Three Gorges Reservoir (China), we incubated phytoplankton communities in bottles placed either at fixed depths or moved vertically through the water column to mimic vertical mixing. Phytoplankton at fixed depths received only the diurnal changes in light (defined as constant light regime), while phytoplankton received rapidly fluctuating light by superimposing the vertical light gradient on the natural sinusoidal diurnal sunlight. The vertically moved samples followed a circular movement with 20 min per revolution, replicating to some extent the full overturn of typical Langmuir cells. Growth, photosynthesis, oxygen production and respiration of communities (at Lake TaiHu) were
measured. To complete these investigations, a physiological experiment was performed in the laboratory on a toxic strain of Microcystis aeruginosa (FACBH 1322) incubated under 20 min period fluctuating light. Here, we measured electron transport rates and net oxygen production at a much higher time resolution (single minute timescale).
The present PhD thesis provides evidence for substantial effects of fluctuating light on the eco-physiology of phytoplankton. Both experiments performed under semi-natural conditions in Lake TaiHu and at the Three Gorges Reservoir gave similar results. The significant decline in community growth efficiencies αµ under fluctuating light was caused for a great share by different frequency distribution of light intensities that shortened the effective daylength for production. The remaining gap in community αµ was attributed to species-specific photoacclimation mechanisms and to light-dependent respiratory losses. In contrast, community maximal growth rates µmax were similar between incubations at constant and fluctuating light. At daily growth saturating light supply, differences in losses for biosynthesis between the two light regimes were observed. Phytoplankton experiencing constant light suffered photo-inhibition - leading to photosynthesis foregone and additional respiratory costs for photosystems repair. On the contrary, intermittent exposure to low and high light intensities prevented photo-inhibition of mixed algae but forced them to develop alternative light strategy. They better harvested and exploited surface irradiance by enhancing their photosynthesis. In the laboratory, we showed that Microcystis aeruginosa increased its oxygen consumption by dark respiration in the light few minutes only after exposure to increasing light intensities. More, we proved that within a simulated Langmuir cell, the net production at saturating light and the compensation light intensity for production at limiting light are positively related. These results are best explained by an accumulation of photosynthetic products at increasing irradiance and mobilization of these fresh resources by rapid enhancement of dark respiration for maintenance and biosynthesis at decreasing irradiance. At the daily timescale, we showed that the enhancement of photosynthesis at high irradiance for biosynthesis of species increased their maintenance respiratory costs at limiting light. Species-specific growth at saturating light µmax and compensation light intensity for growth PARcompμ of species incubated in Lake TaiHu were positively related. Because of this species-specific physiological tradeoff, species displayed different light affinities to limiting and saturating light - thereby exhibiting a gleaner-opportunist tradeoff. In Lake TaiHu, we showed that inter-specific differences in light acquisition traits (µmax and PARcompμ) allowed coexis¬tence of species on a gradient of constant
light while avoiding competitive exclusion. More interestingly we demonstrated for the first time that vertical mixing (inducing fluctuating light supply for phytoplankton) may alter or even reverse the light utilization strategies of species within couple of days. The intra-specific variation in traits under fluctuating light increased the niche space for acclimated species, precluding competitive exclusion.
Overall, this PhD thesis contributes to a better understanding of phytoplankton eco-physiology under fluctuating light supply. This work could enhance the quality of predictions of phytoplankton development under certain weather conditions or climate change scenarios.
Animal personality may affect an animal’s mobility in a given landscape, influencing its propensity to take risks in an unknown environment. We investigated the mobility of translocated common voles in two corridor systems 60 m in length and differing in width (1 m and 3 m). Voles were behaviorally phenotyped in repeated open field and barrier tests. Observed behavioral traits were highly repeatable and described by a continuous personality score. Subsequently, animals were tracked via an automated very high frequency (VHF) telemetry radio tracking system to monitor their movement patterns in the corridor system. Although personality did not explain movement patterns, corridor width determined the amount of time spent in the habitat corridor. Voles in the narrow corridor system entered the corridor faster and spent less time in the corridor than animals in the wide corridor. Thus, landscape features seem to affect movement patterns more strongly than personality. Meanwhile, site characteristics, such as corridor width, could prove to be highly important when designing corridors for conservation, with narrow corridors facilitating faster movement through landscapes than wider corridors.
Light-switchable proteins are being used increasingly to understand and manipulate complex molecular systems. The success of this approach has fueled the development of tailored photo-switchable proteins, to enable targeted molecular events to be studied using light. The development of novel photo-switchable tools has to date largely relied on rational design. Complementing this approach with directed evolution would be expected to facilitate these efforts. Directed evolution, however, has been relatively infrequently used to develop photo-switchable proteins due to the challenge presented by high-throughput evaluation of switchable protein activity. This thesis describes the development of two genetic circuits that can be used to evaluate libraries of switchable proteins, enabling optimization of both the on- and off-states. A screening system is described, which permits detection of DNA-binding activity based on conditional expression of a fluorescent protein. In addition, a tunable selection system is presented, which allows for the targeted selection of protein-protein interactions of a desired affinity range. This thesis additionally describes the development and characterization of a synthetic protein that was designed to investigate chromophore reconstitution in photoactive yellow protein (PYP), a promising scaffold for engineering photo-controlled protein tools.
Since half a century, cytometry has been a major scientific discipline in the field of cytomics - the study of system’s biology at single cell level. It enables the investigation of physiological processes, functional characteristics and rare events with proteins by analysing multiple parameters on an individual cell basis. In the last decade, mass cytometry has been established which increased the parallel measurement to up to 50 proteins. This has shifted the analysis strategy from conventional consecutive manual gates towards multi-dimensional data processing. Novel algorithms have been developed to tackle these high-dimensional protein combinations in the data. They are mainly based on clustering or non-linear dimension reduction techniques, or both, often combined with an upstream downsampling procedure. However, these tools have obstacles either in comprehensible interpretability, reproducibility, computational complexity or in comparability between samples and groups.
To address this bottleneck, a reproducible, semi-automated cytometric data mining workflow PRI (pattern recognition of immune cells) is proposed which combines three main steps: i) data preparation and storage; ii) bin-based combinatorial variable engineering of three protein markers, the so called triploTs, and subsequent sectioning of these triploTs in four parts; and iii) deployment of a data-driven supervised learning algorithm, the cross-validated elastic-net regularized logistic regression, with these triploT sections as input variables. As a result, the selected variables from the models are ranked by their prevalence, which potentially have discriminative value. The purpose is to significantly facilitate the identification of meaningful subpopulations, which are most distinguish between two groups. The proposed workflow PRI is exemplified by a recently published public mass cytometry data set. The authors found a T cell subpopulation which is discriminative between effective and ineffective treatment of breast carcinomas in mice. With PRI, that subpopulation was not only validated, but was further narrowed down as a particular Th1 cell population. Moreover, additional insights of combinatorial protein expressions are revealed in a traceable manner. An essential element in the workflow is the reproducible variable engineering. These variables serve as basis for a clearly interpretable visualization, for a structured variable exploration and as input layers in neural network constructs.
PRI facilitates the determination of marker levels in a semi-continuous manner. Jointly with the combinatorial display, it allows a straightforward observation of correlating patterns, and thus, the dominant expressed markers and cell hierarchies. Furthermore, it enables the identification and complex characterization of discriminating subpopulations due to its reproducible and pseudo-multi-parametric pattern presentation. This endorses its applicability as a tool for unbiased investigations on cell subsets within multi-dimensional cytometric data sets.
Trace elements, like Cu, Zn, Fe, or Se, are important for the proper functioning of antioxidant enzymes. However, in excessive amounts, they can also act as pro-oxidants. Accordingly, trace elements influence redox-modulated signaling pathways, such as the Nrf2 pathway. Vice versa, Nrf2 target genes belong to the group of transport and metal binding proteins. In order to investigate whether Nrf2 directly regulates the systemic trace element status, we used mice to study the effect of a constitutive, whole-body Nrf2 knockout on the systemic status of Cu, Zn, Fe, and Se. As the loss of selenoproteins under Se-deprived conditions has been described to further enhance Nrf2 activity, we additionally analyzed the combination of Nrf2 knockout with feeding diets that provide either suboptimal, adequate, or supplemented amounts of Se. Experiments revealed that the Nrf2 knockout partially affected the trace element concentrations of Cu, Zn, Fe, or Se in the intestine, liver, and/or plasma. However, aside from Fe, the other three trace elements were only marginally modulated in an Nrf2-dependent manner. Selenium deficiency mainly resulted in increased plasma Zn levels. One putative mediator could be the metal regulatory transcription factor 1, which was up-regulated with an increasing Se supply and downregulated in Se-supplemented Nrf2 knockout mice.