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Depending on the biochemical and biotechnical approach, the aim of this work was to understand the mechanism of protein-glucan interactions in regulation and control of starch degradation. Although starch degradation starts with the phosphorylation process, the mechanisms by which this process is controlling and adjusting starch degradation are not yet fully understood. Phosphorylation is a major process performed by the two dikinases enzymes α-glucan, water dikinase (GWD) and phosphoglucan water dikinase (PWD). GWD and PWD enzymes phosphorylate the starch granule surface; thereby stimulate starch degradation by hydrolytic enzymes. Despite these important roles for GWD and PWD, so far the biochemical processes by which these enzymes are able to regulate and adjust the rate of phosphate incorporation into starch during the degradation process haven‘t been understood. Recently, some proteins were found associated with the starch granule. Two of these proteins are named Early Starvation Protein 1 (ESV1) and its homologue Like-Early Starvation Protein 1 (LESV). It was supposed that both are involved in the control of starch degradation, but their function has not been clearly known until now. To understand how ESV1 and LESV-glucan interactions are regulated and affect the starch breakdown, it was analyzed the influence of ESV1 and LESV proteins on the phosphorylating enzyme GWD and PWD and hydrolysing enzymes ISA, BAM, and AMY. However, the analysis determined the location of LESV and ESV1 in the chloroplast stroma of Arabidopsis. Mass spectrometry data predicted ESV1and LESV proteins as a product of the At1g42430 and At3g55760 genes with a predicted mass of ~50 kDa and ~66 kDa, respectively. The ChloroP program predicted that ESV1 lacks the chloroplast transit peptide, but it predicted the first 56 amino acids N-terminal region as a chloroplast transit peptide for LESV. Usually, the transit peptide is processed during transport of the proteins into plastids. Given that this processing is critical, two forms of each ESV1 and LESV were generated and purified, a full-length form and a truncated form that lacks the transit peptide, namely, (ESV1and tESV1) and (LESV and tLESV), respectively. Both protein forms were included in the analysis assays, but only slight differences in glucan binding and protein action between ESV1 and tESV1 were observed, while no differences in the glucan binding and effect on the GWD and PWD action were observed between LESV and tLESV. The results revealed that the presence of the N-terminal is not massively altering the action of ESV1 or LESV. Therefore, it was only used the ESV1 and tLESV forms data to explain the function of both proteins.
However, the analysis of the results revealed that LESV and ESV1 proteins bind strongly at the starch granule surface. Furthermore, not all of both proteins were released after their incubation with starches after washing the granules with 2% [w/v] SDS indicates to their binding to the deeper layers of the granule surface. Supporting of this finding comes after the binding of both proteins to starches after removing the free glucans chains from the surface by the action of ISA and BAM. Although both proteins are capable of binding to the starch structure, only LESV showed binding to amylose, while in ESV1, binding was not observed. The alteration of glucan structures at the starch granule surface is essential for the incorporation of phosphate into starch granule while the phosphorylation of starch by GWD and PWD increased after removing the free glucan chains by ISA. Furthermore, PWD showed the possibility of starch phosphorylation without prephosphorylation by GWD.
Biochemical studies on protein-glucan interactions between LESV or ESV1 with different types of starch showed a potentially important mechanism of regulating and adjusting the phosphorylation process while the binding of LESV and ESV1 leads to altering the glucan structures of starches, hence, render the effect of the action of dikinases enzymes (GWD and PWD) more able to control the rate of starch degradation. Despite the presence of ESV1 which revealed an antagonistic effect on the PWD action as the PWD action was decreased without prephosphorylation by GWD and increased after prephosphorylation by GWD (Chapter 4), PWD showed a significant reduction in its action with or without prephosphorylation by GWD in the presence of ESV1 whether separately or together with LESV (Chapter 5). However, the presence of LESV and ESV1 together revealed the same effect compared to the effect of each one alone on the phosphorylation process, therefore it is difficult to distinguish the specific function between them. However, non-interactions were detected between LESV and ESV1 or between each of them with GWD and PWD or between GWD and PWD indicating the independent work for these proteins. It was also observed that the alteration of the starch structure by LESV and ESV1 plays a role in adjusting starch degradation rates not only by affecting the dikinases but also by affecting some of the hydrolysing enzymes since it was found that the presence of LESV and ESV1leads to the reduction of the action of BAM, but does not abolish it.
Bacteria are one of the most widespread kinds of microorganisms that play essential roles in many biological and ecological processes. Bacteria live either as independent individuals or in organized communities. At the level of single cells, interactions between bacteria, their neighbors, and the surrounding physical and chemical environment are the foundations of microbial processes. Modern microscopy imaging techniques provide attractive and promising means to study the impact of these interactions on the dynamics of bacteria. The aim of this dissertation is to deepen our understanding four fundamental bacterial processes – single-cell motility, chemotaxis, bacterial interactions with environmental constraints, and their communication with neighbors – through a live cell imaging technique. By exploring these processes, we expanded our knowledge on so far unexplained mechanisms of bacterial interactions.
Firstly, we studied the motility of the soil bacterium Pseudomonas putida (P. putida), which swims through flagella propulsion, and has a complex, multi-mode swimming tactic. It was recently reported that P. putida exhibits several distinct swimming modes – the flagella can push and pull the cell body or wrap around it. Using a new combined phase-contrast and fluorescence imaging set-up, the swimming mode (push, pull, or wrapped) of each run phase was automatically recorded, which provided the full swimming statistics of the multi-mode swimmer. Furthermore, the investigation of cell interactions with a solid boundary illustrated an asymmetry for the different swimming modes; in contrast to the push and pull modes, the curvature of runs in wrapped mode was not affected by the solid boundary. This finding suggested that having a multi-mode swimming strategy may provide further versatility to react to environmental constraints.
Then we determined how P. putida navigates toward chemoattractants, i.e. its chemotaxis strategies. We found that individual run modes show distinct chemotactic responses in nutrition gradients. In particular, P. putida cells exhibited an asymmetry in their chemotactic responsiveness; the wrapped mode (slow swimming mode) was affected by the chemoattractant, whereas the push mode (fast swimming mode) was not. These results can be seen as a starting point to understand more complex chemotaxis strategies of multi-mode swimmers going beyond the well-known paradigm of Escherichia coli, that exhibits only one swimming mode.
Finally we considered the cell dynamics in a dense population. Besides physical interactions with their neighbors, cells communicate their activities and orchestrate their population behaviors via quorum-sensing. Molecules that are secreted to the surrounding by the bacterial cells, act as signals and regulate the cell population behaviour. We studied P. putida’s motility in a dense population by exposing the cells to environments with different concentrations of chemical signals. We found that higher amounts of chemical signals in the surrounding influenced the single-cell behaviourr, suggesting that cell-cell communications may also affect the flagellar dynamics.
In summary, this dissertation studies the dynamics of a bacterium with a multi-mode swimming tactic and how it is affected by the surrounding environment using microscopy imaging. The detailed description of the bacterial motility in fundamental bacterial processes can provide new insights into the ecology of microorganisms.
Potato is the 4th most important food crop in the world. Especially in tropical and sub-tropical potato production, drought is a yield limiting factor. Potato is sensitive to water stress. Potato yield loss under water stress could be reduced by using tolerant varieties and adjusted agronomic practices. Direct selection for yield under water-stressed conditions requires long selection cycles. Thus, identification of markers for marker-assisted selection may speed up breeding. The objective of this thesis is to identify morphological markers for drought tolerance by continuously monitoring plant growth and canopy temperature with an automatic phenotyping system.
The phenotyping was performed in drought-stress experiments that were conducted in population A with 64 genotypes and population B with 21 genotypes in the screenhouse in 2015 and 2016 (population A) and in 2017 and 2018 (population B). Drought tolerance was quantified as deviation of the relative tuber starch yield from the experimental median (DRYM) and parent median (DRYMp). Relative tuber starch yield is starch yield under drought stress relative to the average starch yield of the respective cultivar under control conditions in the same experiment. The specific DRYM value was calculated based on the yield data of the same experiment or the global DRYM that was calculated from yield data derived from data combined over yeas of respective population or across multiple experiments including VALDIS and TROST experiments (2011-2016).
Analysis of variance found a significant effect of genotype on DRYM indicating that the tolerance variation required for marker identification was given in both populations.
Canopy growth was monitored continuously six times a day over five to ten weeks by a laser scanner system and yielded information on leaf area, plant height and leaf angle for population A and additionally on leaf inclination and light penetration depth for population B. Canopy temperature was measured 48 times a day over six to seven weeks by infrared thermometry in population B. From the continuous IRT surface temperature data set, the canopy temperature for each plant was selected by matching the time stamp of the IRT data with laser scanner data.
Mean, maximum, range and growth rate values were calculated from continuous laser scanner measurements of respective canopy parameters. Among the canopy parameters, the maximum and mean values in long-term stress conditions showed better correlation with DRYM values calculated in the same experiment than growth rate and diurnal range values. Therefore, drought tolerance index prediction was done from maximum and mean values of canopy parameters.
The tolerance index in specific experiment condition was linearly predicted by simple regression model from different single canopy parameters under long-term stress condition in population A (2016) and population B (2017 and 2018). Among the canopy parameters maximum light penetration depth (2017), mean leaf angle (2017, 2018, and 2016), mean leaf inclination or mean canopy temperature depression (2017 and 2018), maximum plant height (2017) were selected as tolerance predictors. However, no single parameters were sufficient to predict DRYM. Therefore, several independent parameters were integrated in a multiple regression model.
In multiple regression model, specific experiment DRYM values in population A was predicted from mean leaf angle (2016). In population B, specific tolerance could be predicted from maximum light penetration depth and mean leaf inclination (2017) and mean leaf inclination (2018) or mean canopy temperature depression and mean leaf angle (2018).
In data combined over season of population A, the multiple linear regression model selected maximum plant height and mean leaf angle as tolerance predictor. In Population B, mean leaf inclination was selected as tolerance predictor. However, in population A, the variation explained by the final model was too low.
Furthermore, the average tolerances respective to parent median (2011-2018) across FGH plants or all plants (FGH and field) were predicted from maximum plant height (population A) and maximum plant height and mean leaf inclination (population B). Altogether, canopy parameters could be used as markers for drought tolerance. Therefore, water stress breeding in potato could be speed up through using leaf inclination, light penetration depth, plant height and canopy temperature depression as markers for drought tolerance, especially in long-term stress conditions.
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.
Glycosylphosphatidylinositols (GPIs) are highly complex glycolipids that serve as membrane anchors to a large variety of eukaryotic proteins. These are covalently attached to a group of peripheral proteins called GPI-anchored proteins (GPI-APs) through a post-translational modification in the endoplasmic reticulum. The GPI anchor is a unique structure composed of a glycan, with phospholipid tail at one end and a phosphoethanolamine linker at the other where the protein attaches. The glycan part of the GPI comprises a conserved pseudopentasaccharide core that could branch out to carry additional glycosyl or phosphoethanolamine units. GPI-APs are involved in a diverse range of cellular processes, few of which are signal transduction, protein trafficking, pathogenesis by protozoan parasites like the malaria- causing parasite Plasmodium falciparum. GPIs can also exist freely on the membrane surface without an attached protein such as those found in parasites like Toxoplasma gondii, the causative agent of Toxoplasmosis. These molecules are both structurally and functionally diverse, however, their structure-function relationship is still poorly understood. This is mainly because no clear picture exists regarding how the protein and the glycan arrange with respect to the lipid layer. Direct experimental evidence is rather scarce, due to which inconclusive pictures have emerged, especially regarding the orientation of GPIs and GPI-APs on membrane surfaces and the role of GPIs in membrane organization. It appears that computational modelling through molecular dynamics simulations would be a useful method to make progress. In this thesis, we attempt to explore characteristics of GPI anchors and GPI-APs embedded in lipid bilayers by constructing molecular models at two different resolutions – all-atom and coarse-grained.
First, we show how to construct a modular molecular model of GPIs and GPI-anchored proteins that can be readily extended to a broad variety of systems, addressing the micro-heterogeneity of GPIs. We do so by creating a hybrid link to which GPIs of diverse branching and lipid tails of varying saturation with their optimized force fields, GLYCAM06 and Lipid14 respectively, can be attached. Using microsecond simulations, we demonstrate that GPI prefers to “flop-down” on the membrane, thereby, strongly interacting with the lipid heads, over standing upright like a “lollipop”. Secondly, we extend the model of the GPI core to carry out a systematic study of the structural aspects of GPIs carrying different side chains (parasitic and human GPI variants) inserted in lipid bilayers. Our results demonstrate the importance of the side branch residues as these are the most accessible, and thereby, recognizable epitopes. This finding qualitatively agrees with experimental observations that highlight the role of the side branches in immunogenicity of GPIs and the specificity thereof. The overall flop-down orientation of the GPIs with respect to the bilayer surface presents the side chain residues to face the solvent. Upon attaching the green fluorescent protein (GFP) to the GPI, it is seen to lie in close proximity to the bilayer, interacting both with the lipid heads and glycan part of the GPI. However the orientation of GFP is sensitive to the type of GPI it is attached to. Finally, we construct a coarse-grained model of the GPI and GPI-anchored GFP using a modified version of the MARTINI force-field, using which the timescale is enhanced by at least an order of magnitude compared to the atomistic system.
This study provides a theoretical perspective on the conformational behavior of the GPI core and some of its branched variations in presence of lipid bilayers, as well as draws comparisons with experimental observations. Our modular atomistic model of GPI can be further employed to study GPIs of variable branching, and thereby, aid in designing future experiments especially in the area of vaccines and drug therapies. Our coarse-grained model can be used to study dynamic aspects of GPIs and GPI-APs w.r.t plasma membrane organization. Furthermore, the backmapping technique of converting coarse-grained trajectory back to the atomistic model would enable in-depth structural analysis with ample conformational sampling.
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.
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.
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.
Understanding how organisms adapt to their local environment is a major focus of evolutionary biology. Local adaptation occurs when the forces of divergent natural selection are strong enough compared to the action of other evolutionary forces. An improved understanding of the genetic basis of local adaptation can inform about the evolutionary processes in populations and is of major importance because of its relevance to altered selection pressures due to climate change. So far, most insights have been gained by studying model organisms, but our understanding about the genetic basis of local adaptation in wild populations of species with little genomic resources is still limited.
With the work presented in this thesis I therefore set out to provide insights into the genetic basis of local adaptation in populations of two voles species: the common vole (Microtus arvalis) and the bank vole (Myodes glareolus). Both voles species are small mammals, they have a high evolutionary potential compared to their dispersal capabilities and are thus likely to show genetic responses to local conditions, moreover, they have a wide distribution in which they experience a broad range of different environmental conditions, this makes them an ideal species to study local adaptation.
The first study focused on producing a novel mitochondrial genome to facilitate further research in M. arvalis. To this end, I generated the first mitochondrial genome of M. arvalis using shotgun sequencing and an iterative mapping approach. This was subsequently used in a phylogenetic analysis that produced novel insights into the phylogenetic relationships of the Arvicolinae.
The following two studies then focused on the genetic basis of local adaptation using ddRAD-sequencing data and genome scan methods. The first of these involved sequencing the genomic DNA of individuals from three low-altitude and three high-altitude M. arvalis study sites in the Swiss Alps. High-altitude environments with their low temperatures and low levels of oxygen (hypoxia) pose considerable challenges for small mammals. With their small body size and proportional large body surface they have to sustain high rates of aerobic metabolism to support thermogenesis and locomotion, which can be restricted with only limited levels of oxygen available. To generate insights into high-altitude adaptation I identified a large number of single nucleotide polymorphisms (SNPs). These data were first used to identify high levels of differentiation between study sites and a clear pattern of population structure, in line with a signal of isolation by distance. Using genome scan methods, I then identified signals of selection associated with differences in altitude in genes with functions related to oxygen transport into tissue and genes related to aerobic metabolic pathways. This indicates that hypoxia is an important selection pressure driving local adaptation at high altitude in M. arvalis. A number of these genes were linked with high-altitude adaptation in other species before, which lead to the suggestion that high-altitude populations of several species have evolved in a similar manner as a response to the unique conditions at high altitude
The next study also involved the genetic basis of local adaptation, here I provided insights into climate-related adaptation in M. glareolus across its European distribution. Climate is an important environmental factor affecting the physiology of all organisms. In this study I identified a large number of SNPs in individuals from twelve M. glareolus populations distributed across Europe. I used these, to first establish that populations are highly differentiated and found a strong pattern of population structure with signal of isolation by distance. I then employed genome scan methods to identify candidate loci showing signals of selection associated with climate, with a particular emphasis on polygenic loci. A multivariate analysis was used to determine that temperature was the most important climate variable responsible for adaptive genetic variation among all variables tested. By using novel methods and genome annotation of related species I identified the function of genes of candidate loci. This showed that genes under selection have functions related to energy homeostasis and immune processes. Suggesting that M. glareolus populations have evolved in response to local temperature and specific local pathogenic selection pressures.
The studies presented in this thesis provide evidence for the genetic basis of local adaptation in two vole species across different environmental gradients, suggesting that the identified genes are involved in local adaptation. This demonstrates that with the help of novel methods the study of wild populations, which often have little genomic resources available, can provide unique insights into evolutionary processes.
Cardiac valves are essential for the continuous and unidirectional flow of blood throughout the body. During embryonic development, their formation is strictly connected to the mechanical forces exerted by blood flow. The endocardium that lines the interior of the heart is a specialized endothelial tissue and is highly sensitive to fluid shear stress. Endocardial cells harbor a signal transduction machinery required for the translation of these forces into biochemical signaling, which strongly impacts cardiac morphogenesis and physiology. To date, we lack a solid understanding on the mechanisms by which endocardial cells sense the dynamic mechanical stimuli and how they trigger different cellular responses. In the zebrafish embryo, endocardial cells at the atrioventricular canal respond to blood flow by rearranging from a monolayer to a double-layer, composed of a luminal cell population subjected to blood flow and an abluminal one that is not exposed to it. These early morphological changes lead to the formation of an immature valve leaflet. While previous studies mainly focused on genes that are positively regulated by shear stress, the mechanisms regulating cell behaviors and fates in cells that lack the stimulus of blood flow are largely unknown. One key discovery of my work is that the flow-sensitive Notch receptor and Krüppel-like factor (Klf) 2, one of the best characterized flow-regulated transcriptional factors, are activated by shear stress but that they function in two parallel signal transduction pathways. Each of these two pathways is essential for the rearrangement of atrioventricular cells into an immature double-layered valve leaflets. A second key discovery of my study is the finding that both Notch and Klf2 signaling negatively regulate the expression of the angiogenesis receptor Vegfr3/Flt4, which becomes restricted to abluminal endocardial cells of the valve leaflet. Within these cells, Flt4 downregulates the expressions of the cell adhesion proteins Alcam and VE-cadherin. A loss of Flt4 causes abluminal endocardial cells to ectopically express Notch, which is normally restricted to luminal cells, and impairs valve morphology. My study suggests that abluminal endocardial cells that do not experience mechanical stimuli loose Notch expression and this triggers expression of Flt4. In turn, Flt4 negatively regulates Notch on the abluminal side of the valve leaflet. These antagonistic signaling activities and fine-tuned gene regulatory mechanisms ultimately shape cardiac valve leaflets by inducing unique differences in the fates of endocardial cells.