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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.
After endosymbiosis, chloroplasts lost most of their genome. Many former endosymbiotic genes are now nucleus-encoded and the products are re-imported post-translationally. Consequently, photosynthetic complexes are built of nucleus- and plastid-encoded subunits in a well-defined stoichiometry. In Chlamydomonas, the translation of chloroplast-encoded photosynthetic core subunits is feedback-regulated by the assembly state of the complexes they reside in. This process is called Control by Epistasy of Synthesis (CES) and enables the efficient production of photosynthetic core subunits in stoichiometric amounts. In chloroplasts of embryophytes, only Rubisco subunits have been shown to be feedback-regulated. That opens the question if there is additional CES regulation in embryophytes. I analyzed chloroplast gene expression in tobacco and Arabidopsis mutants with assembly defects for each photosynthetic complex to broadly answer this question. My results (i) confirmed CES within Rubisco and hint to potential translational feedback regulation in the synthesis of (ii) cytochrome b6f (Cyt b6f) and (iii) photosystem II (PSII) subunits. This work suggests a CES network in PSII that links psbD, psbA, psbB, psbE, and potentially psbH expression by a feedback mechanism that at least partially differs from that described in Chlamydomonas. Intriguingly, in the Cyt b6f complex, a positive feedback regulation that coordinates the synthesis of PetA and PetB was observed, which was not previously reported in Chlamydomonas. No evidence for CES interactions was found in the expression of NDH and ATP synthase subunits of embryophytes. Altogether, this work provides solid evidence for novel assembly-dependent feedback regulation mechanisms controlling the expression of photosynthetic genes in chloroplasts of embryophytes.
In order to obtain a comprehensive inventory of the rbcL and psbA RNA-binding proteomes (including factors that regulate their expression, especially factors involved in CES), an aptamer based affinity purification method was adapted and refined for the specific purification these transcripts from tobacco chloroplasts. To this end, three different aptamers (MS2, Sephadex ,and streptavidin binding) were stably introduced into the 3’ UTRs of psbA and rbcL by chloroplast transformation. RNA aptamer based purification and subsequent chip analysis (RAP Chip) demonstrated a strong enrichment of psbA and rbcL transcripts and currently, ongoing mass spectrometry analyses shall reveal potential regulatory factors. Furthermore, the suborganellar localization of MS2 tagged psbA and rbcL transcripts was analyzed by a combined affinity, immunology, and electron microscopy approach and demonstrated the potential of aptamer tags for the examination of the spatial distribution of chloroplast transcripts.
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.
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.
With populations growing worldwide and climate change threatening food production there is an urgent need to find ways to ensure food security. Increasing carbon fixation rate in plants is a promising approach to boost crop yields. The carbon-fixing enzyme Rubisco catalyzes, beside the carboxylation reaction, also an oxygenation reaction that generates glycolate-2P, which needs to be recycled via a metabolic route termed photorespiration. Photorespiration dissipates energy and most importantly releases previously fixed CO2, thus significantly lowering carbon fixation rate and yield. Engineering plants to omit photorespiratory CO2 release is the goal of the FutureAgriculture consortium and this thesis is part of this collaboration. The consortium aims to establish alternative glycolate-2P recycling routes that do not release CO2. Ultimately, they are expected to increase carbon fixation rates and crop yields. Natural and novel reactions, which require enzyme engineering, were considered in the pathway design process. Here I describe the engineering of two pathways, the arabinose-5P and the erythrulose shunt. They were designed to recycle glycolate-2P via glycolaldehyde into a sugar phosphate and thereby reassimilate glycolate-2P to the Calvin cycle. I used Escherichia coli gene deletion strains to validate and characterize the activity of both synthetic shunts. The strains’ auxotrophies can be alleviated by the activity of the synthetic route, thus providing a direct way to select for pathway activity. I introduced all pathway components to these dedicated selection strains and discovered inhibitions, limitations and metabolic cross talk interfering with pathway activity. After resolving these issues, I was able to show the in vivo activity of all pathway components and combine them into functional modules.. Specifically, I demonstrate the activity of a new-to-nature module of glycolate reduction to glycolaldehyde. Also, I successfully show a new glycolaldehyde assimilation route via arabinose-5P to ribulose-5P. In addition, all necessary enzymes for glycolaldehyde assimilation via L-erythrulose were shown to be active and an L-threitol assimilation route via L-erythrulose was established in E. coli. On their own, these findings demonstrate the power of using an easily engineerable microbe to test novel pathways; combined, they will form the basis for implementing photorespiration bypasses in plants.
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.
The Cheb Basin (CZ) is a shallow Neogene intracontinental basin located in the western Eger Rift. The Cheb Basin is characterized by active seismicity and diffuse degassing of mantle-derived CO2 in mofette fields. Within the Cheb Basin, the Hartoušov mofette field shows a daily CO2 flux of 23–97 tons. More than 99% of CO2 released over an area of 0.35 km2. Seismic active periods have been observed in 2000 and 2014 in the Hartoušov mofette field. Due to the active geodynamic processes, the Cheb Basin is considered to be an ideal region for the continental deep biosphere research focussing on the interaction of biological processes with geological processes.
To study the influence of CO2 degassing on microbial community in the surface and subsurface environments, two 3-m shallow drillings and a 108.5-m deep scientific drilling were conducted in 2015 and 2016 respectively. Additionally, the fluid retrieved from the deep drilling borehole was also recovered. The different ecosystems were compared regarding their geochemical properties, microbial abundances, and microbial community structures. The geochemistry of the mofette is characterized by low pH, high TOC, and sulfate contents while the subsurface environment shows a neutral pH, and various TOC and sulfate contents in different lithological settings. Striking differences in the microbial community highlight the substantial impact of elevated CO2 concentrations and high saline groundwater on microbial processes. In general, the microorganisms had low abundance in the deep subsurface sediment compared with the shallow mofette. However, within the mofette and the deep subsurface sediment, the abundance of microbes does not show a typical decrease with depth, indicating that the uprising CO2-rich groundwater has a strong influence on the microbial communities via providing sufficient substrate for anaerobic chemolithoautotrophic microorganisms. Illumina MiSeq sequencing of the 16S rRNA genes and multivariate statistics reveals that the pH strongly influences the microbial community composition in the mofette, while the subsurface microbial community is significantly influenced by the groundwater which motivated by the degassing CO2. Acidophilic microorganisms show a much higher relative abundance in the mofette. Meanwhile, the OTUs assigned to family Comamonadaceae are the dominant taxa which characterize the subsurface communities. Additionally, taxa involved in sulfur cycling characterizing the microbial communities in both mofette and CO2 dominated subsurface environments.
Another investigated important geo–bio interaction is the influence of the seismic activity. During seismic events, released H2 may serve as the electron donor for microbial hydrogenotrophic processes, such as methanogenesis. To determine whether the seismic events can potentially trigger methanogenesis by the elevated geogenic H2 concentration, we performed laboratory simulation experiments with sediments retrieved from the drillings. The simulation results indicate that after the addition of hydrogen, substantial amounts of methane were produced in incubated mofette sediments and deep subsurface sediments. The methanogenic hydrogenotrophic genera Methanobacterium was highly enriched during the incubation. The modeling of the in-situ observation of the earthquake swarm period in 2000 at the Novy Kostel focal area/Czech Republic and our laboratory simulation experiments reveals a close relation between seismic activities and microbial methane production via earthquake-induced H2 release. We thus conclude that H2 – which is released during seismic activity – can potentially trigger methanogenic activity in the deep subsurface. Based on this conclusion, we further hypothesize that the hydrogenotrophic early life on Earth was boosted by the Late Heavy Bombardment induced seismic activity in approximately 4.2 to 3.8 Ga.
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.