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- Institut für Ernährungswissenschaft (115)
- Department Linguistik (98)
During the last decades, therapeutical proteins have risen to great significance in the pharmaceutical industry. As non-human proteins that are introduced into the human body cause a distinct immune system reaction that triggers their rapid clearance, most newly approved protein pharmaceuticals are shielded by modification with synthetic polymers to significantly improve their blood circulation time. All such clinically approved protein-polymer conjugates contain polyethylene glycol (PEG) and its conjugation is denoted as PEGylation. However, many patients develop anti-PEG antibodies which cause a rapid clearance of PEGylated molecules upon repeated administration. Therefore, the search for alternative polymers that can replace PEG in therapeutic applications has become important. In addition, although the blood circulation time is significantly prolonged, the therapeutic activity of some conjugates is decreased compared to the unmodified protein. The reason is that these conjugates are formed by the traditional conjugation method that addresses the protein's lysine side chains. As proteins have many solvent exposed lysines, this results in a somewhat uncontrolled attachment of polymer chains, leading to a mixture of regioisomers, with some of them eventually affecting the therapeutic performance.
This thesis investigates a novel method for ligating macromolecules in a site-specific manner, using enzymatic catalysis. Sortase A is used as the enzyme: It is a well-studied transpeptidase which is able to catalyze the intermolecular ligation of two peptides. This process is commonly referred to as sortase-mediated ligation (SML). SML constitutes an equilibrium reaction, which limits product yield. Two previously reported methods to overcome this major limitation were tested with polymers without using an excessive amount of one reactant.
Specific C- or N-terminal peptide sequences (recognition sequence and nucleophile) as part of the protein are required for SML. The complementary peptide was located at the polymer chain end. Grafting-to was used to avoid damaging the protein during polymerization. To be able to investigate all possible combinations (protein-recognition sequence and nucleophile-protein as well as polymer-recognition sequence and nucleophile-polymer) all necessary building blocks were synthesized. Polymerization via reversible deactivation radical polymerization (RDRP) was used to achieve a narrow molecular weight distribution of the polymers, which is required for therapeutic use.
The synthesis of the polymeric building blocks was started by synthesizing the peptide via automated solid-phase peptide synthesis (SPPS) to avoid post-polymerization attachment and to enable easy adaptation of changes in the peptide sequence. To account for the different functionalities (free N- or C-terminus) required for SML, different linker molecules between resin and peptide were used.
To facilitate purification, the chain transfer agent (CTA) for reversible addition-fragmentation chain-transfer (RAFT) polymerization was coupled to the resin-immobilized recognition sequence peptide. The acrylamide and acrylate-based monomers used in this thesis were chosen for their potential to replace PEG.
Following that, surface-initiated (SI) ATRP and RAFT polymerization were attempted, but failed. As a result, the newly developed method of xanthate-supported photo-iniferter (XPI) RAFT polymerization in solution was used successfully to obtain a library of various peptide-polymer conjugates with different chain lengths and narrow molar mass distributions.
After peptide side chain deprotection, these constructs were used first to ligate two polymers via SML, which was successful but revealed a limit in polymer chain length (max. 100 repeat units). When utilizing equimolar amounts of reactants, the use of Ni2+ ions in combination with a histidine after the recognition sequence to remove the cleaved peptide from the equilibrium maximized product formation with conversions of up to 70 %.
Finally, a model protein and a nanobody with promising properties for therapeutical use were biotechnologically modified to contain the peptide sequences required for SML. Using the model protein for C- or N-terminal SML with various polymers did not result in protein-polymer conjugates. The reason is most likely the lack of accessibility of the protein termini to the enzyme. Using the nanobody for C-terminal SML, on the other hand, was successful. However, a similar polymer chain length limit was observed as in polymer-polymer SML. Furthermore, in case of the synthesis of protein-polymer conjugates, it was more effective to shift the SML equilibrium by using an excess of polymer than by employing the Ni2+ ion strategy.
Overall, the experimental data from this work provides a good foundation for future research in this promising field; however, more research is required to fully understand the potential and limitations of using SML for protein-polymer synthesis. In future, the method explored in this dissertation could prove to be a very versatile pathway to obtain therapeutic protein-polymer conjugates that exhibit high activities and long blood circulation times.
This thesis explores word order variability in verb-final languages. Verb-final languages have a reputation for a high amount of word order variability. However, that reputation amounts to an urban myth due to a lack of systematic investigation. This thesis provides such a systematic investigation by presenting original data from several verb-final languages with a focus on four Uralic ones: Estonian, Udmurt, Meadow Mari, and South Sámi. As with every urban myth, there is a kernel of truth in that many unrelated verb-final languages share a particular kind of word order variability, A-scrambling, in which the fronted elements do not receive a special information-structural role, such as topic or contrastive focus. That word order variability goes hand in hand with placing focussed phrases further to the right in the position directly in front of the verb. Variations on this pattern are exemplified by Uyghur, Standard Dargwa, Eastern Armenian, and three of the Uralic languages, Estonian, Udmurt, and Meadow Mari. So far for the kernel of truth, but the fourth Uralic language, South Sámi, is comparably rigid and does not feature this particular kind of word order variability. Further such comparably rigid, non-scrambling verb-final languages are Dutch, Afrikaans, Amharic, and Korean. In contrast to scrambling languages, non-scrambling languages feature obligatory subject movement, causing word order rigidity next to other typical EPP effects.
The EPP is a defining feature of South Sámi clause structure in general. South Sámi exhibits a one-of-a-kind alternation between SOV and SAuxOV order that is captured by the assumption of the EPP and obligatory movement of auxiliaries but not lexical verbs. Other languages that allow for SAuxOV order either lack an alternation because the auxiliary is obligatorily present (Macro-Sudan SAuxOVX languages), or feature an alternation between SVO and SAuxOV (Kru languages; V2 with underlying OV as a fringe case). In the SVO–SAuxOV languages, both auxiliaries and lexical verbs move. Hence, South Sámi shows that the textbook difference between the VO languages English and French, whether verb movement is restricted to auxiliaries, also extends to OV languages. SAuxOV languages are an outlier among OV languages in general but are united by the presence of the EPP.
Word order variability is not restricted to the preverbal field in verb-final languages, as most of them feature postverbal elements (PVE). PVE challenge the notion of verb-finality in a language. Strictly verb-final languages without any clause-internal PVE are rare. This thesis charts the first structural and descriptive typology of PVE. Verb-final languages vary in the categories they allow as PVE. Allowing for non-oblique PVE is a pivotal threshold: when non-oblique PVE are allowed, PVE can be used for information-structural effects. Many areally and genetically unrelated languages only allow for given PVE but differ in whether the PVE are contrastive. In those languages, verb-finality is not at stake since verb-medial orders are marked. In contrast, the Uralic languages Estonian and Udmurt allow for any PVE, including information focus. Verb-medial orders can be used in the same contexts as verb-final orders without semantic and pragmatic differences. As such, verb placement is subject to actual free variation. The underlying verb-finality of Estonian and Udmurt can only be inferred from a range of diagnostics indicating optional verb movement in both languages. In general, it is not possible to account for PVE with a uniform analysis: rightwards merge, leftward verb movement, and rightwards phrasal movement are required to capture the cross- and intralinguistic variation.
Knowing that a language is verb-final does not allow one to draw conclusions about word order variability in that language. There are patterns of homogeneity, such as the word order variability driven by directly preverbal focus and the givenness of postverbal elements, but those are not brought about by verb-finality alone. Preverbal word order variability is restricted by the more abstract property of obligatory subject movement, whereas the determinant of postverbal word order variability has to be determined in the future.
The automotive industry is a prime example of digital technologies reshaping mobility. Connected, autonomous, shared, and electric (CASE) trends lead to new emerging players that threaten existing industrial-aged companies. To respond, incumbents need to bridge the gap between contrasting product architecture and organizational principles in the physical and digital realms. Over-the-air (OTA) technology, that enables seamless software updates and on-demand feature additions for customers, is an example of CASE-driven digital product innovation. Through an extensive longitudinal case study of an OTA initiative by an industrial- aged automaker, this dissertation explores how incumbents accomplish digital product innovation. Building on modularity, liminality, and the mirroring hypothesis, it presents a process model that explains the triggers, mechanisms, and outcomes of this process. In contrast to the literature, the findings emphasize the primacy of addressing product architecture challenges over organizational ones and highlight the managerial implications for success.
Human activities modify nature worldwide via changes in the environment, biodiversity and the functioning of ecosystems, which in turn disrupt ecosystem services and feed back negatively on humans. A pressing challenge is thus to limit our impact on nature, and this requires detailed understanding of the interconnections between the environment, biodiversity and ecosystem functioning. These three components of ecosystems each include multiple dimensions, which interact with each other in different ways, but we lack a comprehensive picture of their interconnections and underlying mechanisms. Notably, diversity is often viewed as a single facet, namely species diversity, while many more facets exist at different levels of biological organisation (e.g. genetic, phenotypic, functional, multitrophic diversity), and multiple diversity facets together constitute the raw material for adaptation to environmental changes and shape ecosystem functioning. Consequently, investigating the multidimensionality of ecosystems, and in particular the links between multifaceted diversity, environmental changes and ecosystem functions, is crucial for ecological research, management and conservation. This thesis aims to explore several aspects of this question theoretically.
I investigate three broad topics in this thesis. First, I focus on how food webs with varying levels of functional diversity across three trophic levels buffer environmental changes, such as a sudden addition of nutrients or long-term changes (e.g. warming or eutrophication). I observed that functional diversity generally enhanced ecological stability (i.e. the buffering capacity of the food web) by increasing trophic coupling. More precisely, two aspects of ecological stability (resistance and resilience) increased even though a third aspect (the inverse of the time required for the system to reach its post-perturbation state) decreased with increasing functional diversity. Second, I explore how several diversity facets served as a raw material for different sources of adaptation and how these sources affected multiple ecosystem functions across two trophic levels. Considering several sources of adaptation enabled the interplay between ecological and evolutionary processes, which affected trophic coupling and thereby ecosystem functioning. Third, I reflect further on the multifaceted nature of diversity by developing an index K able to quantify the facet of functional diversity, which is itself multifaceted. K can provide a comprehensive picture of functional diversity and is a rather good predictor of ecosystem functioning. Finally I synthesise the interdependent mechanisms (complementarity and selection effects, trophic coupling and adaptation) underlying the relationships between multifaceted diversity, ecosystem functioning and the environment, and discuss the generalisation of my findings across ecosystems and further perspectives towards elaborating an operational biodiversity-ecosystem functioning framework for research and conservation.
Homomorphisms are a fundamental concept in mathematics expressing the similarity of structures. They provide a framework that captures many of the central problems of computer science with close ties to various other fields of science. Thus, many studies over the last four decades have been devoted to the algorithmic complexity of homomorphism problems. Despite their generality, it has been found that non-uniform homomorphism problems, where the target structure is fixed, frequently feature complexity dichotomies. Exploring the limits of these dichotomies represents the common goal of this line of research.
We investigate the problem of counting homomorphisms to a fixed structure over a finite field of prime order and its algorithmic complexity. Our emphasis is on graph homomorphisms and the resulting problem #_{p}Hom[H] for a graph H and a prime p. The main research question is how counting over a finite field of prime order affects the complexity.
In the first part of this thesis, we tackle the research question in its generality and develop a framework for studying the complexity of counting problems based on category theory. In the absence of problem-specific details, results in the language of category theory provide a clear picture of the properties needed and highlight common ground between different branches of science. The proposed problem #Mor^{C}[B] of counting the number of morphisms to a fixed object B of C is abstract in nature and encompasses important problems like constraint satisfaction problems, which serve as a leading example for all our results. We find explanations and generalizations for a plethora of results in counting complexity. Our main technical result is that specific matrices of morphism counts are non-singular. The strength of this result lies in its algebraic nature. First, our proofs rely on carefully constructed systems of linear equations, which we know to be uniquely solvable. Second, by exchanging the field that the matrix is defined by to a finite field of order p, we obtain analogous results for modular counting. For the latter, cancellations are implied by automorphisms of order p, but intriguingly we find that these present the only obstacle to translating our results from exact counting to modular counting. If we restrict our attention to reduced objects without automorphisms of order p, we obtain results analogue to those for exact counting. This is underscored by a confluent reduction that allows this restriction by constructing a reduced object for any given object. We emphasize the strength of the categorial perspective by applying the duality principle, which yields immediate consequences for the dual problem of counting the number of morphisms from a fixed object.
In the second part of this thesis, we focus on graphs and the problem #_{p}Hom[H]. We conjecture that automorphisms of order p capture all possible cancellations and that, for a reduced graph H, the problem #_{p}Hom[H] features the complexity dichotomy analogue to the one given for exact counting by Dyer and Greenhill. This serves as a generalization of the conjecture by Faben and Jerrum for the modulus 2. The criterion for tractability is that H is a collection of complete bipartite and reflexive complete graphs. From the findings of part one, we show that the conjectured dichotomy implies dichotomies for all quantum homomorphism problems, in particular counting vertex surjective homomorphisms and compactions modulo p. Since the tractable cases in the dichotomy are solved by trivial computations, the study of the intractable cases remains. As an initial problem in a series of reductions capable of implying hardness, we employ the problem of counting weighted independent sets in a bipartite graph modulo prime p. A dichotomy for this problem is shown, stating that the trivial cases occurring when a weight is congruent modulo p to 0 are the only tractable cases. We reduce the possible structure of H to the bipartite case by a reduction to the restricted homomorphism problem #_{p}Hom^{bip}[H] of counting modulo p the number of homomorphisms between bipartite graphs that maintain a given order of bipartition. This reduction does not have an impact on the accessibility of the technical results, thanks to the generality of the findings of part one. In order to prove the conjecture, it suffices to show that for a connected bipartite graph that is not complete, #_{p}Hom^{bip}[H] is #_{p}P-hard. Through a rigorous structural study of bipartite graphs, we establish this result for the rich class of bipartite graphs that are (K_{3,3}\{e}, domino)-free. This overcomes in particular the substantial hurdle imposed by squares, which leads us to explore the global structure of H and prove the existence of explicit structures that imply hardness.
Among the different meanings carried by numerical information, cardinality is fundamental for survival and for the development of basic as well as of higher numerical skills. Importantly, the human brain inherits from evolution a predisposition to map cardinality onto space, as revealed by the presence of spatial-numerical associations (SNAs) in humans and animals. Here, the mapping of cardinal information onto physical space is addressed as a hallmark signature characterizing numerical cognition.
According to traditional approaches, cognition is defined as complex forms of internal information processing, taking place in the brain (cognitive processor). On the contrary, embodied cognition approaches define cognition as functionally linked to perception and action, in the continuous interaction between a biological body and its physical and sociocultural environment.
Embracing the principles of the embodied cognition perspective, I conducted four novel studies designed to unveil how SNAs originate, develop, and adapt, depending on characteristics of the organism, the context, and their interaction. I structured my doctoral thesis in three levels. At the grounded level (Study 1), I unfold the biological foundations underlying the tendency to map cardinal information across space; at the embodied level (Study 2), I reveal the impact of atypical motor development on the construction of SNAs; at the situated level (Study 3), I document the joint influence of visuospatial attention and task properties on SNAs. Furthermore, I experimentally investigate the presence of associations between physical and numerical distance, another numerical property fundamental for the development of efficient mathematical minds (Study 4).
In Study 1, I present the Brain’s Asymmetric Frequency Tuning hypothesis that relies on hemispheric asymmetries for processing spatial frequencies, a low-level visual feature that the (in)vertebrate brain extracts from any visual scene to create a coherent percept of the world. Computational analyses of the power spectra of the original stimuli used to document the presence of SNAs in human newborns and animals, support the brain’s asymmetric frequency tuning as a theoretical account and as an evolutionarily inherited mechanism scaffolding the universal and innate tendency to represent cardinality across horizontal space.
In Study 2, I explore SNAs in children with rare genetic neuromuscular diseases: spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD). SMA children never accomplish independent motoric exploration of their environment; in contrast, DMD children do explore but later lose this ability. The different SNAs reported by the two groups support the critical role of early sensorimotor experiences in the spatial representation of cardinality.
In Study 3, I directly compare the effects of overt attentional orientation during explicit and implicit processing of numerical magnitude. First, the different effects of attentional orienting based on the type of assessment support different mechanisms underlying SNAs during explicit and implicit assessment of numerical magnitude. Secondly, the impact of vertical shifts of attention on the processing of numerical distance sheds light on the correspondence between numerical distance and peri-personal distance.
In Study 4, I document the presence of different SNAs, driven by numerical magnitude and numerical distance, by employing different response mappings (left vs. right and near vs. distant).
In the field of numerical cognition, the four studies included in the present thesis contribute to unveiling how the characteristics of the organism and the environment influence the emergence, the development, and the flexibility of our attitude to represent cardinal information across space, thus supporting the predictions of the embodied cognition approach. Furthermore, they inform a taxonomy of body-centred factors (biological properties of the brain and sensorimotor system) modulating the spatial representation of cardinality throughout the course of life, at the grounded, embodied, and situated levels.
If the awareness for different variables influencing SNAs over the course of life is important, it is equally important to consider the organism as a whole in its sensorimotor interaction with the world. Inspired by my doctoral research, here I propose a holistic perspective that considers the role of evolution, embodiment, and environment in the association of cardinal information with directional space. The new perspective advances the current approaches to SNAs, both at the conceptual and at the methodological levels.
Unveiling how the mental representation of cardinality emerges, develops, and adapts is necessary to shape efficient mathematical minds and achieve economic productivity, technological progress, and a higher quality of life.
Water stored in the unsaturated soil as soil moisture is a key component of the hydrological cycle influencing numerous hydrological processes including hydrometeorological extremes. Soil moisture influences flood generation processes and during droughts when precipitation is absent, it provides plant with transpirable water, thereby sustaining plant growth and survival in agriculture and natural ecosystems.
Soil moisture stored in deeper soil layers e.g. below 100 cm is of particular importance for providing plant transpirable water during dry periods. Not being directly connected to the atmosphere and located outside soil layers with the highest root densities, water in these layers is less susceptible to be rapidly evaporated and transpired. Instead, it provides longer-term soil water storage increasing the drought tolerance of plants and ecosystems.
Given the importance of soil moisture in the context of hydro-meteorological extremes in a warming climate, its monitoring is part of official national adaption strategies to a changing climate. Yet, soil moisture is highly variable in time and space which challenges its monitoring on spatio-temporal scales relevant for flood and drought risk modelling and forecasting.
Introduced over a decade ago, Cosmic-Ray Neutron Sensing (CRNS) is a noninvasive geophysical method that allows for the estimation of soil moisture at relevant spatio-temporal scales of several hectares at a high, subdaily temporal resolution. CRNS relies on the detection of secondary neutrons above the soil surface which are produced from high-energy cosmic-ray particles in the atmosphere and the ground. Neutrons in a specific epithermal energy range are sensitive to the amount of hydrogen present in the surroundings of the CRNS neutron detector. Due to same mass as the hydrogen nucleus, neutrons lose kinetic energy upon collision and are subsequently absorbed when reaching low, thermal energies. A higher amount of hydrogen therefore leads to fewer neutrons being detected per unit time. Assuming that the largest amount of hydrogen is stored in most terrestrial ecosystems as soil moisture, changes of soil moisture can be estimated through an inverse relationship with observed neutron intensities.
Although important scientific advancements have been made to improve the methodological framework of CRNS, several open challenges remain, of which some are addressed in the scope of this thesis. These include the influence of atmospheric variables such as air pressure and absolute air humidity, as well as, the impact of variations in incoming primary cosmic-ray intensity on observed epithermal and thermal neutron signals and their correction. Recently introduced advanced neutron-to-soil moisture transfer functions are expected to improve CRNS-derived soil moisture estimates, but potential improvements need to be investigated at study sites with differing environmental conditions. Sites with strongly heterogeneous, patchy soil moisture distributions challenge existing transfer functions and further research is required to assess the impact of, and correction of derived soil moisture estimates under heterogeneous site conditions. Despite its capability of measuring representative averages of soil moisture at the field scale, CRNS lacks an integration depth below the first few decimetres of the soil. Given the importance of soil moisture also in deeper soil layers, increasing the observational window of CRNS through modelling approaches or in situ measurements is of high importance for hydrological monitoring applications.
By addressing these challenges, this thesis aids to closing knowledge gaps and finding answers to some of the open questions in CRNS research. Influences of different environmental variables are quantified, correction approaches are being tested and developed. Neutron-to-soil moisture transfer functions are evaluated and approaches to reduce effects of heterogeneous soil moisture distributions are presented. Lastly, soil moisture estimates from larger soil depths are derived from CRNS through modified, simple modelling approaches and in situ estimates by using CRNS as a downhole technique. Thereby, this thesis does not only illustrate the potential of new, yet undiscovered applications of CRNS in future but also opens a new field of CRNS research. Consequently, this thesis advances the methodological framework of CRNS for above-ground and downhole applications. Although the necessity of further research in order to fully exploit the potential of CRNS needs to be emphasised, this thesis contributes to current hydrological research and not least to advancing hydrological monitoring approaches being of utmost importance in context of intensifying hydro-meteorological extremes in a changing climate.
Overcoming natural biomass limitations in gram-negative bacteria through synthetic carbon fixation
(2024)
The carbon demands of an ever-increasing human population and the concomitant rise in net carbon emissions requires CO2 sequestering approaches for production of carbon-containing molecules. Microbial production of carbon-containing products from plant-based sugars could replace current fossil-based production. However, this form of sugar-based microbial production directly competes with human food supply and natural ecosystems. Instead, one-carbon feedstocks derived from CO2 and renewable energy were proposed as an alternative. The one carbon molecule formate is a stable, readily soluble and safe-to-store energetic mediator that can be electrochemically generated from CO2 and (excess off-peak) renewable electricity. Formate-based microbial production could represent a promising approach for a circular carbon economy. However, easy-to-engineer and efficient formate-utilizing microbes are lacking. Multiple synthetic metabolic pathways were designed for better-than-nature carbon fixation. Among them, the reductive glycine pathway was proposed as the most efficient pathway for aerobic formate assimilation. While some of these pathways have been successfully engineered in microbial hosts, these synthetic strains did so far not exceed the performance of natural strains. In this work, I engineered and optimized two different synthetic formate assimilation pathways in gram-negative bacteria to exceed the limits of a natural carbon fixation pathway, the Calvin cycle.
The first chapter solidified Cupriavidus necator as a promising formatotrophic host to produce value-added chemicals. The formate tolerance of C. necator was assessed and a production pathway for crotonate established in a modularized fashion. Last, bioprocess optimization was leveraged to produce crotonate from formate at a titer of 148 mg/L.
In the second chapter, I chromosomally integrated and optimized the synthetic reductive glycine pathway in C. necator using a transposon-mediated selection approach. The insertion methodology allowed selection for condition-specific tailored pathway expression as improved pathway performance led to better growth. I then showed my engineered strains to exceed the biomass yields of the Calvin cycle utilizing wildtype C. necator on formate. This demonstrated for the first time the superiority of a synthetic formate assimilation pathway and by extension of synthetic carbon fixation efforts as a whole.
In chapter 3, I engineered a segment of a synthetic carbon fixation cycle in Escherichia coli. The GED cycle was proposed as a Calvin cycle alternative that does not perform a wasteful oxygenation reaction and is more energy efficient. The pathways simple architecture and reasonable driving force made it a promising candidate for enhanced carbon fixation. I created a deletion strain that coupled growth to carboxylation via the GED pathway segment. The CO2 dependence of the engineered strain and 13C-tracer analysis confirmed operation of the pathway in vivo.
In the final chapter, I present my efforts of implementing the GED cycle also in C. necator, which might be a better-suited host, as it is accustomed to formatotrophic and hydrogenotrophic growth. To provide the carboxylation substrate in vivo, I engineered C. necator to utilize xylose as carbon source and created a selection strain for carboxylase activity. I verify activity of the key enzyme, the carboxylase, in the decarboxylative direction. Although CO2-dependent growth of the strain was not obtained, I showed that all enzymes required for operation of the GED cycle are active in vivo in C. necator.
I then evaluate my success with engineering a linear and cyclical one-carbon fixation pathway in two different microbial hosts. The linear reductive glycine pathway presents itself as a much simpler metabolic solution for formate dependent growth over the sophisticated establishment of hard-to-balance carbon fixation cycles. Last, I highlight advantages and disadvantages of C. necator as an upcoming microbial benchmark organism for synthetic metabolism efforts and give and outlook on its potential for the future of C1-based manufacturing.