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Floral scent is an important way for plants to communicate with insects, but scent emission has been lost or strongly reduced during the transition from pollinator-mediated outbreeding to selfing. The shift from outcrossing to selfing is not only accompanied by scent loss, but also by a reduction in other pollinator-attracting traits like petal size and can be observed multiple times among angiosperms. These changes are summarized by the term selfing syndrome and represent one of the most prominent examples of convergent evolution within the plant kingdom. In this work the genus Capsella was used as a model to study convergent evolution in two closely related selfers with separate transitions to self-fertilization.
Compared to their outbreeding ancestor C. grandiflora, the emission of benzaldehyde as main compound of floral scent is lacking or strongly reduced in the selfing species C. rubella and C. orientalis. In C. rubella the loss of benzaldehyde was caused by mutations to cinnamate:CoA ligase CNL1, but the biochemical basis and evolutionary history of this loss remained unknown, together with the genetic basis of scent loss in C. orientalis. Here, a combination of plant transformations, in vitro enzyme assays, population genetics and quantitative genetics has been used to address these questions. The results indicate that CNL1 has been inactivated twice independently by point mutations in C. rubella, leading to a loss of benzaldehyde emission. Both inactivated haplotypes can be found around the Mediterranean Sea, indicating that they arose before the species´ geographical spread. This study confirmed CNL1 as a hotspot for mutations to eliminate benzaldehyde emission, as it has been suggested by previous studies. In contrast to these findings, CNL1 in C. orientalis remains active. To test whether similar mechanisms underlie the convergent evolution of scent loss in C. orientalis a QTL mapping approach was used and the results suggest that this closely related species followed a different evolutionary route to reduce floral scent, possibly reflecting that the convergent evolution of floral scent is driven by ecological rather than genetic factors.
In parallel with studying the genetic basis of repeated scent loss a method for testing the adaptive value of individual selfing syndrome traits was established. The established method allows estimating outcrossing rates with a high throughput of samples and detects successfully insect-mediated outcrossing events, providing major advantages regarding time and effort compared to other approaches. It can be applied to correlate outcrossing rates with differences in individual traits by using quasi-isogenic lines as demonstrated here or with environmental or morphological parameters.
Convergent evolution can not only be observed for scent loss in Capsella but also for the morphological evolution of petal size. Previous studies detected several QTLs underlying the petal size reduction in C. orientalis and C. rubella, some of them shared among both species. One shared QTL is PAQTL1 which might map to NUBBIN, a growth factor. To better understand the morphological evolution and genetic basis of petal size reduction, this QTL was studied. Mapping this QTL to a gene might identify another example for a hotspot gene, in this case for the convergent evolution of petal size.
Light-induced pH cycle
(2019)
Background Many biochemical reactions depend on the pH of their environment and some are strongly accelerated in an acidic surrounding. A classical approach to control biochemical reactions non-invasivly is by changing the temperature. However, if the pH could be controlled by optical means using photo-active chemicals, this would mean to be able to accelerate suitable biochemical reactions. Optically switching the pH can be achieved by using photoacids. A photoacid is a molecule with a functional group that releases a proton upon irradiation with the suitable wavelength, acidifying the environmental aqueous surrounding. A major goal of this work was to establish a non-invasive method of optically controlling the pH in aqueous solutions, offering the opportunity to enhance the known chemical reactions portfolio. To demonstrate the photo-switchable pH cycling we chose an enzymatic assay using acid phosphatase, which is an enzyme with a strong pH dependent activity.
Results In this work we could demonstrate a light-induced, reversible control of the enzymatic activity of acid phosphatase non-invasivly. To successfully conduct those experiments a high power LED array was designed and built, suitable for a 96 well standard microtiter plate, not being commercially available. Heat management and a lateral ventilation system to avoid heat accumulation were established and a stable light intensity achieved. Different photoacids were characterised and their pH dependent absorption spectra recorded. By using the reversible photoacid G-acid as a proton donor, the pH can be changed reversibly using high power UV 365 nm LEDs. To demonstrate the pH cycling, acid phosphatase with hydrolytic activity under acidic conditions was chosen. An assay using the photoacid together with the enzyme was established, also providing that G-acid does not inhibit acid phosphatase. The feasibility of reversibly regulating the enzyme’s pH dependent activity by optical means was demonstrated, by controlling the enzymatic activity with light. It was demonstrated that the enzyme activity depends on the light exposure time only. When samples are not illuminated and left in the dark, no enzymatic activity was recorded. The process can be rapidly controlled by simply switching the light on and off and should be applicable to a wide range of enzymes and biochemical reactions.
Conclusions Reversible photoacids offer a light-dependent regulation of pH, making them extremely attractive for miniaturizable, non-invasive and time-resolved control of biochemical reactions. Many enzymes have a sharp pH dependent activity, thus the established setup in this thesis could be used for a versatile enzyme portfolio. Even though the demonstrated photo-switchable strategy could also be used for non-enzymatic assays, greatly facilitating the assay establishment. Photoacids have the potential for high throughput methods and automation. We demonstrated that it is possible to control photoacids using commonly available LEDs, making their use in highly integrated devices and instruments more attractive. The successfully designed 96 well high power UV LED array presents an opportunity for general combinatorial analysis in e.g. photochemistry, where a high light intensity is needed for the investigation of various reactions.
Light-switchable proteins are being used increasingly to understand and manipulate complex molecular systems. The success of this approach has fueled the development of tailored photo-switchable proteins, to enable targeted molecular events to be studied using light. The development of novel photo-switchable tools has to date largely relied on rational design. Complementing this approach with directed evolution would be expected to facilitate these efforts. Directed evolution, however, has been relatively infrequently used to develop photo-switchable proteins due to the challenge presented by high-throughput evaluation of switchable protein activity. This thesis describes the development of two genetic circuits that can be used to evaluate libraries of switchable proteins, enabling optimization of both the on- and off-states. A screening system is described, which permits detection of DNA-binding activity based on conditional expression of a fluorescent protein. In addition, a tunable selection system is presented, which allows for the targeted selection of protein-protein interactions of a desired affinity range. This thesis additionally describes the development and characterization of a synthetic protein that was designed to investigate chromophore reconstitution in photoactive yellow protein (PYP), a promising scaffold for engineering photo-controlled protein tools.
Predators can have numerical and behavioral effects on prey animals. While numerical effects are well explored, the impact of behavioral effects is unclear. Furthermore, behavioral effects are generally either analyzed with a focus on single individuals or with a focus on consequences for other trophic levels. Thereby, the impact of fear on the level of prey communities is overlooked, despite potential consequences for conservation and nature management. In order to improve our understanding of predator-prey interactions, an assessment of the consequences of fear in shaping prey community structures is crucial.
In this thesis, I evaluated how fear alters prey space use, community structure and composition, focusing on terrestrial mammals. By integrating landscapes of fear in an existing individual-based and spatially-explicit model, I simulated community assembly of prey animals via individual home range formation. The model comprises multiple hierarchical levels from individual home range behavior to patterns of prey community structure and composition. The mechanistic approach of the model allowed for the identification of underlying mechanism driving prey community responses under fear.
My results show that fear modified prey space use and community patterns. Under fear, prey animals shifted their home ranges towards safer areas of the landscape. Furthermore, fear decreased the total biomass and the diversity of the prey community and reinforced shifts in community composition towards smaller animals. These effects could be mediated by an increasing availability of refuges in the landscape. Under landscape changes, such as habitat loss and fragmentation, fear intensified negative effects on prey communities. Prey communities in risky environments were subject to a non-proportional diversity loss of up to 30% if fear was taken into account. Regarding habitat properties, I found that well-connected, large safe patches can reduce the negative consequences of habitat loss and fragmentation on prey communities. Including variation in risk perception between prey animals had consequences on prey space use. Animals with a high risk perception predominantly used safe areas of the landscape, while animals with a low risk perception preferred areas with a high food availability. On the community level, prey diversity was higher in heterogeneous landscapes of fear if individuals varied in their risk perception compared to scenarios in which all individuals had the same risk perception.
Overall, my findings give a first, comprehensive assessment of the role of fear in shaping prey communities. The linkage between individual home range behavior and patterns at the community level allows for a mechanistic understanding of the underlying processes. My results underline the importance of the structure of the landscape of fear as a key driver of prey community responses, especially if the habitat is threatened by landscape changes. Furthermore, I show that individual landscapes of fear can improve our understanding of the consequences of trait variation on community structures. Regarding conservation and nature management, my results support calls for modern conservation approaches that go beyond single species and address the protection of biotic interactions.
A contemporary challenge in Ecology and Evolutionary Biology is to anticipate the fate of populations of organisms in the context of a changing world. Climate change and landscape changes due to anthropic activities have been of major concern in the contemporary history. Organisms facing these threats are expected to respond by local adaptation (i.e., genetic changes or phenotypic plasticity) or by shifting their distributional range (migration). However, there are limits to their responses. For example, isolated populations will have more difficulties in developing adaptive innovations by means of genetic changes than interconnected metapopulations. Similarly, the topography of the environment can limit dispersal opportunities for crawling organisms as compared to those that rely on wind. Thus, populations of species with different life history strategy may differ in their ability to cope with changing environmental conditions. However, depending on the taxon, empirical studies investigating organisms’ responses to environmental change may become too complex, long and expensive; plus, complications arising from dealing with endangered species. In consequence, eco-evolutionary modeling offers an opportunity to overcome these limitations and complement empirical studies, understand the action and limitations of underlying mechanisms, and project into possible future scenarios. In this work I take a modeling approach and investigate the effect and relative importance of evolutionary mechanisms (including phenotypic plasticity) on the ability for local adaptation of populations with different life strategy experiencing climate change scenarios. For this, I performed a review on the state of the art of eco-evolutionary Individual-Based Models (IBMs) and identify gaps for future research. Then, I used the results from the review to develop an eco-evolutionary individual-based modeling tool to study the role of genetic and plastic mechanisms in promoting local adaption of populations of organisms with different life strategies experiencing scenarios of climate change and environmental stochasticity. The environment was simulated through a climate variable (e.g., temperature) defining a phenotypic optimum moving at a given rate of change. The rate of change was changed to simulate different scenarios of climate change (no change, slow, medium, rapid climate change). Several scenarios of stochastic noise color resembling different climatic conditions were explored. Results show that populations of sexual species will rely mainly on standing genetic variation and phenotypic plasticity for local adaptation. Population of species with relatively slow growth rate (e.g., large mammals) – especially those of small size – are the most vulnerable, particularly if their plasticity is limited (i.e., specialist species). In addition, whenever organisms from these populations are capable of adaptive plasticity, they can buffer fitness losses in reddish climatic conditions. Likewise, whenever they can adjust their plastic response (e.g., bed-hedging strategy) they will cope with bluish environmental conditions as well. In contrast, life strategies of high fecundity can rely on non-adaptive plasticity for their local adaptation to novel environmental conditions, unless the rate of change is too rapid. A recommended management measure is to guarantee interconnection of isolated populations into metapopulations, such that the supply of useful genetic variation can be increased, and, at the same time, provide them with movement opportunities to follow their preferred niche, when local adaptation becomes problematic. This is particularly important for bluish and reddish climatic conditions, when the rate of change is slow, or for any climatic condition when the level of stress (rate of change) is relatively high.
Predation drives coexistence, evolution and population dynamics of species in food webs, and has strong impacts on related ecosystem functions (e.g. primary production). The effect of predation on these processes largely depends on the trade-offs between functional traits in the predator and prey community. Trade-offs between defence against predation and competitive ability, for example, allow for prey speciation and predator-mediated coexistence of prey species with different strategies (defended or competitive), which may stabilize the overall food web dynamics. While the importance of such trade-offs for coexistence is widely known, we lack an understanding and the empirical evidence of how the variety of differently shaped trade-offs at multiple trophic levels affect biodiversity, trait adaptation and biomass dynamics in food webs. Such mechanistic understanding is crucial for predictions and management decisions that aim to maintain biodiversity and the capability of communities to adapt to environmental change ensuring their persistence.
In this dissertation, after a general introduction to predator-prey interactions and tradeoffs, I first focus on trade-offs in the prey between qualitatively different types of defence (e.g. camouflage or escape behaviour) and their costs. I show that these different types lead to different patterns of predator-mediated coexistence and population dynamics, by using a simple predator-prey model. In a second step, I elaborate quantitative aspects of trade-offs and demonstrates that the shape of the trade-off curve in combination with trait-fitness relationships strongly affects competition among different prey types: Either specialized species with extreme trait combinations (undefended or completely defended) coexist, or a species with an intermediate defence level dominates. The developed theory on trade-off shapes and coexistence is kept general, allowing for applications apart from defence-competitiveness trade-offs. Thirdly, I tested the theory on trade-off shapes on a long-term field data set of phytoplankton from Lake Constance. The measured concave trade-off between defence and growth governs seasonal trait changes of phytoplankton in response to an altering grazing pressure by zooplankton, and affects the maintenance of trait variation in the community. In a fourth step, I analyse the interplay of different tradeoffs at multiple trophic levels with plankton data of Lake Constance and a corresponding tritrophic food web model. The results show that the trait and biomass dynamics of the different three trophic levels are interrelated in a trophic biomass-trait cascade, leading to unintuitive patterns of trait changes that are reversed in comparison to predictions from bitrophic systems. Finally, in the general discussion, I extract main ideas on trade-offs in multitrophic systems, develop a graphical theory on trade-off-based coexistence, discuss the interplay of intra- and interspecific trade-offs, and end with a management-oriented view on the results of the dissertation, describing how food webs may respond to future global changes, given their trade-offs.
The natural abundance of Coiled Coil (CC) motifs in cytoskeleton and extracellular matrix proteins suggests that CCs play an important role as passive (structural) and active (regulatory) mechanical building blocks. CCs are self-assembled superhelical structures consisting of 2-7 α-helices. Self-assembly is driven by hydrophobic and ionic interactions, while the helix propensity of the individual helices contributes additional stability to the structure. As a direct result of this simple sequence-structure relationship, CCs serve as templates for protein design and sequences with a pre-defined thermodynamic stability have been synthesized de novo. Despite this quickly increasing knowledge and the vast number of possible CC applications, the mechanical function of CCs has been largely overlooked and little is known about how different CC design parameters determine the mechanical stability of CCs. Once available, this knowledge will open up new applications for CCs as nanomechanical building blocks, e.g. in biomaterials and nanobiotechnology.
With the goal of shedding light on the sequence-structure-mechanics relationship of CCs, a well-characterized heterodimeric CC was utilized as a model system. The sequence of this model system was systematically modified to investigate how different design parameters affect the CC response when the force is applied to opposing termini in a shear geometry or separated in a zipper-like fashion from the same termini (unzip geometry). The force was applied using an atomic force microscope set-up and dynamic single-molecule force spectroscopy was performed to determine the rupture forces and energy landscape properties of the CC heterodimers under study. Using force as a denaturant, CC chain separation is initiated by helix uncoiling from the force application points. In the shear geometry, this allows uncoiling-assisted sliding parallel to the force vector or dissociation perpendicular to the force vector. Both competing processes involve the opening of stabilizing hydrophobic (and ionic) interactions. Also in the unzip geometry, helix uncoiling precedes the rupture of hydrophobic contacts.
In a first series of experiments, the focus was placed on canonical modifications in the hydrophobic core and the helix propensity. Using the shear geometry, it was shown that both a reduced core packing and helix propensity lower the thermodynamic and mechanical stability of the CC; however, with different effects on the energy landscape of the system. A less tightly packed hydrophobic core increases the distance to the transition state, with only a small effect on the barrier height. This originates from a more dynamic and less tightly packed core, which provides more degrees of freedom to respond to the applied force in the direction of the force vector. In contrast, a reduced helix propensity decreases both the distance to the transition state and the barrier height. The helices are ‘easier’ to unfold and the remaining structure is less thermodynamically stable so that dissociation perpendicular to the force axis can occur at smaller deformations.
Having elucidated how canonical sequence modifications influence CC mechanics, the pulling geometry was investigated in the next step. Using one and the same sequence, the force application points were exchanged and two different shear and one unzipping geometry were compared. It was shown that the pulling geometry determines the mechanical stability of the CC. Different rupture forces were observed in the different shear as well as in the unzipping geometries, suggesting that chain separation follows different pathways on the energy landscape. Whereas the difference between CC shearing and unzipping was anticipated and has also been observed for other biological structures, the observed difference for the two shear geometries was less expected. It can be explained with the structural asymmetry of the CC heterodimer. It is proposed that the direction of the α-helices, the different local helix propensities and the position of a polar asparagine in the hydrophobic core are responsible for the observed difference in the chain separation pathways. In combination, these factors are considered to influence the interplay between processes parallel and perpendicular to the force axis.
To obtain more detailed insights into the role of helix stability, helical turns were reinforced locally using artificial constraints in the form of covalent and dynamic ‘staples’. A covalent staple bridges to adjacent helical turns, thus protecting them against uncoiling. The staple was inserted directly at the point of force application in one helix or in the same terminus of the other helix, which did not experience the force directly. It was shown that preventing helix uncoiling at the point of force application reduces the distance to the transition state while slightly increasing the barrier height. This confirms that helix uncoiling is critically important for CC chain separation. When inserted into the second helix, this stabilizing effect is transferred across the hydrophobic core and protects the force-loaded turns against uncoiling. If both helices were stapled, no additional increase in mechanical stability was observed. When replacing the covalent staple with a dynamic metal-coordination bond, a smaller decrease in the distance to the transition was observed, suggesting that the staple opens up while the CC is under load.
Using fluorinated amino acids as another type of non-natural modification, it was investigated how the enhanced hydrophobicity and the altered packing at the interface influences CC mechanics. The fluorinated amino acid was inserted into one central heptad of one or both α-helices. It was shown that this substitution destabilized the CC thermodynamically and mechanically. Specifically, the barrier height was decreased and the distance to the transition state increased. This suggests that a possible stabilizing effect of the increased hydrophobicity is overruled by a disturbed packing, which originates from a bad fit of the fluorinated amino acid into the local environment. This in turn increases the flexibility at the interface, as also observed for the hydrophobic core substitution described above. In combination, this confirms that the arrangement of the hydrophobic side chains is an additional crucial factor determining the mechanical stability of CCs.
In conclusion, this work shows that knowledge of the thermodynamic stability alone is not sufficient to predict the mechanical stability of CCs. It is the interplay between helix propensity and hydrophobic core packing that defines the sequence-structure-mechanics relationship. In combination, both parameters determine the relative contribution of processes parallel and perpendicular to the force axis, i.e. helix uncoiling and uncoiling-assisted sliding as well as dissociation. This new mechanistic knowledge provides insight into the mechanical function of CCs in tissues and opens up the road for designing CCs with pre-defined mechanical properties. The library of mechanically characterized CCs developed in this work is a powerful starting point for a wide spectrum of applications, ranging from molecular force sensors to mechanosensitive crosslinks in protein nanostructures and synthetic extracellular matrix mimics.
The unprecedented increase in atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHG) by anthropogenic activities since the Industrial Revolution impacts on various earth system processes, commonly referred to as `climate change´ (CC). CC faces aquatic ecosystems with extreme abiotic perturbations that potentially alter the interrelations between functional autotrophic and heterotrophic plankton groups. These relations, however, modulate biogeochemical cycling and mediate the functioning of aquatic ecosystems as C sources or sinks to the atmosphere. The aim of this thesis was therefore to investigate how different aspects of CC influence community composition and functioning of pelagic heterotrophic bacteria. These organisms constitute a major component of biogeochemical cycling and largely determine the balance between autotrophic and heterotrophic processes.
Due to the vast amount of potential CC impacts, this thesis focuses on the following two aspects: (1) Increased exchange of CO2 across the atmosphere-water interface and reaction of CO2 with seawater leads to profound shifts in seawater carbonate chemistry, commonly termed as `ocean acidification´ (OA), with consequences for organism physiology and the availability of dissolved inorganic carbon (DIC) in seawater. (2) The increase in atmospheric GHG concentration impacts on the efficiency with which the Earth cools to space, affecting global surface temperature and climate. With ongoing CC, shifts in frequency and severity of episodic weather events, such as storms, are expected that in particular might affect lake ecosystems by disrupting thermal summer stratification. Both aspects of CC were studied at the ecosystem-level in large-volume mesocosm experiments by using the Kiel Off-shore Mesocosms for Future Ocean Simulations (KOSMOS) deployed at different coastal marine locations, and the LakeLab facility in Lake Stechlin.
We evaluated the impact of OA on heterotrophic bacterial metabolism in a brackish coastal ecosystem during low-nutrient summer months in the Baltic Sea. There are several in situ experiments that already assessed potential OA-induced changes in natural plankton communities at diverse spatial and seasonal conditions. However, most studies were performed at high phytoplankton biomass conditions, partly provoked by nutrient amendments. Our study highlights potential OA effects at low-nutrient conditions that are representative for most parts of the ocean and of particular interest in current OA research. The results suggest that during extended periods at low-nutrient concentrations, increasing pCO2 levels indirectly impact the growth balance of heterotrophic bacteria via trophic bacteria-phytoplankton interactions and shift the ecosystem to a more autotrophic system.
Further work investigated how OA affects heterotrophic bacterial dissolved organic matter (DOM) transformation in two mesocsom studies, performed at different nutrient conditions. We observed similar succession patterns for individual compound pools during a phytoplankton bloom and subsequent accumulation of these compounds irrespective of the pCO2 treatment. Our results indicate that OA-induced changes in the dynamics of bacterial DOM transformation and potential impacts on DOM quality are unlikely. In addition, there have been no indications that in dependence of nutrient conditions, different amounts of photosynthetic organic matter are channelled into the more recalcitrant DOM pool. This provides novel insights into the general dynamics of the marine DOM pool.
A fourth enclosure experiment in oligo-mesotrophic Lake Stechlin assessed the impact of a severe summer storm on lake bacterial communities during thermal stratification by artificially mixing. Mixing disrupted and lowered the thermocline, increasing the upper mixed layer and substantially changed water physical-chemical variables. Deep water entrainment and associated changes in water physical-chemical variables significantly affected relative bacterial abundances for about one week. Afterwards a pronounced cyanobacterial bloom developed in response to mixing which affected community assembly of heterotrophic bacteria. Colonization and mineralization of senescent phytoplankton cells by heterotrophic bacteria largely determined C-sequestration to the sediment. About six weeks after mixing, bacterial communities and measured activity parameters converged to control conditions. As such, summer storms have the potential to affect bacterial communities for a prolonged period during summer stratification. The results highlight effects on community assembly and heterotrophic bacterial metabolism that are associated to entrainment of deep water into the mixed water layer and assess consequences of an episodic disturbance event for the coupling between bacterial metabolism and autochthonous DOM production in large volume clear-water lakes.
Altogether, this doctoral thesis reveales substantial sensitivities of heterotrophic bacterial metabolism and community structure in response to OA and a simulated summer storm event, which should be considered when assessing the impact of climate change on marine and lake ecosystems.
Simulating the impact of herbicide drift exposure on non-target terrestrial plant communities
(2019)
In Europe, almost half of the terrestrial landscape is used for agriculture. Thus, semi-natural habitats such as field margins are substantial for maintaining diversity in intensively managed farmlands. However, plants located at field margins are threatened by agricultural practices such as the application of pesticides within the fields. Pesticides are chemicals developed to control for undesired species within agricultural fields to enhance yields. The use of pesticides implies, however, effects on non-target organisms within and outside of the agricultural fields. Non-target organisms are organisms not intended to be sprayed or controlled for. For example, plants occurring in field margins are not intended to be sprayed, however, can be impaired due to herbicide drift exposure. The authorization of plant protection products such as herbicides requires risk assessments to ensure that the application of the product has no unacceptable effects on the environment. For non-target terrestrial plants (NTTPs), the risk assessment is based on standardized greenhouse studies on plant individual level. To account for the protection of plant populations and communities under realistic field conditions, i.e. extrapolating from greenhouse studies to field conditions and from individual-level to community-level, assessment factors are applied. However, recent studies question the current risk assessment scheme to meet the specific protection goals for non-target terrestrial plants as suggested by the European Food Safety Authority (EFSA). There is a need to clarify the gaps of the current risk assessment and to include suitable higher tier options in the upcoming guidance document for non-target terrestrial plants.
In my thesis, I studied the impact of herbicide drift exposure on NTTP communities using a mechanistic modelling approach. I addressed main gaps and uncertainties of the current risk assessment and finally suggested this modelling approach as a novel higher tier option in future risk assessments. Specifically, I extended the plant community model IBC-grass (Individual-based community model for grasslands) to reflect herbicide impacts on plant individuals. In the first study, I compared model predictions of short-term herbicide impacts on artificial plant communities with empirical data. I demonstrated the capability of the model to realistically reflect herbicide impacts. In the second study, I addressed the research question whether or not reproductive endpoints need to be included in future risk assessments to protect plant populations and communities. I compared the consequences of theoretical herbicide impacts on different plant attributes for long-term plant population dynamics in the community context. I concluded that reproductive endpoints only need to be considered if the herbicide effect is assumed to be very high. The endpoints measured in the current vegetative vigour and seedling emergence studies had high impacts for the dynamic of plant populations and communities already at lower effect intensities. Finally, the third study analysed long-term impacts of herbicide application for three different plant communities. This study highlighted the suitability of the modelling approach to simulate different communities and thus detecting sensitive environmental conditions.
Overall, my thesis demonstrates the suitability of mechanistic modelling approaches to be used as higher tier options for risk assessments. Specifically, IBC-grass can incorporate available individual-level effect data of standardized greenhouse experiments to extrapolate to community-level under various environmental conditions. Thus, future risk assessments can be improved by detecting sensitive scenarios and including worst-case impacts on non-target plant communities.
Force plays a fundamental role in the regulation of biological processes. Cells can sense the mechanical properties of the extracellular matrix (ECM) by applying forces and transmitting mechanical signals. They further use mechanical information for regulating a wide range of cellular functions, including adhesion, migration, proliferation, as well as differentiation and apoptosis. Even though it is well understood that mechanical signals play a crucial role in directing cell fate, surprisingly little is known about the range of forces that define cell-ECM interactions at the molecular level.
Recently, synthetic molecular force sensor (MFS) designs have been established for measuring the molecular forces acting at the cell-ECM interface. MFSs detect the traction forces generated by cells and convert this mechanical input into an optical readout. They are composed of calibrated mechanoresponsive building blocks and are usually equipped with a fluorescence reporter system. Up to date, many different MFS designs have been introduced and successfully used for measuring forces involved in the adhesion of mammalian cells. These MFSs utilize different molecular building blocks, such as double-stranded deoxyribonucleic acid (dsDNA) molecules, DNA hairpins and synthetic polymers like polyethylene glycol (PEG). These currently available MFS designs lack ECM mimicking properties.
In this work, I introduce a new MFS building block for cell biology applications, derived from the natural ECM. It combines mechanical tunability with the ability to mimic the native cellular microenvironment. Inspired by structural ECM proteins with load bearing function, this new MFS design utilizes coiled coil (CC)-forming peptides. CCs are involved in structural and mechanical tasks in the cellular microenvironment and many of the key protein components of the cytoskeleton and the ECM contain CC structures. The well-known folding motif of CC structures, an easy synthesis via solid phase methods and the many roles CCs play in biological processes have inspired studies to use CCs as tunable model systems for protein design and assembly. All these properties make CCs ideal candidates as building blocks for MFSs. In this work, a series of heterodimeric CCs were designed, characterized and further used as molecular building blocks for establishing a novel, next-generation MFS prototype.
A mechanistic molecular understanding of their structural response to mechanical load is essential for revealing the sequence-structure-mechanics relationships of CCs. Here, synthetic heterodimeric CCs of different length were loaded in shear geometry and their mechanical response was investigated using a combination of atomic force microscope (AFM)-based single-molecule force spectroscopy (SMFS) and steered molecular dynamics (SMD) simulations. SMFS showed that the rupture forces of short heterodimeric CCs (3-5 heptads) lie in the range of 20-50 pN, depending on CC length, pulling geometry and the applied loading rate (dF/dt). Upon shearing, an initial rise in the force, followed by a force plateau and ultimately strand separation was observed in SMD simulations. A detailed structural analysis revealed that CC response to shear load depends on the loading rate and involves helix uncoiling, uncoiling-assisted sliding in the direction of the applied force and uncoiling-assisted dissociation perpendicular to the force axis.
The application potential of these mechanically characterized CCs as building blocks for MFSs has been tested in 2D cell culture applications with the goal of determining the threshold force for cell adhesion. Fully calibrated, 4- to 5-heptad long, CC motifs (CC-A4B4 and CC-A5B5) were used for functionalizing glass surfaces with MFSs. 3T3 fibroblasts and endothelial cells carrying mutations in a signaling pathway linked to cell adhesion and mechanotransduction processes were used as model systems for time-dependent adhesion experiments. A5B5-MFS efficiently supported cell attachment to the functionalized surfaces for both cell types, while A4B4-MFS failed to maintain attachment of 3T3 fibroblasts after the first 2 hours of initial cell adhesion. This difference in cell adhesion behavior demonstrates that the magnitude of cell-ECM forces varies depending on the cell type and further supports the application potential of CCs as mechanoresponsive and tunable molecular building blocks for the development of next-generation protein-based MFSs.This novel CC-based MFS design is expected to provide a powerful new tool for observing cellular mechanosensing processes at the molecular level and to deliver new insights into the mechanisms and forces involved. This MFS design, utilizing mechanically tunable CC building blocks, will not only allow for measuring the molecular forces acting at the cell-ECM interface, but also yield a new platform for the development of mechanically controlled materials for a large number of biological and medical applications.