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All life-sustaining processes are ultimately driven by thousands of biochemical reactions occurring in the cells: the metabolism. These reactions form an intricate network which produces all required chemical compounds, i.e., metabolites, from a set of input molecules. Cells regulate the activity through metabolic reactions in a context-specific way; only reactions that are required in a cellular context, e.g., cell type, developmental stage or environmental condition, are usually active, while the rest remain inactive. The context-specificity of metabolism can be captured by several kinds of experimental data, such as by gene and protein expression or metabolite profiles. In addition, these context-specific data can be assimilated into computational models of metabolism, which then provide context-specific metabolic predictions.
This thesis is composed of three individual studies focussing on context-specific experimental data integration into computational models of metabolism. The first study presents an optimization-based method to obtain context-specific metabolic predictions, and offers the advantage of being fully automated, i.e., free of user defined parameters. The second study explores the effects of alternative optimal solutions arising during the generation of context-specific metabolic predictions. These alternative optimal solutions are metabolic model predictions that represent equally well the integrated data, but that can markedly differ. This study proposes algorithms to analyze the space of alternative solutions, as well as some ways to cope with their impact in the predictions.
Finally, the third study investigates the metabolic specialization of the guard cells of the plant Arabidopsis thaliana, and compares it with that of a different cell type, the mesophyll cells. To this end, the computational methods developed in this thesis are applied to obtain metabolic predictions specific to guard cell and mesophyll cells. These cell-specific predictions are then compared to explore the differences in metabolic activity between the two cell types. In addition, the effects of alternative optima are taken into consideration when comparing the two cell types. The computational results indicate a major reorganization of the primary metabolism in guard cells. These results are supported by an independent 13C labelling experiment.
Background: Animals show consistent individual behavioural patterns over time and over situations. This phenomenon has been referred to as animal personality or behavioural syndromes. Little is known about consistency of animal personalities over entire life times. We investigated the repeatability of behaviour in common voles (Microtus arvalis) at different life stages, with different time intervals, and in different situations. Animals were tested using four behavioural tests in three experimental groups: 1. before and after maturation over three months, 2. twice as adults during one week, and 3. twice as adult animals over three months, which resembles a substantial part of their entire adult life span of several months.
Results: Different behaviours were correlated within and between tests and a cluster analysis showed three possible behavioural syndrome-axes, which we name boldness, exploration and activity. Activity and exploration behaviour in all tests was highly repeatable in adult animals tested over one week. In animals tested over maturation, exploration behaviour was consistent whereas activity was not. Voles that were tested as adults with a three-month interval showed the opposite pattern with stable activity but unstable exploration behaviour.
Conclusions: The consistency in behaviour over time suggests that common voles do express stable personality over short time. Over longer periods however, behaviour is more flexible and depending on life stage (i.e. tested before/after maturation or as adults) of the tested individual. Level of boldness or activity does not differ between tested groups and maintenance of variation in behavioural traits can therefore not be explained by expected future assets as reported in other studies.
Background: Female sperm storage has evolved independently multiple times among vertebrates to control reproduction in response to the environment. In internally fertilising amphibians, female salamanders store sperm in cloacal spermathecae, whereas among anurans sperm storage in oviducts is known only in tailed frogs. Facilitated through extensive field sampling following historical observations we tested for sperm storing structures in the female urogenital tract of fossorial, tropical caecilian amphibians.
Findings: In the oviparous Ichthyophis cf. kohtaoensis, aggregated sperm were present in a distinct region of the posterior oviduct but not in the cloaca in six out of seven vitellogenic females prior to oviposition. Spermatozoa were found most abundantly between the mucosal folds. In relation to the reproductive status decreased amounts of sperm were present in gravid females compared to pre-ovulatory females. Sperm were absent in females past oviposition.
Conclusions: Our findings indicate short-term oviductal sperm storage in the oviparous Ichthyophis cf. kohtaoensis. We assume that in female caecilians exhibiting high levels of parental investment sperm storage has evolved in order to optimally coordinate reproductive events and to increase fitness.
Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. Interactions are also studied experimentally, however, a lacking consent on the experimental protocol hinders direct comparison of results. As a consequence, contradictory classifications as additive, synergistic or antagonistic are reported in literature.
In the present thesis we developed a novel mathematical model for bacterial growth that integrates cell-level processes into the population growth level. The scope of the model is to predict bacterial growth under antimicrobial perturbation by multiple antibiotics in vitro.
To this end, we combined cell-level data from literature with population growth data for Bacillus subtilis, Escherichia coli and Staphylococcus aureus. The cell-level data described growth-determining characteristics of a reference cell, including the ribosomal concentration and efficiency. The population growth data comprised extensive time-kill curves for clinically relevant antibiotics (tetracycline, chloramphenicol, vancomycin, meropenem, linezolid, including dual combinations).
The new cell-level approach allowed for the first time to simultaneously describe single and combined effects of the aforementioned antibiotics for different experimental protocols, in particular different growth phases (lag and exponential phase). Consideration of ribosomal dynamics and persisting sub-populations explained the decreased potency of linezolid on cultures in the lag phase compared to exponential phase cultures. The model captured growth rate dependent killing and auto-inhibition of meropenem and - also for vancomycin exposure - regrowth of the bacterial cultures due to adaptive resistance development. Stochastic interaction surface analysis demonstrated the pronounced antagonism between meropenem and linezolid to be robust against variation in the growth phase and pharmacodynamic endpoint definition, but sensitive to a change in the experimental duration.
Furthermore, the developed approach included a detailed representation of the bacterial cell-cycle. We used this representation to describe septation dynamics during the transition of a bacterial culture from the exponential to stationary growth phase. Resulting from a new mechanistic understanding of transition processes, we explained the lag time between the increase in cell number and bacterial biomass during the transition from the lag to exponential growth phase. Furthermore, our model reproduces the increased intracellular RNA mass fraction during long term exposure of bacteria to chloramphenicol.
In summary, we contribute a new approach to disentangle the impact of drug effects, assay readout and experimental protocol on antibiotic interactions. In the absence of a consensus on the corresponding experimental protocols, this disentanglement is key to translate information between heterogeneous experiments and also ultimately to the clinical setting.
Background
Much of the organismal variation we observe in nature is due to differences in organ size. The observation that even closely related species can show large, stably inherited differences in organ size indicates a strong genetic component to the control of organ size. Despite recent progress in identifying factors controlling organ growth in plants, our overall understanding of this process remains limited, partly because the individual factors have not yet been connected into larger regulatory pathways or networks. To begin addressing this aim, we have studied the upstream regulation of expression of BIG BROTHER (BB), a central growth-control gene in Arabidopsis thaliana that prevents overgrowth of organs. Final organ size and BB expression levels are tightly correlated, implying the need for precise control of its expression. BB expression mirrors proliferative activity, yet the gene functions to limit proliferation, suggesting that it acts in an incoherent feedforward loop downstream of growth activators to prevent over-proliferation.
Results
To investigate the upstream regulation of BB we combined a promoter deletion analysis with a phylogenetic footprinting approach. We were able to narrow down important, highly conserved, cis-regulatory elements within the BB promoter. Promoter sequences of other Brassicaceae species were able to partially complement the A. thaliana bb-1 mutant, suggesting that at least within the Brassicaceae family the regulatory pathways are conserved.
Conclusions
This work underlines the complexity involved in precise quantitative control of gene expression and lays the foundation for identifying important upstream regulators that determine BB expression levels and thus final organ size.
Background
A territory as a prerequisite for breeding limits the maximum number of breeders in a given area, and thus lowers the proportion of breeders if population size increases. However, some territorially breeding animals can have dramatic density fluctuations and little is known about the change from density-dependent processes to density-independence of breeding during a population increase or an outbreak. We suggest that territoriality, breeding suppression and its break-down can be understood with an incomplete-control model, developed for social breeders and social suppression.
Results
We studied density dependence in an arvicoline species, the bank vole, known as a territorial breeder with cyclic and non-cyclic density fluctuations and periodically high densities in different parts of its range. Our long-term data base from 38 experimental populations in large enclosures in boreal grassland confirms that breeding rates are density-regulated at moderate densities, probably by social suppression of subordinate potential breeders. We conducted an experiment, were we doubled and tripled this moderate density under otherwise the same conditions and measured space use, mortality, reproduction and faecal stress hormone levels (FGM) of adult females. We found that mortality did not differ among the densities, but the regulation of the breeding rate broke down: at double and triple densities all females were breeding, while at the low density the breeding rate was regulated as observed before. Spatial overlap among females increased with density, while a minimum territory size was maintained. Mean stress hormone levels were higher in double and triple densities than at moderate density.
Conclusions
At low and moderate densities, breeding suppression by the dominant breeders, But above a density-threshold (similar to a competition point), the dominance of breeders could not be sustained (incomplete control). In our experiment, this point was reached after territories could not shrink any further, while the number of intruders continued to increase with increasing density. Probably suppression becomes too costly for the dominants, and increasing number of other breeders reduces the effectiveness of threats. In wild populations, crossing this threshold would allow for a rapid density increase or population outbreaks, enabling territorial species to escape density-dependency.
Background
Protected areas are the most common and important instrument for the conservation of biological diversity and are called for under the United Nations' Convention on Biological Diversity. Growing human population densities, intensified land-use, invasive species and increasing habitat fragmentation threaten ecosystems worldwide and protected areas are often the only refuge for endangered species. Climate change is posing an additional threat that may also impact ecosystems currently under protection. Therefore, it is of crucial importance to include the potential impact of climate change when designing future nature conservation strategies and implementing protected area management. This approach would go beyond reactive crisis management and, by necessity, would include anticipatory risk assessments. One avenue for doing so is being provided by simulation models that take advantage of the increase in computing capacity and performance that has occurred over the last two decades.
Here we review the literature to determine the state-of-the-art in modeling terrestrial protected areas under climate change, with the aim of evaluating and detecting trends and gaps in the current approaches being employed, as well as to provide a useful overview and guidelines for future research.
Results
Most studies apply statistical, bioclimatic envelope models and focus primarily on plant species as compared to other taxa. Very few studies utilize a mechanistic, process-based approach and none examine biotic interactions like predation and competition. Important factors like land-use, habitat fragmentation, invasion and dispersal are rarely incorporated, restricting the informative value of the resulting predictions considerably.
Conclusion
The general impression that emerges is that biodiversity conservation in protected areas could benefit from the application of modern modeling approaches to a greater extent than is currently reflected in the scientific literature. It is particularly true that existing models have been underutilized in testing different management options under climate change. Based on these findings we suggest a strategic framework for more effectively incorporating the impact of climate change in models exploring the effectiveness of protected areas.