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- Institut für Biochemie und Biologie (24) (remove)
Mathematical modeling of biological systems is a powerful tool to systematically investigate the functions of biological processes and their relationship with the environment. To obtain accurate and biologically interpretable predictions, a modeling framework has to be devised whose assumptions best approximate the examined scenario and which copes with the trade-off of complexity of the underlying mathematical description: with attention to detail or high coverage. Correspondingly, the system can be examined in detail on a smaller scale or in a simplified manner on a larger scale. In this thesis, the role of photosynthesis and its related biochemical processes in the context of plant metabolism was dissected by employing modeling approaches ranging from kinetic to stoichiometric models. The Calvin-Benson cycle, as primary pathway of carbon fixation in C3 plants, is the initial step for producing starch and sucrose, necessary for plant growth. Based on an integrative analysis for model ranking applied on the largest compendium of (kinetic) models for the Calvin-Benson cycle, those suitable for development of metabolic engineering strategies were identified. Driven by the question why starch rather than sucrose is the predominant transitory carbon storage in higher plants, the metabolic costs for their synthesis were examined. The incorporation of the maintenance costs for the involved enzymes provided a model-based support for the preference of starch as transitory carbon storage, by only exploiting the stoichiometry of synthesis pathways. Many photosynthetic organisms have to cope with processes which compete with carbon fixation, such as photorespiration whose impact on plant metabolism is still controversial. A systematic model-oriented review provided a detailed assessment for the role of this pathway in inhibiting the rate of carbon fixation, bridging carbon and nitrogen metabolism, shaping the C1 metabolism, and influencing redox signal transduction. The demand of understanding photosynthesis in its metabolic context calls for the examination of the related processes of the primary carbon metabolism. To this end, the Arabidopsis core model was assembled via a bottom-up approach. This large-scale model can be used to simulate photoautotrophic biomass production, as an indicator for plant growth, under so-called optimal, carbon-limiting and nitrogen-limiting growth conditions. Finally, the introduced model was employed to investigate the effects of the environment, in particular, nitrogen, carbon and energy sources, on the metabolic behavior. This resulted in a purely stoichiometry-based explanation for the experimental evidence for preferred simultaneous acquisition of nitrogen in both forms, as nitrate and ammonium, for optimal growth in various plant species. The findings presented in this thesis provide new insights into plant system's behavior, further support existing opinions for which mounting experimental evidences arise, and posit novel hypotheses for further directed large-scale experiments.
Biosensors for the detection of benzaldehyde and g-aminobutyric acid (GABA) are reported using aldehyde oxidoreductase PaoABC from Escherichia coli immobilized in a polymer containing bound low potential osmium redox complexes. The electrically connected enzyme already electrooxidizes benzaldehyde at potentials below −0.15 V (vs. Ag|AgCl, 1 M KCl). The pH-dependence of benzaldehyde oxidation can be strongly influenced by the ionic strength. The effect is similar with the soluble osmium redox complex and therefore indicates a clear electrostatic effect on the bioelectrocatalytic efficiency of PaoABC in the osmium containing redox polymer. At lower ionic strength, the pH-optimum is high and can be switched to low pH-values at high ionic strength. This offers biosensing at high and low pH-values. A “reagentless” biosensor has been formed with enzyme wired onto a screen-printed electrode in a flow cell device. The response time to addition of benzaldehyde is 30 s, and the measuring range is between 10–150 µM and the detection limit of 5 µM (signal to noise ratio 3:1) of benzaldehyde. The relative standard deviation in a series (n = 13) for 200 µM benzaldehyde is 1.9%. For the biosensor, a response to succinic semialdehyde was also identified. Based on this response and the ability to work at high pH a biosensor for GABA is proposed by coimmobilizing GABA-aminotransferase (GABA-T) and PaoABC in the osmium containing redox polymer.
Catalytic bio–chemo and bio–bio tandem oxidation reactions for amide and carboxylic acid synthesis
(2014)
A catalytic toolbox for three different water-based one-pot cascades to convert aryl alcohols to amides and acids and cyclic amines to lactams, involving combination of oxidative enzymes (monoamine oxidase, xanthine dehydrogenase, galactose oxidase and laccase) and chemical oxidants (TBHP or CuI(cat)/H2O2) at mild temperatures, is presented. Mutually compatible conditions were found to afford products in good to excellent yields.
Polyadenylation is a decisive 3’ end processing step during the maturation of pre-mRNAs. The length of the poly(A) tail has an impact on mRNA stability, localization and translatability. Accordingly, many eukaryotic organisms encode several copies of canonical poly(A) polymerases (cPAPs). The disruption of cPAPs in mammals results in lethality. In plants, reduced cPAP activity is non-lethal. Arabidopsis encodes three nuclear cPAPs, PAPS1, PAPS2 and PAPS4, which are constitutively expressed throughout the plant. Recently, the detailed analysis of Arabidopsis paps1 mutants revealed a subset of genes that is preferentially polyadenylated by the cPAP isoform PAPS1 (Vi et al. 2013). Thus, the specialization of cPAPs might allow the regulation of different sets of genes in order to optimally face developmental or environmental challenges.
To gain insights into the cPAP-based gene regulation in plants, the phenotypes of Arabidopsis cPAPs mutants under different conditions are characterized in detail in the following work. An involvement of all three cPAPs in flowering time regulation and stress response regulation is shown. While paps1 knockdown mutants flower early, paps4 and paps2 paps4 knockout mutants exhibit a moderate late-flowering phenotype. PAPS1 promotes the expression of the major flowering inhibitor FLC, supposedly by specific polyadenylation of an FLC activator. PAPS2 and PAPS4 exhibit partially overlapping functions and ensure timely flowering by repressing FLC and at least one other unidentified flowering inhibitor. The latter two cPAPs act in a novel regulatory pathway downstream of the autonomous pathway component FCA and act independently from the polyadenylation factors and flowering time regulators CstF64 and FY. Moreover, PAPS1 and PAPS2/PAPS4 are implicated in different stress response pathways in Arabidopsis. Reduced activity of the poly(A) polymerase PAPS1 results in enhanced resistance to osmotic and oxidative stress. Simultaneously, paps1 mutants are cold-sensitive. In contrast, PAPS2/PAPS4 are not involved in the regulation of osmotic or cold stress, but paps2 paps4 loss-of-function mutants exhibit enhanced sensitivity to oxidative stress provoked in the chloroplast. Thus, both PAPS1 and PAPS2/PAPS4 are required to maintain a balanced redox state in plants. PAPS1 seems to fulfil this function in concert with CPSF30, a polyadenylation factor that regulates alternative polyadenylation and tolerance to oxidative stress.
The individual paps mutant phenotypes and the cPAP-specific genetic interactions support the model of cPAP-dependent polyadenylation of selected mRNAs. The high similarity of the polyadenylation machineries in yeast, mammals and plants suggests that similar regulatory mechanisms might be present in other organism groups. The cPAP-dependent developmental and physiological pathways identified in this work allow the design of targeted experiments to better understand the ecological and molecular context underlying cPAP-specialization.
Monoclonal antibodies (mAbs) are engineered immunoglobulins G (IgG) used for more than 20 years as targeted therapy in oncology, infectious diseases and (auto-)immune disorders. Their protein nature greatly influences their pharmacokinetics (PK), presenting typical linear and non-linear behaviors.
While it is common to use empirical modeling to analyze clinical PK data of mAbs, there is neither clear consensus nor guidance to, on one hand, select the structure of classical compartment models and on the other hand, interpret mechanistically PK parameters. The mechanistic knowledge present in physiologically-based PK (PBPK) models is likely to support rational classical model selection and thus, a methodology to link empirical and PBPK models is desirable. However, published PBPK models for mAbs are quite diverse in respect to the physiology of distribution spaces and the parameterization of the non-specific elimination involving the neonatal Fc receptor (FcRn) and endogenous IgG (IgGendo). The remarkable discrepancy between the simplicity of biodistribution data and the complexity of published PBPK models translates in parameter identifiability issues.
In this thesis, we address this problem with a simplified PBPK model—derived from a hierarchy of more detailed PBPK models and based on simplifications of tissue distribution model. With the novel tissue model, we are breaking new grounds in mechanistic modeling of mAbs disposition: We demonstrate that binding to FcRn is indeed linear and that it is not possible to infer which tissues are involved in the unspecific elimination of wild-type mAbs. We also provide a new approach to predict tissue partition coefficients based on mechanistic insights: We directly link tissue partition coefficients (Ktis) to data-driven and species-independent published antibody biodistribution coefficients (ABCtis) and thus, we ensure the extrapolation from pre-clinical species to human with the simplified PBPK model. We further extend the simplified PBPK model to account for a target, relevant to characterize the non-linear clearance due to mAb-target interaction.
With model reduction techniques, we reduce the dimensionality of the simplified PBPK model to design 2-compartment models, thus guiding classical model development with physiological and mechanistic interpretation of the PK parameters. We finally derive a new scaling approach for anatomical and physiological parameters in PBPK models that translates the inter-individual variability into the design of mechanistic covariate models with direct link to classical compartment models, specially useful for PK population analysis during clinical development.
The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. Here we analyse a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (similar to 22x) and seven to similar to 1x coverage, to investigate the impact of these on Europe's genetic landscape. These data suggest genomic shifts with the advent of the Neolithic, Bronze and Iron Ages, with interleaved periods of genome stability. The earliest Neolithic context genome shows a European hunter-gatherer genetic signature and a restricted ancestral population size, suggesting direct contact between cultures after the arrival of the first farmers into Europe. The latest, Iron Age, sample reveals an eastern genomic influence concordant with introduced Steppe burial rites. We observe transition towards lighter pigmentation and surprisingly, no Neolithic presence of lactase persistence.
Metabolic systems tend to exhibit steady states that can be measured in terms of their concentrations and fluxes. These measurements can be regarded as a phenotypic representation of all the complex interactions and regulatory mechanisms taking place in the underlying metabolic network. Such interactions determine the system's response to external perturbations and are responsible, for example, for its asymptotic stability or for oscillatory trajectories around the steady state. However, determining these perturbation responses in the absence of fully specified kinetic models remains an important challenge of computational systems biology. Structural kinetic modeling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a parameterised representation of the system's Jacobian matrix in which the model parameters encode information about the enzyme-metabolite interactions. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. The parameter space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Because the sampled parameters are equivalent to the elasticities used in metabolic control analysis (MCA), the results are easy to interpret biologically. In this project, the SKM framework was extended by several novel methodological improvements. These improvements were evaluated in a simulation study using a set of small example pathways with simple Michaelis Menten rate laws. Afterwards, a detailed analysis of the dynamic properties of the neuronal TCA cycle was performed in order to demonstrate how the new insights obtained in this work could be used for the study of complex metabolic systems. The first improvement was achieved by examining the biological feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, the findings showed that the majority of sampled SK-models would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion was formulated that mitigates such infeasible models and the application of this criterion changed the conclusions of the SKM experiment. The second improvement of this work was the application of supervised machine-learning approaches in order to analyse SKM experiments. So far, SKM experiments have focused on the detection of individual enzymes to identify single reactions important for maintaining the stability or oscillatory trajectories. In this work, this approach was extended by demonstrating how SKM enables the detection of ensembles of enzymes or metabolites that act together in an orchestrated manner to coordinate the pathways response to perturbations. In doing so, stable and unstable states served as class labels, and classifiers were trained to detect elasticity regions associated with stability and instability. Classification was performed using decision trees and relevance vector machines (RVMs). The decision trees produced good classification accuracy in terms of model bias and generalizability. RVMs outperformed decision trees when applied to small models, but encountered severe problems when applied to larger systems because of their high runtime requirements. The decision tree rulesets were analysed statistically and individually in order to explore the role of individual enzymes or metabolites in controlling the system's trajectories around steady states. The third improvement of this work was the establishment of a relationship between the SKM framework and the related field of MCA. In particular, it was shown how the sampled elasticities could be converted to flux control coefficients, which were then investigated for their predictive information content in classifier training. After evaluation on the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle with respect to their intrinsic mechanisms responsible for stability or instability. The findings showed that several elasticities were jointly coordinated to control stability and that the main source for potential instabilities were mutations in the enzyme alpha-ketoglutarate dehydrogenase.
Background
The forelimb-specific gene tbx5 is highly conserved and essential for the development of forelimbs in zebrafish, mice, and humans. Amongst birds, a single order, Dinornithiformes, comprising the extinct wingless moa of New Zealand, are unique in having no skeletal evidence of forelimb-like structures.
Results
To determine the sequence of tbx5 in moa, we used a range of PCR-based techniques on ancient DNA to retrieve all nine tbx5 exons and splice sites from the giant moa, Dinornis. Moa Tbx5 is identical to chicken Tbx5 in being able to activate the downstream promotors of fgf10 and ANF. In addition we show that missexpression of moa tbx5 in the hindlimb of chicken embryos results in the formation of forelimb features, suggesting that Tbx5 was fully functional in wingless moa. An alternatively spliced exon 1 for tbx5 that is expressed specifically in the forelimb region was shown to be almost identical between moa and ostrich, suggesting that, as well as being fully functional, tbx5 is likely to have been expressed normally in moa since divergence from their flighted ancestors, approximately 60 mya.
Conclusions
The results suggests that, as in mice, moa tbx5 is necessary for the induction of forelimbs, but is not sufficient for their outgrowth. Moa Tbx5 may have played an important role in the development of moa’s remnant forelimb girdle, and may be required for the formation of this structure. Our results further show that genetic changes affecting genes other than tbx5 must be responsible for the complete loss of forelimbs in moa.
Der Bittergeschmack dient Säugern vermutlich zur Wahrnehmung und Vermeidung toxischer Substanzen. Bitterstoffe können jedoch auch gesund sein oder werden oft bereitwillig mit der Nahrung aufgenommen. Ob sie geschmacklich unterschieden werden können, ist allerdings umstritten. Detektiert werden Bitterstoffe von oralen Bittergeschmacksrezeptoren, den TAS2R (human) bzw. Tas2r (murin). In der Literatur gibt es aber immer mehr Hinweise darauf, dass überdies Tas2r nicht nur in extragustatorischen Organen exprimiert werden, sondern dort auch wichtige Aufgaben erfüllen könnten, was wiederum die Aufklärung ihrer noch nicht vollständig entschlüsselten Funktionsweisen erfordert. So ist noch unbekannt, ob alle bisher als funktionell identifizierten Tas2r wirklich gustatorische Funktionen erfüllen.
Im Rahmen der Charakterisierung neu generierter, im Locus des Bittergeschmacksrezeptors Tas2r131 genetisch modifizierter Mauslinien, wurde in vorliegender Arbeit die gustatorische sowie extragustatorische Expression von Tas2r131 untersucht. Dass Tas2r131 nicht nur in Pilzpapillen, Wall- und Blätterpapillen (VP+FoP), Gaumen, Ductus nasopalatinus, Vomeronasalorgan und Kehldeckel, sondern auch in Thymus, Testes und Nebenhodenkopf, in Gehirnarealen sowie im Ganglion geniculatum nachgewiesen wurde, bildete die Grundlage für weiterführende Studien. Die vorliegende Arbeit zeigt außerdem, dass Tas2r108, Tas2r126, Tas2r135, Tas2r137 und Tas2r143 in Blut exprimiert werden, was auf eine heterogene Funktion der Tas2r hindeutet. Dass zusätzlich erstmals die Expression aller 35 als funktionell beschriebenen Tas2r im gustatorischen VP+FoP-Epithel von C57BL/6-Mäusen nachgewiesen wurde, verweist auf deren Relevanz als funktionelle Geschmacksrezeptoren.
Weiter zeigten Untersuchungen zur Aufklärung eines möglichen Bitter-Unterscheidungsvermögens in Geschmackspapillen von Mäusen mit fluoreszenzmarkierten oder ablatierten Tas2r131-Zellen, dass Tas2r131 exprimierende Zellen eine Tas2r-Zellsubpopulation bilden. Darüber hinaus existieren innerhalb der Bitterzellen geordnete Tas2r-Expressionsmuster, die sich nach der chromosomalen Lage ihrer Gene richten. Isolierte Bitterzellen reagieren heterogen auf bekannte Bitterstoffe. Und Mäuse mit ablatierter Tas2r131-Zellpopulation besitzen noch andere Tas2r-Zellen und schmecken damit einige Bitterstoffe kaum noch, andere aber noch sehr gut. Diese Befunde belegen die Existenz verschiedener gustatorischer Tas2r-Zellpopulationen, welche die Voraussetzung bilden, Bitterstoffe heterogen zu detektieren. Ob dies die Grundlage für ein divergierendes Verhalten gegenüber unverträglichen und harmlosen oder gar nützlichen Bitterstoffen darstellt, kann mit Hilfe der dargelegten Tas2r-Expressionsmuster künftig in Verhaltensexperimenten geprüft werden.
Die Bittergeschmackswahrnehmung in Säugetieren stellt sich als ein hochkomplexer Mechanismus dar, dessen Vielschichtigkeit durch die hier neu aufgezeigten heterogenen Tas2r-Expressions- und Funktionsmuster erneut verdeutlicht wird.