@phdthesis{Schuette2011,
  author    = {Sch{\"u}tte, Moritz},
  title     = {Evolutionary fingerprints in genome-scale networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-57483},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.},
  language  = {en}
}
@phdthesis{Stanke2023,
  author    = {Stanke, Sandra},
  title     = {AC electrokinetic immobilization of influenza viruses and antibodies on nanoelectrode arrays for on-chip immunoassays},
  doi       = {10.25932/publishup-61716},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-617165},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 115},
  year      = {2023},
  abstract  = {In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.},
  language  = {en}
}
@phdthesis{Martin2013,
  author    = {Martin, Benjamin},
  title     = {Linking individual-based models and dynamic energy budget theory : lessons for ecology and ecotoxicology},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-67001},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {In the context of ecological risk assessment of chemicals, individual-based population models hold great potential to increase the ecological realism of current regulatory risk assessment procedures. However, developing and parameterizing such models is time-consuming and often ad hoc. Using standardized, tested submodels of individual organisms would make individual-based modelling more efficient and coherent. In this thesis, I explored whether Dynamic Energy Budget (DEB) theory is suitable for being used as a standard submodel in individual-based models, both for ecological risk assessment and theoretical population ecology. First, I developed a generic implementation of DEB theory in an individual-based modeling (IBM) context: DEB-IBM. Using the DEB-IBM framework I tested the ability of the DEB theory to predict population-level dynamics from the properties of individuals. We used Daphnia magna as a model species, where data at the individual level was available to parameterize the model, and population-level predictions were compared against independent data from controlled population experiments. We found that DEB theory successfully predicted population growth rates and peak densities of experimental Daphnia populations in multiple experimental settings, but failed to capture the decline phase, when the available food per Daphnia was low. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detecting gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. In addition to theoretical explorations, we tested the potential of DEB theory combined with IBMs to extrapolate effects of chemical stress from the individual to population level. For this we used information at the individual level on the effect of 3,4-dichloroanailine on Daphnia. The individual data suggested direct effects on reproduction but no significant effects on growth. Assuming such direct effects on reproduction, the model was able to accurately predict the population response to increasing concentrations of 3,4-dichloroaniline. We conclude that DEB theory combined with IBMs holds great potential for standardized ecological risk assessment based on ecological models.},
  language  = {en}
}
@phdthesis{Mubeen2018,
  author    = {Mubeen, Umarah},
  title     = {Regulation of central carbon and nitrogen metabolism by Target of Rapamycin (TOR) kinase in Chlamydomonas reinhardtii},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 153},
  year      = {2018},
  abstract  = {The highly conserved protein complex containing the Target of Rapamycin (TOR) kinase is known to integrate intra- and extra-cellular stimuli controlling nutrient allocation and cellular growth. This thesis describes three studies aimed to understand how TOR signaling pathway influences carbon and nitrogen metabolism in Chlamydomonas reinhardtii. The first study presents a time-resolved analysis of the molecular and physiological features across the diurnal cycle. The inhibition of TOR leads to 50\% reduction in growth followed by nonlinear delays in the cell cycle progression. The metabolomics analysis showed that the growth repression is mainly driven by differential carbon partitioning between anabolic and catabolic processes. Furthermore, the high accumulation of nitrogen-containing compounds indicated that TOR kinase controls the carbon to nitrogen balance of the cell, which is responsible for biomass accumulation, growth and cell cycle progression. In the second study the cause of the high accumulation of amino acids is explained. For this purpose, the effect of TOR inhibition on Chlamydomonas was examined under different growth regimes using stable 13C- and 15N-isotope labeling. The data clearly showed that an increased nitrogen uptake is induced within minutes after the inhibition of TOR. Interestingly, this increased N-influx is accompanied by increased activities of nitrogen assimilating enzymes. Accordingly, it was concluded that TOR inhibition induces de-novo amino acid synthesis in Chlamydomonas. The recognition of this novel process opened an array of questions regarding potential links between central metabolism and TOR signaling. Therefore a detailed phosphoproteomics study was conducted to identify the potential substrates of TOR pathway regulating central metabolism. Interestingly, some of the key enzymes involved in carbon metabolism as well as amino acid synthesis exhibited significant changes in the phosphosite intensities immediately after TOR inhibition. Altogether, these studies provide a) detailed insights to metabolic response of Chlamydomonas to TOR inhibition, b) identification of a novel process causing rapid upshifts in amino acid levels upon TOR inhibition and c) finally highlight potential targets of TOR signaling regulating changes in central metabolism. Further biochemical and molecular investigations could confirm these observations and advance the understanding of growth signaling in microalgae.},
  language  = {en}
}
@phdthesis{Robalo2018,
  author    = {Robalo, Jo{\~a}o Ramiro Alavedra Mendes},
  title     = {Investigating the role of fluorinated amino acids on protein structure and function using simulation},
  school      = {Universit{\"a}t Potsdam},
  pages     = {84},
  year      = {2018},
  language  = {en}
}
@phdthesis{Swart2017,
  author    = {Swart, Corn{\´e}},
  title     = {Managing protein activity in A. thaliana},
  school      = {Universit{\"a}t Potsdam},
  pages     = {160},
  year      = {2017},
  language  = {en}
}
@phdthesis{Yishai2019,
  author    = {Yishai, Oren},
  title     = {Engineering the reductive glycine pathway in Escherichia coli},
  school      = {Universit{\"a}t Potsdam},
  pages     = {86},
  year      = {2019},
  language  = {en}
}
@phdthesis{Pellegrino2022,
  author    = {Pellegrino, Antonio},
  title     = {miRNA profiling for diagnosis of chronic pain in polyneuropathy},
  doi       = {10.25932/publishup-58385},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-583858},
  school      = {Universit{\"a}t Potsdam},
  pages     = {viii, 97, xi},
  year      = {2022},
  abstract  = {This dissertation aimed to determine differential expressed miRNAs in the context of chronic pain in polyneuropathy. For this purpose, patients with chronic painful polyneuropathy were compared with age matched healthy patients. Taken together, all miRNA pre library preparation quality controls were successful and none of the samples was identified as an outlier or excluded for library preparation. Pre sequencing quality control showed that library preparation worked for all samples as well as that all samples were free of adapter dimers after BluePippin size selection and reached the minimum molarity for further processing. Thus, all samples were subjected to sequencing. The sequencing control parameters were in their optimal range and resulted in valid sequencing results with strong sample to sample correlation for all samples. The resulting FASTQ file of each miRNA library was analyzed and used to perform a differential expression analysis. The differentially expressed and filtered miRNAs were subjected to miRDB to perform a target prediction. Three of those four miRNAs were downregulated: hsa-miR-3135b, hsa-miR-584-5p and hsa-miR-12136, while one was upregulated: hsa-miR-550a-3p. miRNA target prediction showed that chronic pain in polyneuropathy might be the result of a combination of miRNA mediated high blood flow/pressure and neural activity dysregulations/disbalances. Thus, leading to the promising conclusion that these four miRNAs could serve as potential biomarkers for the diagnosis of chronic pain in polyneuropathy. Since TRPV1 seems to be one of the major contributors of nociception and is associated with neuropathic pain, the influence of PKA phosphorylated ARMS on the sensitivity of TRPV1 as well as the part of AKAP79 during PKA phosphorylation of ARMS was characterized. Therefore, possible PKA-sites in the sequence of ARMS were identified. This revealed five canonical PKA-sites: S882, T903, S1251/52, S1439/40 and S1526/27. The single PKA-site mutants of ARMS revealed that PKA-mediated ARMS phosphorylation seems not to influence the interaction rate of TRPV1/ARMS. While phosphorylation of ARMST903 does not increase the interaction rate with TRPV1, ARMSS1526/27 is probably not phosphorylated and leads to an increased interaction rate. The calcium flux measurements indicated that the higher the interaction rate of TRPV1/ARMS, the lower the EC50 for capsaicin of TRPV1, independent of the PKA phosphorylation status of ARMS. In addition, the western blot analysis confirmed the previously observed TRPV1/ARMS interaction. More importantly, AKAP79 seems to be involved in the TRPV1/ARMS/PKA signaling complex. To overcome the problem of ARMS-mediated TRPV1 sensitization by interaction, ARMS was silenced by shRNA. ARMS silencing resulted in a restored TRPV1 desensitization without affecting the TRPV1 expression and therefore could be used as new topical therapeutic analgesic alternative to stop ARMS mediated TRPV1 sensitization.},
  language  = {en}
}