@phdthesis{Zhang2018,
  author    = {Zhang, Yunming},
  title     = {Understanding the functional specialization of poly(A) polymerases in Arabidopsis thaliana},
  school      = {Universit{\"a}t Potsdam},
  pages     = {131},
  year      = {2018},
  language  = {de}
}
@phdthesis{Westbury2018,
  author    = {Westbury, Michael V.},
  title     = {Unraveling evolution through Next Generation Sequencing},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409981},
  school      = {Universit{\"a}t Potsdam},
  pages     = {129},
  year      = {2018},
  abstract  = {The sequencing of the human genome in the early 2000s led to an increased interest in cheap and fast sequencing technologies. This interest culminated in the advent of next generation sequencing (NGS). A number of different NGS platforms have arisen since then all promising to do the same thing, i.e. produce large amounts of genetic information for relatively low costs compared to more traditional methods such as Sanger sequencing. The capabilities of NGS meant that researchers were no longer bound to species for which a lot of previous work had already been done (e.g. model organisms and humans) enabling a shift in research towards more novel and diverse species of interest. This capability has greatly benefitted many fields within the biological sciences, one of which being the field of evolutionary biology. Researchers have begun to move away from the study of laboratory model organisms to wild, natural populations and species which has greatly expanded our knowledge of evolution. NGS boasts a number of benefits over more traditional sequencing approaches. The main benefit comes from the capability to generate information for drastically more loci for a fraction of the cost. This is hugely beneficial to the study of wild animals as, even when large numbers of individuals are unobtainable, the amount of data produced still allows for accurate, reliable population and species level results from a small selection of individuals. The use of NGS to study species for which little to no previous research has been carried out on and the production of novel evolutionary information and reference datasets for the greater scientific community were the focuses of this thesis. Two studies in this thesis focused on producing novel mitochondrial genomes from shotgun sequencing data through iterative mapping, bypassing the need for a close relative to serve as a reference sequence. These mitochondrial genomes were then used to infer species level relationships through phylogenetic analyses. The first of these studies involved reconstructing a complete mitochondrial genome of the bat eared fox (Otocyon megalotis). Phylogenetic analyses of the mitochondrial genome confidently placed the bat eared fox as sister to the clade consisting of the raccoon dog and true foxes within the canidae family. The next study also involved reconstructing a mitochondrial genome but in this case from the extinct Macrauchenia of South America. As this study utilised ancient DNA, it involved a lot of parameter testing, quality controls and strict thresholds to obtain a near complete mitochondrial genome devoid of contamination known to plague ancient DNA studies. Phylogenetic analyses confidently placed Macrauchenia as sister to all living representatives of Perissodactyla with a divergence time of ~66 million years ago. The third and final study of this thesis involved de novo assemblies of both nuclear and mitochondrial genomes from brown and striped hyena and focussed on demographic, genetic diversity and population genomic analyses within the brown hyena. Previous studies of the brown hyena hinted at very low levels of genomic diversity and, perhaps due to this, were unable to find any notable population structure across its range. By incorporating a large number of genetic loci, in the form of complete nuclear genomes, population structure within the brown hyena was uncovered. On top of this, genomic diversity levels were compared to a number of other species. Results showed the brown hyena to have the lowest genomic diversity out of all species included in the study which was perhaps caused by a continuous and ongoing decline in effective population size that started about one million years ago and dramatically accelerated towards the end of the Pleistocene. The studies within this thesis show the power NGS sequencing has and its utility within evolutionary biology. The most notable capabilities outlined in this thesis involve the study of species for which no reference data is available and in the production of large amounts of data, providing evolutionary answers at the species and population level that data produced using more traditional techniques simply could not.},
  language  = {en}
}
@phdthesis{Ullmann2018,
  author    = {Ullmann, Wiebke},
  title     = {Understanding animal movement behaviour in dynamic agricultural landscapes},
  doi       = {10.25932/publishup-42715},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427153},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 183},
  year      = {2018},
  abstract  = {The movement of organisms has formed our planet like few other processes. Movements shape populations, communities, entire ecosystems, and guarantee fundamental ecosystem functions and services, like seed dispersal and pollination. Global, regional and local anthropogenic impacts influence animal movements across ecosystems all around the world. In particular, land-use modification, like habitat loss and fragmentation disrupt movements between habitats with profound consequences, from increased disease transmissions to reduced species richness and abundance. However, neither the influence of anthropogenic change on animal movement processes nor the resulting effects on ecosystems are well understood. Therefore, we need a coherent understanding of organismal movement processes and their underlying mechanisms to predict and prevent altered animal movements and their consequences for ecosystem functions. In this thesis I aim at understanding the influence of anthropogenically caused land-use change on animal movement processes and their underlying mechanisms. In particular, I am interested in the synergistic influence of large-scale landscape structure and fine-scale habitat features on basic-level movement behaviours (e.g. the daily amount of time spend running, foraging, and resting) and their emerging higher-level movements (home range formation). Based on my findings, I identify the likely consequences of altered animal movements that lead to the loss of species richness and abundances. The study system of my thesis are hares in agricultural landscapes. European brown hares (Lepus europaeus) are perfectly suited to study animal movements in agricultural landscapes, as hares are hermerophiles and prefer open habitats. They have historically thrived in agricultural landscapes, but their numbers are in decline. Agricultural areas are undergoing strong land-use changes due to increasing food demand and fast developing agricultural technologies. They are already the largest land-use class, covering 38\% of the world's terrestrial surface. To consider the relevance of a given landscape structure for animal movement behaviour I selected two differently structured agricultural landscapes - a simple landscape in Northern Germany with large fields and few landscape elements (e.g. hedges and tree stands), and a complex landscape in Southern Germany with small fields and many landscape elements. I applied GPS devices (hourly fixes) with internal high-resolution accelerometers (4 min samples) to track hares, receiving an almost continuous observation of the animals' behaviours via acceleration analyses. I used the spatial and behavioural information in combination with remote sensing data (normalized difference vegetation index, or NDVI, a proxy for resource availability), generating an almost complete idea of what the animal was doing when, why and where. Apart from landscape structure (represented by the two differently structured study areas), I specifically tested whether the following fine-scale habitat features influence animal movements: resource, agricultural management events, habitat diversity, and habitat structure. My results show that, irrespective of the movement process or mechanism and the type of fine-scale habitat features, landscape structure was the overarching variable influencing hare movement behaviour. High resource variability forces hares to enlarge their home ranges, but only in the simple and not in the complex landscape. Agricultural management events result in home range shifts in both landscapes, but force hares to increase their home ranges only in the simple landscape. Also the preference of habitat patches with low vegetation and the avoidance of high vegetation, was stronger in the simple landscape. High and dense crop fields restricted hare movements temporarily to very local and small habitat patch remnants. Such insuperable barriers can separate habitat patches that were previously connected by mobile links. Hence, the transport of nutrients and genetic material is temporarily disrupted. This mechanism is also working on a global scale, as human induced changes from habitat loss and fragmentation to expanding monocultures cause a reduction in animal movements worldwide. The mechanisms behind those findings show that higher-level movements, like increasing home ranges, emerge from underlying basic-level movements, like the behavioural modes. An increasing landscape simplicity first acts on the behavioural modes, i.e. hares run and forage more, but have less time to rest. Hence, the emergence of increased home range sizes in simple landscapes is based on an increased proportion of time running and foraging, largely due to longer travelling times between distant habitats and scarce resource items in the landscape. This relationship was especially strong during the reproductive phase, demonstrating the importance of high-quality habitat for reproduction and the need to keep up self-maintenance first, in low quality areas. These changes in movement behaviour may release a cascade of processes that start with more time being allocated to running and foraging, resulting into an increased energy expenditure and may lead to a decline in individual fitness. A decrease in individual fitness and reproductive output will ultimately affect population viability leading to local extinctions. In conclusion, I show that landscape structure has one of the most important effects on hare movement behaviour. Synergistic effects of landscape structure, and fine-scale habitat features, first affect and modify basic-level movement behaviours, that can scales up to altered higher-level movements and may even lead to the decline of species richness and abundances, and the disruption of ecosystem functions. Understanding the connection between movement mechanisms and processes can help to predict and prevent anthropogenically induced changes in movement behaviour. With regard to the paramount importance of landscape structure, I strongly recommend to decrease the size of agricultural fields and increase crop diversity. On the small-scale, conservation policies should assure the year round provision of areas with low vegetation height and high quality forage. This could be done by generating wildflower strips and additional (semi-) natural habitat patches. This will not only help to increase the populations of European brown hares and other farmland species, but also ensure and protects the continuity of mobile links and their intrinsic value for sustaining important ecosystem functions and services.},
  language  = {en}
}
@phdthesis{Stoessel2018,
  author    = {St{\"o}ßel, Daniel},
  title     = {Biomarker Discovery in Multiple Sclerosis and Parkinson's disease},
  school      = {Universit{\"a}t Potsdam},
  pages     = {135},
  year      = {2018},
  abstract  = {Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression. By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS. In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation.},
  language  = {en}
}
@phdthesis{Schoene2018,
  author    = {Sch{\"o}ne, Anne-Christin},
  title     = {Degradation of Aliphatic Polyesters at the Air-Water Interface - Capabilities of the Langmuir Monolayer Technique},
  school      = {Universit{\"a}t Potsdam},
  pages     = {109, XXXIX},
  year      = {2018},
  language  = {en}
}
@phdthesis{Schwarzer2018,
  author    = {Schwarzer, Christian},
  title     = {Climate change, adaptive divergence and their effects on species interactions in European bog-plant communities},
  school      = {Universit{\"a}t Potsdam},
  pages     = {169},
  year      = {2018},
  language  = {en}
}
@phdthesis{Schwanhold2018,
  author    = {Schwanhold, Nadine},
  title     = {Die Funktion und Spezifit{\"a}t der Molybd{\"a}n-Cofaktor-bindenden Chaperone f{\"u}r die Formiat-Dehydrogenasen aus Escherichia coli und Rhodobacter capsulatus},
  school      = {Universit{\"a}t Potsdam},
  pages     = {132},
  year      = {2018},
  language  = {de}
}
@phdthesis{Schwahn2018,
  author    = {Schwahn, Kevin},
  title     = {Data driven approaches to infer the regulatory mechanism shaping and constraining levels of metabolites in metabolic networks},
  doi       = {10.25932/publishup-42324},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423240},
  school      = {Universit{\"a}t Potsdam},
  pages     = {109},
  year      = {2018},
  abstract  = {Systems biology aims at investigating biological systems in its entirety by gathering and analyzing large-scale data sets about the underlying components. Computational systems biology approaches use these large-scale data sets to create models at different scales and cellular levels. In addition, it is concerned with generating and testing hypotheses about biological processes. However, such approaches are inevitably leading to computational challenges due to the high dimensionality of the data and the differences in the dimension of data from different cellular layers. This thesis focuses on the investigation and development of computational approaches to analyze metabolite profiles in the context of cellular networks. This leads to determining what aspects of the network functionality are reflected in the metabolite levels. With these methods at hand, this thesis aims to answer three questions: (1) how observability of biological systems is manifested in metabolite profiles and if it can be used for phenotypical comparisons; (2) how to identify couplings of reaction rates from metabolic profiles alone; and (3) which regulatory mechanism that affect metabolite levels can be distinguished by integrating transcriptomics and metabolomics read-outs. I showed that sensor metabolites, identified by an approach from observability theory, are more correlated to each other than non-sensors. The greater correlations between sensor metabolites were detected both with publicly available metabolite profiles and synthetic data simulated from a medium-scale kinetic model. I demonstrated through robustness analysis that correlation was due to the position of the sensor metabolites in the network and persisted irrespectively of the experimental conditions. Sensor metabolites are therefore potential candidates for phenotypical comparisons between conditions through targeted metabolic analysis. Furthermore, I demonstrated that the coupling of metabolic reaction rates can be investigated from a purely data-driven perspective, assuming that metabolic reactions can be described by mass action kinetics. Employing metabolite profiles from domesticated and wild wheat and tomato species, I showed that the process of domestication is associated with a loss of regulatory control on the level of reaction rate coupling. I also found that the same metabolic pathways in Arabidopsis thaliana and Escherichia coli exhibit differences in the number of reaction rate couplings. I designed a novel method for the identification and categorization of transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approach determines the partial correlation of metabolites with control by the principal components of the transcript levels. The principle components contain the majority of the transcriptomic information allowing to partial out the effect of the transcriptional layer from the metabolite profiles. Depending whether the correlation between metabolites persists upon controlling for the effect of the transcriptional layer, the approach allows us to group metabolite pairs into being associated due to post-transcriptional or transcriptional regulation, respectively. I showed that the classification of metabolite pairs into those that are associated due to transcriptional or post-transcriptional regulation are in agreement with existing literature and findings from a Bayesian inference approach. The approaches developed, implemented, and investigated in this thesis open novel ways to jointly study metabolomics and transcriptomics data as well as to place metabolic profiles in the network context. The results from these approaches have the potential to provide further insights into the regulatory machinery in a biological system.},
  language  = {en}
}
@phdthesis{RodriguezCubillos2018,
  author    = {Rodriguez Cubillos, Andres Eduardo},
  title     = {Understanding the impact of heterozygosity on metabolism, growth and hybrid necrosis within a local Arabidopsis thaliana collection site},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-416758},
  school      = {Universit{\"a}t Potsdam},
  pages     = {106},
  year      = {2018},
  abstract  = {Plants are unable to move away from unwanted environments and therefore have to locally adapt to changing conditions. Arabidopsis thaliana (Arabidopsis), a model organism in plant biology, has been able to rapidly colonize a wide spectrum of environments with different biotic and abiotic challenges. In recent years, natural variation in Arabidopsis has shown to be an excellent resource to study genes underlying adaptive traits and hybridization's impact on natural diversity. Studies on Arabidopsis hybrids have provided information on the genetic basis of hybrid incompatibilities and heterosis, as well as inheritance patterns in hybrids. However, previous studies have focused mainly on global accessions and yet much remains to be known about variation happening within a local growth habitat. In my PhD, I investigated the impact of heterozygosity at a local collection site of Arabidopsis and its role in local adaptation. I focused on two different projects, both including hybrids among Arabidopsis individuals collected around T{\"u}bingen in Southern Germany. The first project sought to understand the impact of hybridization on metabolism and growth within a local Arabidopsis collection site. For this, the inheritance patterns in primary and secondary metabolism, together with rosette size of full diallel crosses among seven parents originating from Southern Germany were analyzed. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed pronounced non-additive inheritance patterns. In addition, defense metabolites, mainly glucosinolates, displayed the highest degree of variation from the midparent values and were positively correlated with a proxy for plant size. In the second project, the role of ACCELERATED CELL DEATH 6 (ACD6) in the defense response pathway of Arabidopsis necrotic hybrids was further characterized. Allelic interactions of ACD6 have been previously linked to hybrid necrosis, both among global and local Arabidopsis accessions. Hence, I characterized the early metabolic and ionic changes induced by ACD6, together with marker gene expression assays of physiological responses linked to its activation. An upregulation of simple sugars and metabolites linked to non-enzymatic antioxidants and the TCA cycle were detected, together with putrescine and acids linked to abiotic stress responses. Senescence was found to be induced earlier in necrotic hybrids and cytoplasmic calcium signaling was unaffected in response to temperature. In parallel, GFP-tagged constructs of ACD6 were developed. This work therefore gave novel insights on the role of heterozygosity in natural variation and adaptation and expanded our current knowledge on the physiological and molecular responses associated with ACD6 activation.},
  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}
}