@phdthesis{Bemm2018,
  author    = {Bemm, Felix Mathias},
  title     = {Genetic foundation of unrivaled survival strategies - Of water bears and carnivorous plants -},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157109},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {All living organisms leverage mechanisms and response systems to optimize reproduction, defense, survival, and competitiveness within their natural habitat. Evolutionary theories such as the universal adaptive strategy theory (UAST) developed by John Philip Grime (1979) attempt to describe how these systems are limited by the trade-off between growth, maintenance and regeneration; known as the universal three-way trade-off. Grime introduced three adaptive strategies that enable organisms to coop with either high or low intensities of stress (e.g., nutrient deficiency) and environmental disturbance (e.g., seasons). The competitor is able to outcompete other organisms by efficiently tapping available resources in environments of low intensity stress and disturbance (e.g., rapid growers). A ruderal specism is able to rapidly complete the life cycle especially during high intensity disturbance and low intensity stress (e.g., annual colonizers). The stress tolerator is able to respond to high intensity stress with physiological variability but is limited to low intensity disturbance environments. Carnivorous plants like D. muscipula and tardigrades like M. tardigradum are two extreme examples for such stress tolerators. D. muscipula traps insects in its native habitat (green swamps in North and South Carolina) with specialized leaves and thereby is able to tolerate nutrient deficient soils. M. tardigradum on the other side, is able to escape desiccation of its terrestrial habitat like mosses and lichens which are usually covered by a water film but regularly fall completely dry. The stress tolerance of the two species is the central study object of this thesis. In both cases, high througput sequencing data and methods were used to test for transcriptomic (D. muscipula) or genomic adaptations (M. tardigradum) which underly the stress tolerance. A new hardware resource including computing cluster and high availability storage system was implemented in the first months of the thesis work to effectively analyze the vast amounts of data generated for both projects. Side-by-side, the data management resource TBro [14] was established together with students to intuitively approach complex biological questions and enhance collaboration between researchers of several different disciplines. Thereafter, the unique trapping abilities of D. muscipula were studied using a whole transcriptome approach. Prey-dependent changes of the transcriptional landscape as well as individual tissue-specific aspects of the whole plant were studied. The analysis revealed that non-stimulated traps of D. muscipula exhibit the expected hallmarks of any typical leaf but operates evolutionary conserved stress-related pathways including defense-associated responses when digesting prey. An integrative approach, combining proteome and transcriptome data further enabled the detailed description of the digestive cocktail and the potential nutrient uptake machinery of the plant. The published work [25] as well as a accompanying video material (https://www.eurekalert.org/pub_releases/ 2016-05/cshl-fgr042816.php; Video credit: S{\"o}nke Scherzer) gained global press coverage and successfully underlined the advantages of D. muscipula as experimental system to understand the carnivorous syndrome. The analysis of the peculiar stress tolerance of M. tardigradum during cryptobiosis was carried out using a genomic approach. First, the genome size of M. tardigradum was estimated, the genome sequenced, assembled and annotated. The first draft of M. tardigradum and the workflow used to established its genome draft helped scrutinizing the first ever released tardigrade genome (Hypsibius dujardini) and demonstrated how (bacterial) contamination can influence whole genome analysis efforts [27]. Finally, the M. tardigradum genome was compared to two other tardigrades and all species present in the current release of the Ensembl Metazoa database. The analysis revealed that tardigrade genomes are not that different from those of other Ecdysozoa. The availability of the three genomes allowed the delineation of their phylogenetic position within the Ecdysozoa and placed them as sister taxa to the nematodes. Thereby, the comparative analysis helped to identify evolutionary trends within this metazoan lineage. Surprisingly, the analysis did not reveal general mechanisms (shared by all available tardigrade genomes) behind the arguably most peculiar feature of tardigrades; their enormous stress tolerance. The lack of molecular evidence for individual tardigrade species (e.g., gene expression data for M. tardigradum) and the non-existence of a universal experimental framework which enables hypothesis testing withing the whole phylum Tardigrada, made it nearly impossible to link footprints of genomic adaptations to the unusual physiological capabilities. Nevertheless, the (comparative) genomic framework established during this project will help to understand how evolution tinkered, rewired and modified existing molecular systems to shape the remarkable phenotypic features of tardigrades.},
  subject      = {B{\"a}rtierchen},
  language  = {en}
}
@phdthesis{Kessie2021,
  author    = {Kessie, David Komla},
  title     = {Characterisation of Bordetella pertussis virulence mechanisms using engineered human airway tissue models},
  doi       = {10.25972/OPUS-23571},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235717},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Pertussis is a highly contagious acute respiratory disease of humans which is mainly caused by the gram-negative obligate human pathogen Bordetella pertussis. Despite the availability and extensive use of vaccines, the disease persists and has shown periodic re-emergence resulting in an estimated 640,000 deaths worldwide in 2014. The pathogen expresses various virulence factors that enable it to modulate the host immune response, allowing it to colonise the ciliated airway mucosa. Many of these factors also directly interfere with host signal transduction systems, causing damage to the ciliated airway mucosa and increase mucous production. Of the many virulence factors of B. pertussis, only the tracheal cytotoxin (TCT) is able to recapitulate the pathophysiology of ciliated cell extrusion and blebbing in animal models and in human nasal biopsies. Furthermore, due to the lack of appropriate human models and donor materials, the role of bacterial virulence factors has been extrapolated from studies using animal models infected with either B. pertussis or with the closely related species B. bronchiseptica which naturally causes respiratory infections in these animals and produces many similar virulence factors. Thus, in the present work, in vitro airway mucosa models developed by co-culturing human airway epithelia cells and fibroblasts from the conduction zone of the respiratory tract on a decellularized porcine small intestine submucosa scaffold (SISser®) were used, since these models have a high correlation to native human conducting zone respiratory epithelia. The major aim was to use the engineered airway mucosa models to elucidate the contribution of B. pertussis TCT in the pathophysiology of the disease as well as the virulence mechanism of B. pertussis in general. TCT and lipopolysaccharide (LPS) either alone or in combination were observed to induce epithelial cell blebbing and necrosis in the in vitro airway mucosa model. Additionally, the toxins induced viscous hyper-mucous secretion and significantly disrupted barrier properties of the in vitro airway mucosa models. This work also sought to assess the invasion and intracellular survival of B. pertussis in the polarised epithelia, which has been critically discussed for many years in the literature. Infection of the models with B. pertussis showed that the bacteria can adhere to the models and invade the epithelial cells as early as 6 hours post inoculation. Invasion and intracellular survival assays indicated the bacteria could invade and persist intracellularly in the epithelial cells for up to 3 days. Due to the novelty of the in vitro airway mucosa models, this work also intended to establish a method for isolating individual cells for scRNA-seq after infection with B. pertussis. Cold dissociation with Bacillus licheniformis subtilisin A was found to be capable of dissociating the cells without inducing a strong fragmentation, a problem which occurs when collagenase and trypsin/EDTA are used. In summary, the present work showed that TCT acts possibly in conjunction with LPS to disrupt the human airway mucosa much like previously shown in the hamster tracheal ring models and thus appears to play an important role during the natural B. pertussis infection. Furthermore, we established a method for infecting and isolating infected cells from the airway mucosa models in order to further investigate the effect of B. pertussis infection on the different cell populations in the airway by single cell analytics in the future.},
  subject      = {Tissue engineering},
  language  = {en}
}
@phdthesis{Dietrich2024,
  author    = {Dietrich, Oliver},
  title     = {Integrating single-cell multi-omics to decipher host-pathogen interactions},
  doi       = {10.25972/OPUS-36013},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-360138},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Interactions between host and pathogen determine the development, progression and outcomes of disease. Medicine benefits from better descriptions of these interactions through increased precision of prevention, diagnosis and treatment of diseases. Single-cell genomics is a disruptive technology revolutionizing science by increasing the resolution with which we study diseases. Cell type specific changes in abundance or gene expression are now routinely investigated in diseases. Meanwhile, detecting cellular phenotypes across diseases can connect scientific fields and fuel discovery. Insights acquired through systematic analysis of high resolution data will soon be translated into clinical practice and improve decision making. Therefore, the continued use of single-cell technologies and their application towards clinical samples will improve molecular interpretation, patient stratification, and the prediction of outcomes. In the past years, I was fortunate to participate in interdisciplinary research groups bridging biology, clinical research and data science. I was able to contribute to diverse projects through computational analysis and biological interpretation of sequencing data. Together, we were able to discover cellular phenotypes that influence disease progression and outcomes as well as the response to treatment. Here, I will present four studies that I have conducted in my PhD. First, we performed a case study of relapse from cell-based immunotherapy in Multiple Myeloma. We identified genomic deletion of the epitope as mechanism of immune escape and implicate heterozygosity or monosomy of the genomic locus at baseline as a potential risk factor. Second, we investigated the pathomechanisms of severe COVID-19 at the earliest stage of the COVID- 19 pandemic in Germany in March 2020. We discovered that profibrotic macrophages and lung fibrosis can be caused by SARS-CoV-2 infection. Third, we used a mouse model of chronic infection with Staphylococcus aureus that causes Osteomyelitis similar to the human disease. We were able to identify dysregulated immunometabolism associated with the generation of myeloid-derived suppressor cells (MDSC). Fourth, we investigated Salmonella infection of the human small intestine in an in vitro model and describe features of pathogen invasion and host response. Overall, I have been able to successfully employ single-cell sequencing to discover important aspects of diseases ranging from development to treatment and outcome. I analyzed samples from the clinics, human donors, mouse models and organoid models to investigate different aspects of diseases and managed to integrate data across sample types, technologies and diseases. Based on successful studies, we increased our efforts to combine data from multiple sources to build comprehensive references for the integration of large collections of clinical samples. Our findings exemplify how single-cell sequencing can improve clinical research and highlights the potential of mechanistic discoveries to drive precision medicine.},
  subject      = {Einzelzellanalyse},
  language  = {en}
}