Development of a read mapping analysis software and computational pan genome analysis of 20 Pseudomonas aeruginosa strains

Hilker R. Development of a read mapping analysis software and computational pan genome analysis of 20 Pseudomonas aeruginosa strains. Bielefeld: Bielefeld University; 2015.In times of multi-resistant pathogenic bacteria, their detailed study is of utmost importance. Their comparative analysis can even aid the emerging field of personalized medicine by enabling optimized treatment depending on the presence of virulence factors and antibiotic resistances in the infection concerned. The weaknesses and functionality of these pathogenic bacteria can be investigated using modern computer science and novel sequencing technologies. One of these methods is the bioinformatics evaluation of high-throughput sequencing data. A pathogenic bacterium posing severe health care issues is the ubiquitous Pseudomonas aeruginosa. It is involved in a wide range of infections mainly affecting the pulmonary or urinary tract, open wounds and burns. The prevalence of chronic obstructive pulmonary disease cases with P. aeruginosa in Germany alone is ~600,000 per year. Within the framework of this dissertation, computational comparative genomics experiments were conducted with a panel of 20 of the most abundant Pseudomonas aeruginosa strains. 15 of these strains were isolated from clinical cases, while the remaining 5 were strains without a known infection history isolated from the environment. This division was chosen to enable direct comparison of the pathogenic potential of clinical and environmental strains and identification of their possible characteristic differences. When designing the bioinformatics experiments and searching for an efficient visualization and automatic analysis platform for read alignment (mapping) data, it became evident that no adequate solution was available that included all required functionalities. On these grounds, the decision was made to define two main subjects for this dissertation. Besides the P. aeruginosa pan genome analysis, a novel read mapping visualization and analysis software was developed and published in the journal Bioinformatics. This software - ReadXplorer - is partly based upon a prototype, which was developed during a preceding master's thesis at the Center for Biotechnology of the Bielefeld University under the name VAMP. The software was developed into a comprehensive user-friendly platform augmented with several newly developed and implemented automatic bioinformatics read mapping analyses. Two examples of these are the transcription start site detection and the single nucleotide polymorphism detection. Moreover, new intuitive visualizations were added to the existent ones and existing visualizations were greatly enhanced. ReadXplorer is designed to support not only DNA-seq data as accrued in the P. aeruginosa experiments, but also any kind of standard read mapping data as obtained from RNA-seq or ChIP-seq experiments. The data management was designed to comply with the latest performance and efficiency needs emerging from the large next generation sequencing data sets. Finally, ReadXplorer was empowered to deal with eukaryotic read mapping data as well. Amongst other software, ReadXplorer was then used to analyze different comparative genomics aspects of P. aeruginosa and to draw conclusions regarding the development of their pathogenicity. The list of conducted experiments includes phylogeny and gene set determination, analysis of regions of genomic plasticity and identification of single nucleotide polymorphisms. The achieved results were published in the journal Environmental Biology

Estructura genética, filogeografía, variación adaptativa y especiación en árboles tropicales del género Symphonia

The genetic structure within a species is the result of the levels of the genetic diversity and its spatial distribution. Also, it depends significantly on the specific evolutionary history experienced by the species. Thus, to disentangle the overlapping evolutionary processes acting at different levels in a species or a taxon, it will be necessary to work at different spatial scales and at different taxonomic levels as complementary approaches. The study of the fine-scale spatial genetic structure in plants (the micro scale approach) will imply to work at the shortest spatial scales and to capture detailed information on the spatial distribution of genotypes at within-population scale. The analysis at this scale will help to detect mainly evolutionary and ecological processes more related to short‐term periods of time and/or smaller spatial scales such as habitat fragmentation and other disturbances, efficiency of dispersal mechanisms or gene dispersal distances. On the other side, the study of the genetic structure at wider scales (the macro scale approach), including both geographical and taxonomic (i.e., speciation) points of view, will usually imply to detect larger spatio-temporal processes and to work with deeper evolutionary timescales. In this sense, the spatial genetic structure within a species at this macro scale will be the result of different historical and contemporary influences such as connectivity across the range of the species and landscape barriers, environmental adaptation, demographic history or climatic events, among others. Finally, if we include the taxonomic perspective in the analysis of genetic structure in a group of closely related species, we will be able to analyse the processes leading to speciation, which also may involve those previously mentioned.La estructura genética que presenta una especie es el resultado de sus niveles de diversidad genética, así como de su distribución espacial. Además, depende significativamente de la historia evolutiva específica que ha sufrido la especie. Así, para desentrañar los procesos evolutivos que actúan simultáneamente a diferentes niveles en una especie o taxon, será necesario trabajar mediante enfoques complementarios, orientados a diferentes escalas espaciales y a diferentes niveles taxonómicos. El estudio de la estructura genética espacial a pequeña escala en plantas (un enfoque en escala micro) implicará trabajar en las escalas espaciales más pequeñas, así como recoger información detallada de la distribución espacial de genotipos dentro de las poblaciones. El análisis a esta escala ayudará a detectar principalmente procesos evolutivos y ecológicos relacionados principalmente con periodos de tiempo cortos y/o a escala espacial pequeña, tales como fragmentación de hábitats y otras perturbaciones, eficiencia de los mecanismos de dispersión o distancias de dispersión genética. Por otro lado, el estudio de la estructura genética a escala más amplia (un enfoque en escala macro), incluyendo los puntos de vista geográfico y taxonómico (es decir, de especiación), normalmente implicará detectar procesos espacio-temporales más amplios y trabajar con escalas evolutivas de tiempo más largas. En este sentido, la estructura genética espacial de una especie a escala macro será el resultado de diferentes influencias históricas y contemporáneas, tales como la conectividad a lo largo de la distribución de la especie, las barreras del paisaje, la adaptación al medio, la historia demográfica o los eventos climáticos, entre otros. Finalmente, si incluímos la perspectiva taxonómica en el análisis de la estructura genética de un grupo de especies muy relacionadas, podremos ser capaces de analizar los procesos que conducen a la especiación, entre los cuales se pueden encontrar también los ya previamente mencionados.Doctorado en Conservación y Uso Sostenible de Sistemas Forestale

Role of genomic imprinting in cerebral cortex development

Genomic imprinting is an epigenetic process that leads to parent of origin-specific gene expression in a subset of genes. Imprinted genes are essential for brain development, and deregulation of imprinting is associated with neurodevelopmental diseases and the pathogenesis of psychiatric disorders. However, the cell-type specificity of imprinting at single cell resolution, and how imprinting and thus gene dosage regulates neuronal circuit assembly is still largely unknown. Here, MADM (Mosaic Analysis with Double Markers) technology was employed to assess genomic imprinting at single cell level. By visualizing MADM-induced uniparental disomies (UPDs) in distinct colors at single cell level in genetic mosaic animals, this experimental paradigm provides a unique quantitative platform to systematically assay the UPD-mediated imbalances in imprinted gene expression at unprecedented resolution. An experimental pipeline based on FACS, RNA-seq and bioinformatics analysis was established and applied to systematically map cell-type-specific ‘imprintomes’ in the mouse brain. The results revealed that parental-specific expression of imprinted genes per se is rarely cell-type-specific even at the individual cell level. Conversely, when we extended the comparison to downstream responses resulting from imbalanced imprinted gene expression, we discovered an unexpectedly high degree of cell-type specificity. Furthermore, we determined a novel function of genomic imprinting in cortical astrocyte production and in olfactory bulb (OB) granule cell generation. These results suggest important functional implication of genomic imprinting for generating cell-type diversity in the brain. In addition, MADM provides a powerful tool to study candidate genes by concomitant genetic manipulation and fluorescent labelling of single cells. MADM-based candidate gene approach was utilized to identify potential imprinted genes involved in the generation of cortical astrocytes and OB granule cells. We investigated p57Kip2, a maternally expressed gene and known cell cycle regulator. Although we found that p57Kip2 does not play a role in these processes, we detected an unexpected function of the paternal allele previously thought to be silent. Finally, we took advantage of a key property of MADM which is to allow unambiguous investigation of environmental impact on single cells. The experimental pipeline based on FACS and RNA-seq analysis of MADM-labeled cells was established to probe the functional differences of single cell loss of gene function compared to global loss of function on a transcriptional level. With this method, both common and distinct responses were isolated due to cell-autonomous and non-autonomous effects acting on genotypically identical cells. As a result, transcriptional changes were identified which result solely from the surrounding environment. Using the MADM technology to study genomic imprinting at single cell resolution, we have identified cell-type-specific gene expression, novel gene function and the impact of environment on single cell transcriptomes. Together, these provide important insights to the understanding of mechanisms regulating cell-type specificity and thus diversity in the brain

Investigating the Effect of Putative Cytokinin Antagonists on Root Growth in Rice, and their Efficacy in Mitigating Stress

There is a plethora of challenges that must be addressed this century to ensure the demand for food, fodder and biofuel is met. Feeding 9 billion people whilst counteracting the negative effects that erratic and more severe weather events are having due to climate change is a challenge that requires innovative approaches. Drought and salinity are significant limiting factors to crop yields, and modifying plant traits to avoid these stresses has been identified as a method of improving crop productivity. This study investigated the ability of putative root-specific cytokinin antagonists, molecules that block activity of the plant hormone cytokinin, to promote root growth in rice as a mechanism for improving crop abiotic stress tolerance. In addition to the parent compound, four novel compounds synthesised by Globachem Discovery Ltd. were found to promote root growth of the rice variety, Nipponbare, in liquid media. Subsequently, seed priming was established as a way of applying the compounds, significantly reducing preparation time and the quantity of product required. The long-term effects of priming were found to not affect aboveground biomass but did confer a negative effect to yield. The compounds were also tested for their ability to promote root growth in commercially relevant rice varieties and growth settings under drought and salt stress. However, the increase in root length found in Nipponbare was not observed in a commercial setting or commercially used rice varieties under optimum or stress conditions, highlighting the high specificity of the compounds. These findings show that whilst there is potential for these compounds to promote root growth, their use must be further optimised for agricultural purposes. In parallel to the lab-based studies, three models were designed and implemented in Chapters 2, 4 and 5. A machine learning technique was used to predict the likelihood of a compound having biological activity, based on its chemical properties. In a subsequent chapter the effects of spatial heterogeneity within a glasshouse were quantified and accounted for statistically. Finally, geospatial modelling was used to identify key regions where plant growth regulators could be applied most effectively. These models allow the optimisation of current practice, from agrochemical design to dissemination of a product, thereby contributing to a more robust agricultural system. The lab-based assays and different modelling approaches used in this study highlight the multi-faceted and collaborative approaches that are required to tackle the pressing humanitarian and environmental challenges of this century. This study goes some way to addressing these challenges

Identification and functional characterization of relaxin-type and pedal peptide/orcokinin-type neuropeptides in the starfish Asterias rubens

PhDNeuropeptides are neuronal signaling molecules that regulate many physiological and behavioural processes in vertebrates and invertebrates. Investigation of neuropeptide signaling in echinoderms (e.g. starfish) can provide insights into the evolution of neuropeptide systems because as deuterostomian invertebrates they occupy an “intermediate” phylogenetic position between vertebrates and protostomian invertebrates. Recent analysis of neural transcriptome data from the starfish Asterias rubens has identified 40 transcripts encoding neuropeptide precursors. Here the expression and function of neuropeptides derived from four of these precursors was investigated: relaxin-like gonad-stimulating peptide precursor (AruRGPP), relaxin-like peptide precursor 2 (AruRLPP2), pedal peptide-like neuropeptide precursors 1 and 2 (ArPPLNP1 and ArPPLNP2). AruRGP induces spawning of ovarian fragments from A. rubens. Analysis of the expression of AruRGPP in A. rubens using mRNA in situ hybridization revealed expression by cells in the radial nerve cords, circumoral nerve ring and tube feet. Furthermore, a band of AruRGPP-expressing cells was also identified in the body wall epithelium lining the cavity that surrounds the sensory terminal tentacle and optic cushion at the tips of the arms. Discovery of these cells is important because they are candidate physiological mediators for hormonal control of starfish spawning in response to environmental cues. Interestingly, AruRLPP2 is also expressed in the same region of the arm tip as AruRGPP but the physiological role(s) of AruRLP2 is not yet known. Analysis of the expression of ArPPLNP1 and ArPPLNP2 using mRNA in situ hybridization revealed a widespread pattern of expression in A. rubens. Furthermore, immunohistochemical localization of peptides derived from these precursors revealed immunostaining in neuronal processes innervating muscles. Consistent with this pattern of expression, peptides derived from ArPPLNP1 and ArPPLNP2 act as muscle relaxants in starfish. Interestingly, this contrasts with previous findings from protostomian invertebrates, where pedal peptide/orcokinin-type neuropeptides act as muscle contractants

Transcription factor Pax6 protects mouse cortical cell fate specification

The mammalian cortex is composed of two main types of neuron. Principal cells (PCs) are glutamatergic and use glutamate as the main neurotransmitter. Interneurons are mostly GABAergic and use GABA as their main neurotransmitter. PCs are the output units of the cortex and comprise ~80-85% of the mouse cortex. Interneurons modulate the activity of PCs and comprise ~20-15% of the mouse cortex. These two broad cell types originate from separate regions of the developing nervous system. Early embryo development is dependent on the balance between cell proliferation and differentiation. The process of cortical progenitor pool expansion, division and production of postmitotic cells starts at around embryonic day (E) 10.5. PCs arise from the dorsal telencephalon while interneurons arise from the ventral telencephalon. The process of telencephalon regionalization is regulated by differential expression of transcription factors (TFs). Pax6 is one of such TFs. Importantly, it is expressed strongly in the PC dorsal Emx1 lineage but much less so or not at all in interneuron ventral lineages. Here I investigated the postnatal characteristics of a Cre-loxP recombinant mouse that had Pax6 removed from the Emx1-lineage at E11.5. I targeted L5 and L2/3 of the somatosensory cortex and recorded their intrinsic electrophysiological properties. The results suggested that PCs can be specified without the need for Pax6 as the intrinsic properties of neurons in layers 5 and layers 2 and 3 were not significantly different than those of control cells. I explored an ectopic population of cells from the Emx1-lineage that expressed GABAergic markers in the embryo using electrophysiology and immunostaining. The results indicated that ectopic cells do not develop much electrical activity and stay in a state of arrested development. I investigated the consequences of deleting Pax6 in Emx1-lineage progenitor cell cultures. The results revealed the possibility that Emx1-lineage progenitors can produce interneurons in the absence of Pax6 if Sonic Hedgehog is activated. Taken together, the results support the hypothesis that Pax6 protects cortical PC specification by inhibiting interneuron-inducing signals

IST Austria Thesis

Mosaic genetic analysis has been widely used in different model organisms such as the fruit fly to study gene-function in a cell-autonomous or tissue-specific fashion. More recently, and less easily conducted, mosaic genetic analysis in mice has also been enabled with the ambition to shed light on human gene function and disease. These genetic tools are of particular interest, but not restricted to, the study of the brain. Notably, the MADM technology offers a genetic approach in mice to visualize and concomitantly manipulate small subsets of genetically defined cells at a clonal level and single cell resolution. MADM-based analysis has already advanced the study of genetic mechanisms regulating brain development and is expected that further MADM-based analysis of genetic alterations will continue to reveal important insights on the fundamental principles of development and disease to potentially assist in the development of new therapies or treatments. In summary, this work completed and characterized the necessary genome-wide genetic tools to perform MADM-based analysis at single cell level of the vast majority of mouse genes in virtually any cell type and provided a protocol to perform lineage tracing using the novel MADM resource. Importantly, this work also explored and revealed novel aspects of biologically relevant events in an in vivo context, such as the chromosome-specific bias of chromatid sister segregation pattern, the generation of cell-type diversity in the cerebral cortex and in the cerebellum and finally, the relevance of the interplay between the cell-autonomous gene function and cell-non-autonomous (community) effects in radial glial progenitor lineage progression. This work provides a foundation and opens the door to further elucidating the molecular mechanisms underlying neuronal diversity and astrocyte generation

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities. This survey article assesses the potential of DL in IIoT applications and presents a brief architecture of IIoT with key enabling technologies. Several well-known DL algorithms are then discussed along with their theoretical backgrounds and several software and hardware frameworks for DL implementations. Potential deployments of DL techniques in IIoT applications are briefly discussed. Finally, this survey highlights significant challenges and future directions for future research endeavors

Mathematics & Statistics 2017 APR Self-Study & Documents

UNM Mathematics & Statistics APR self-study report, review team report, response report, and initial action plan for Spring 2017, fulfilling requirements of the Higher Learning Commission