@phdthesis{Ankenbrand2018, author = {Ankenbrand, Markus Johannes}, title = {Squeezing more information out of biological data - development and application of bioinformatic tools for ecology, evolution and genomics}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-156344}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2018}, abstract = {New experimental methods have drastically accelerated the pace and quantity at which biological data is generated. High-throughput DNA sequencing is one of the pivotal new technologies. It offers a number of novel applications in various fields of biology, including ecology, evolution, and genomics. However, together with those opportunities many new challenges arise. Specialized algorithms and software are required to cope with the amount of data, often requiring substantial training in bioinformatic methods. Another way to make those data accessible to non-bioinformaticians is the development of programs with intuitive user interfaces. In my thesis I developed analyses and programs to tackle current problems with high-throughput data in biology. In the field of ecology this covers the establishment of the bioinformatic workflow for pollen DNA meta-barcoding. Furthermore, I developed an application that facilitates the analysis of ecological communities in the context of their traits. Information from multiple public databases have been aggregated and can now be mapped automatically to existing community tables for interactive inspection. In evolution the new data are used to reconstruct phylogenetic trees from multiple genes. I developed the tool bcgTree to automate this process for bacteria. Many plant genomes have been sequenced in current years. Sequencing reads of those projects also contain data from the chloroplasts. The tool chloroExtractor supports the targeted extraction and analysis of the chloroplast genome. To compare the structure of multiple genomes specialized software is required for calculation and visualization of the relationships. I developed AliTV to address this. In contrast to existing programs for this task it allows interactive adjustments of produced graphics. Thus, facilitating the discovery of biologically relevant information. Another application I developed helps to analyze transcriptomes even if no reference genome is present. This is achieved by aggregating the different pieces of information, like functional annotation and expression level, for each transcript in a web platform. Scientists can then search, filter, subset, and visualize the transcriptome. Together the methods and tools expedite insights into biological systems that were not possible before.}, language = {en} } @article{HelmprobstKneitzKlotzetal.2021, author = {Helmprobst, Frederik and Kneitz, Susanne and Klotz, Barbara and Naville, Magali and Dechaud, Corentin and Volff, Jean-Nicolas and Schartl, Manfred}, title = {Differential expression of transposable elements in the medaka melanoma model}, series = {PLoS One}, volume = {16}, journal = {PLoS One}, number = {10}, doi = {10.1371/journal.pone.0251713}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260615}, year = {2021}, abstract = {Malignant melanoma incidence is rising worldwide. Its treatment in an advanced state is difficult, and the prognosis of this severe disease is still very poor. One major source of these difficulties is the high rate of metastasis and increased genomic instability leading to a high mutation rate and the development of resistance against therapeutic approaches. Here we investigate as one source of genomic instability the contribution of activation of transposable elements (TEs) within the tumor. We used the well-established medaka melanoma model and RNA-sequencing to investigate the differential expression of TEs in wildtype and transgenic fish carrying melanoma. We constructed a medaka-specific TE sequence library and identified TE sequences that were specifically upregulated in tumors. Validation by qRT- PCR confirmed a specific upregulation of a LINE and an LTR element in malignant melanomas of transgenic fish.}, language = {en} } @article{HoehneProkopovKuhletal.2021, author = {H{\"o}hne, Christin and Prokopov, Dmitry and Kuhl, Heiner and Du, Kang and Klopp, Christophe and Wuertz, Sven and Trifonov, Vladimir and St{\"o}ck, Matthias}, title = {The immune system of sturgeons and paddlefish (Acipenseriformes): a review with new data from a chromosome-scale sturgeon genome}, series = {Reviews in Aquaculture}, volume = {13}, journal = {Reviews in Aquaculture}, number = {3}, doi = {10.1111/raq.12542}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-239865}, pages = {1709 -- 1729}, year = {2021}, abstract = {Sturgeon immunity is relevant for basic evolutionary and applied research, including caviar- and meat-producing aquaculture, protection of wild sturgeons and their re-introduction through conservation aquaculture. Starting from a comprehensive overview of immune organs, we discuss pathways of innate and adaptive immune systems in a vertebrate phylogenetic and genomic context. The thymus as a key organ of adaptive immunity in sturgeons requires future molecular studies. Likewise, data on immune functions of sturgeon-specific pericardial and meningeal tissues are largely missing. Integrating immunological and endocrine functions, the sturgeon head kidney resembles that of teleosts. Recently identified pattern recognition receptors in sturgeon require research on downstream regulation. We review first acipenseriform data on Toll-like receptors (TLRs), type I transmembrane glycoproteins expressed in membranes and endosomes, initiating inflammation and host defence by molecular pattern-induced activation. Retinoic acid-inducible gene-I-like (RIG-like) receptors of sturgeons present RNA and key sensors of virus infections in most cell types. Sturgeons and teleosts share major components of the adaptive immune system, including B cells, immunoglobulins, major histocompatibility complex and the adaptive cellular response by T cells. The ontogeny of the sturgeon innate and onset of adaptive immune genes in different organs remain understudied. In a genomics perspective, our new data on 100 key immune genes exemplify a multitude of evolutionary trajectories after the sturgeon-specific genome duplication, where some single-copy genes contrast with many duplications, allowing tissue specialization, sub-functionalization or both. Our preliminary conclusion should be tested by future evolutionary bioinformatics, involving all >1000 immunity genes. This knowledge update about the acipenseriform immune system identifies several important research gaps and presents a basis for future applications.}, language = {en} } @phdthesis{Liang2009, author = {Liang, Chunguang}, title = {Tools for functional genomics applied to Staphylococci, Listeriae, Vaccinia virus and other organisms}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-48051}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2009}, abstract = {Genome sequence analysis A combination of genome analysis application has been established here during this project. This offers an efficient platform to interactively compare similar genome regions and reveal loci differences. The genes and operons can be rapidly analyzed and local collinear blocks (LCBs) categorized according to their function. The features of interests are parsed, recognized, and clustered into reports. Phylogenetic relationships can be readily examined such as the evolution of critical factors or a certain highly-conserved region. The resulting platform-independent software packages (GENOVA and inGeno), have been proven to be efficient and easy to handle in a number of projects. The capabilities of the software allowed the investigation of virulence factors, e.g., rsbU, strains' biological design, and in particular pathogenicity feature storage and management. We have successfully investigated the genomes of Staphylococcus aureus strains (COL, N315, 8325, RN1HG, Newman), Listeria spp. (welshimeri, innocua and monocytogenes), E.coli strains (O157:H7 and MG1655) and Vaccinia strains (WR, Copenhagen, Lister, LIVP, GLV-1h68 and parental strains). Metabolic network analysis Our YANAsquare package offers a workbench to rapidly establish the metabolic network of such as Staphylococcous aureus bacteria in genome-scale size as well as metabolic networks of interest such as the murine phagosome lipid signalling network. YANAsquare recruits reactions from online databases using an integrated KEGG browser. This reduces the efforts in building large metabolic networks. The involved calculation routines (METATOOL-derived wrapper or native Java implementation) readily obtain all possible flux modes (EM/EP) for metabolite fluxes within the network. Advanced layout algorithms visualize the topological structure of the network. In addition, the generated structure can be dynamically modified in the graphic interface. The generated network as well as the manipulated layout can be validated and stored (XML file: scheme of SBML level-2). This format can be further parsed and analyzed by other systems biology software, such as CellDesigner. Moreover, the integrated robustness-evaluation routine is able to examine the synthesis rates affected by each single mutation throughout the whole network. We have successfully applied the method to simulate single and multiple gene knockouts, and the affected fluxes are comprehensively revealed. Recently we applied the method to proteomic data and extra-cellular metabolite data of Staphylococci, the physiological changes regarding the flux distribution are studied. Calculations at different time points, including different conditions such as hypoxia or stress, show a good fit to experimental data. Moreover, using the proteomic data (enzyme amounts) calculated from 2D-Gel-EP experiments our study provides a way to compare the fluxome and the enzyme expression. Oncolytic vaccinia virus (VACV) We investigated the genetic differences between the de novo sequence of the recombinant oncolytic GLV-1h68 and other related VACVs, including function predictions for all found genome differences. Our phylogenetic analysis indicates that GLV-1h68 is closest to Lister strains but has lost several ORFs present in its parental LIVP strain, including genes encoding CrmE and a viral Golgi anti-apoptotic protein, v-GAAP. Functions of viral genes were either strain-specific, tissue-specific or host-specific comparing viral genes in the Lister, WR and COP strains. This helps to rationally design more optimized oncolytic virus strains to benefit cancer therapy in human patients. Identified differences from the comparison in open reading frames (ORFs) include genes for host-range selection, virulence and immune modulation proteins, e.g. ankyrin-like proteins, serine proteinase inhibitor SPI-2/CrmA, tumor necrosis factor (TNF) receptor homolog CrmC, semaphorin-like and interleukin-1 receptor homolog proteins. The contribution of foreign gene expression cassettes in the therapeutic and oncolytic virus GLV-1h68 was studied, including the F14.5L, J2R and A56R loci. The contribution of F14.5L inactivation to the reduced virulence is demonstrated by comparing the virulence data of GLV-1h68 with its F14.5L-null and revertant viruses. The comparison suggests that insertion of a foreign gene expression cassette in a nonessential locus in the viral genome is a practical way to attenuate VACVs, especially if the nonessential locus itself contains a virulence gene. This reduces the virulence of the virus without compromising too much the replication competency of the virus, the key to its oncolytic activity. The reduced pathogenicity of GLV-1h68 was confirmed by our experimental collaboration partners in male mice bearing C6 rat glioma and in immunocompetent mice bearing B16-F10 murine melanoma. In conclusion, bioinformatics and experimental data show that GLV-1h68 is a promising engineered VACV variant for anticancer therapy with tumor-specific replication, reduced pathogenicity and benign tissue tropism.}, subject = {Genanalyse}, language = {en} } @article{MehmoodAlsalehWantetal.2023, author = {Mehmood, Rashid and Alsaleh, Alanoud and Want, Muzamil Y. and Ahmad, Ijaz and Siraj, Sami and Ishtiaq, Muhammad and Alshehri, Faizah A. and Naseem, Muhammad and Yasuhara, Noriko}, title = {Integrative molecular analysis of DNA methylation dynamics unveils molecules with prognostic potential in breast cancer}, series = {BioMedInformatics}, volume = {3}, journal = {BioMedInformatics}, number = {2}, issn = {2673-7426}, doi = {10.3390/biomedinformatics3020029}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-321171}, pages = {434 -- 445}, year = {2023}, abstract = {DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer.}, language = {en} }