@article{UppaluriNaglerStellamannsetal.2011, author = {Uppaluri, Sravanti and Nagler, Jan and Stellamanns, Eric and Heddergott, Niko and Herminghaus, Stephan and Pfohl, Thomas and Engstler, Markus}, title = {Impact of Microscopic Motility on the Swimming Behavior of Parasites: Straighter Trypanosomes are More Directional}, series = {PLoS Computational Biology}, volume = {7}, journal = {PLoS Computational Biology}, number = {6}, doi = {10.1371/journal.pcbi.1002058}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140814}, pages = {e1002058}, year = {2011}, abstract = {Microorganisms, particularly parasites, have developed sophisticated swimming mechanisms to cope with a varied range of environments. African Trypanosomes, causative agents of fatal illness in humans and animals, use an insect vector (the Tsetse fly) to infect mammals, involving many developmental changes in which cell motility is of prime importance. Our studies reveal that differences in cell body shape are correlated with a diverse range of cell behaviors contributing to the directional motion of the cell. Straighter cells swim more directionally while cells that exhibit little net displacement appear to be more bent. Initiation of cell division, beginning with the emergence of a second flagellum at the base, correlates to directional persistence. Cell trajectory and rapid body fluctuation correlation analysis uncovers two characteristic relaxation times: a short relaxation time due to strong body distortions in the range of 20 to 80 ms and a longer time associated with the persistence in average swimming direction in the order of 15 seconds. Different motility modes, possibly resulting from varying body stiffness, could be of consequence for host invasion during distinct infective stages.}, language = {en} } @article{WagnerFischerThomaetal.2011, author = {Wagner, Toni U. and Fischer, Andreas and Thoma, Eva C. and Schartl, Manfred}, title = {CrossQuery: A Web Tool for Easy Associative Querying of Transcriptome Data}, series = {PLoS ONE}, volume = {6}, journal = {PLoS ONE}, number = {12}, doi = {10.1371/journal.pone.0028990}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134787}, pages = {e28990}, year = {2011}, abstract = {Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.}, language = {en} } @article{KaltdorfSchulzeHelmprobstetal.2017, author = {Kaltdorf, Kristin Verena and Schulze, Katja and Helmprobst, Frederik and Kollmannsberger, Philip and Dandekar, Thomas and Stigloher, Christian}, title = {Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms}, series = {PLoS Computational Biology}, volume = {13}, journal = {PLoS Computational Biology}, number = {1}, doi = {10.1371/journal.pcbi.1005317}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172112}, year = {2017}, abstract = {Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.}, language = {en} } @article{TemmeFriebeSchmidtetal.2017, author = {Temme, Sebastian and Friebe, Daniela and Schmidt, Timo and Poschmann, Gereon and Hesse, Julia and Steckel, Bodo and St{\"u}hler, Kai and Kunz, Meik and Dandekar, Thomas and Ding, Zhaoping and Akhyari, Payam and Lichtenberg, Artur and Schrader, J{\"u}rgen}, title = {Genetic profiling and surface proteome analysis of human atrial stromal cells and rat ventricular epicardium-derived cells reveals novel insights into their cardiogenic potential}, series = {Stem Cell Research}, volume = {25}, journal = {Stem Cell Research}, doi = {10.1016/j.scr.2017.11.006}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172716}, pages = {183-190}, year = {2017}, abstract = {Epicardium-derived cells (EPDC) and atrial stromal cells (ASC) display cardio-regenerative potential, but the molecular details are still unexplored. Signals which induce activation, migration and differentiation of these cells are largely unknown. Here we have isolated rat ventricular EPDC and rat/human ASC and performed genetic and proteomic profiling. EPDC and ASC expressed epicardial/mesenchymal markers (WT-1, Tbx18, CD73,CD90, CD44, CD105), cardiac markers (Gata4, Tbx5, troponin T) and also contained phosphocreatine. We used cell surface biotinylation to isolate plasma membrane proteins of rEPDC and hASC, Nano-liquid chromatography with subsequent mass spectrometry and bioinformatics analysis identified 396 rat and 239 human plasma membrane proteins with 149 overlapping proteins. Functional GO-term analysis revealed several significantly enriched categories related to extracellular matrix (ECM), cell migration/differentiation, immunology or angiogenesis. We identified receptors for ephrin and growth factors (IGF, PDGF, EGF, anthrax toxin) known to be involved in cardiac repair and regeneration. Functional category enrichment identified clusters around integrins, PI3K/Akt-signaling and various cardiomyopathies. Our study indicates that EPDC and ASC have a similar molecular phenotype related to cardiac healing/regeneration. The cell surface proteome repository will help to further unravel the molecular details of their cardio-regenerative potential and their role in cardiac diseases.}, language = {en} }