TY - JOUR A1 - Dütting, Sebastian A1 - Gaits-Iacovoni, Frederique A1 - Stegner, David A1 - Popp, Michael A1 - Antkowiak, Adrien A1 - van Eeuwijk, Judith M.M. A1 - Nurden, Paquita A1 - Stritt, Simon A1 - Heib, Tobias A1 - Aurbach, Katja A1 - Angay, Oguzhan A1 - Cherpokova, Deya A1 - Heinz, Niels A1 - Baig, Ayesha A. A1 - Gorelashvili, Maximilian G. A1 - Gerner, Frank A1 - Heinze, Katrin G. A1 - Ware, Jerry A1 - Krohne, Georg A1 - Ruggeri, Zaverio M. A1 - Nurden, Alan T. A1 - Schulze, Harald A1 - Modlich, Ute A1 - Pleines, Irina A1 - Brakebusch, Cord A1 - Nieswandt, Bernhard T1 - A Cdc42/RhoA regulatory circuit downstream of glycoprotein Ib guides transendothelial platelet biogenesis JF - Nature Communications N2 - Blood platelets are produced by large bone marrow (BM) precursor cells, megakaryocytes (MKs), which extend cytoplasmic protrusions (proplatelets) into BM sinusoids. The molecular cues that control MK polarization towards sinusoids and limit transendothelial crossing to proplatelets remain unknown. Here, we show that the small GTPases Cdc42 and RhoA act as a regulatory circuit downstream of the MK-specific mechanoreceptor GPIb to coordinate polarized transendothelial platelet biogenesis. Functional deficiency of either GPIb or Cdc42 impairs transendothelial proplatelet formation. In the absence of RhoA, increased Cdc42 activity and MK hyperpolarization triggers GPIb-dependent transmigration of entire MKs into BM sinusoids. These findings position Cdc42 (go-signal) and RhoA (stop-signal) at the centre of a molecular checkpoint downstream of GPIb that controls transendothelial platelet biogenesis. Our results may open new avenues for the treatment of platelet production disorders and help to explain the thrombocytopenia in patients with Bernard–Soulier syndrome, a bleeding disorder caused by defects in GPIb-IX-V. KW - megakaryocytes KW - blood platelets KW - regulatory circuit downstream KW - glycoprotein Ib Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-170797 VL - 8 IS - 15838 ER - TY - JOUR A1 - Katja, Schulze A1 - López, Diana A. A1 - Tillich, Ulrich M. A1 - Frohme, Marcus T1 - A simple viability analysis for unicellular cyanobacteria using a new autofluorescence assay, automated microscopy, and ImageJ JF - BMC Biotechnology N2 - Background Currently established methods to identify viable and non-viable cells of cyanobacteria are either time-consuming (eg. plating) or preparation-intensive (eg. fluorescent staining). In this paper we present a new and fast viability assay for unicellular cyanobacteria, which uses red chlorophyll fluorescence and an unspecific green autofluorescence for the differentiation of viable and non-viable cells without the need of sample preparation. Results The viability assay for unicellular cyanobacteria using red and green autofluorescence was established and validated for the model organism Synechocystis sp. PCC 6803. Both autofluorescence signals could be observed simultaneously allowing a direct classification of viable and non-viable cells. The results were confirmed by plating/colony count, absorption spectra and chlorophyll measurements. The use of an automated fluorescence microscope and a novel ImageJ based image analysis plugin allow a semi-automated analysis. Conclusions The new method simplifies the process of viability analysis and allows a quick and accurate analysis. Furthermore results indicate that a combination of the new assay with absorption spectra or chlorophyll concentration measurements allows the estimation of the vitality of cells. KW - variability analysis KW - unicellular cyanobacteria KW - autofluorescence Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-137735 VL - 11 IS - 118 ER - TY - THES A1 - Schulze, Katja T1 - Automatisierte Klassifizierung und Viabilitätsanalyse von Phytoplankton T1 - Automated classification and viability analysis for phytoplankton N2 - Zentrales Ziel dieser Arbeit war es, Methoden der Mikroskopie, Bildverarbeitung und Bilderkennung für die Charakterisierungen verschiedener Phyotplankter zu nutzen, um deren Analyse zu verbessern und zu vereinfachen. Der erste Schwerpunkt der Arbeit lag auf der Analyse von Phytoplanktongemeinschaften, die im Rahmen der Überprüfung der Süßwasserqualität als Marker dienen. Die konventionelle Analyse ist dabei sehr aufwendig, da diese noch immer vollständig von Hand durchgeführt wird und hierfür speziell ausgebildetes Personal eingesetzt werden muss. Ziel war es, ein System zur automatischen Erkennung aufzubauen, um die Analyse vereinfachen zu können. Mit Hilfe von automatischer Mikroskopie war es möglich Plankter unterschiedlicher Ausdehnung durch die Integration mehrerer Schärfeebenen besser in einem Bild aufzunehmen. Weiterhin wurden verschiedene Fluoreszenzeigenschaften in die Analyse integriert. Mit einem für ImageJ erstellten Plugin können Organismen vom Hintergrund der Aufnahmen abgetrennt und eine Vielzahl von Merkmalen berechnet werden. Über das Training von neuralen Netzen wird die Unterscheidung von verschieden Gruppen von Planktontaxa möglich. Zudem können weitere Taxa einfach in die Analyse integriert und die Erkennung erweitert werden. Die erste Analyse von Mischproben, bestehend aus 10 verschiedenen Taxa, zeigte dabei eine durchschnittliche Erkennungsrate von 94.7% und eine durchschnittliche Falsch-Positiv Rate von 5.5%. Im Vergleich mit bestehenden Systemen konnte die Erkennungsrate verbessert und die Falsch Positiv Rate deutlich gesenkt werde. Bei einer Erweiterung des Datensatzes auf 22 Taxa wurde darauf geachtet, Arten zu verwenden, die verschiedene Stadien in ihrem Wachstum durchlaufen oder höhere Ähnlichkeiten zu den bereits vorhandenen Arten aufweisen, um evtl. Schwachstellen des Systemes erkennen zu können. Hier ergab sich eine gute Erkennungsrate (86.8%), bei der der Ausschluss von nicht-planktonischen Partikeln (11.9%) weiterhin verbessert war. Der Vergleich mit weiteren Klassifikationsverfahren zeigte, dass neuronale Netze anderen Verfahren bei dieser Problemstellung überlegen sind. Ähnlich gute Klassifikationsraten konnten durch Support Vektor Maschinen erzielt werden. Allerdings waren diese bei der Unterscheidung von unbekannten Partikeln dem neuralen Netz deutlich unterlegen. Der zweite Abschnitt stellt die Entwicklung einer einfachen Methode zur Viabilitätsanalyse von Cyanobakterien, bei der keine weitere Behandlung der Proben notwendig ist, dar. Dabei wird die rote Chlorophyll - Autofluoreszenz als Marker für lebende Zellen und eine grüne unspezifische Fluoreszenz als Marker für tote Zellen genutzt. Der Assay wurde mit dem Modellorganismus Synechocystis sp. PCC 6803 etabliert und validiert. Die Auswahl eines geeigeneten Filtersets ermöglicht es beide Signale gleichzeitig anzuregen und zu beobachten und somit direkt zwischen lebendenden und toten Zellen zu unterscheiden. Die Ergebnisse zur Etablierung des Assays konnten durch Ausplattieren, Chlorophyllbestimmung und Bestimmung des Absorbtionsspektrums bestätigt werden. Durch den Einsatz von automatisierter Mikroskopie und einem neu erstellten ImageJ Plugin wurde eine sehr genaue und schnelle Analyse der Proben möglich. Der Einsatz beim Monitoring einer mutagenisierten Kultur zur Erhöhung der Temperaturtoleranz ermöglichte genaue und zeitnahe Einblicke in den Zustand der Kultur. Weitere Ergebnisse weisen darauf hin, dass die Kombination mit Absorptionsspektren es ermöglichen können bessere Einblicke in die Vitalität der Kultur zu erhalten. N2 - Central goal of this work was to improve and simplify the characterization of different phytoplankter by the use of automated microscopy, image processing and image analysis. The first part of the work dealt with the analysis of pytoplankton communities, which are used as a marker for the determination of fresh water quality. The current routine analysis, is very time consuming and expensive, as it is carried out manually by trained personnel. Thus the goal of this work was to develop a system for automating the analysis. With the use of automated microscopy different focal planes could be integrated into one image, which made it possible to image plankter of different focus levels simultaneously. Additionally it allowed the integration of different fluorescence characteristics into the analysis. An image processing routine, developed in ImageJ, allows the segmentation of organisms from the image background and the calculation of a large range of features. Neural networks are then used for the classification of previously defined groups of plankton taxa. The program allows easy integration of additional taxa and expansion of the recognition targets. The analysis of samples containing 10 different taxa showed an average recognition rate of 94.7% and an average error rate of 5.5%. The obtained recognition rate was better than those of existing systems and the exclusion of non-plankton particles could be greatly improved. After extending the data set to 22 different classes of (more demanding) taxa a still good recognition (86.9 %) and still improved error rate (11.9 %) were obtained. This extended set was specifically selected in order to target potential weaknesses of the system. It contained mainly taxa that showed strong similarities to each other or taxa that go through various different morphological stages during their growth. The obtained recognition rates were comparable or better than those of existing systems and the exclusion of non-plankton particles could be greatly improved. A comparison of different classification methods showed, that neural networks are superior to all other investigated methods when used for this specific task. While similar recognition rates could be achieved with the use of support vector machines they were vastly inferior for the differentiation of unknown particles. The second part focused on the development of a simple live - dead assay for unicellular cyanobacteria without the need of sample preparation. The assay uses red chlorophyll fluorescence, corresponding to viable cells, and an unspecific green autofluorescence, that can only be observed in non viable cells. The assay was established and validated for the model organism Synechocystis sp. PCC 6803. With the selection of a suitable filter-set both signals could be excited and observed simultaneously, allowing a direct classification of viable and non-viable cells. The results were confirmed by plating/colony count, absorption spectra and chlorophyll measurements. The use of an automated fluorescence microscope and an ImageJ based image analysis plugin allows a very precise and fast analysis. The monitoring of a random mutagenized culture undergoing selection for improved temperature tolerance allowed an accurate and prompt insight into the condition of the culture. Further results indicate that a combination of the new assay with absorption spectra or chlorophyll concentration measurements allows the estimation of the vitality of cells. KW - Bilderkennnung KW - Bioinformatik KW - Phytoplankton KW - Bilderkennung KW - Phytoplankton KW - Viabilität KW - Mikroskopie KW - Bioinformatik Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-107174 ER - TY - JOUR A1 - Jaite, Charlotte A1 - Bühren, Katharina A1 - Dahmen, Brigitte A1 - Dempfle, Astrid A1 - Becker, Katja A1 - Correll, Christoph U. A1 - Egberts, Karin M. A1 - Ehrlich, Stefan A1 - Fleischhaker, Christian A1 - von Gontard, Alexander A1 - Hahn, Freia A1 - Kolar, David A1 - Kaess, Michael A1 - Legenbauer, Tanja A1 - Renner, Tobias J. A1 - Schulze, Ulrike A1 - Sinzig, Judith A1 - Thomae, Ellen A1 - Weber, Linda A1 - Wessing, Ida A1 - Antony, Gisela A1 - Hebebrand, Johannes A1 - Föcker, Manuel A1 - Herpertz-Dahlmann, Beate T1 - Clinical Characteristics of Inpatients with Childhood vs. Adolescent Anorexia Nervosa JF - Nutrients N2 - We aimed to compare the clinical data at first presentation to inpatient treatment of children (<14 years) vs. adolescents (≥14 years) with anorexia nervosa (AN), focusing on duration of illness before hospital admission and body mass index (BMI) at admission and discharge, proven predictors of the outcomes of adolescent AN. Clinical data at first admission and at discharge in 289 inpatients with AN (children: n = 72; adolescents: n = 217) from a German multicenter, web-based registry for consecutively enrolled patients with childhood and adolescent AN were analyzed. Inclusion criteria were a maximum age of 18 years, first inpatient treatment due to AN, and a BMI <10th BMI percentile at admission. Compared to adolescents, children with AN had a shorter duration of illness before admission (median: 6.0 months vs. 8.0 months, p = 0.004) and higher BMI percentiles at admission (median: 0.7 vs. 0.2, p = 0.004) as well as at discharge (median: 19.3 vs. 15.1, p = 0.011). Thus, in our study, children with AN exhibited clinical characteristics that have been associated with better outcomes, including higher admission and discharge BMI percentile. Future studies should examine whether these factors are actually associated with positive long-term outcomes in children. KW - anorexia nervosa KW - children KW - adolescents KW - clinical characteristics KW - BMI KW - outcome Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193160 SN - 2072-6643 VL - 11 IS - 11 ER - TY - JOUR A1 - Kaltdorf, Kristin Verena A1 - Schulze, Katja A1 - Helmprobst, Frederik A1 - Kollmannsberger, Philip A1 - Dandekar, Thomas A1 - Stigloher, Christian T1 - Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms JF - PLoS Computational Biology N2 - 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. KW - Biology KW - Vesicles KW - Caenorhabditis elegans KW - Zebrafish KW - Septins KW - Synaptic vesicles KW - Neuromuscular junctions KW - Computer software KW - Synapses Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-172112 VL - 13 IS - 1 ER - TY - JOUR A1 - Schulze, Katja A1 - Tillich, Ulrich M. A1 - Dandekar, Thomas A1 - Frohme, Marcus T1 - PlanktoVision – an automated analysis system for the identification of phytoplankton JF - BMC Bioinformatics N2 - Background Phytoplankton communities are often used as a marker for the determination of fresh water quality. The routine analysis, however, is very time consuming and expensive as it is carried out manually by trained personnel. The goal of this work is to develop a system for an automated analysis. Results A novel open source system for the automated recognition of phytoplankton by the use of microscopy and image analysis was developed. It integrates the segmentation of the organisms from the background, the calculation of a large range of features, and a neural network for the classification of imaged organisms into different groups of plankton taxa. The analysis of samples containing 10 different taxa showed an average recognition rate of 94.7% and an average error rate of 5.5%. The presented system has a flexible framework which easily allows expanding it to include additional taxa in the future. Conclusions The implemented automated microscopy and the new open source image analysis system - PlanktoVision - showed classification results that were comparable or better than existing systems and the exclusion of non-plankton particles could be greatly improved. The software package is published as free software and is available to anyone to help make the analysis of water quality more reproducible and cost effective. KW - Bioinformatik Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96395 UR - http://www.biomedcentral.com/1471-2105/14/115 ER - TY - JOUR A1 - Machata, Silke A1 - Sreekantapuram, Sravya A1 - Hünniger, Kerstin A1 - Kurzai, Oliver A1 - Dunker, Christine A1 - Schubert, Katja A1 - Krüger, Wibke A1 - Schulze-Richter, Bianca A1 - Speth, Cornelia A1 - Rambach, Günter A1 - Jacobsen, Ilse D. T1 - Significant Differences in Host-Pathogen Interactions Between Murine and Human Whole Blood JF - Frontiers in Immunology N2 - Murine infection models are widely used to study systemic candidiasis caused by C. albicans. Whole-blood models can help to elucidate host-pathogens interactions and have been used for several Candida species in human blood. We adapted the human whole-blood model to murine blood. Unlike human blood, murine blood was unable to reduce fungal burden and more substantial filamentation of C. albicans was observed. This coincided with less fungal association with leukocytes, especially neutrophils. The lower neutrophil number in murine blood only partially explains insufficient infection and filamentation control, as spiking with murine neutrophils had only limited effects on fungal killing. Furthermore, increased fungal survival is not mediated by enhanced filamentation, as a filament-deficient mutant was likewise not eliminated. We also observed host-dependent differences for interaction of platelets with C. albicans, showing enhanced platelet aggregation, adhesion and activation in murine blood. For human blood, opsonization was shown to decrease platelet interaction suggesting that complement factors interfere with fungus-to-platelet binding. Our results reveal substantial differences between murine and human whole-blood models infected with C. albicans and thereby demonstrate limitations in the translatability of this ex vivo model between hosts. KW - whole blood ex vivo model KW - host-pathogen interaction KW - neutrophils KW - mice Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-222575 SN - 1664-3224 VL - 11 ER -