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34 Publications visible to you, out of a total of 34
Streptococcus pneumoniae From Patients With Hemolytic Uremic Syndrome Binds Human Plasminogen via the Surface Protein PspC and Uses Plasmin to Damage Human Endothelial Cells.

Abstract (Expand)

Pneumococcal hemolytic uremic syndrome (HUS) in children is caused by infections with Streptococcus pneumoniae. Because endothelial cell damage is a hallmark of HUS, we studied how HUS-inducing pneumococci … derived from infant HUS patients during the acute phase disrupt the endothelial layer. HUS pneumococci efficiently bound human plasminogen. These clinical isolates of HUS pneumococci efficiently bound human plasminogen via the bacterial surface proteins Tuf and PspC. When activated to plasmin at the bacterial surface, the active protease degraded fibrinogen and cleaved C3b. Here, we show that PspC is a pneumococcal plasminogen receptor and that plasmin generated on the surface of HUS pneumococci damages endothelial cells, causing endothelial retraction and exposure of the underlying matrix. Thus, HUS pneumococci damage endothelial cells in the blood vessels and disturb local complement homeostasis. Thereby, HUS pneumococci promote a thrombogenic state that drives HUS pathology.

Authors: C. Meinel, G. Sparta, H. M. Dahse, F. Horhold, R. Konig, M. Westermann, S. M. Coldewey, Z. Cseresnyes, M. T. Figge, S. Hammerschmidt, C. Skerka, P. F. Zipfel

Date Published: 17th Jan 2018

Publication Type: Not specified

Dimensionality of Motion and Binding Valency Govern Receptor-Ligand Kinetics As Revealed by Agent-Based Modeling.

Abstract (Expand)

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. … We here consider the general problem of receptor-ligand binding in the context of antibody-antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors-such as their dimensionality of motion, morphology, and binding valency-on the receptor-ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.

Authors: T. Lehnert, M. T. Figge

Date Published: 19th Dec 2017

Publication Type: Not specified

Untangling cell tracks: Quantifying cell migration by time lapse image data analysis.

Abstract (Expand)

Automated microscopy has given researchers access to great amounts of live cell imaging data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks from such data using … a plethora of segmentation and tracking algorithms, but further analysis is normally required to draw biologically relevant conclusions. Such relevant conclusions may be whether the migration is directed or not, whether the population has homogeneous or heterogeneous migration patterns. This review focuses on the analysis of cell migration data that are extracted from time lapse images. We discuss a range of measures and models used to analyze cell tracks independent of the biological system or the way the tracks were obtained. For single-cell migration, we focus on measures and models giving examples of biological systems where they have been applied, for example, migration of bacteria, fibroblasts, and immune cells. For collective migration, we describe the model systems wound healing, neural crest migration, and Drosophila gastrulation and discuss methods for cell migration within these systems. We also discuss the role of the extracellular matrix and subsequent differences between track analysis in vitro and in vivo. Besides methods and measures, we are putting special focus on the need for openly available data and code, as well as a lack of common vocabulary in cell track analysis. (c) 2017 International Society for Advancement of Cytometry.

Authors: C. M. Svensson, A. Medyukhina, I. Belyaev, N. Al-Zaben, M. T. Figge

Date Published: 5th Oct 2017

Publication Type: Not specified

Hessian-based quantitative image analysis of host-pathogen confrontation assays.

Abstract (Expand)

Host-fungus interactions have gained a lot of interest in the past few decades, mainly due to an increasing number of fungal infections that are often associated with a high mortality rate in the absence … of effective therapies. These interactions can be studied at the genetic level or at the functional level via imaging. Here, we introduce a new image processing method that quantifies the interaction between host cells and fungal invaders, for example, alveolar macrophages and the conidia of Aspergillus fumigatus. The new technique relies on the information content of transmitted light bright field microscopy images, utilizing the Hessian matrix eigenvalues to distinguish between unstained macrophages and the background, as well as between macrophages and fungal conidia. The performance of the new algorithm was measured by comparing the results of our method with that of an alternative approach that was based on fluorescence images from the same dataset. The comparison shows that the new algorithm performs very similarly to the fluorescence-based version. Consequently, the new algorithm is able to segment and characterize unlabeled cells, thus reducing the time and expense that would be spent on the fluorescent labeling in preparation for phagocytosis assays. By extending the proposed method to the label-free segmentation of fungal conidia, we will be able to reduce the need for fluorescence-based imaging even further. Our approach should thus help to minimize the possible side effects of fluorescence labeling on biological functions. (c) 2017 International Society for Advancement of Cytometry.

Authors: Z. Cseresnyes, K. Kraibooj, M. T. Figge

Date Published: 16th Sep 2017

Publication Type: Not specified

Deciphering the Counterplay of Aspergillus fumigatus Infection and Host Inflammation by Evolutionary Games on Graphs.

Abstract (Expand)

Microbial invaders are ubiquitously present and pose the constant risk of infections that are opposed by various defence mechanisms of the human immune system. A tight regulation of the immune response … ensures clearance of microbial invaders and concomitantly limits host damage that is crucial for host viability. To investigate the counterplay of infection and inflammation, we simulated the invasion of the human-pathogenic fungus Aspergillus fumigatus in lung alveoli by evolutionary games on graphs. The layered structure of the innate immune system is represented by a sequence of games in the virtual model. We show that the inflammatory cascade of the immune response is essential for microbial clearance and that the inflammation level correlates with the infection-dose. At low infection-doses, corresponding to daily inhalation of conidia, the resident alveolar macrophages may be sufficient to clear infections, however, at higher infection-doses their primary task shifts towards recruitment of neutrophils to infection sites.

Authors: J. Pollmacher, S. Timme, S. Schuster, A. A. Brakhage, P. F. Zipfel, M. T. Figge

Date Published: 13th Jun 2016

Publication Type: Not specified

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions

Abstract (Expand)

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens … by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

Authors: T. Lehnert, , J. Pollmacher, , ,

Date Published: 19th Jun 2015

Publication Type: Not specified

Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli.

Abstract (Expand)

The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame … of 4-8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.

Authors: J. Pollmacher, M. T. Figge

Date Published: 16th Jun 2015

Publication Type: Not specified

Automated quantification of the phagocytosis of Aspergillus fumigatus conidia by a novel image analysis algorithm

Abstract (Expand)

Studying the pathobiology of the fungus Aspergillus fumigatus has gained a lot of attention in recent years. This is due to the fact that this fungus is a human pathogen that can cause severe diseases, … like invasive pulmonary aspergillosis in immunocompromised patients. Because alveolar macrophages belong to the first line of defense against the fungus, here, we conduct an image-based study on the host-pathogen interaction between murine alveolar macrophages and A. fumigatus. This is achieved by an automated image analysis approach that uses a combination of thresholding, watershed segmentation and feature-based object classification. In contrast to previous approaches, our algorithm allows for the segmentation of individual macrophages in the images and this enables us to compute the distribution of phagocytosed and macrophage-adherent conidia over all macrophages. The novel automated image-based analysis provides access to all cell-cell interactions in the assay and thereby represents a framework that enables comprehensive computation of diverse characteristic parameters and comparative investigation for different strains. We here apply automated image analysis to confocal laser scanning microscopy images of the two wild-type strains ATCC 46645 and CEA10 of A. fumigatus and investigate the ability of macrophages to phagocytose the respective conidia. It is found that the CEA10 strain triggers a stronger response of the macrophages as revealed by a higher phagocytosis ratio and a larger portion of the macrophages being active in the phagocytosis process.

Authors: K. Kraibooj, , C. M. Svensson, ,

Date Published: 9th Jun 2015

Publication Type: Not specified

Neutrophil activation by Candida glabrata but not Candida albicans promotes fungal uptake by monocytes

Abstract (Expand)

Candida albicans and Candida glabrata account for the majority of candidiasis cases worldwide. Although both species are in the same genus, they differ in key virulence attributes. Within this work, … live cell imaging was used to examine the dynamics of neutrophil activation after confrontation with either C. albicans or C. glabrata. Analyses revealed higher phagocytosis rates of C. albicans than C. glabrata that resulted in stronger PMN (polymorphonuclear cells) activation by C. albicans. Furthermore, we observed differences in the secretion of chemokines, indicating chemotactic differences in PMN signalling towards recruitment of further immune cells upon confrontation with Candida spp. Supernatants from co-incubations of neutrophils with C. glabrata primarily attracted monocytes and increased the phagocytosis of C. glabrata by monocytes. In contrast, PMN activation by C. albicans resulted in recruitment of more neutrophils. Two complex infection models confirmed distinct targeting of immune cell populations by the two Candida spp.: In a human whole blood infection model, C. glabrata was more effectively taken up by monocytes than C. albicans and histopathological analyses of murine model infections confirmed primarily monocytic infiltrates in C. glabrata kidney infection in contrast to PMN-dominated infiltrates in C. albicans infection. Taken together, our data demonstrate that the human opportunistic fungi C. albicans and C. glabrata are differentially recognized by neutrophils and one outcome of this differential recognition is the preferential uptake of C. glabrata by monocytes.

Authors: S. Duggan, F. Essig, , Z. Mokhtari, , T. Lehnert, S. Brandes, A. Hader, , R. Martin, ,

Date Published: 5th May 2015

Publication Type: Not specified

Image-based systems biology of infection

Abstract (Expand)

The successful treatment of infectious diseases requires interdisciplinary studies of all aspects of infection processes. The overarching combination of experimental research and theoretical analysis … in a systems biology approach can unravel mechanisms of complex interactions between pathogens and the human immune system. Taking into account spatial information is especially important in the context of infection, since the migratory behavior and spatial interactions of cells are often decisive for the outcome of the immune response. Spatial information is provided by image and video data that are acquired in microscopy experiments and that are at the heart of an image-based systems biology approach. This review demonstrates how image-based systems biology improves our understanding of infection processes. We discuss the three main steps of this approach--imaging, quantitative characterization, and modeling--and consider the application of these steps in the context of studying infection processes. After summarizing the most relevant microscopy and image analysis approaches, we discuss ways to quantify infection processes, and address a number of modeling techniques that exploit image-derived data to simulate host-pathogen interactions in silico.

Authors: A. Medyukhina, , Z. Mokhtari,

Date Published: 29th Jan 2015

Publication Type: Not specified

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