Publications

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203 Publications visible to you, out of a total of 203

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

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

Abstract (Expand)

Fungal infections have increased dramatically in the last 2 decades, and fighting infectious diseases requires innovative approaches such as the combination of two drugs acting on different targets or even targeting a salvage pathway of one of the drugs. The fungal cell wall biosynthesis is inhibited by the clinically used antifungal drug caspofungin. This antifungal activity has been found to be potentiated by humidimycin, a new natural product identified from the screening of a collection of 20,000 microbial extracts, which has no major effect when used alone. An analysis of transcriptomes and selected Aspergillus fumigatus mutants indicated that humidimycin affects the high osmolarity glycerol response pathway. By combining humidimycin and caspofungin, a strong increase in caspofungin efficacy was achieved, demonstrating that targeting different signaling pathways provides an excellent basis to develop novel anti-infective strategies.

Authors: , M. C. Monteiro, J. Martin, R. Altwasser, N. El Aouad, I. Gonzalez, , E. Mellado, S. Palomo, N. de Pedro, I. Perez-Victoria, J. R. Tormo, F. Vicente, F. Reyes, O. Genilloud,

Date Published: 8th Jun 2015

Publication Type: Not specified

Abstract (Expand)

The Tor (target of rapamycin) kinase is one of the major regulatory nodes in eukaryotes. Here, we analyzed the Tor kinase in Aspergillus fumigatus, which is the most important airborne fungal pathogen of humans. Because deletion of the single tor gene was apparently lethal, we generated a conditional lethal tor mutant by replacing the endogenous tor gene by the inducible xylp-tor gene cassette. By both 2DE and gel-free LC-MS/MS, we found that Tor controls a variety of proteins involved in nutrient sensing, stress response, cell cycle progression, protein biosynthesis and degradation, but also processes in mitochondria, such as respiration and ornithine metabolism, which is required for siderophore formation. qRT-PCR analyses indicated that mRNA levels of ornithine biosynthesis genes were increased under iron limitation. When tor was repressed, iron regulation was lost. In a deletion mutant of the iron regulator HapX also carrying the xylp-tor cassette, the regulation upon iron deprivation was similar to that of the single tor inducible mutant strain. In line, hapX expression was significantly reduced when tor was repressed. Thus, Tor acts either upstream of HapX or independently of HapX as a repressor of the ornithine biosynthesis genes and thereby regulates the production of siderophores.

Authors: C. Baldin, V. Valiante, T. Kruger, L. Schafferer, H. Haas, O. Kniemeyer,

Date Published: 26th May 2015

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: Adjusting the capacity of metabolic pathways in response to rapidly changing environmental conditions is an important component of microbial adaptation strategies to stochastic environments. In this work, we use advanced dynamic optimization techniques combined with theoretical models to study which reactions in pathways are optimally targeted by regulatory interactions in order to minimize the regulatory effort that is required to adjust the flux through a complex metabolic network. Moreover, we analyze how constraints in the speed at which an organism can respond on a proteomic level influences these optimal targets of pathway control. RESULTS: We find that limitations in protein biosynthetic rates have a strong influence. With increasing protein biosynthetic rates the regulatory effort targeting the initial enzyme in a pathway is reduced while the regulatory effort in the terminal enzyme is increased. Studying the impact of allosteric regulation for different pathway topologies, we find that the presence of feedback inhibition by products of metabolic pathways allows organisms to reduce the regulatory effort that is required to control a metabolic pathway in all cases. In a linear pathway this even leads to the case where the sole transcriptional regulatory control of the terminal enzyme is sufficient to control flux through the entire pathway. We confirm the utilization of these pathway regulation strategies through the large-scale analysis of transcriptional regulation in several hundred prokaryotes. CONCLUSIONS: This work expands our knowledge about optimal programs of pathway control. Optimal targets of pathway control strongly depend on the speed at which proteins can be synthesized. Moreover, post-translational regulation such as allosteric regulation allows to strongly reduce the number of transcriptional regulatory interactions required to control a metabolic pathway across different pathway topologies.

Authors: G. M. de Hijas-Liste, E. Balsa-Canto, J. Ewald, M. Bartl, P. Li, J. R. Banga,

Date Published: 16th May 2015

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: Adjusting the capacity of metabolic pathways in response to rapidly changing environmental conditions is an important component of microbial adaptation strategies to stochastic environments. In this work, we use advanced dynamic optimization techniques combined with theoretical models to study which reactions in pathways are optimally targeted by regulatory interactions in order to minimize the regulatory effort that is required to adjust the flux through a complex metabolic network. Moreover, we analyze how constraints in the speed at which an organism can respond on a proteomic level influences these optimal targets of pathway control. RESULTS: We find that limitations in protein biosynthetic rates have a strong influence. With increasing protein biosynthetic rates the regulatory effort targeting the initial enzyme in a pathway is reduced while the regulatory effort in the terminal enzyme is increased. Studying the impact of allosteric regulation for different pathway topologies, we find that the presence of feedback inhibition by products of metabolic pathways allows organisms to reduce the regulatory effort that is required to control a metabolic pathway in all cases. In a linear pathway this even leads to the case where the sole transcriptional regulatory control of the terminal enzyme is sufficient to control flux through the entire pathway. We confirm the utilization of these pathway regulation strategies through the large-scale analysis of transcriptional regulation in several hundred prokaryotes. CONCLUSIONS: This work expands our knowledge about optimal programs of pathway control. Optimal targets of pathway control strongly depend on the speed at which proteins can be synthesized. Moreover, post-translational regulation such as allosteric regulation allows to strongly reduce the number of transcriptional regulatory interactions required to control a metabolic pathway across different pathway topologies.

Authors: G. M. de Hijas-Liste, E. Balsa-Canto, , M. Bartl, P. Li, J. R. Banga,

Date Published: 16th May 2015

Publication Type: Not specified

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

Abstract (Expand)

In this work, we investigate optimality principles behind synthesis strategies for protein complexes using a dynamic optimization approach. We show that the cellular capacity of protein synthesis has a strong influence on optimal synthesis strategies reaching from a simultaneous to a sequential synthesis of the subunits of a protein complex. Sequential synthesis is preferred if protein synthesis is strongly limited, whereas a simultaneous synthesis is optimal in situations with a high protein synthesis capacity. We confirm the predictions of our optimization approach through the analysis of the operonic organization of protein complexes in several hundred prokaryotes. Thereby, we are able to show that cellular protein synthesis capacity is a driving force in the dissolution of operons comprising the subunits of a protein complex. Thus, we also provide a tested hypothesis explaining why the subunits of many prokaryotic protein complexes are distributed across several operons despite the presumably less precise co-regulation.

Authors: J. Ewald, M. Kotzing, M. Bartl,

Date Published: 1st May 2015

Publication Type: Not specified

Abstract (Expand)

In this work, we investigate optimality principles behind synthesis strategies for protein complexes using a dynamic optimization approach. We show that the cellular capacity of protein synthesis has a strong influence on optimal synthesis strategies reaching from a simultaneous to a sequential synthesis of the subunits of a protein complex. Sequential synthesis is preferred if protein synthesis is strongly limited, whereas a simultaneous synthesis is optimal in situations with a high protein synthesis capacity. We confirm the predictions of our optimization approach through the analysis of the operonic organization of protein complexes in several hundred prokaryotes. Thereby, we are able to show that cellular protein synthesis capacity is a driving force in the dissolution of operons comprising the subunits of a protein complex. Thus, we also provide a tested hypothesis explaining why the subunits of many prokaryotic protein complexes are distributed across several operons despite the presumably less precise co-regulation.

Authors: , M. Kotzing, M. Bartl,

Date Published: 1st May 2015

Publication Type: Not specified

Abstract (Expand)

Pathogens manipulate the cellular mechanisms of host organisms via pathogen-host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein-protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature.

Authors: S. Durmus, T. Cakir, A. Ozgur,

Date Published: 9th Apr 2015

Publication Type: Not specified

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