Abstract (Expand)

Aspergillus fumigatus is a ubiquitous opportunistic fungal pathogen that can cause severe infections in immunocompromised patients. Conidia that reach the lower respiratory tract are confronted with alveolar macrophages, which are the resident phagocytic cells, constituting the first line of defense. If not efficiently removed in time, A. fumigatus conidia can germinate causing severe infections associated with high mortality rates. Mice are the most extensively used model organism in research on A. fumigatus infections. However, in addition to structural differences in the lung physiology of mice and the human host, applied infection doses in animal experiments are typically orders of magnitude larger compared to the daily inhalation doses of humans. The influence of these factors, which must be taken into account in a quantitative comparison and knowledge transfer from mice to humans, is difficult to measure since in vivo live cell imaging of the infection dynamics under physiological conditions is currently not possible. In the present study, we compare A. fumigatus infection in mice and humans by virtual infection modeling using a hybrid agent-based model that accounts for the respective lung physiology and the impact of a wide range of infection doses on the spatial infection dynamics. Our computer simulations enable comparative quantification of A. fumigatus infection clearance in the two hosts to elucidate (i) the complex interplay between alveolar morphometry and the fungal burden and (ii) the dynamics of infection clearance, which for realistic fungal burdens is found to be more efficiently realized in mice compared to humans.

Authors: M. Blickensdorf, Sandra Timme, Marc Thilo Figge

Date Published: 27th Feb 2019

Journal: Front Immunol

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, Kaswara Kraibooj, Marc Thilo Figge

Date Published: 16th Sep 2017

Journal: Cytometry A

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, Sandra Timme, Stefan Schuster, Axel Brakhage, Peter Zipfel, Marc Thilo Figge

Date Published: 13th Jun 2016

Journal: Sci Rep

Abstract (Expand)

BACKGROUND: Invasive aspergillosis is started after germination of Aspergillus fumigatus conidia that are inhaled by susceptible individuals. Fungal hyphae can grow in the lung through the epithelial tissue and disseminate hematogenously to invade into other organs. Low fungaemia indicates that fungal elements do not reside in the bloodstream for long. RESULTS: We analyzed whether blood represents a hostile environment to which the physiology of A. fumigatus has to adapt. An in vitro model of A. fumigatus infection was established by incubating mycelium in blood. Our model allowed to discern the changes of the gene expression profile of A. fumigatus at various stages of the infection. The majority of described virulence factors that are connected to pulmonary infections appeared not to be activated during the blood phase. Three active processes were identified that presumably help the fungus to survive the blood environment in an advanced phase of the infection: iron homeostasis, secondary metabolism, and the formation of detoxifying enzymes. CONCLUSIONS: We propose that A. fumigatus is hardly able to propagate in blood. After an early stage of sensing the environment, virtually all uptake mechanisms and energy-consuming metabolic pathways are shut-down. The fungus appears to adapt by trans-differentiation into a resting mycelial stage. This might reflect the harsh conditions in blood where A. fumigatus cannot take up sufficient nutrients to establish self-defense mechanisms combined with significant growth.

Authors: H. Irmer, S. Tarazona, C. Sasse, P. Olbermann, J. Loeffler, S. Krappmann, A. Conesa, G. H. Braus

Date Published: 28th Aug 2015

Journal: BMC Genomics

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, Marc Thilo Figge

Date Published: 16th Jun 2015

Journal: Front Microbiol

Abstract (Expand)

The human pathogenic fungus Aspergillus fumigatus normally lives as a soil saprophyte. Its environment includes poorly oxygenated substrates that also occur during tissue invasive growth of the fungus in the human host. Up to now, few cellular factors have been identified that allow the fungus to efficiently adapt its energy metabolism to hypoxia. Here, we cultivated A. fumigatus in an O2 -controlled fermenter and analysed its responses to O2 limitation on a minute timescale. Transcriptome sequencing revealed several genes displaying a rapid and highly dynamic regulation. One of these genes was analysed in detail and found to encode fungoglobin, a previously uncharacterized member of the sensor globin protein family widely conserved in filamentous fungi. Besides low O2 , iron limitation also induced transcription, but regulation was not entirely dependent on the two major transcription factors involved in adaptation to iron starvation and hypoxia, HapX and SrbA respectively. The protein was identified as a functional haemoglobin, as binding of this cofactor was detected for the recombinant protein. Gene deletion in A. fumigatus confirmed that haem-binding fungoglobins are important for growth in microaerobic environments with O2 levels far lower than in hypoxic human tissue.

Authors: F. Hillmann, Jörg Linde, N. Beckmann, M. Cyrulies, M. Strassburger, T. Heinekamp, H. Haas, Reinhard Guthke, Olaf Kniemeyer, Axel Brakhage

Date Published: 7th Jul 2014

Journal: Mol Microbiol

Abstract (Expand)

BACKGROUND: In System Biology, iterations of wet-lab experiments followed by modelling approaches and model-inspired experiments describe a cyclic workflow. This approach is especially useful for the inference of gene regulatory networks based on high-throughput gene expression data. Experiments can verify or falsify the predicted interactions allowing further refinement of the network model. Aspergillus fumigatus is a major human fungal pathogen. One important virulence trait is its ability to gain sufficient amounts of iron during infection process. Even though some regulatory interactions are known, we are still far from a complete understanding of the way iron homeostasis is regulated. RESULTS: In this study, we make use of a reverse engineering strategy to infer a regulatory network controlling iron homeostasis in A. fumigatus. The inference approach utilizes the temporal change in expression data after a change from iron depleted to iron replete conditions. The modelling strategy is based on a set of linear differential equations and offers the possibility to integrate known regulatory interactions as prior knowledge. Moreover, it makes use of important selection criteria, such as sparseness and robustness. By compiling a list of known regulatory interactions for iron homeostasis in A. fumigatus and softly integrating them during network inference, we are able to predict new interactions between transcription factors and target genes. The proposed activation of the gene expression of hapX by the transcriptional regulator SrbA constitutes a so far unknown way of regulating iron homeostasis based on the amount of metabolically available iron. This interaction has been verified by Northern blots in a recent experimental study. In order to improve the reliability of the predicted network, the results of this experimental study have been added to the set of prior knowledge. The final network includes three SrbA target genes. Based on motif searching within the regulatory regions of these genes, we identify potential DNA-binding sites for SrbA. Our wet-lab experiments demonstrate high-affinity binding capacity of SrbA to the promoters of hapX, hemA and srbA. CONCLUSIONS: This study presents an application of the typical Systems Biology circle and is based on cooperation between wet-lab experimentalists and in silico modellers. The results underline that using prior knowledge during network inference helps to predict biologically important interactions. Together with the experimental results, we indicate a novel iron homeostasis regulating system sensing the amount of metabolically available iron and identify the binding site of iron-related SrbA target genes. It will be of high interest to study whether these regulatory interactions are also important for close relatives of A. fumigatus and other pathogenic fungi, such as Candida albicans.

Authors: Jörg Linde, P. Hortschansky, E. Fazius, Axel Brakhage, Reinhard Guthke, H. Haas

Date Published: 19th Jan 2012

Journal: BMC Syst Biol

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