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32 Publications visible to you, out of a total of 32
Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions

Abstract (Expand)

Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational … systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host-pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling.

Authors: J. Schleicher, , M. Gustafsson, G. Cedersund, ,

Date Published: 10th Feb 2016

Publication Type: Not specified

Editorial: Computational Systems Biology of Pathogen-Host Interactions

Abstract

Not specified

Authors: S. Durmus, T. Cakir,

Date Published: 4th Feb 2016

Publication Type: Not specified

Candida albicans infection leads to barrier breakdown and a MAPK/NF-kappaB mediated stress response in the intestinal epithelial cell line C2BBe1

Abstract (Expand)

Intestinal epithelial cells (IEC) form a tight barrier to the gut lumen. Paracellular permeability of the intestinal barrier is regulated by tight junction proteins and can be modulated by microorganisms … and other stimuli. The polymorphic fungus Candida albicans, a frequent commensal of the human mucosa has the capacity of traversing this barrier and establishing systemic disease within the host. Infection of polarized C2BBe1 IEC with wild-type C. albicans led to a transient increase of transepithelial electric resistance (TEER) before subsequent barrier disruption, accompanied by a strong decline of junctional protein levels and substantial, but considerably delayed cytotoxicity. Time-resolved microarray-based transcriptome analysis of C. albicans challenged IEC revealed a prominent role of NF-kappaB and MAPK signaling pathways in the response to infection. Hence, we inferred a gene regulatory network based on differentially expressed NF-kappaB and MAPK pathway components and their predicted transcriptional targets. The network model predicted activation of GDF15 by NF-kappaB was experimentally validated. Furthermore, inhibition of NF-kappaB activation in C. albicans infected C2BBe1 cells led to enhanced cytotoxicity in the epithelial cells. Taken together our study identifies NF-kappaB activation as an important protective signaling pathway in the response of epithelial cells to C. albicans. This article is protected by copyright. All rights reserved.

Authors: M. Bohringer, S. Pohlers, , , J. Piegsa, M. Weber, R. Martin, , , ,

Date Published: 12th Jan 2016

Publication Type: Not specified

Network Modeling Reveals Cross Talk of MAP Kinases during Adaptation to Caspofungin Stress in Aspergillus fumigatus

Abstract (Expand)

Mitogen activated protein kinases (MAPKs) are highly conserved in eukaryotic organisms. In pathogenic fungi, their activities were assigned to different physiological functions including drug adaptation … and resistance. Aspergillus fumigatus is a human pathogenic fungus, which causes life-threatening invasive infections. Therapeutic options against invasive mycoses are still limited. One of the clinically used drugs is caspofungin, which specifically targets the fungal cell wall biosynthesis. A systems biology approach, based on comprehensive transcriptome data sets and mathematical modeling, was employed to infer a regulatory network and identify key interactions during adaptation to caspofungin stress in A. fumigatus. Mathematical modeling and experimental validations confirmed an intimate cross talk occurring between the cell wall-integrity and the high osmolarity-glycerol signaling pathways. Specifically, increased concentrations of caspofungin promoted activation of these signalings. Moreover, caspofungin affected the intracellular transport, which caused an additional osmotic stress that is independent of glucan inhibition. High concentrations of caspofungin reduced this osmotic stress, and thus decreased its toxic activity. Our results demonstrated that MAPK signaling pathways play a key role during caspofungin adaptation and are contributing to the paradoxical effect exerted by this drug.

Authors: R. Altwasser, C. Baldin, J. Weber, , O. Kniemeyer, , , V. Valiante

Date Published: 10th Sep 2015

Publication Type: Not specified

Draft Genome Sequence of the Fungus Penicillium brasilianum MG11

Abstract (Expand)

The genus Penicillium belongs to the phylum Ascomycota and includes a variety of fungal species important for food and drug production. We report the draft genome sequence of Penicillium brasilianum … MG11. This strain was isolated from soil, and it was reported to produce different secondary metabolites.

Authors: F. Horn, , D. J. Mattern, G. Walther, , , V. Valiante

Date Published: 5th Sep 2015

Publication Type: Not specified

Computing the various pathways of penicillin synthesis and their molar yields

Abstract (Expand)

More than 80 years after its discovery, penicillin is still a widely used and commercially highly important antibiotic. Here, we analyse the metabolic network of penicillin synthesis in Penicillium … chrysogenum based on the concept of elementary flux modes. In particular, we consider the synthesis of the invariant molecular core of the various subtypes of penicillin and the two major ways of incorporating sulfur: transsulfuration and direct sulfhydrylation. 66 elementary modes producing this invariant core are obtained. These show four different yields with respect to glucose, notably (1/2), 2/5, 1/3, and 2/7, with the highest yield of (1/2) occurring only when direct sulfhydrylation is used and alpha-aminoadipate is completely recycled. In the case of no recycling of this intermediate, we find the maximum yield to be 2/7. We compare these values with earlier literature values. Our analysis provides a systematic overview of the redundancy in penicillin synthesis and a detailed insight into the corresponding routes. Moreover, we derive suggestions for potential knockouts that could increase the average yield.

Authors: M. T. Prausse, S. Schauble, ,

Date Published: 19th Aug 2015

Publication Type: Not specified

Hitting the caspofungin salvage pathway of human-pathogenic fungi with the novel lasso peptide humidimycin (MDN-0010)

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

A review on computational systems biology of pathogen-host interactions

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

Biomarker-based classification of bacterial and fungal whole-blood infections in a genome-wide expression study

Abstract (Expand)

Sepsis is a clinical syndrome that can be caused by bacteria or fungi. Early knowledge on the nature of the causative agent is a prerequisite for targeted anti-microbial therapy. Besides currently used … detection methods like blood culture and PCR-based assays, the analysis of the transcriptional response of the host to infecting organisms holds great promise. In this study, we aim to examine the transcriptional footprint of infections caused by the bacterial pathogens Staphylococcus aureus and Escherichia coli and the fungal pathogens Candida albicans and Aspergillus fumigatus in a human whole-blood model. Moreover, we use the expression information to build a random forest classifier to classify if a sample contains a bacterial, fungal, or mock-infection. After normalizing the transcription intensities using stably expressed reference genes, we filtered the gene set for biomarkers of bacterial or fungal blood infections. This selection is based on differential expression and an additional gene relevance measure. In this way, we identified 38 biomarker genes, including IL6, SOCS3, and IRG1 which were already associated to sepsis by other studies. Using these genes, we trained the classifier and assessed its performance. It yielded a 96% accuracy (sensitivities >93%, specificities >97%) for a 10-fold stratified cross-validation and a 92% accuracy (sensitivities and specificities >83%) for an additional test dataset comprising Cryptococcus neoformans infections. Furthermore, the classifier is robust to Gaussian noise, indicating correct class predictions on datasets of new species. In conclusion, this genome-wide approach demonstrates an effective feature selection process in combination with the construction of a well-performing classification model. Further analyses of genes with pathogen-dependent expression patterns can provide insights into the systemic host responses, which may lead to new anti-microbial therapeutic advances.

Authors: , , M. Weber, , ,

Date Published: 11th Mar 2015

Publication Type: Not specified

Data- and knowledge-based modeling of gene regulatory networks: an update

Abstract (Expand)

Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network … inference methods focusing on novel techniques for data acquisition, network inference assessment, network inference for interacting species and the integration of prior knowledge. After the advance of Next-Generation-Sequencing of cDNAs derived from RNA samples (RNA-Seq) we discuss in detail its application to network inference. Furthermore, we present progress for large-scale or even full-genomic network inference as well as for small-scale condensed network inference and review advances in the evaluation of network inference methods by crowdsourcing. Finally, we reflect the current availability of data and prior knowledge sources and give an outlook for the inference of gene regulatory networks that reflect interacting species, in particular pathogen-host interactions.

Authors: , , S. G. Henkel,

Date Published: 2nd Mar 2015

Publication Type: Not specified

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