Publications

What is a Publication?
203 Publications visible to you, out of a total of 203

Abstract (Expand)

Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, with the help of high-throughput experiments such as RNA-seq or microarrays. The adaptation of the gene expression to environmental changes within cells is mediated through complex gene regulatory networks. Often, our knowledge of these networks is incomplete. Network inference predicts gene regulatory interactions based on transcriptome data. An emerging application of high-throughput transcriptome studies are dual transcriptomics experiments. Here, the transcriptome of two or more interacting species is measured simultaneously. Based on a dual RNA-seq data set of murine dendritic cells infected with the fungal pathogen Candida albicans, the software tool NetGenerator was applied to predict an inter-species gene regulatory network. To promote further investigations of molecular inter-species interactions, we recently discussed dual RNA-seq experiments for host-pathogen interactions and extended the applied tool NetGenerator (Schulze et al., 2015). The updated version of NetGenerator makes use of measurement variances in the algorithmic procedure and accepts gene expression time series data with missing values. Additionally, we tested multiple modeling scenarios regarding the stimuli functions of the gene regulatory network. Here, we summarize the work by Schulze et al. (2015) and put it into a broader context. We review various studies making use of the dual transcriptomics approach to investigate the molecular basis of interacting species. Besides the application to host-pathogen interactions, dual transcriptomics data are also utilized to study mutualistic and commensalistic interactions. Furthermore, we give a short introduction into additional approaches for the prediction of gene regulatory networks and discuss their application to dual transcriptomics data. We conclude that the application of network inference on dual-transcriptomics data is a promising approach to predict molecular inter-species interactions.

Authors: , J. Schleicher, ,

Date Published: 31st Mar 2016

Publication Type: Not specified

Abstract (Expand)

Cytolytic proteins and peptide toxins are classical virulence factors of several bacterial pathogens which disrupt epithelial barrier function, damage cells and activate or modulate host immune responses. Such toxins have not been identified previously in human pathogenic fungi. Here we identify the first, to our knowledge, fungal cytolytic peptide toxin in the opportunistic pathogen Candida albicans. This secreted toxin directly damages epithelial membranes, triggers a danger response signalling pathway and activates epithelial immunity. Membrane permeabilization is enhanced by a positive charge at the carboxy terminus of the peptide, which triggers an inward current concomitant with calcium influx. C. albicans strains lacking this toxin do not activate or damage epithelial cells and are avirulent in animal models of mucosal infection. We propose the name 'Candidalysin' for this cytolytic peptide toxin; a newly identified, critical molecular determinant of epithelial damage and host recognition of the clinically important fungus, C. albicans.

Authors: D. L. Moyes, D. Wilson, J. P. Richardson, S. Mogavero, S. X. Tang, J. Wernecke, S. Hofs, R. L. Gratacap, J. Robbins, M. Runglall, C. Murciano, M. Blagojevic, S. Thavaraj, , B. Hebecker, , G. Vizcay, S. I. Iancu, N. Kichik, A. Hader, , T. Luo, T. Kruger, O. Kniemeyer, E. Cota, O. Bader, R. T. Wheeler, T. Gutsmann, , J. R. Naglik

Date Published: 30th Mar 2016

Publication Type: Not specified

Abstract (Expand)

Invasive aspergillosis (IA) is a devastating opportunistic infection and its treatment constitutes a considerable burden for the health care system. Immunocompromised patients are at an increased risk for IA, which is mainly caused by the species Aspergillus fumigatus. An early and reliable diagnosis is required to initiate the appropriate antifungal therapy. However, diagnostic sensitivity and accuracy still needs to be improved, which can be achieved at least partly by the definition of new biomarkers. Besides the direct detection of the pathogen by the current diagnostic methods, the analysis of the host response is a promising strategy toward this aim. Following this approach, we sought to identify new biomarkers for IA. For this purpose, we analyzed gene expression profiles of hematological patients and compared profiles of patients suffering from IA with non-IA patients. Based on microarray data, we applied a comprehensive feature selection using a random forest classifier. We identified the transcript coding for the S100 calcium-binding protein B (S100B) as a potential new biomarker for the diagnosis of IA. Considering the expression of this gene, we were able to classify samples from patients with IA with 82.3% sensitivity and 74.6% specificity. Moreover, we validated the expression of S100B in a real-time reverse transcription polymerase chain reaction (RT-PCR) assay and we also found a down-regulation of S100B in A. fumigatus stimulated DCs. An influence on the IL1B and CXCL1 downstream levels was demonstrated by this S100B knockdown. In conclusion, this study covers an effective feature selection revealing a key regulator of the human immune response during IA. S100B may represent an additional diagnostic marker that in combination with the established techniques may improve the accuracy of IA diagnosis.

Authors: , K. Czakai, J. Springer, M. Fliesser, M. Bonin, , A. L. Schmitt, , ,

Date Published: 21st Mar 2016

Publication Type: Not specified

Abstract (Expand)

Aspergillus fumigatus is the predominant airborne pathogenic fungus causing invasive aspergillosis in immunocompromised patients. During infection A. fumigatus has to adapt to oxygen-limiting conditions in inflammatory or necrotic tissue. Previously, we identified a mitochondrial protein to be highly up-regulated during hypoxic adaptation. Here, this protein was found to represent the novel oxidoreductase HorA. In Saccharomyces cerevisiae a homologue was shown to play a role in biosynthesis of coenzyme Q. Consistently, reduced coenzyme Q content in the generated DeltahorA mutant indicated a respective function in A. fumigatus. Since coenzyme Q is involved in cellular respiration and maintaining cellular redox homeostasis, the strain DeltahorA displayed an impaired response to both oxidative and reductive stress, a delay in germination and an accumulation of NADH. Moreover, an increased resistance against antifungal drugs was observed. All phenotypes were completely reversed by the addition of the synthetic electron carrier menadione. The deletion strain DeltahorA showed significantly attenuated virulence in two murine infection models of invasive pulmonary aspergillosis. Therefore, the biosynthesis of coenzyme Q and, particularly, the fungal-specific protein HorA play a crucial role in virulence of A. fumigatus. Due to its absence in mammals, HorA might represent a novel therapeutic target against fungal infections. This article is protected by copyright. All rights reserved.

Authors: K. Kroll, E. Shekhova, D. J. Mattern, A. Thywissen, , M. Strassburger, T. Heinekamp, , ,

Date Published: 19th Mar 2016

Publication Type: Not specified

Abstract (Expand)

Aspergillus fumigatus is the species that most commonly causes the opportunistic infection invasive aspergillosis (IA) in patients being treated for hematological malignancies. Little is known about the A. fumigatus proteins that trigger the production of Aspergillus-specific IgG antibodies during the course of IA. To characterize the serological response to A. fumigatus protein antigens, mycelial proteins were separated by 2-D gel electrophoresis. The gels were immunoblotted with sera from patients with probable and proven IA and control patients without IA. We identified 49 different fungal proteins, which gave a positive IgG antibody signal. Most of these antigens play a role in primary metabolism and stress responses. Overall, our analysis identified 18 novel protein antigens from A. fumigatus. To determine whether these antigens can be used as diagnostic or prognostic markers or exhibit a protective activity, we employed supervised machine learning with decision trees. We identified two candidates for further analysis, the protein antigens CpcB and Shm2. Heterologously produced Shm2 induced a strongly proinflammatory response in human peripheral blood mononuclear cells after in vitro stimulation. In contrast, CpcB did not activate the immune response of PBMCs. These findings could serve as the basis for the development of an immunotherapy of IA.

Authors: J. Teutschbein, S. Simon, J. Lother, J. Springer, P. Hortschansky, C. O. Morton, , , E. Conneally, T. R. Rogers, , ,

Date Published: 15th Mar 2016

Publication Type: Not specified

Abstract (Expand)

Here, we report the draft genome sequence of Aspergillus calidoustus (strain SF006504). The functional annotation of A. calidoustus predicts a relatively large number of secondary metabolite gene clusters. The presented genome sequence builds the basis for further genome mining.

Authors: F. Horn, , D. J. Mattern, G. Walther, , K. Scherlach, K. Martin, , L. Petzke,

Date Published: 12th Mar 2016

Publication Type: Not specified

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

Abstract

Not specified

Authors: S. Durmus, T. Cakir,

Date Published: 4th Feb 2016

Publication Type: Not specified

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

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

Powered by
(v.1.14.2)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH