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

Abstract (Expand)

Farnesol, produced by the polymorphic fungus Candida albicans, is the first quorum-sensing molecule discovered in eukaryotes. Its main function is control of C. albicans filamentation, a process closely linked to pathogenesis. In this study, we analyzed the effects of farnesol on innate immune cells known to be important for fungal clearance and protective immunity. Farnesol enhanced the expression of activation markers on monocytes (CD86 and HLA-DR) and neutrophils (CD66b and CD11b) and promoted oxidative burst and the release of proinflammatory cytokines (tumor necrosis factor alpha [TNF-alpha] and macrophage inflammatory protein 1 alpha [MIP-1alpha]). However, this activation did not result in enhanced fungal uptake or killing. Furthermore, the differentiation of monocytes to immature dendritic cells (iDC) was significantly affected by farnesol. Several markers important for maturation and antigen presentation like CD1a, CD83, CD86, and CD80 were significantly reduced in the presence of farnesol. Furthermore, farnesol modulated migrational behavior and cytokine release and impaired the ability of DC to induce T cell proliferation. Of major importance was the absence of interleukin 12 (IL-12) induction in iDC generated in the presence of farnesol. Transcriptome analyses revealed a farnesol-induced shift in effector molecule expression and a down-regulation of the granulocyte-macrophage colony-stimulating factor (GM-CSF) receptor during monocytes to iDC differentiation. Taken together, our data unveil the ability of farnesol to act as a virulence factor of C. albicans by influencing innate immune cells to promote inflammation and mitigating the Th1 response, which is essential for fungal clearance. IMPORTANCE: Farnesol is a quorum-sensing molecule which controls morphological plasticity of the pathogenic yeast Candida albicans. As such, it is a major mediator of intraspecies communication. Here, we investigated the impact of farnesol on human innate immune cells known to be important for fungal clearance and protective immunity. We show that farnesol is able to enhance inflammation by inducing activation of neutrophils and monocytes. At the same time, farnesol impairs differentiation of monocytes into immature dendritic cells (iDC) by modulating surface phenotype, cytokine release and migrational behavior. Consequently, iDC generated in the presence of farnesol are unable to induce proper T cell responses and fail to secrete Th1 promoting interleukin 12 (IL-12). As farnesol induced down-regulation of the granulocyte-macrophage colony-stimulating factor (GM-CSF) receptor, desensitization to GM-CSF could potentially explain transcriptional reprofiling of iDC effector molecules. Taken together, our data show that farnesol can also mediate Candida-host communication and is able to act as a virulence factor.

Authors: I. Leonhardt, S. Spielberg, M. Weber, D. Albrecht-Eckardt, M. Blass, R. Claus, D. Barz, K. Scherlach, C. Hertweck, J. Loffler, ,

Date Published: 19th Mar 2015

Publication Type: Not specified

Abstract (Expand)

Candida albicans is a major cause of bloodstream infection which may present as sepsis and septic shock - major causes of morbidity and mortality world-wide. After invasion of the pathogen, innate mechanisms govern the early response. Here, we outline the models used to study these mechanisms and summarize our current understanding of innate immune responses during Candida bloodstream infection. This includes protective immunity as well as harmful responses resulting in Candida induced sepsis. Neutrophilic granulocytes are considered principal effector cells conferring protection and recognize C. albicans mainly via complement receptor 3. They possess a range of effector mechanisms, contributing to elimination of the pathogen. Neutrophil activation is closely linked to complement and modulated by activated mononuclear cells. A thorough understanding of these mechanisms will help in creating an individualized approach to patients suffering from systemic candidiasis and aid in optimizing clinical management.

Authors: S. Duggan, I. Leonhardt, ,

Date Published: 18th Mar 2015

Publication Type: Not specified

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

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

Abstract (Expand)

Only few Candida species, e.g., Candida albicans, Candida glabrata, Candida dubliniensis, and Candida parapsilosis, are successful colonizers of a human host. Under certain circumstances these species can cause infections ranging from superficial to life-threatening disseminated candidiasis. The success of C. albicans, the most prevalent and best studied Candida species, as both commensal and human pathogen depends on its genetic, biochemical, and morphological flexibility which facilitates adaptation to a wide range of host niches. In addition, formation of biofilms provides additional protection from adverse environmental conditions. Furthermore, in many host niches Candida cells coexist with members of the human microbiome. The resulting fungal-bacterial interactions have a major influence on the success of C. albicans as commensal and also influence disease development and outcome. In this chapter, we review the current knowledge of important survival strategies of Candida spp., focusing on fundamental fitness and virulence traits of C. albicans.

Authors: M. Polke, ,

Date Published: 24th Feb 2015

Publication Type: Not specified

Abstract (Expand)

Inference of inter-species gene regulatory networks based on gene expression data is an important computational method to predict pathogen-host interactions (PHIs). Both the experimental setup and the nature of PHIs exhibit certain characteristics. First, besides an environmental change, the battle between pathogen and host leads to a constantly changing environment and thus complex gene expression patterns. Second, there might be a delay until one of the organisms reacts. Third, toward later time points only one organism may survive leading to missing gene expression data of the other organism. Here, we account for PHI characteristics by extending NetGenerator, a network inference tool that predicts gene regulatory networks from gene expression time series data. We tested multiple modeling scenarios regarding the stimuli functions of the interaction network based on a benchmark example. We show that modeling perturbation of a PHI network by multiple stimuli better represents the underlying biological phenomena. Furthermore, we utilized the benchmark example to test the influence of missing data points on the inference performance. Our results suggest that PHI network inference with missing data is possible, but we recommend to provide complete time series data. Finally, we extended the NetGenerator tool to incorporate gene- and time point specific variances, because complex PHIs may lead to high variance in expression data. Sample variances are directly considered in the objective function of NetGenerator and indirectly by testing the robustness of interactions based on variance dependent disturbance of gene expression values. We evaluated the method of variance incorporation on dual RNA sequencing (RNA-Seq) data of Mus musculus dendritic cells incubated with Candida albicans and proofed our method by predicting previously verified PHIs as robust interactions.

Authors: S. Schulze, S. G. Henkel, D. Driesch, R. Guthke, J. Linde

Date Published: 6th Feb 2015

Publication Type: Not specified

Abstract (Expand)

Candida albicans is the most important fungal pathogen of humans, causing severe infections, especially in nosocomial and immunocompromised settings. However, it is also the most prevalent fungus of the normal human microbiome, where it shares its habitat with hundreds of trillions of other microbial cells. Despite weak organic acids (WOAs) being among the most abundant metabolites produced by bacterial microbiota, little is known about their effect on C. albicans. Here we used a sequencing-based profiling strategy to systematically investigate the transcriptional stress response of C. albicans to lactic, acetic, propionic, and butyric acid at several time points after treatment. Our data reveal a complex transcriptional response, with individual WOAs triggering unique gene expression profiles and with important differences between acute and chronic exposure. Despite these dissimilarities, we found significant overlaps between the gene expression changes induced by each WOA, which led us to uncover a core transcriptional response that was largely unrelated to other previously published C. albicans transcriptional stress responses. Genes commonly up-regulated by WOAs were enriched in several iron transporters, which was associated with an overall decrease in intracellular iron concentrations. Moreover, chronic exposure to any WOA lead to down-regulation of RNA synthesis and ribosome biogenesis genes, which resulted in significant reduction of total RNA levels and of ribosomal RNA in particular. In conclusion, this study suggests that gastrointestinal microbiota might directly influence C. albicans physiology via production of WOAs, with possible implications of how this fungus interacts with its host in both health and disease.

Authors: F. Cottier, A. S. Tan, J. Chen, J. Lum, F. Zolezzi, M. Poidinger, N. Pavelka

Date Published: 1st Feb 2015

Publication Type: Not specified

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

Abstract (Expand)

Verticillium hemipterigenum (anamorph Torrubiella hemipterigena) is an entomopathogenic fungus and produces a broad range of secondary metabolites. Here, we present the draft genome sequence of the fungus, including gene structure and functional annotation. Genes were predicted incorporating RNA-Seq data and functionally annotated to provide the basis for further genome studies.

Authors: F. Horn, A. Habel, D. H. Scharf, J. Dworschak, , , C. Hertweck,

Date Published: 24th Jan 2015

Publication Type: Not specified

Abstract (Expand)

Candida glabrata is the second most common pathogenic Candida species and has emerged as a leading cause of nosocomial fungal infections. Its reduced susceptibility to antifungal drugs and its close relationship to Saccharomyces cerevisiae make it an interesting research focus. Although its genome sequence was published in 2004, little is known about its transcriptional dynamics. Here, we provide a detailed RNA-Seq-based analysis of the transcriptomic landscape of C. glabrata in nutrient-rich media, as well as under nitrosative stress and during pH shift. Using RNA-Seq data together with state-of-the-art gene prediction tools, we refined the annotation of the C. glabrata genome and predicted 49 novel protein-coding genes. Of these novel genes, 14 have homologs in S. cerevisiae and six are shared with other Candida species. We experimentally validated four novel protein-coding genes of which two are differentially regulated during pH shift and interaction with human neutrophils, indicating a potential role in host-pathogen interaction. Furthermore, we identified 58 novel non-protein-coding genes, 38 new introns and condition-specific alternative splicing. Finally, our data suggest different patterns of adaptation to pH shift and nitrosative stress in C. glabrata, Candida albicans and S. cerevisiae and thus further underline a distinct evolution of virulence in yeast.

Authors: , S. Duggan, M. Weber, F. Horn, , D. Hellwig, , , R. Martin, ,

Date Published: 13th Jan 2015

Publication Type: Not specified

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