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36 Publications visible to you, out of a total of 36

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)

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

Authors: T. Lehnert, , J. Pollmacher, , ,

Date Published: 19th Jun 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)

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)

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

Abstract (Expand)

Polymorphonuclear neutrophilic granulocytes (PMN) as cellular components of innate immunity play a crucial role in the defense against systemic Candida albicans infection. To analyze stimuli that are required for PMN activity during C. albicans infection in a situation similar to in vivo, we used a human whole-blood infection model. In this model, PMN activation 10 min after C. albicans infection was largely dependent on the anaphylatoxin C5a. Most importantly, C5a enabled blood PMN to overcome filament-restricted recognition of C. albicans and allowed efficient elimination of nonfilamentous C. albicans cph1Delta/efg1Delta from blood. Major PMN effector mechanisms, including oxidative burst, release of secondary granule contents and initial fungal phagocytosis could be prevented by blocking C5a receptor signaling. Identical effects were achieved using a humanized Ab specifically targeting human C5a. Phagocytosis of C. albicans 10 min postinfection was mediated by C5a-dependent enhancement of CD11b surface expression on PMN, thus establishing the C5a-C5aR-CD11b axis as a major modulator of early anti-Candida immune responses in human blood. In contrast, phagocytosis of C. albicans by PMN 60 min postinfection occurred almost independently of C5a and mainly contributed to activation of phagocytically active PMN at later time points. Our results show that C5a is a critical mediator in human blood during C. albicans infection.

Authors: , K. Bieber, R. Martin, T. Lehnert, , J. Loffler, R. F. Guo, N. C. Riedemann,

Date Published: 24th Dec 2014

Publication Type: Not specified

Abstract (Expand)

Following antifungal treatment, Candida albicans, and other human pathogenic fungi can undergo microevolution, which leads to the emergence of drug resistance. However, the capacity for microevolutionary adaptation of fungi goes beyond the development of resistance against antifungals. Here we used an experimental microevolution approach to show that one of the central pathogenicity mechanisms of C. albicans, the yeast-to-hyphae transition, can be subject to experimental evolution. The C. albicans cph1Delta/efg1Delta mutant is nonfilamentous, as central signaling pathways linking environmental cues to hyphal formation are disrupted. We subjected this mutant to constant selection pressure in the hostile environment of the macrophage phagosome. In a comparatively short time-frame, the mutant evolved the ability to escape macrophages by filamentation. In addition, the evolved mutant exhibited hyper-virulence in a murine infection model and an altered cell wall composition compared to the cph1Delta/efg1Delta strain. Moreover, the transcriptional regulation of hyphae-associated, and other pathogenicity-related genes became re-responsive to environmental cues in the evolved strain. We went on to identify the causative missense mutation via whole genome- and transcriptome-sequencing: a single nucleotide exchange took place within SSN3 that encodes a component of the Cdk8 module of the Mediator complex, which links transcription factors with the general transcription machinery. This mutation was responsible for the reconnection of the hyphal growth program with environmental signals in the evolved strain and was sufficient to bypass Efg1/Cph1-dependent filamentation. These data demonstrate that even central transcriptional networks can be remodeled very quickly under appropriate selection pressure.

Authors: A. Wartenberg, , R. Martin, M. Schreiner, F. Horn, , S. Jenull, , K. Kuchler, , , A. Forche, C. d'Enfert, S. Brunke,

Date Published: 4th Dec 2014

Publication Type: Not specified

Abstract (Expand)

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points.

Authors: S. Brandes, Z. Mokhtari, F. Essig, , ,

Date Published: 8th Nov 2014

Publication Type: Not specified

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