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

Abstract (Expand)

BACKGROUND: Viruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora. RESULTS: VirMiner achieved 41.06% +/- 17.51% sensitivity and 81.91% +/- 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% +/- 16.94%) than VirFinder (34.63% +/- 17.96%) and VirSorter (18.75% +/- 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at http://sbb.hku.hk/VirMiner/ . CONCLUSIONS: We developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder-the most widely used tools-VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics. TRIAL REGISTRATION: The European Union Clinical Trials Register, EudraCT Number: 2013-003378-28 . Registered on 9 April 2014.

Authors: T. Zheng, J. Li, Y. Ni, K. Kang, M. A. Misiakou, L. Imamovic, B. K. C. Chow, A. A. Rode, P. Bytzer, M. Sommer, G. Panagiotou

Date Published: 19th Mar 2019

Publication Type: Not specified

Abstract (Expand)

Th17 cells provide protection at barrier tissues but may also contribute to immune pathology. The relevance and induction mechanisms of pathologic Th17 responses in humans are poorly understood. Here, we identify the mucocutaneous pathobiont Candida albicans as the major direct inducer of human anti-fungal Th17 cells. Th17 cells directed against other fungi are induced by cross-reactivity to C. albicans. Intestinal inflammation expands total C. albicans and cross-reactive Th17 cells. Strikingly, Th17 cells cross-reactive to the airborne fungus Aspergillus fumigatus are selectively activated and expanded in patients with airway inflammation, especially during acute allergic bronchopulmonary aspergillosis. This indicates a direct link between protective intestinal Th17 responses against C. albicans and lung inflammation caused by airborne fungi. We identify heterologous immunity to a single, ubiquitous member of the microbiota as a central mechanism for systemic induction of human anti-fungal Th17 responses and as a potential risk factor for pulmonary inflammatory diseases.

Authors: P. Bacher, T. Hohnstein, E. Beerbaum, M. Rocker, M. G. Blango, S. Kaufmann, J. Rohmel, P. Eschenhagen, C. Grehn, K. Seidel, V. Rickerts, L. Lozza, U. Stervbo, M. Nienen, N. Babel, J. Milleck, M. Assenmacher, O. A. Cornely, M. Ziegler, H. Wisplinghoff, G. Heine, M. Worm, B. Siegmund, J. Maul, P. Creutz, C. Tabeling, C. Ruwwe-Glosenkamp, L. E. Sander, C. Knosalla, S. Brunke, B. Hube, O. Kniemeyer, A. A. Brakhage, C. Schwarz, A. Scheffold

Date Published: 7th Mar 2019

Publication Type: Not specified

Abstract (Expand)

Migration and interactions of immune cells are routinely studied by time-lapse microscopy of in vitro migration and confrontation assays. To objectively quantify the dynamic behavior of cells, software tools for automated cell tracking can be applied. However, many existing tracking algorithms recognize only rather short fragments of a whole cell track and rely on cell staining to enhance cell segmentation. While our previously developed segmentation approach enables tracking of label-free cells, it still suffers from frequently recognizing only short track fragments. In this study, we identify sources of track fragmentation and provide solutions to obtain longer cell tracks. This is achieved by improving the detection of low-contrast cells and by optimizing the value of the gap size parameter, which defines the number of missing cell positions between track fragments that is accepted for still connecting them into one track. We find that the enhanced track recognition increases the average length of cell tracks up to 2.2-fold. Recognizing cell tracks as a whole will enable studying and quantifying more complex patterns of cell behavior, e.g. switches in migration mode or dependence of the phagocytosis efficiency on the number and type of preceding interactions. Such quantitative analyses will improve our understanding of how immune cells interact and function in health and disease.

Authors: N. Al-Zaben, A. Medyukhina, S. Dietrich, A. Marolda, K. Hunniger, O. Kurzai, M. T. Figge

Date Published: 1st Mar 2019

Publication Type: Not specified

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, S. Timme, M. T. Figge

Date Published: 27th Feb 2019

Publication Type: Not specified

Abstract (Expand)

Molecular mimicry is the formation of specific molecules by microbial pathogens to avoid recognition and attack by the immune system of the host. Several pathogenic Ascomycota and Zygomycota show such a behaviour by utilizing human complement factor H to hide in the blood stream. We call this type of mimicry molecular crypsis. Such a crypsis can reach a point where the immune system can no longer clearly distinguish between self and non-self cells. Thus, a trade-off between attacking disguised pathogens and erroneously attacking host cells has to be made. Based on signalling theory and protein-interaction modelling, we here present a mathematical model of molecular crypsis of pathogenic fungi using the example of Candida albicans. We tackle the question whether perfect crypsis is feasible, which would imply that protection of human cells by complement factors would be useless. The model identifies pathogen abundance relative to host cell abundance as the predominant factor influencing successful or unsuccessful molecular crypsis. If pathogen cells gain a (locally) quantitative advantage over host cells, even autoreactivity may occur. Our new model enables insights into the mechanisms of candidiasis-induced sepsis and complement-associated autoimmune diseases.

Authors: S. N. Lang, S. Germerodt, C. Glock, C. Skerka, P. F. Zipfel, S. Schuster

Date Published: 20th Feb 2019

Publication Type: Not specified

Abstract (Expand)

The clonal population structure of Candida albicans suggests that (para)sexual recombination does not play an important role in the lifestyle of this opportunistic fungal pathogen, an assumption that is strengthened by the fact that most C. albicans strains are heterozygous at the mating type locus (MTL) and therefore mating-incompetent. On the other hand, mating might occur within clonal populations and allow the combination of advantageous traits that were acquired by individual cells to adapt to adverse conditions. We have investigated if parasexual recombination may be involved in the evolution of highly drug-resistant strains exhibiting multiple resistance mechanisms against fluconazole, an antifungal drug that is commonly used to treat infections by C. albicans Growth of strains that were heterozygous for MTL and different fluconazole resistance mutations in the presence of the drug resulted in the emergence of derivatives that had become homozygous for the mutated allele and the mating type locus and exhibited increased drug resistance. When MTL a/a and MTLalpha/alpha cells of these strains were mixed in all possible combinations, we could isolate mating products containing the genetic material from both parents. The initial mating products did not exhibit higher drug resistance than their parental strains, but further propagation under selective pressure resulted in the loss of the wild-type alleles and increased fluconazole resistance. Therefore, fluconazole treatment not only selects for resistance mutations but also promotes genomic alterations that confer mating competence, which allows cells in an originally clonal population to exchange individually acquired resistance mechanisms and generate highly drug-resistant progeny.IMPORTANCE Sexual reproduction is an important mechanism in the evolution of species, since it allows the combination of advantageous traits of individual members in a population. The pathogenic yeast Candida albicans is a diploid organism that normally propagates in a clonal fashion, because heterozygosity at the mating type locus (MTL) inhibits mating between cells. Here we show that C. albicans cells that have acquired drug resistance mutations during treatment with the commonly used antifungal agent fluconazole rapidly develop further increased resistance by genome rearrangements that result in simultaneous loss of heterozygosity for the mutated allele and the mating type locus. This enables the drug-resistant cells of a population to switch to the mating-competent opaque morphology and mate with each other to combine different individually acquired resistance mechanisms. The tetraploid mating products reassort their merged genomes and, under selective pressure by the drug, generate highly resistant progeny that have retained the advantageous mutated alleles. Parasexual propagation, promoted by stress-induced genome rearrangements that result in the acquisition of mating competence in cells with adaptive mutations, may therefore be an important mechanism in the evolution of C. albicans populations.

Authors: C. Popp, B. Ramirez-Zavala, S. Schwanfelder, I. Kruger, J. Morschhauser

Date Published: 5th Feb 2019

Publication Type: Not specified

Abstract (Expand)

To efficiently exploit the potential of several millions of droplets that can be considered as individual bioreactors in microfluidic experiments, methods to encode different experimental conditions in droplets are needed. The approach presented here is based on coencapsulation of colored polystyrene beads with biological samples. The decoding of the droplets, as well as content quantification, are performed by automated analysis of triggered images of individual droplets in-flow using bright-field microscopy. The decoding strategy combines bead classification using a random forest classifier and Bayesian inference to identify different codes and thus experimental conditions. Antibiotic susceptibility testing of nine different antibiotics and the determination of the minimal inhibitory concentration of a specific antibiotic against a laboratory strain of Escherichia coli are presented as a proof-of-principle. It is demonstrated that this method allows successful encoding and decoding of 20 different experimental conditions within a large droplet population of more than 10(5) droplets per condition. The decoding strategy correctly assigns 99.6% of droplets to the correct condition and a method for the determination of minimal inhibitory concentration using droplet microfluidics is established. The current encoding and decoding pipeline can readily be extended to more codes by adding more bead colors or color combinations.

Authors: C. M. Svensson, O. Shvydkiv, S. Dietrich, L. Mahler, T. Weber, M. Choudhary, M. Tovar, M. T. Figge, M. Roth

Date Published: 15th Dec 2018

Publication Type: Not specified

Abstract (Expand)

PURPOSE: The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. EXPERIMENTAL DESIGN: MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). RESULTS: In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. CONCLUSIONS AND CLINICAL RELEVANCE: The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

Authors: F. Hoffmann, C. Umbreit, T. Kruger, D. Pelzel, G. Ernst, O. Kniemeyer, O. Guntinas-Lichius, A. Berndt, F. von Eggeling

Date Published: 10th Nov 2018

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: Omics data provide deep insights into overall biological processes of organisms. However, integration of data from different molecular levels such as transcriptomics and proteomics, still remains challenging. Analyzing lists of differentially abundant molecules from diverse molecular levels often results in a small overlap mainly due to different regulatory mechanisms, temporal scales, and/or inherent properties of measurement methods. Module-detecting algorithms identifying sets of closely related proteins from protein-protein interaction networks (PPINs) are promising approaches for a better data integration. RESULTS: Here, we made use of transcriptome, proteome and secretome data from the human pathogenic fungus Aspergillus fumigatus challenged with the antifungal drug caspofungin. Caspofungin targets the fungal cell wall which leads to a compensatory stress response. We analyzed the omics data using two different approaches: First, we applied a simple, classical approach by comparing lists of differentially expressed genes (DEGs), differentially synthesized proteins (DSyPs) and differentially secreted proteins (DSePs); second, we used a recently published module-detecting approach, ModuleDiscoverer, to identify regulatory modules from PPINs in conjunction with the experimental data. Our results demonstrate that regulatory modules show a notably higher overlap between the different molecular levels and time points than the classical approach. The additional structural information provided by regulatory modules allows for topological analyses. As a result, we detected a significant association of omics data with distinct biological processes such as regulation of kinase activity, transport mechanisms or amino acid metabolism. We also found a previously unreported increased production of the secondary metabolite fumagillin by A. fumigatus upon exposure to caspofungin. Furthermore, a topology-based analysis of potential key factors contributing to drug-caused side effects identified the highly conserved protein polyubiquitin as a central regulator. Interestingly, polyubiquitin UbiD neither belonged to the groups of DEGs, DSyPs nor DSePs but most likely strongly influenced their levels. CONCLUSION: Module-detecting approaches support the effective integration of multilevel omics data and provide a deep insight into complex biological relationships connecting these levels. They facilitate the identification of potential key players in the organism's stress response which cannot be detected by commonly used approaches comparing lists of differentially abundant molecules.

Authors: T. Conrad, O. Kniemeyer, S. G. Henkel, T. Kruger, D. J. Mattern, V. Valiante, R. Guthke, I. D. Jacobsen, A. A. Brakhage, S. Vlaic, J. Linde

Date Published: 20th Oct 2018

Publication Type: Not specified

Abstract (Expand)

Alternative splicing (AS) is an important regulatory mechanism in eukaryotes but only little is known about its impact in fungi. Human fungal pathogens are of high clinical interest causing recurrent or life-threatening infections. AS can be well-investigated genome-wide and quantitatively with the powerful technology of RNA-Seq. Here, we systematically studied AS in human fungal pathogens based on RNA-Seq data. To do so, we investigated its effect in seven fungi during conditions simulating ex vivo infection processes and during in vitro stress. Genes undergoing AS are species-specific and act independently from differentially expressed genes pointing to an independent mechanism to change abundance and functionality. Candida species stand out with a low number of introns with higher and more varying lengths and more alternative splice sites. Moreover, we identified a functional difference between response to host and other stress conditions: During stress, AS affects more genes and is involved in diverse regulatory functions. In contrast, during response-to-host conditions, genes undergoing AS have membrane functionalities and might be involved in the interaction with the host. We assume that AS plays a crucial regulatory role in pathogenic fungi and is important in both response to host and stress conditions.

Authors: P. Sieber, K. Voigt, P. Kammer, S. Brunke, S. Schuster, J. Linde

Date Published: 19th Oct 2018

Publication Type: Not specified

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