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The Candida albicans Histone Acetyltransferase Hat1 Regulates Stress Resistance and Virulence via Distinct Chromatin Assembly Pathways.
INF

Abstract (Expand)

Human fungal pathogens like Candida albicans respond to host immune surveillance by rapidly adapting their transcriptional programs. Chromatin assembly factors are involved in the regulation of stress … genes by modulating the histone density at these loci. Here, we report a novel role for the chromatin assembly-associated histone acetyltransferase complex NuB4 in regulating oxidative stress resistance, antifungal drug tolerance and virulence in C. albicans. Strikingly, depletion of the NuB4 catalytic subunit, the histone acetyltransferase Hat1, markedly increases resistance to oxidative stress and tolerance to azole antifungals. Hydrogen peroxide resistance in cells lacking Hat1 results from higher induction rates of oxidative stress gene expression, accompanied by reduced histone density as well as subsequent increased RNA polymerase recruitment. Furthermore, hat1Delta/Delta cells, despite showing growth defects in vitro, display reduced susceptibility to reactive oxygen-mediated killing by innate immune cells. Thus, clearance from infected mice is delayed although cells lacking Hat1 are severely compromised in killing the host. Interestingly, increased oxidative stress resistance and azole tolerance are phenocopied by the loss of histone chaperone complexes CAF-1 and HIR, respectively, suggesting a central role for NuB4 in the delivery of histones destined for chromatin assembly via distinct pathways. Remarkably, the oxidative stress phenotype of hat1Delta/Delta cells is a species-specific trait only found in C. albicans and members of the CTG clade. The reduced azole susceptibility appears to be conserved in a wider range of fungi. Thus, our work demonstrates how highly conserved chromatin assembly pathways can acquire new functions in pathogenic fungi during coevolution with the host.

Authors: M. Tscherner, F. Zwolanek, S. Jenull, F. J. Sedlazeck, A. Petryshyn, I. E. Frohner, J. Mavrianos, N. Chauhan, A. von Haeseler, K. Kuchler

Date Published: No date defined

Journal: PLoS Pathog

MetGEMs Toolbox: Metagenome-scale models as integrative toolbox for uncovering metabolic functions and routes of human gut microbiome.
INF, B5

Abstract (Expand)

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible … way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

Authors: P. Patumcharoenpol, M. Nakphaichit, Gianni Panagiotou, A. Senavonge, N. Suratannon, W. Vongsangnak

Date Published: 6th Jan 2021

Journal: PLoS Comput Biol

Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels.
INF, A5, C1, C2, B5

Abstract (Expand)

Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. … albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal-bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.

Authors: Mohammad Mirhakkak, Sascha Schäuble, Tilman Klassert, S. Brunke, Philipp Brandt, D. Loos, R. V. Uribe, F. Senne de Oliveira Lino, Y. Ni, Slavena Vylkova, Hortense Slevogt, Bernhard Hube, Esther Weiß, M. O. A. Sommer, Gianni Panagiotou

Date Published: 15th Dec 2020

Journal: ISME J

Lipid metabolic signatures deviate in sepsis survivors compared to non-survivors.
INF, C5

Abstract (Expand)

Sepsis remains a major cause of death despite advances in medical care. Metabolic deregulation is an important component of the survival process. Metabolomic analysis allows profiling of critical … metabolic functions with the potential to classify patient outcome. Our prospective longitudinal characterization of 33 septic and non-septic critically ill patients showed that deviations, independent of direction, in plasma levels of lipid metabolites were associated with sepsis mortality. We identified a coupling of metabolic signatures between liver and plasma of a rat sepsis model that allowed us to apply a human kinetic model of mitochondrial beta-oxidation to reveal differing enzyme concentrations for medium/short-chain hydroxyacyl-CoA dehydrogenase (elevated in survivors) and crotonase (elevated in non-survivors). These data suggest a need to monitor cellular energy metabolism beyond the available biomarkers. A loss of metabolic adaptation appears to be reflected by an inability to maintain cellular (fatty acid) metabolism within a "corridor of safety".

Authors: W. Khaliq, Peter Großmann, S. Neugebauer, A. Kleyman, R. Domizi, S. Calcinaro, D. Brealey, M. Graler, M. Kiehntopf, Sascha Schäuble, M. Singer, Gianni Panagiotou, Michael Bauer

Date Published: 11th Dec 2020

Journal: Comput Struct Biotechnol J

Effects of Agricultural Fungicide Use on Aspergillus fumigatus Abundance, Antifungal Susceptibility, and Population Structure.
INF, B5

Abstract (Expand)

Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is both an environmental saprobe and an opportunistic human fungal pathogen, resistance is … suggested to arise from fungicide use in agriculture, as the azoles used for plant protection share the same molecular target as the frontline antifungals used clinically. However, limiting azole fungicide use on crop fields to preserve their activity for clinical use could threaten the global food supply via a reduction in yield. In this study, we clarify the link between azole fungicide use on crop fields and resistance in a prototypical human pathogen through systematic soil sampling on farms in Germany and surveying fields before and after fungicide application. We observed a reduction in the abundance of A. fumigatus on fields following fungicide treatment in 2017, a finding that was not observed on an organic control field with only natural plant protection agents applied. However, this finding was less pronounced during our 2018 sampling, indicating that the impact of fungicides on A. fumigatus population size is variable and influenced by additional factors. The overall resistance frequency among agricultural isolates is low, with only 1 to 3% of isolates from 2016 to 2018 displaying resistance to medical azoles. Isolates collected after the growing season and azole exposure show a subtle but consistent decrease in susceptibility to medical and agricultural azoles. Whole-genome sequencing indicates that, despite the alterations in antifungal susceptibility, fungicide application does not significantly affect the population structure and genetic diversity of A. fumigatus in fields. Given the low observed resistance rate among agricultural isolates as well the lack of genomic impact following azole application, we do not find evidence that azole use on crops is significantly driving resistance in A. fumigatus in this context.IMPORTANCE Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is an environmental fungus that also causes life-threatening infections in humans, antimicrobial resistance is suggested to arise from fungicide use in agriculture, as the chemicals used for plant protection are almost identical to the antifungals used clinically. However, removing azole fungicides from crop fields threatens the global food supply via a reduction in yield. In this study, we survey crop fields before and after fungicide application. We find a low overall azole resistance rate among agricultural isolates, as well as a lack of genomic and population impact following fungicide application, leading us to conclude azole use on crops does not significantly contribute to resistance in A. fumigatus.

Authors: A. E. Barber, J. Riedel, T. Sae-Ong, K. Kang, W. Brabetz, Gianni Panagiotou, H. B. Deising, Oliver Kurzai

Date Published: 24th Nov 2020

Journal: mBio

Triple RNA-Seq Reveals Synergy in a Human Virus-Fungus Co-infection Model.
INF, A2, B5

Abstract (Expand)

High-throughput RNA sequencing (RNA-seq) is routinely applied to study diverse biological processes; however, when performed separately on interacting organisms, systemic noise intrinsic to RNA extraction, … library preparation, and sequencing hampers the identification of cross-species interaction nodes. Here, we develop triple RNA-seq to simultaneously detect transcriptomes of monocyte-derived dendritic cells (moDCs) infected with the frequently co-occurring pulmonary pathogens Aspergillus fumigatus and human cytomegalovirus (CMV). Comparing expression patterns after co-infection with those after single infections, our data reveal synergistic effects and mutual interferences between host responses to the two pathogens. For example, CMV attenuates the fungus-mediated activation of pro-inflammatory cytokines through NF-kappaB (nuclear factor kappaB) and NFAT (nuclear factor of activated T cells) cascades, while A. fumigatus impairs viral clearance by counteracting viral nucleic acid-induced activation of type I interferon signaling. Together, the analytical power of triple RNA-seq proposes molecular hubs in the differential moDC response to fungal/viral single infection or co-infection that contribute to our understanding of the etiology and, potentially, clearance of post-transplant infections.

Authors: Bastian Seelbinder, J. Wallstabe, Lothar Marischen, Esther Weiß, S. Wurster, L. Page, C. Loffler, L. Bussemer, A. L. Schmitt, Thomas Wolf, Jörg Linde, L. Cicin-Sain, J. Becker, U. Kalinke, J. Vogel, Gianni Panagiotou, Hermann Einsele, A. J. Westermann, Sascha Schäuble, Jürgen Löffler

Date Published: 17th Nov 2020

Journal: Cell Rep

Proteome analysis of bronchoalveolar lavage fluids reveals host and fungal proteins highly expressed during invasive pulmonary aspergillosis in mice and humans.
INF, A5, C5

Abstract (Expand)

Invasive pulmonary aspergillosis (IPA) is a severe infection that is difficult to diagnose due to the ubiquitous presence of fungal spores, the underlying diseases of risk patients, and limitations of … currently available markers. In this study, we performed a comprehensive liquid chromatography tandem mass spectrometry (LC-MS/MS)-based identification of host and fungal proteins expressed during IPA in mice and humans. The proteomic analysis of bronchoalveolar lavage samples of individual IPA and control cases allowed the description of common host factors that had significantly increased abundance in both infected animals and IPA patients compared to their controls. Although increased levels of these individual host proteins might not be sufficient to distinguish bacterial from fungal infection, a combination of these markers might be beneficial to improve diagnosis. We also identified 16 fungal proteins that were specifically detected during infection and may be valuable candidates for biomarker evaluation.

Authors: S. Machata, Wolfgang Müller, R. Lehmann, Patricia Sieber, Gianni Panagiotou, A. Carvalho, C. Cunha, K. Lagrou, J. Maertens, Hortense Slevogt, Ilse Jacobsen

Date Published: 12th Oct 2020

Journal: Virulence

Survival Strategies of Pathogenic Candida Species in Human Blood Show Independent and Specific Adaptations.
INF, B3 (E), C1, C3

Abstract (Expand)

Only four species, Candida albicans, C. glabrata, C. parapsilosis, and C. tropicalis, together account for about 90% of all Candida bloodstream infections and are among the most common causes of invasive … fungal infections of humans. However, virulence potential varies among these species, and the phylogenetic tree reveals that their pathogenicity may have emerged several times independently during evolution. We therefore tested these four species in a human whole-blood infection model to determine, via comprehensive dual-species RNA-sequencing analyses, which fungal infection strategies are conserved and which are recent evolutionary developments. The ex vivo infection progressed from initial immune cell interactions to nearly complete killing of all fungal cells. During the course of infection, we characterized important parameters of pathogen-host interactions, such as fungal survival, types of interacting immune cells, and cytokine release. On the transcriptional level, we obtained a predominantly uniform and species-independent human response governed by a strong upregulation of proinflammatory processes, which was downregulated at later time points after most of the fungal cells were killed. In stark contrast, we observed that the different fungal species pursued predominantly individual strategies and showed significantly different global transcriptome patterns. Among other findings, our functional analyses revealed that the fungal species relied on different metabolic pathways and virulence factors to survive the host-imposed stress. These data show that adaptation of Candida species as a response to the host is not a phylogenetic trait, but rather has likely evolved independently as a prerequisite to cause human infections.IMPORTANCE To ensure their survival, pathogens have to adapt immediately to new environments in their hosts, for example, during the transition from the gut to the bloodstream. Here, we investigated the basis of this adaptation in a group of fungal species which are among the most common causes of hospital-acquired infections, the Candida species. On the basis of a human whole-blood infection model, we studied which genes and processes are active over the course of an infection in both the host and four different Candida pathogens. Remarkably, we found that, while the human host response during the early phase of infection is predominantly uniform, the pathogens pursue largely individual strategies and each one regulates genes involved in largely disparate processes in the blood. Our results reveal that C. albicans, C. glabrata, C. parapsilosis, and C. tropicalis all have developed individual strategies for survival in the host. This indicates that their pathogenicity in humans has evolved several times independently and that genes which are central for survival in the host for one species may be irrelevant in another.

Authors: P. Kammer, S. McNamara, Thomas Wolf, Theresia Conrad, Stefanie Allert, F. Gerwien, Kerstin Hünniger, Oliver Kurzai, Reinhard Guthke, Bernhard Hube, Jörg Linde, S. Brunke

Date Published: 6th Oct 2020

Journal: mBio

Reconstituting NK Cells After Allogeneic Stem Cell Transplantation Show Impaired Response to the Fungal Pathogen Aspergillus fumigatus.
INF, A2, A3, C3

Abstract (Expand)

Delayed natural killer (NK) cell reconstitution after allogeneic stem cell transplantation (alloSCT) is associated with a higher risk of developing invasive aspergillosis. The interaction of NK cells … with the human pathogen Aspergillus (A.) fumigatus is mediated by the fungal recognition receptor CD56, which is relocated to the fungal interface after contact. Blocking of CD56 signaling inhibits the fungal mediated chemokine secretion of MIP-1alpha, MIP-1beta, and RANTES and reduces cell activation, indicating a functional role of CD56 in fungal recognition. We collected peripheral blood from recipients of an allograft at defined time points after alloSCT (day 60, 90, 120, 180). NK cells were isolated, directly challenged with live A. fumigatus germ tubes, and cell function was analyzed and compared to healthy age and gender-matched individuals. After alloSCT, NK cells displayed a higher percentage of CD56(bright)CD16(dim) cells throughout the time of blood collection. However, CD56 binding and relocalization to the fungal contact side were decreased. We were able to correlate this deficiency to the administration of corticosteroid therapy that further negatively influenced the secretion of MIP-1alpha, MIP-1beta, and RANTES. As a consequence, the treatment of healthy NK cells ex vivo with corticosteroids abrogated chemokine secretion measured by multiplex immunoassay. Furthermore, we analyzed NK cells regarding their actin cytoskeleton by Structured Illumination Microscopy (SIM) and flow cytometry and demonstrate an actin dysfunction of NK cells shown by reduced F-actin content after fungal co-cultivation early after alloSCT. This dysfunction remains until 180 days post-alloSCT, concluding that further actin-dependent cellular processes may be negatively influenced after alloSCT. To investigate the molecular pathomechansism, we compared CD56 receptor mobility on the plasma membrane of healthy and alloSCT primary NK cells by single-molecule tracking. The results were very robust and reproducible between tested conditions which point to a different molecular mechanism and emphasize the importance of proper CD56 mobility.

Authors: Esther Weiß, J. Schlegel, Ulrich Terpitz, Michael Weber, Jörg Linde, A. L. Schmitt, Kerstin Hünniger, Lothar Marischen, F. Gamon, J. Bauer, C. Loffler, Oliver Kurzai, C. O. Morton, M. Sauer, Hermann Einsele, Jürgen Löffler

Date Published: 5th Oct 2020

Journal: Front Immunol

Antibiotics create a shift from mutualism to competition in human gut communities with a longer-lasting impact on fungi than bacteria.
INF, C1, B5

Abstract (Expand)

BACKGROUND: Antibiotic treatment has a well-established detrimental effect on the gut bacterial composition, but effects on the fungal community are less clear. Bacteria in the lumen of the gastrointestinal … tract may limit fungal colonization and invasion. Antibiotic drugs targeting bacteria are therefore seen as an important risk factor for fungal infections and induced allergies. However, antibiotic effects on gut bacterial-fungal interactions, including disruption and resilience of fungal community compositions, were not investigated in humans. We analysed stool samples collected from 14 healthy human participants over 3 months following a 6-day antibiotic administration. We integrated data from shotgun metagenomics, metatranscriptomics, metabolomics, and fungal ITS2 sequencing. RESULTS: While the bacterial community recovered mostly over 3 months post treatment, the fungal community was shifted from mutualism at baseline to competition. Half of the bacterial-fungal interactions present before drug intervention had disappeared 3 months later. During treatment, fungal abundances were associated with the expression of bacterial genes with functions for cell growth and repair. By extending the metagenomic species approach, we revealed bacterial strains inhibiting the opportunistic fungal pathogen Candida albicans. We demonstrated in vitro how C. albicans pathogenicity and host cell damage might be controlled naturally in the human gut by bacterial metabolites such as propionate or 5-dodecenoate. CONCLUSIONS: We demonstrated that antibacterial drugs have long-term influence on the human gut mycobiome. While bacterial communities recovered mostly 30-days post antibacterial treatment, the fungal community was shifted from mutualism towards competition. Video abstract.

Authors: Bastian Seelbinder, J. Chen, S. Brunke, R. Vazquez-Uribe, R. Santhaman, A. C. Meyer, F. S. de Oliveira Lino, K. F. Chan, D. Loos, L. Imamovic, C. C. Tsang, R. P. Lam, S. Sridhar, K. Kang, Bernhard Hube, P. C. Woo, M. O. A. Sommer, Gianni Panagiotou

Date Published: 12th Sep 2020

Journal: Microbiome

Comparative Transcriptomic Analysis of Rhinovirus and Influenza Virus Infection.
INF, B5

Abstract (Expand)

Rhinovirus (RV) and influenza virus are the most frequently detected respiratory viruses among adult patients with community acquired pneumonia. Previous clinical studies have identified major differences … in the clinical presentations and inflammatory or immune response during these infections. A systematic transcriptomic analysis directly comparing influenza and RV is lacking. Here, we sought to compare the transcriptomic response to these viral infections. Human airway epithelial Calu-3 cells were infected with contemporary clinical isolates of RV, influenza A virus (IAV), or influenza B virus (IBV). Host gene expression was determined using RNA-seq. Differentially expressed genes (DEGs) with respect to mock-infected cells were identified using the overlapping gene-set of four different statistical models. Transcriptomic analysis showed that RV-infected cells have a more blunted host response with fewer DEGs than IAV or IBV-infected cells. IFNL1 and CXCL10 were among the most upregulated DEGs during RV, IAV, and IBV infection. Other DEGs that were highly expressed for all 3 viruses were mainly genes related to type I or type III interferons (RSAD2, IDO1) and chemokines (CXCL11). Notably, ICAM5, a known receptor for enterovirus D68, was highly expressed during RV infection only. Gene Set Enrichment Analysis (GSEA) confirmed that pathways associated with interferon response, innate immunity, or regulation of inflammatory response, were most perturbed for all three viruses. Network analysis showed that steroid-related pathways were enriched. Taken together, our data using contemporary virus strains suggests that genes related to interferon and chemokine predominated the host response associated with RV, IAV, and IBV infection. Several highly expressed genes, especially ICAM5 which is preferentially-induced during RV infection, deserve further investigation.

Authors: T. K. Dissanayake, Sascha Schäuble, Mohammad Mirhakkak, W. L. Wu, A. C. Ng, C. C. Y. Yip, A. G. Lopez, Thomas Wolf, M. L. Yeung, K. H. Chan, K. Y. Yuen, Gianni Panagiotou, K. K. To

Date Published: 28th Aug 2020

Journal: Front Microbiol

Novel Approaches for Systems Biology of Metabolism-Oriented Pathogen-Human Interactions: A Mini-Review.
INF, B5

Abstract (Expand)

Pathogenic microorganisms exploit host metabolism for sustained survival by rewiring its metabolic interactions. Therefore, several metabolic changes are induced in both pathogen and host cells in the … course of infection. A systems-based approach to elucidate those changes includes the integrative use of genome-scale metabolic networks and molecular omics data, with the overall goal of better characterizing infection mechanisms for novel treatment strategies. This review focuses on novel aspects of metabolism-oriented systems-based investigation of pathogen-human interactions. The reviewed approaches are the generation of dual-omics data for the characterization of metabolic signatures of pathogen-host interactions, the reconstruction of pathogen-host integrated genome-scale metabolic networks, which has a high potential to be applied to pathogen-gut microbiota interactions, and the structure-based analysis of enzymes playing role in those interactions. The integrative use of those approaches will pave the way for the identification of novel biomarkers and drug targets for the prediction and prevention of infectious diseases.

Authors: T. Cakir, Gianni Panagiotou, R. Uddin, S. Durmus

Date Published: 3rd Mar 2020

Journal: Front Cell Infect Microbiol

Gastric bypass surgery in a rat model alters the community structure and functional composition of the intestinal microbiota independently of weight loss.
INF, B5

Abstract (Expand)

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is a last-resort treatment to induce substantial and sustained weight loss in cases of severe obesity. This anatomical rearrangement affects the … intestinal microbiota, but so far, little information is available on how it interferes with microbial functionality and microbial-host interactions independently of weight loss. METHODS: A rat model was employed where the RYGB-surgery cohort is compared to sham-operated controls which were kept at a matched body weight by food restriction. We investigated the microbial taxonomy and functional activity using 16S rRNA amplicon gene sequencing, metaproteomics, and metabolomics on samples collected from theileum, the cecum, and the colon, and separately analysed the lumen and mucus-associated microbiota. RESULTS: Altered gut architecture in RYGB increased the relative occurrence of Actinobacteria, especially Bifidobacteriaceae and Proteobacteria, while in general, Firmicutes were decreased although Streptococcaceae and Clostridium perfringens were observed at relative higher abundances independent of weight loss. A decrease of conjugated and secondary bile acids was observed in the RYGB-gut lumen. The arginine biosynthesis pathway in the microbiota was altered, as indicated by the changes in the abundance of upstream metabolites and enzymes, resulting in lower levels of arginine and higher levels of aspartate in the colon after RYGB. CONCLUSION: The anatomical rearrangement in RYGB affects microbiota composition and functionality as well as changes in amino acid and bile acid metabolism independently of weight loss. The shift in the taxonomic structure of the microbiota after RYGB may be mediated by the resulting change in the composition of the bile acid pool in the gut and by changes in the composition of nutrients in the gut. Video abstract.

Authors: S. B. Haange, N. Jehmlich, U. Krugel, C. Hintschich, D. Wehrmann, M. Hankir, F. Seyfried, J. Froment, T. Hubschmann, S. Muller, D. K. Wissenbach, K. Kang, C. Buettner, Gianni Panagiotou, M. Noll, U. Rolle-Kampczyk, W. Fenske, M. von Bergen

Date Published: 7th Feb 2020

Journal: Microbiome

Gut Microbiome Fermentation Determines the Efficacy of Exercise for Diabetes Prevention.
INF, B5

Abstract (Expand)

Exercise is an effective strategy for diabetes management but is limited by the phenomenon of exercise resistance (i.e., the lack of or the adverse response to exercise on metabolic health). Here, in … 39 medication-naive men with prediabetes, we found that exercise-induced alterations in the gut microbiota correlated closely with improvements in glucose homeostasis and insulin sensitivity (clinicaltrials.gov entry NCT03240978). The microbiome of responders exhibited an enhanced capacity for biosynthesis of short-chain fatty acids and catabolism of branched-chain amino acids, whereas those of non-responders were characterized by increased production of metabolically detrimental compounds. Fecal microbial transplantation from responders, but not non-responders, mimicked the effects of exercise on alleviation of insulin resistance in obese mice. Furthermore, a machine-learning algorithm integrating baseline microbial signatures accurately predicted personalized glycemic response to exercise in an additional 30 subjects. These findings raise the possibility of maximizing the benefits of exercise by targeting the gut microbiota.

Authors: Y. Liu, Y. Wang, Y. Ni, C. K. Y. Cheung, K. S. L. Lam, Y. Wang, Z. Xia, D. Ye, J. Guo, M. A. Tse, Gianni Panagiotou, A. Xu

Date Published: 7th Jan 2020

Journal: Cell Metab

Treatment with etanercept and low monocyte concentration contribute to the risk of invasive aspergillosis in patients post allogeneic stem cell transplantation.
INF, A2, C3

Abstract (Expand)

Invasive aspergillosis (IA) is a life-threatening complication among allogeneic hematopoietic stem cell transplant (alloSCT) recipients. Despite well known risk factors and different available assays, … diagnosis of invasive aspergillosis remains challenging. 103 clinical variables from patients with hematological malignancies and subsequent alloSCT were collected. Associations between collected variables and patients with (n = 36) and without IA (n = 36) were investigated by applying univariate and multivariable logistic regression. The predictive power of the final model was tested in an independent patient cohort (23 IA cases and 25 control patients). Findings were investigated further by in vitro studies, which analysed the effect of etanercept on A. fumigatus-stimulated macrophages at the gene expression and cytokine secretion. Additionally, the release of C-X-C motif chemokine ligand 10 (CXCL10) in patient sera was studied. Low monocyte concentration (p = 4.8 x 10(-06)), severe GvHD of the gut (grade 2-4) (p = 1.08 x 10(-02)) and etanercept treatment of GvHD (p = 3.5 x 10(-03)) were significantly associated with IA. Our studies showed that etanercept lowers CXCL10 concentrations in vitro and ex vivo and down-regulates genes involved in immune responses and TNF-alpha signaling. Our study offers clinicians new information regarding risk factors for IA including low monocyte counts and administration of etanercept. After necessary validation, such information may be used for decision making regarding antifungal prophylaxis or closely monitoring patients at risk.

Authors: T. Zoran, Michael Weber, J. Springer, P. L. White, J. Bauer, A. Schober, C. Loffler, B. Seelbinder, Kerstin Hünniger, Oliver Kurzai, A. Scherag, Sascha Schäuble, C. O. Morton, Hermann Einsele, Jörg Linde, Jürgen Löffler

Date Published: 21st Nov 2019

Journal: Sci Rep

Mining, analyzing, and integrating viral signals from metagenomic data.
INF, B5

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, Gianni Panagiotou

Date Published: 19th Mar 2019

Journal: Microbiome

Module-detection approaches for the integration of multilevel omics data highlight the comprehensive response of Aspergillus fumigatus to caspofungin.
INF, A1, C5

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: Theresia Conrad, Olaf Kniemeyer, S. G. Henkel, T. Kruger, D. J. Mattern, V. Valiante, Reinhard Guthke, Ilse Jacobsen, Axel Brakhage, S. Vlaic, Jörg Linde

Date Published: 20th Oct 2018

Journal: BMC Syst Biol

Comparative Study on Alternative Splicing in Human Fungal Pathogens Suggests Its Involvement During Host Invasion.
INF, B1

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: Patricia Sieber, Kerstin Voigt, P. Kammer, S. Brunke, Stefan Schuster, Jörg Linde

Date Published: 19th Oct 2018

Journal: Front Microbiol

ModuleDiscoverer: Identification of regulatory modules in protein-protein interaction networks.
INF, B1

Abstract (Expand)

The identification of disease-associated modules based on protein-protein interaction networks (PPINs) and gene expression data has provided new insights into the mechanistic nature of diverse diseases. … However, their identification is hampered by the detection of protein communities within large-scale, whole-genome PPINs. A presented successful strategy detects a PPIN's community structure based on the maximal clique enumeration problem (MCE), which is a non-deterministic polynomial time-hard problem. This renders the approach computationally challenging for large PPINs implying the need for new strategies. We present ModuleDiscoverer, a novel approach for the identification of regulatory modules from PPINs and gene expression data. Following the MCE-based approach, ModuleDiscoverer uses a randomization heuristic-based approximation of the community structure. Given a PPIN of Rattus norvegicus and public gene expression data, we identify the regulatory module underlying a rodent model of non-alcoholic steatohepatitis (NASH), a severe form of non-alcoholic fatty liver disease (NAFLD). The module is validated using single-nucleotide polymorphism (SNP) data from independent genome-wide association studies and gene enrichment tests. Based on gene enrichment tests, we find that ModuleDiscoverer performs comparably to three existing module-detecting algorithms. However, only our NASH-module is significantly enriched with genes linked to NAFLD-associated SNPs. ModuleDiscoverer is available at http://www.hki-jena.de/index.php/0/2/490 (Others/ModuleDiscoverer).

Authors: S. Vlaic, Theresia Conrad, C. Tokarski-Schnelle, M. Gustafsson, U. Dahmen, Reinhard Guthke, Stefan Schuster

Date Published: 11th Jan 2018

Journal: Sci Rep

Two's company: studying interspecies relationships with dual RNA-seq.
INF

Abstract (Expand)

Organisms do not exist isolated from each other, but constantly interact. Cells can sense the presence of interaction partners by a range of receptors and, via complex regulatory networks, specifically … react by changing the expression of many of their genes. Technological advances in next-generation sequencing over the recent years now allow us to apply RNA sequencing to two species at the same time (dual RNA-seq), and thus to directly study the gene expression of two interacting species without the need to physically separate cells or RNA. In this review, we give an overview over the latest studies in interspecies interactions made possible by dual RNA-seq, ranging from pathogenic to symbiotic relationships. We summarize state-of-the-art experimental techniques, bioinformatic data analysis and data interpretation, while also highlighting potential problems and pitfalls starting from the selection of meaningful time points and number of reads to matters of rRNA depletion. A short outlook on new trends in the field of dual RNA-seq concludes this review, looking at sequencing of non-coding RNAs during host-pathogen interactions and the prediction of molecular interspecies interactions networks.

Authors: Thomas Wolf, P. Kammer, S. Brunke, Jörg Linde

Date Published: 29th Sep 2017

Journal: Curr Opin Microbiol

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.
INF

Abstract (Expand)

Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present … large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naive Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.

Authors: R. Magnusson, G. P. Mariotti, M. Kopsen, W. Lovfors, D. R. Gawel, R. Jornsten, Jörg Linde, T. E. M. Nordling, E. Nyman, Sylvie Schulze, C. E. Nestor, H. Zhang, G. Cedersund, M. Benson, A. Tjarnberg, M. Gustafsson

Date Published: 24th Jun 2017

Journal: PLoS Comput Biol

Specific and Novel microRNAs Are Regulated as Response to Fungal Infection in Human Dendritic Cells.
INF, A2, B3 (E), C3

Abstract (Expand)

Within the last two decades, the incidence of invasive fungal infections has been significantly increased. They are characterized by high mortality rates and are often caused by Candida albicans and … Aspergillus fumigatus. The increasing number of infections underlines the necessity for additional anti-fungal therapies, which require extended knowledge of gene regulations during fungal infection. MicroRNAs are regulators of important cellular processes, including the immune response. By analyzing their regulation and impact on target genes, novel therapeutic and diagnostic approaches may be developed. Here, we examine the role of microRNAs in human dendritic cells during fungal infection. Dendritic cells represent the bridge between the innate and the adaptive immune systems. Therefore, analysis of gene regulation of dendritic cells is of particular significance. By applying next-generation sequencing of small RNAs, we quantify microRNA expression in monocyte-derived dendritic cells after 6 and 12 h of infection with C. albicans and A. fumigatus as well as treatment with lipopolysaccharides (LPS). We identified 26 microRNAs that are differentially regulated after infection by the fungi or LPS. Three and five of them are specific for fungal infections after 6 and 12 h, respectively. We further validated interactions of miR-132-5p and miR-212-5p with immunological relevant target genes, such as FKBP1B, KLF4, and SPN, on both RNA and protein level. Our results indicate that these microRNAs fine-tune the expression of immune-related target genes during fungal infection. Beyond that, we identified previously undiscovered microRNAs. We validated three novel microRNAs via qRT-PCR. A comparison with known microRNAs revealed possible relations with the miR-378 family and miR-1260a/b for two of them, while the third one features a unique sequence with no resemblance to known microRNAs. In summary, this study analyzes the effect of known microRNAs in dendritic cells during fungal infections and proposes novel microRNAs that could be experimentally verified.

Authors: Andreas Dix, K. Czakai, I. Leonhardt, K. Schaferhoff, M. Bonin, Reinhard Guthke, Hermann Einsele, Oliver Kurzai, Jürgen Löffler, Jörg Linde

Date Published: 11th Mar 2017

Journal: Front Microbiol

Smelling the difference: Transcriptome, proteome and volatilome changes after mating
FungiNet A - Aspergillus projects, INF

Abstract (Expand)

Mushrooms, such as Schizophyllum commune, have a specific odor. Whether this is linked to mating, prerequisite for mushroom formation, or also found in monokaryotic, unmated strains, was investigated … with a comprehensive study on the transcriptome and proteome of this model organism. Mating interactions were investigated using a complete, cytosolic proteome map for unmated, monokaryotic, as well as for mated, dikaryotic mycelia. The regulations of the proteome were compared to transcriptional changes upon mating and to changes in smell by volatilome studies. We could show a good overlap between proteome and transcriptome data, but extensive posttranslational regulation was identified for more than 80% of transcripts. This suggests down-stream regulation upon interaction of mating partners and formation of the dikaryon that is competent to form fruiting bodies. The volatilome was shown to respond to mating by a broader spectrum of volatiles and increased emission of the mushroom smell molecules 3-octanone and 1-octen-3-ol, as well as ethanol and beta-bisabolol in the dikaryon. Putatively involved biosynthetic proteins like alcohol dehydrogenases, Ppo-like oxygenases, or sesquiterpene synthases showed correlating transcriptional regulation depending on either mono- or dikaryotic stages.

Authors: D. Freihorst, M. Brunsch, S. Wirth, K. Krause, Olaf Kniemeyer, Jörg Linde, M. Kunert, W. Boland, E. Kothe

Date Published: 7th Sep 2016

Journal: Fungal Genet Biol

Kruppel-like Factor 4 modulates interleukin-6 release in human dendritic cells after in vitro stimulation with Aspergillus fumigatus and Candida albicans
FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF

Abstract (Expand)

Invasive fungal infections are associated with high mortality rates and are mostly caused by the opportunistic fungi Aspergillus fumigatus and Candida albicans. Immune responses against these fungi are … still not fully understood. Dendritic cells (DCs) are crucial players in initiating innate and adaptive immune responses against fungal infections. The immunomodulatory effects of fungi were compared to the bacterial stimulus LPS to determine key players in the immune response to fungal infections. A genome wide study of the gene regulation of human monocyte-derived dendritic cells (DCs) confronted with A. fumigatus, C. albicans or LPS was performed and Kruppel-like factor 4 (KLF4) was identified as the only transcription factor that was down-regulated in DCs by both fungi but induced by stimulation with LPS. Downstream analysis demonstrated the influence of KLF4 on the interleukine-6 expression in human DCs. Furthermore, KLF4 regulation was shown to be dependent on pattern recognition receptor ligation. Therefore KLF4 was identified as a controlling element in the IL-6 immune response with a unique expression pattern comparing fungal and LPS stimulation.

Authors: K. Czakai, I. Leonhardt, Andreas Dix, M. Bonin, Jörg Linde, Hermann Einsele, Oliver Kurzai, Jürgen Löffler

Date Published: 28th Jun 2016

Journal: Sci Rep

Use of systems biology to decipher host microbial interactions and predict pathological consequences
FungiNet B - Bioinformatics projects, INF, B3 (E)

Abstract (Expand)

In systems biology, researchers aim to understand complex biological systems as a whole, which is often achieved by mathematical modelling and the analyses of high-throughput data. In this review, we … give an overview of medical applications of systems biology approaches with special focus on host-pathogen interactions. After introducing general ideas of systems biology, we focus on (1) the detection of putative biomarkers for improved diagnosis and support of therapeutic decisions; (2) network modelling for the identification of regulatory interactions between cellular molecules to reveal putative drug targets; (3) module discovery for the detection of phenotype-specific modules in molecular interaction networks. Biomarker detection applies supervised machine learning methods utilising high-throughput data (e.g. SNP detection, RNA-seq, proteomics) and clinical data. We demonstrate structural analysis of molecular networks, especially by identification of disease modules as novel strategy, and discuss possible applications to host-pathogen interactions. Pioneering work was done to predict molecular host-pathogen interactions networks based on dual RNA-seq data. However, currently this network modelling is restricted to a small number of genes. With increasing number and quality of databases and data repositories, also the prediction of large-scale networks will be feasible that can used for multi-dimensional diagnosis and decision support for prevention and therapy of diseases. Finally, we outline further perspective issues such as support of personalised medicine with high-throughput data and generation of multi-scale host-pathogen interaction models.

Authors: Andreas Dix, S. Vlaic, Reinhard Guthke, Jörg Linde

Date Published: 27th Apr 2016

Journal: Clin Microbiol Infect

Data-based Reconstruction of Gene Regulatory Networks of Fungal Pathogens
FungiNet B - Bioinformatics projects, INF, B3 (E)

Abstract (Expand)

In the emerging field of systems biology of fungal infection, one of the central roles belongs to the modeling of gene regulatory networks (GRNs). Utilizing omics-data, GRNs can be predicted by … mathematical modeling. Here, we review current advances of data-based reconstruction of both small-scale and large-scale GRNs for human pathogenic fungi. The advantage of large-scale genome-wide modeling is the possibility to predict central (hub) genes and thereby indicate potential biomarkers and drug targets. In contrast, small-scale GRN models provide hypotheses on the mode of gene regulatory interactions, which have to be validated experimentally. Due to the lack of sufficient quantity and quality of both experimental data and prior knowledge about regulator-target gene relations, the genome-wide modeling still remains problematic for fungal pathogens. While a first genome-wide GRN model has already been published for Candida albicans, the feasibility of such modeling for Aspergillus fumigatus is evaluated in the present article. Based on this evaluation, opinions are drawn on future directions of GRN modeling of fungal pathogens. The crucial point of genome-wide GRN modeling is the experimental evidence, both used for inferring the networks (omics 'first-hand' data as well as literature data used as prior knowledge) and for validation and evaluation of the inferred network models.

Authors: Reinhard Guthke, S. Gerber, Theresia Conrad, S. Vlaic, S. Durmus, T. Cakir, F. E. Sevilgen, Ekaterina Shelest, Jörg Linde

Date Published: 22nd Apr 2016

Journal: Front Microbiol

How to Predict Molecular Interactions between Species
FungiNet B - Bioinformatics projects, INF

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: Sylvie Schulze, J. Schleicher, Reinhard Guthke, Jörg Linde

Date Published: 31st Mar 2016

Journal: Front Microbiol

Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis
FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, INF, B3 (E)

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: Andreas Dix, K. Czakai, J. Springer, M. Fliesser, M. Bonin, Reinhard Guthke, A. L. Schmitt, Hermann Einsele, Jörg Linde, Jürgen Löffler

Date Published: 21st Mar 2016

Journal: Front Microbiol

Draft Genome Sequences of Fungus Aspergillus calidoustus
INF

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, Jörg Linde, D. J. Mattern, G. Walther, Reinhard Guthke, K. Scherlach, K. Martin, Axel Brakhage, L. Petzke, Vito Valiante

Date Published: 12th Mar 2016

Journal: Genome Announc

Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions
FungiNet B - Bioinformatics projects, INF, B3 (E)

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, Theresia Conrad, M. Gustafsson, G. Cedersund, Reinhard Guthke, Jörg Linde

Date Published: 10th Feb 2016

Journal: Brief Funct Genomics

Editorial: Computational Systems Biology of Pathogen-Host Interactions
FungiNet B - Bioinformatics projects, INF, B3 (E)

Abstract

Not specified

Authors: S. Durmus, T. Cakir, Reinhard Guthke

Date Published: 4th Feb 2016

Journal: Front Microbiol

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

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, Sylvie Schulze, Daniela Albrecht-Eckardt, J. Piegsa, M. Weber, R. Martin, Kerstin Hünniger, Jörg Linde, Reinhard Guthke, Oliver Kurzai

Date Published: 12th Jan 2016

Journal: Cell Microbiol

Network Modeling Reveals Cross Talk of MAP Kinases during Adaptation to Caspofungin Stress in Aspergillus fumigatus
FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, INF

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, Reinhard Guthke, O. Kniemeyer, Axel Brakhage, Jörg Linde, V. Valiante

Date Published: 10th Sep 2015

Journal: PLoS One

Biomarker-based classification of bacterial and fungal whole-blood infections in a genome-wide expression study
FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF

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: Andreas Dix, Kerstin Hünniger, M. Weber, Reinhard Guthke, Oliver Kurzai, Jörg Linde

Date Published: 11th Mar 2015

Journal: Front Microbiol

Data- and knowledge-based modeling of gene regulatory networks: an update
FungiNet B - Bioinformatics projects, INF, B3 (E)

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: Jörg Linde, Sylvie Schulze, S. G. Henkel, Reinhard Guthke

Date Published: 2nd Mar 2015

Journal: EXCLI J

Computational prediction of molecular pathogen-host interactions based on dual transcriptome data
FungiNet B - Bioinformatics projects, INF

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

Journal: Front Microbiol

Draft Genome Sequence and Gene Annotation of the Entomopathogenic Fungus Verticillium hemipterigenum
FungiNet A - Aspergillus projects, INF

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, Axel Brakhage, Reinhard Guthke, C. Hertweck, Jörg Linde

Date Published: 24th Jan 2015

Journal: Genome Announc

Defining the transcriptomic landscape of Candida glabrata by RNA-Seq
FungiNet C - Candida projects, INF

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: Jörg Linde, S. Duggan, M. Weber, F. Horn, Patricia Sieber, D. Hellwig, Konstantin Riege, Manja Marz, R. Martin, Reinhard Guthke, Oliver Kurzai

Date Published: 13th Jan 2015

Journal: Nucleic Acids Res

Microevolution of Candida albicans in macrophages restores filamentation in a nonfilamentous mutant
FungiNet C - Candida projects, INF

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, Jörg Linde, R. Martin, M. Schreiner, F. Horn, Ilse Jacobsen, S. Jenull, Thomas Wolf, K. Kuchler, Reinhard Guthke, Oliver Kurzai, A. Forche, C. d'Enfert, S. Brunke, Bernhard Hube

Date Published: 4th Dec 2014

Journal: PLoS Genet

Draft Genome Sequence of Streptomyces iranensis
FungiNet A - Aspergillus projects, INF

Abstract (Expand)

Streptomyces iranensis HM 35 has been shown to exhibit 72.7% DNA-DNA similarity to the important drug rapamycin (sirolimus)-producing Streptomyces rapamycinicus NRRL5491. Here, we report the genome … sequence of HM 35, which represents a partially overlapping repertoire of secondary metabolite gene clusters with S. rapamycinicus, including the gene cluster for rapamycin biosynthesis.

Authors: F. Horn, V. Schroeckh, T. Netzker, Reinhard Guthke, Axel Brakhage, Jörg Linde

Date Published: 19th Jul 2014

Journal: Genome Announc

The novel globin protein fungoglobin is involved in low oxygen adaptation of Aspergillus fumigatus
FungiNet A - Aspergillus projects, INF, Z2

Abstract (Expand)

The human pathogenic fungus Aspergillus fumigatus normally lives as a soil saprophyte. Its environment includes poorly oxygenated substrates that also occur during tissue invasive growth of the fungus … in the human host. Up to now, few cellular factors have been identified that allow the fungus to efficiently adapt its energy metabolism to hypoxia. Here, we cultivated A. fumigatus in an O2 -controlled fermenter and analysed its responses to O2 limitation on a minute timescale. Transcriptome sequencing revealed several genes displaying a rapid and highly dynamic regulation. One of these genes was analysed in detail and found to encode fungoglobin, a previously uncharacterized member of the sensor globin protein family widely conserved in filamentous fungi. Besides low O2 , iron limitation also induced transcription, but regulation was not entirely dependent on the two major transcription factors involved in adaptation to iron starvation and hypoxia, HapX and SrbA respectively. The protein was identified as a functional haemoglobin, as binding of this cofactor was detected for the recombinant protein. Gene deletion in A. fumigatus confirmed that haem-binding fungoglobins are important for growth in microaerobic environments with O2 levels far lower than in hypoxic human tissue.

Authors: F. Hillmann, Jörg Linde, N. Beckmann, M. Cyrulies, M. Strassburger, T. Heinekamp, H. Haas, Reinhard Guthke, Olaf Kniemeyer, Axel Brakhage

Date Published: 7th Jul 2014

Journal: Mol Microbiol

Regulatory networks controlling nitrogen sensing and uptake in Candida albicans
FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF

Abstract (Expand)

Nitrogen is one of the key nutrients for microbial growth. During infection, pathogenic fungi like C. albicans need to acquire nitrogen from a broad range of different and changing sources inside the … host. Detecting the available nitrogen sources and adjusting the expression of genes for their uptake and degradation is therefore crucial for survival and growth as well as for establishing an infection. Here, we analyzed the transcriptional response of C. albicans to nitrogen starvation and feeding with the infection-relevant nitrogen sources arginine and bovine serum albumin (BSA), representing amino acids and proteins, respectively. The response to nitrogen starvation was marked by an immediate repression of protein synthesis and an up-regulation of general amino acid permeases, as well as an up-regulation of autophagal processes in its later stages. Feeding with arginine led to a fast reduction in expression of general permeases for amino acids and to resumption of protein synthesis. The response to BSA feeding was generally slower, and was additionally characterized by an up-regulation of oligopeptide transporter genes. From time-series data, we inferred network interaction models for genes relevant in nitrogen detection and uptake. Each individual network was found to be largely specific for the experimental condition (starvation or feeding with arginine or BSA). In addition, we detected several novel connections between regulator and effector genes, with putative roles in nitrogen uptake. We conclude that C. albicans adopts a particular nitrogen response network, defined by sets of specific gene-gene connections for each environmental condition. All together, they form a grid of possible gene regulatory networks, increasing the transcriptional flexibility of C. albicans.

Authors: S. Ramachandra, Jörg Linde, Matthias Brock, Reinhard Guthke, Bernhard Hube, S. Brunke

Date Published: 20th Mar 2014

Journal: PLoS One

An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells
FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF

Abstract (Expand)

The ability to adapt to diverse micro-environmental challenges encountered within a host is of pivotal importance to the opportunistic fungal pathogen Candida albicans. We have quantified C. albicans … and M. musculus gene expression dynamics during phagocytosis by dendritic cells in a genome-wide, time-resolved analysis using simultaneous RNA-seq. A robust network inference map was generated from this dataset using NetGenerator, predicting novel interactions between the host and the pathogen. We experimentally verified predicted interdependent sub-networks comprising Hap3 in C. albicans, and Ptx3 and Mta2 in M. musculus. Remarkably, binding of recombinant Ptx3 to the C. albicans cell wall was found to regulate the expression of fungal Hap3 target genes as predicted by the network inference model. Pre-incubation of C. albicans with recombinant Ptx3 significantly altered the expression of Mta2 target cytokines such as IL-2 and IL-4 in a Hap3-dependent manner, further suggesting a role for Mta2 in host-pathogen interplay as predicted in the network inference model. We propose an integrated model for the functionality of these sub-networks during fungal invasion of immune cells, according to which binding of Ptx3 to the C. albicans cell wall induces remodeling via fungal Hap3 target genes, thereby altering the immune response to the pathogen. We show the applicability of network inference to predict interactions between host-pathogen pairs, demonstrating the usefulness of this systems biology approach to decipher mechanisms of microbial pathogenesis.

Authors: L. Tierney, Jörg Linde, S. Muller, S. Brunke, J. C. Molina, Bernhard Hube, U. Schock, Reinhard Guthke, K. Kuchler

Date Published: 12th Mar 2012

Journal: Front Microbiol

FungiFun: a web-based application for functional categorization of fungal genes and proteins
INF

Abstract (Expand)

FungiFun assigns functional annotations to fungal genes or proteins and performs gene set enrichment analysis. Based on three different classification methods (FunCat, GO and KEGG), FungiFun categorizes … genes and proteins for several fungal species on different levels of annotation detail. It is web-based and accessible to users without any programming skills. FungiFun is the first tool offering gene set enrichment analysis including the FunCat categorization. Two biological datasets for Aspergillus fumigatus and Candida albicans were analyzed using FungiFun, providing an overview of the usage and functions of the tool. FungiFun is freely accessible at https://www.omnifung.hki-jena.de/FungiFun/.

Authors: S. Priebe, Jörg Linde, D. Albrecht, Reinhard Guthke, A. A. Brakhage

Date Published: 10th Nov 2010

Journal: Fungal Genet Biol

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