Gene regulatory network inference in human pathogenic fungi

Pathogenic fungi are a serious threat to people with impeded immune system, especially during organ transplantation and HIV infections. As the number of treatments that include a weakening of the patients immune system increase, so does the number of fungal infections. Often, the infection is opportunistic, meaning the pathogen already lives as a commensal in the host and uses the weak immune system to spread out and starts to colonise different parts of the host. These infections can lead to systemic, life-threatening infections, lowering the survival rate of the often already weakened host. Two of the most common human pathogens are Candida albicans and Aspergillus fumigatus. While C. albicans is a commensal and part of the healthy human flora, it can turn to an opportunistic pathogen, once the hosts immune system fails to contain it. Conidia of A. fumigatus are inhaled by humans every day and removed again by the immune system. In a weakened host, A. fumigatus can colonise the lung of the host and spread to other parts of the body, which can lead to fatal results, if no treatment is administered. The first part of this thesis aims to study the gene regulatory network of C. albicans on a genome-wide level, with a scale-free distribution of node degrees. These networks can be used to identify genes with central regulatory functions, called hubs, which are possible drug targets and can be the starting point for future studies. The modeling process included a large set of gene expression data measured by microarrays, the use of prior knowledge and a automatically harvested gold standard for the evaluation of the results. The final model is used to identify several hubs and is also able to reproduce current knowledge. A focused small-scale gene regulatory network is inferred for A. fumigatus while it is treated with the clinically applied drug caspofungin. The chapter describes the process from mapping of the RNA-Seq data over the selection of candidate genes and the harvest of prior knowledge to the application of the NetGenerator tool. A network model of 26 genes is tested for robustness against noise and used to identify a so far unknown cross-talk between to key regulators of major drug response pathways in A. fumigatus, which could be experimentally verified by the collaboration partner. Both, the large- and the small-scale network inference are later compared to give guidance on the correct application depending on the scientific question. To further study the influence of drug treatment on A. fumigatus caspofungin treatment was paired with the use of humidimycin, which does not have antifungal properties on its own, but seems to enhance the effect of caspofungin. Analysis of differential expression and clustering revealed that the combination of the two drugs lowers the number of differentially expressed genes in A. fumigatus, giving hints on how the enhancing effect of humidimycin works on the genetic level.Pathogene Pilze stellen eine ernste Bedrohung für Menschen mit geschwächtem Immunsystem dar. Die betrifft insbesondere Menschen während Organtransplantationen und HIV-Infizierte. Mit der steigenden Anzahl von Behandlungen, bei denen eine Schwächung des Immunsystems einhergeht, steigt auch die Anzahl der Pilzinfektionen. Diese sind häufig opportunistisch, was bedeutet, das der Pathogen bereits als Nutznießer im Wirt lebt und ein geschwächtes Immunsystem nutzt, um sich auszubreiten. Dies kann zu systematischen, lebensbedrohenden Infektionen führen, welche die Überlebenswahrscheinlichkeit des oft bereits geschwächten Wirts weiter senkt. Zwei der am weitesten verbreiteten Pathogene sind Candida albicans und Aspergillus fumigatus. Während C. albicans gewöhnlich als Teil der gesunden menschlichen Flora lebt, ohne Schaden anzurichten, kann es sich zu einem opportunistischem Pathogen entwickeln, sobald das Immunsystem des Wirts ihn nicht mehr eindämmen kann. Sporen von A. fumigatus werden von Menschen jeden Tag eingeatmet und vom Immunsystem wieder entfernt. In einem geschwächtem Wirt kann A. fumigatus die Lunge besiedeln und sich auf andere Teile des Körpers ausbreiten. Ohne Behandlung kann dies tödliche Folgen für den Wirt haben. Der erste Teil dieser Doktorarbeit zielt auf die Untersuchung der genregulatorischen Netzwerke von C. albicans auf genomweiter Ebene ab. Dabei wurden Netzwerke mit einer skalenfreien Verteilung der Kantengrade erzeugt. Diese Netzwerke können dafür verwendet werden, Gene mit zentraler regulatorischer Funktion zu identifizieren. Diese so genannten Hubs sind mögliche Zielgene für Medikamente und können der Anfang für zukünftige Studien sein. Die Modellierung enthält die Verwendung von Vorwissen und ein automatisch gesammelter Goldstandard zu Evaluierung der Ergebnisse. Das endgültige Modell wird benutzt um verschiedene Hubs zu identifizieren und ist auch in der Lage, aktuelles Wissen wiederzugeben. Darüber hinaus wird ein fokussiertes genregulatorisches Netzwerk für A. fumigatus erstellt, während es mit dem klinischem Medikament Caspofungin behandelt wird. Hier beschrieben wird der Vorgang von der Kartierung der RNA-Seq-Daten über die Auswahl der Kandidatengene und das Sammeln von Vorwissen zu der Anwendung des NetGenerator Programms. Ein Netzwerkmodel aus 26 Genen wird bezüglich seiner Robustheit gegen Rauschen in den Daten und fehlendes Vorwissen getestet. Dabei wird eine bisher unbekannte Regulation zwischen zwei zentralen Genen gefunden, welche für die Stressantwort gegen Medikamente in A. fumigatus verantwortlich sind. Diese Regulation konnte experimentell durch Kollaborationspartner bestätigt werden. Sowohl die genomweite, als auch die fokussierte Netzwerkinfernz werden anschließend verglichen, um Hinweise für ihre korrekte Anwendung zu geben, abhängig von der biologischen Fragestellung. Um den Einfluß von Medikamenten auf A. fumigatus weiter zu untersuchen, wurde die Kombination von Caspofungin mit Humidimycin untersucht. Humidimycin besitzt selbst keine antifungielle Wirkung, scheint jedoch die Wirkung von Caspofungin zu verstärken. Eine Analyse der differentiell exprimierten Gene und Clustering zeigte, das die Kombination beider Medikamente die Anzahl der differentiell exprimierten Gene gegenüber der Einzelbehandlung mit Caspofungin verringert. Dies gibt Hinweise darauf, wie der verstärkende Effekt von Humidimycin auf Genebene funktioniert

The transcriptome landscape of the carcinogenic treatment response in the blind mole rat: insights into cancer resistance mechanisms

Abstract Background Spalax, the blind mole rat, developed an extraordinary cancer resistance during 40 million years of evolution in a subterranean, hypoxic, thus DNA damaging, habitat. In 50 years of Spalax research, no spontaneous cancer development has been observed. The mechanisms underlying this resistance are still not clarified. We investigated the genetic difference between Spalax and mice that might enable the Spalax relative resistance to cancer development. We compared Spalax and mice responses to a treatment with the carcinogen 3-Methylcholantrene, as a model to assess Spalax’ cancer-resistance. Results We compared RNA-Seq data of untreated Spalax to Spalax with a tumor and identified a high number of differentially expressed genes. We filtered these genes by their expression in tolerant Spalax that resisted the 3MCA, and in mice, and found 25 genes with a consistent expression pattern in the samples susceptible to cancer among species. Contrasting the expressed genes in Spalax with benign granulomas to those in Spalax with malignant fibrosarcomas elucidated significant differences in several pathways, mainly related to the extracellular matrix and the immune system. We found a central cluster of ECM genes that differ greatly between conditions. Further analysis of these genes revealed potential microRNA targets. We also found higher levels of gene expression of some DNA repair pathways in Spalax than in other murines, like the majority of Fanconi Anemia pathway. Conclusion The comparison of the treated with the untreated tissue revealed a regulatory complex that might give an answer how Spalax is able to restrict the tumor growth. By remodeling the extracellular matrix, the possible growth is limited, and the proliferation of cancer cells was potentially prevented. We hypothesize that this regulatory cluster plays a major role in the cancer resistance of Spalax. Furthermore, we identified 25 additional candidate genes that showed a distinct expression pattern in untreated or tolerant Spalax compared to animals that developed a developed either a benign or malignant tumor. While further study is necessary, we believe that these genes may serve as candidate markers in cancer detection

Network Modeling Reveals Cross Talk of MAP Kinases during Adaptation to Caspofungin Stress in <i>Aspergillus fumigatus</i>

<div><p>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. <i>Aspergillus fumigatus</i> 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 <i>A</i>. <i>fumigatus</i>. 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.</p></div

Depiction of the workflow.

<p>Genes were selected based on their expression steady-state levels and their assigned function. RNA-Seq data and prior-knowledge were used as inputs for the Net<i>Gene</i>rator. Using a mathematical modeling, a network was predicted, which was then evaluated and tested for robustness. A final model was selected, which led to new hypotheses that were experimentally validated.</p

FunCat-enriched categories during caspofungin stress.

<p>FunCat-enriched categories were obtained by analyzing the total number of genes differentially expressed in response to caspofungin (0.1 μg ml^-1). Enrichment analysis using selected genes having log₂ fold change > 2, and p-value <0.01. The identified FunCat IDs are shown on the x-axis. (A) FunCat-enriched categories identifiedin <i>A</i>. <i>fumigatus</i> CEA10 wild-type strains during caspofungin stress at the reported time points, and (B) a table showing all the identified categories displayed on the x-axes. Comparative analyses of selected genes in the <i>A</i>. <i>fumigatus</i> Δ<i>akuB</i>, Δ<i>sakA</i> and Δ<i>mpkA</i> mutant strains are shown. Categorization was implemented by considering differentially regulated genes identified at 3 different time points (0, 1 and 4 h after induction, for all selected mutant strains). In the picture are shown the FunCat-enriched categories uniquely identified in the Δ<i>akuB</i> (wt) strain (C), in the Δ<i>mpkA</i> strain (D), and in the Δ<i>sakA</i> strain (E). Categorization of genes differentially regulated in all strains (F), and the obtained Venn diagram (G), are also shown. Genes used for the analysis are reported in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136932#pone.0136932.s002" target="_blank">S2 Database</a>.</p

Net<i>Gene</i>rator used for modeling prediction.

<p>(A) Collected prior-knowledge interactions with activating effects. (B) Collected prior-knowledge interactions with inhibiting effects. (C) Activating and (D) inhibiting interactions of the final predicted network. The legend is shown below the figure. Input marks caspofungin induction. Information about the selected genes is reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136932#pone.0136932.t001" target="_blank">Table 1</a>.</p

Differentially expressed genes selected for modeling.

<p>Differentially expressed genes selected for modeling.</p

Effects of caspofungin on membrane efflux.

<p>Transporter-mediated efflux of rhodamine 123 was determined in absence (blue line) and presence of caspofungin (red line). The wild-type CEA10 strain was challenged with different caspofungin concentrations, while the mutant strains were analyzed using only a caspofungin sub-lethal concentration (0.1 μg ml^-1). For each sample, cytosolic content was extracted and measured (excitation/ emission 480/520 nm) at the reported time points. ± Standard error of the mean.</p

Validation of cross talk between MAPKs.

<p>A) The reported strains were tested against caspofungin (CAS) at different concentrations. The indicated number of conidia was spotted on AMM agar plates and incubated at 37°C for 48 hours. B) Results of the qRT-PCR analysis for selected genes in the Δ<i>akuB</i>, Δ<i>mpkA</i>, Δ<i>sakA</i> and Δ<i>ptcH</i> mutant strains are shown. Total RNA was extracted before (T0) and 4 h after caspofungin induction (T4). In all performed experiments, the fold changes for each gene were obtained applying the 2^-ΔΔCt method (reported in the <i>y</i> axes). Data ± SDs. Statistical significance was determined for all the experiments by a Student’s t test. Significance of differences of data with P<0.005 (*) and P<0.001 (**) is indicated. qRT-PCR data for each strain are marked in different colours, as indicated below. Empties bars indicate expression levels for untreated samples, while treated samples are speckled.</p

Effects of different caspofungin concentrations on MAPK cascades.

<p>(A) When caspofungin is used at inhibitory concentrations (1 μg ml^-1), a repression of MpkA and SakA phosphorylation levels is observed. Under these conditions, the cellular transport is stimulated and the inhibition of MpkA and SakA avoids the turn-on of compensatory pathways. (B) The use of caspofungin at higher doses strongly activates MpkA and SakA. Under these conditions, cellular transport is inhibited and cell-wall compensatory pathways are more active.</p