Project B3 (E)

Predictive modeling of host-fungal pathogen interactions by reconstruction of gene regulatory networks

Project Description

Systems biology of fungal infection aims at understanding the interaction of the host, in particular the immune system, with components of the fungal pathogens by analysing two interacting networks. Consequently, it is feasible to computationally depict the main interactions of cells and molecules and to draw conclusions for diagnostics and personalised therapy. Within this project, gene regulatory network models will be reconstructed (inferred) with top down approaches based on the analysis of high-throughput data integrating prior knowledge. The network inference is hypothesis-free at the beginning, which is a prerequisite to avoid missing any components or trends by initial filtering and/or biased analysis of large-scale data-sets available from the partners of the CRC/Transregio. We will mainly focus on the transcriptional regulatory networks, which allow a straightforward incorporation of gene expression data together with promoter sequence information. As a result, a set of potential target genes can be predicted, which presumably are responsible for the interaction of the fungal pathogens with the host. This information, in turn, can be used as a starting point for the investigation of the host’s response against the attack of the pathogen. Several iterations of such a molecular interplay can be observed and interpreted through expression data obtained on the side of both the pathogen and the host. The experimental data to be analysed, i.e., transcriptome and other genome-wide data as well as microbial, biochemical and clinical data, will be generated by the members of the CRC/Transregio and also received from public databases. Prior knowledge will be semi-automatically extracted from databases and literature repositories. The resulting gene regulatory network analysis, i.e., analysis of the modular structure and network motifs, will support both diagnosis and therapy of fungal infections. Common and distinctive traits on both the transcriptome and the proteome level of the pathogens Aspergillus fumigatus und Candida albicans with respect to their interaction with the (human) host will be identified from the large-scale data by comparative gene regulatory network analysis.

In the analysis, we will not only include proteins and protein-coding genes but also non-coding RNAs (ncRNAs). In order to determine functions of ncRNAs in fungus-host interaction networks, we will investigate up- and down-regulation of ncRNAs in wild-type and mutant strains of A. fumigatus and C. albicans during infection. We plan to analyse and predict the influence of the fungus-host interaction on the secondary structure of ncRNAs by focussing on posttranscriptional modifications and splicing products with the aim to elucidate the functions of these ncRNAs and their possible use as diagnostic markers.

Host-pathogen interaction at the level of interacting gene regulatory networks
Host-pathogen interaction at the level of interacting gene regulatory networks

Principal Investigators

Prof. Dr. Reinhard Guthke
Prof. Dr. Reinhard Guthke

Research Group Systems Biology and Bioinformatics

Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute

Prof. Dr. Manja Marz
Prof. Dr. Manja Marz

Faculty of Mathematics and Computer Science  Bioinformatics/High Throughput Analysis

Friedrich Schiller University Jena

Dr. Ekaterina Shelest
Dr. Ekaterina Shelest

Research group Systems Biology and Bioinformatics 

Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute – (HKI)


Author Year Title Journal Links
Schulze S, Henkel SG, Driesch D, Guthke R, Linde J 2015 Computational prediction of molecular pathogen-host interactions based on dual transcriptome data. Front Microbiol 6: 65 PubMed
Dix A, Hünniger K, Weber M, Guthke R, Kurzai O, Linde J 2015 Biomarker-based classification of bacterial and fungal whole-blood infections in a genome-wide expression study. Front Microbiol 6: 171 PubMed
Linde J, Schulze S, Henkel SG, Guthke R 2015 Data- and knowledge-based modeling of gene regulatory networks: An update. EXCLI J 14: 346-78 EXCLI Journal

Linde J, Duggan S, Weber M, Horn F, Sieber P, Hellwig D, Riege K, Marz M, Martin R, Guthke R, Kurzai O 2015 Defining the transcriptomic landscape of Candida glabrata by RNA-Seq. Nucleic Acids Res 43: 1392-406 PubMed
Durmuş S, Çakır T, Özgür A, Guthke R 2015 A review on computational systems biology of pathogen-host interactions.

Front Microbiol 6: 235

Ramachandra S, Linde J, Brock M, Guthke R, Hube B, Brunke S 2014

Regulatory networks controlling nitrogen sensing and uptake in Candida albicans.

PLoS One 9: e92734 PubMed
Prauße MT, Schäuble S, Guthke R, Schuster S 2016 Computing the various pathways of penicillin synthesis and their molar yields. Biotechnol Bioeng 113: 173-81
Durmuş S, Çakır T, Guthke R 2016 Editorial: Computational systems biology of pathogen-host interactions. Front Microbiol 7: 21 PubMed
Böhringer M, Pohlers S, Schulze S, Albrecht-Eckardt D, Piegsa J, Weber M, Martin R, Hünniger K, Linde J, Guthke R, Kurzai O 2016 Candida albicans infection leads to barrier breakdown and a MAPK/NF-κB mediated stress response in the
intestinal epithelial cell line C2BBe1.
Cell Microbiol 18: 889-904 Cell Microbiol
Dix A, Czakai K, Springer J, Fliesser M, Bonin M, Guthke R, Schmitt AL, Einsele H, Linde J, Löffler J 2016 Genome-wide expression profiling reveals S100B as biomarker for invasive Aspergillosis. Front Microbiol 7: 320 PubMed
Kroll K, Shekhova E, Mattern DJ, Thywissen A, Jacobsen ID, Strassburger M, Heinekamp T, Shelest E, Brakhage AA, Kniemeyer O 2016 The hypoxia-induced dehydrogenase HorA is required for coenzyme Q10 biosynthesis, azole sensitivity and virulence of Aspergillus fumigatus.

Mol Microbiol 101: 92-108

Teutschbein J, Simon S, Lother J, Springer J, Hortschansky P, Morton CO, Löffler J, Einsele H, Conneally E, Rogers TR, Guthke R, Brakhage AA, Kniemeyer O 2016 Proteomic profiling of serological responses to Aspergillus fumigatus antigens in patients with invasive aspergillosis.

J Proteome Res 15: 1580-91

Dix A, Vlaic S, Guthke R, Linde J 2016 Use of systems biology to decipher host-microbial interaction networks and predict biomarkers. Clin Microbiol Infect 22: 600-6 PubMed
Guthke R, Gerber S, Conrad T, Vlaic S, Durmuş S, Çakır T, Sevilgen FE, Shelest E, Linde J 2016 Data-based reconstruction of gene regulatory networks of fungal pathogens. Front Microbiol 7: 570 PubMed
Schulze S, Schleicher J, Guthke R, Linde J 2016 How to predict molecular interactions between species? Front Microbiol 7: 442 PubMed
Czakai K, Leonhardt I, Dix A, Bonin M, Linde J, Einsele H, Kurzai O, Loeffler J 2016

Krüppel-like Factor 4 modulates interleukin-6 release in human dendritic cells after in vitro stimulation with Aspergillus fumigatus and Candida albicans

Sci Rep 6: 27990 PubMed
Shelest E, Wingender E 2016 Editorial: Systems biology of transcription regulation.

Front Genet 7: 124

Klassert TE, Bräuer J, Hölzer M, Stock M, Riege K, Zubiría-Barrera C, Müller MM, Rummler S, Skerka C, Marz M, Slevogt H 2017 Differential effects of Vitamins A and D on the transcriptional landscape of human monocytes during Infection. Sci Rep 7: 40599 PubMed
Riege K, Hölzer M, Klassert TE, Barth E, Bräuer J, Collatz M, Hufsky F, Mostajo N, Stock M, Vogel B, Slevogt H, Marz M 2017 Massive effect on LncRNAs in human monocytes during fungal and bacterial infections and in response to vitamins A and D. Sci Rep 7: 40598 PubMed

Dix A, Czakai K, Leonhardt I, Schäferhoff K, Bonin M, Guthke R, Einsele H, Kurzai O, Löffler J, Linde J

2017 Specific and novel microRNAs are regulated as response to fungal infection in human dendritic cells. Front Microbiol 8: 270 PubMed