Project INF

Integrated database and standardised analysis of experimental data

Project Description

The project INF aims at (i) supporting the web-based sharing and exchange of data, models and expertise (e.g., SOPs) across the FungiNet consortium, (ii) providing an integrated platform to foster the collaboration between the project partners, (iii) preparing the integrated analysis of different data by mathematical modelling within the research area B and (iv) – via modelling – to direct and support further experiments by prediction of so far unknown interrelations and model-based experimental design.

INF is concerned with all service-oriented data and all knowledge management aspects of the CRC/Transregio. INF will specify and further develop the web-based data warehouse OmniFung (www.omnifung.hki-jena.de) established at the HKI, which provides data collection, storage, pre-processing and primary analysis of genome, transcriptome and proteome data as well as other experimental data (biochemical, microbiological, clinical). INF also provides curation and integration of knowledge of biomolecular databases.

An aspect of pivotal importance is the standardisation, collection and storage of experimental datasets as well as the establishment of FungiNet-specific knowledge databases, all required for adequate computational and mathematical modelling. Data storage will be organised in a way that (i) allows exchange of data and results between the experimentally working laboratories (Research areas A and C) and (ii) makes biological data available as soon as possible for molecular network modelling by the B projects and, thus, for generation of scientific hypotheses and the next steps of experimental design. Within the A and C projects experimental data sets will be generated based on high-throughput technologies such as microarrays and Next Generation Sequencing (RNA-seq) for transcriptome analyses but also proteome data (2D gel- and MS-based) under different experimental conditions and in different quality. These massive and complex structured data have to be stored and analysed together with metadata that annotate the experimental setup.

Principal Investigator

Dr. Jörg Linde
Dr. Jörg Linde

Junior Research Group PiDOMICS 

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

joerg.linde@leibniz-hki.de

Publications

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
Priebe S, Kreisel C, Horn F, Guthke R, Linde J 2015 FungiFun2: a comprehensive online resource for systematic analysis of gene lists from fungal species. Bioinformatics 31: 445-6 PubMed
Horn F, Üzüm Z, Möbius N, Guthke R, Linde J, Hertweck C 2015 Draft genome sequences of symbiotic and nonsymbiotic Rhizopus microsporus Strains CBS 344.29 and ATCC 62417. Genome Announc 3(1) pii: e01370-14 PubMed
Horn F, Habel A, Scharf DH, Dworschak J, Brakhage AA, Guthke R, Hertweck C, Linde J 2015 Draft genome sequence and gene annotation of the entomopathogenic fungus Verticillium hemipterigenum. Genome Announc 3(1) pii: e01439-14 PubMed
Hillmann F, Linde J, Beckmann N, Cyrulies M, Strassburger M, Heinekamp T, Haas H, Guthke R, Kniemeyer O, Brakhage AA 2014 The novel globin protein fungoglobin is involved in low oxygen adaptation of Aspergillus fumigatus. Mol Microbiol 93: 539-53 PubMed
Horn F, Schroeckh V, Netzker T, Guthke R, Brakhage AA, Linde J 2014 Draft genome sequence of Streptomyces iranensis. Genome Announc 2(4) pii: e00616-14 PubMed
Linde J, Schwartze V, Binder U, Lass-Flörl C, Voigt K, Horn F 2014 De Novo whole-genome sequence and genome annotation of Lichtheimia ramosa. Genome Announc 2(5): e00888-14 PubMed
Durmuş S, Çakır T, Özgür A, Guthke R 2015 A review on computational systems biology of pathogen-host interactions.

Front Microbiol 6: 235

PubMed
Wartenberg A, Linde J, Martin R, Schreiner M, Horn F, Jacobsen ID, Jenull S, Wolf T, Kuchler K, Guthke R, Kurzai O, Forche A, d'Enfert C, Brunke S, Hube B 2014

Microevolution of Candida albicans in macrophages restores filamentation in a nonfilamentous mutant.

PLoS Genet 10: e1004824

PubMed
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

Altwasser R, Baldin C, Weber J, Guthke R, Kniemeyer O, Brakhage AA, Linde J, Valiante V

2015

Network modeling reveals cross talk of MAP kinases during adaptation to caspofungin stress in Aspergillus fumigatus.

PLoS One 10: e0136932 PubMed

Horn F, Linde J, Mattern DJ, Walther G, Guthke R, Brakhage AA, Valiante V

2015

Draft genome sequence of the fungus Penicillium brasilianum MG11.

Genome Announc 3(5) pii: e00724-15 PubMed
Schleicher J, Conrad T, Gustafsson M, Cedersund G, Guthke R, Linde J 2015 Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions. Brief Funct Genomics pii: elv064 PubMed
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
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

Horn F, Linde J, Mattern DJ, Walther G, Guthke R, Scherlach K, Martin K, Brakhage AA, Petzke L, Valiante V

2016 Draft genome sequences of fungus Aspergillus calidoustus. Genome Announc 4(2): e00102-16 PubMed
Hebecker B, Vlaic S, Conrad T, Bauer M, Brunke S, Kapitan M, Linde J, Hube B, Jacobsen ID 2016 Dual-species transcriptional profiling during systemic candidiasis reveals organ-specific host-pathogen interactions. Sci Rep 6: 36055 PubMed
Gerwien F, Safyan A, Wisgott S, Hille F, Kaemmer P, Linde J, Brunke S, Kasper L, Hube B 2016 A novel hybrid iron regulation network combines features from pathogenic and nonpathogenic yeasts.

mBio 7(5) pii: e01782-16

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
Wolf T, Kämmer P, Brunke S, Linde J 2017 Two's company: Studying interspecies relationships with dual RNA-seq.

Curr Opin Microbiol 42: 7-12

PubMed
Magnusson R, Mariotti GP, Köpsén M, Lövfors W, Gawel DR, Jörnsten R, Linde J, Nordling TEM, Nyman E, Schulze S, Nestor CE, Zhang H, Cedersund G, Benson M, Tjärnberg A, Gustafsson M 2017 LASSIM-A network inference toolbox for genome-wide mechanistic modeling. PLoS Comput Biol 13(6): e1005608 PubMed