Reinhard Guthke

Overview
Related items

About Reinhard Guthke:

Bioprocess data analysis (data mining) Transcriptomics and proteomics data analysis and modelling Gene Regulatory Network inference (Reverse engineering) Decision making support systems in diagnostics, therapy and biotechnology

SEEK ID: https://funginet.hki-jena.de/people/2

Location: Germany

ORCID: Not specified

Joined: 28th Sep 2012

Expertise: Integrative Data Analysis, Mathematical Modelling, Gene Regulatory Network Inference

Tools: ODE, Matlab, R

Their tags

Candida albicans database Integrative Data Analysis Metadata modelling Regulatory Network regulatory network inference RNA-seq

Related items

Advanced Programmes list for this Person with search and filtering

Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

The yeast Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of life-threatening invasive mycoses in Europe. Despite the increasing incidence of these infections, the current diagnosis is still difficult and often too late, and options for therapies are limited. Moreover, A. fumigatus and C. albicans have developed multiple sophisticated, specific and unique pathogenicity mechanisms. Many of these mechanisms are not well understood. Research on ...

Projects: FungiNet total, FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF, A1, A2, A3, A4 (E), A5, B1, B2, B3 (E), B4, C1, C2, C3, C4 (E), C5, C6 (E), Z2, Z1, B5, A6, A7, A8, C7

Web page: http://www.funginet.de/home.html

Showing 5 out of a possible 6 Projects Advanced Projects list for this Person with search and filtering

FungiNet total: inactive since 2018-06-04

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/home.html

Organisms: Aspergillus fumigatus, Candida albicans

FungiNet C - Candida projects: inactive since 2018-06-12

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-c.html

Organisms: Candida albicans

C5: inactive since 2018-06-12

Gastrointestinal colonisation and mechanisms of translocation of Candida albicans through gut mucosa

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-c5.html

Organisms: Candida albicans

B3 (E): inactive since 2018-06-07

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

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-b3.html

Organisms: Aspergillus fumigatus, Candida albicans

FungiNet A - Aspergillus projects: inactive since 2018-06-04

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-a.html

Organisms: Aspergillus fumigatus

View all 6 Projects

Advanced Institutions list for this Person with search and filtering

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

Country: Germany

City: 07745 Jena

Web page: http://www.hki-jena.de

Advanced Investigations list for this Person with search and filtering

4 hidden items

Advanced Studies list for this Person with search and filtering

4 hidden items

Advanced Assays list for this Person with search and filtering

5 hidden items

Advanced Data files list for this Person with search and filtering

Annual Meeting CRC/TR 124 FungiNet - 2014 - Program

FungiNet total

No description specified

Creator: Reinhard Guthke

Submitter: Reinhard Guthke

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Download

Created: 4th Mar 2016 at 12:45, Last updated: 7th Jun 2018 at 15:41

DMykG_2015 Programmheft

FungiNet total, FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF, Z2

No description specified

Creator: Reinhard Guthke

Submitter: Reinhard Guthke

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Download

Created: 4th Mar 2016 at 16:00, Last updated: 7th Jun 2018 at 15:41

DMykG 2015 Programmheft

FungiNet total, FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF, Z2

No description specified

Creator: Reinhard Guthke

Submitter: Reinhard Guthke

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Download

Created: 4th Mar 2016 at 16:02, Last updated: 7th Jun 2018 at 15:41

2 hidden items

Advanced Models list for this Person with search and filtering

[DEMO] Response of hepatocytes to rapid change in the medium composition (gene regulatory network): Model 1100 "freshMedia"

FungiNet total, FungiNet B - Bioinformatics projects

(Show All)

Primary hepatocytes were exposed to a stimulus by exchanging culture medium, thereby simulating changes in the blood composition. The expression of genes at different time points was recorded. Differentially expressed genes were clustered using fuzzy c-means algorithm into five groups. The arcs of the possible network were identified using the NetGenerator algorithm under the restriction of biological knowledge. The analysis was restricted to the main metabolic pathways of hepatocytes. The reverse ...

Creators: Thomas Wolf, Wolfgang Schmidt-Heck, Reinhard Guthke

Submitter: Thomas Wolf

Model type: Ordinary differential equations (ODE)

Model format: SBML

Environment: JWS Online

Organism: Not specified

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Download

Created: 6th Jun 2017 at 07:38, Last updated: 27th Feb 2018 at 13:25

6 hidden items

Advanced SOPs list for this Person with search and filtering

SOP Processing of RNA-Seq Data

FungiNet B - Bioinformatics projects

RNA-Seq is a method to measure the transcript/gene expression by adaption of High-throughput sequencing technologies. In contrast to microarrays where the measurement is based on a hybridization process, RNA-Seq sequences cDNA in order to get information about a sample's RNA content.

Creators: Reinhard Guthke, Jörg Linde, Steffen Priebe

Submitters: Reinhard Guthke, Sascha Schäuble

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Download

Created: 30th Oct 2012 at 16:44, Last updated: 17th Feb 2021 at 14:18

3 hidden items

Showing 5 out of a possible 32 Publications Advanced Publications list for this Person with search and filtering

Survival Strategies of Pathogenic Candida Species in Human Blood Show Independent and Specific Adaptations.

INF, B3 (E), C1, C3

(Show All)

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, T. Wolf, T. Conrad, S. Allert, F. Gerwien, K. Hunniger, O. Kurzai, R. Guthke, B. Hube, J. Linde, S. Brunke

Date Published: 6th Oct 2020

Publication Type: Not specified

PubMed ID: 33024045

Citation: mBio. 2020 Oct 6;11(5). pii: mBio.02435-20. doi: 10.1128/mBio.02435-20.

Created: 11th Feb 2021 at 08:45, Last updated: 17th Jan 2024 at 10:24

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

INF, A1, C5

(Show All)

Abstract (Expand)

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

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

Date Published: 20th Oct 2018

Publication Type: Not specified

PubMed ID: 30342519

Citation: BMC Syst Biol. 2018 Oct 20;12(1):88. doi: 10.1186/s12918-018-0620-8.

Created: 11th Feb 2021 at 09:27, Last updated: 17th Jan 2024 at 10:24

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

INF, B1

(Show All)

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. …

Authors: S. Vlaic, T. Conrad, C. Tokarski-Schnelle, M. Gustafsson, U. Dahmen, R. Guthke, S. Schuster

Date Published: 11th Jan 2018

Publication Type: Not specified

PubMed ID: 29323246

Citation: Sci Rep. 2018 Jan 11;8(1):433. doi: 10.1038/s41598-017-18370-2.

Created: 11th Feb 2021 at 09:20, Last updated: 17th Jan 2024 at 10:24

Specific and Novel microRNAs Are Regulated as Response to Fungal Infection in Human Dendritic Cells.

INF, A2, B3 (E), C3

(Show All)

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 …

Authors: A. Dix, K. Czakai, I. Leonhardt, K. Schaferhoff, M. Bonin, R. Guthke, H. Einsele, O. Kurzai, J. Loffler, J. Linde

Date Published: 11th Mar 2017

Publication Type: Not specified

PubMed ID: 28280489

Citation: Front Microbiol. 2017 Feb 23;8:270. doi: 10.3389/fmicb.2017.00270. eCollection 2017.

Created: 11th Feb 2021 at 09:34, Last updated: 17th Jan 2024 at 10:24

Use of systems biology to decipher host microbial interactions and predict pathological consequences

FungiNet B - Bioinformatics projects, INF, B3 (E)

(Show All)

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 …

Authors: , S. Vlaic, ,

Date Published: 27th Apr 2016

Publication Type: Not specified

PubMed ID: 27113568

Citation:

Created: 10th May 2016 at 08:23, Last updated: 17th Jan 2024 at 10:24

View all 32 Publications

Advanced Presentations list for this Person with search and filtering

27 hidden items

Advanced Events list for this Person with search and filtering