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Thomas Dandekar

About Thomas Dandekar:

Name
Prof. Dr. Thomas Dandekar
Position Professor and Chairman
Affiliation
Dept. of bioinformatics,
Biocenter
University of Würzburg
Am Hubland
97074 Würzburg
Phone 0931-318-4551
dandekar@biozentrum.uni-wuerzburg.de
Born 23.07.1960


Career 1979-1986 Studies in medicine at the Ludwig Maximilians University of Munich
1982-1986 MD, Max Planck Inst. of Psychiatry, Dept. Neuropharmacology, Martinsried
1987-1988 Post-Doc, Institute Pasteur, Paris
1988- now Scientist at the European Molecular Biology Laboratory Heidelberg;
1994 Habilitation for Biochemistry, Univ. Heidelberg
2000-2001 Reader (AR) for bioinformatics, Medical School Freiburg
since 2001 Professor (C4) and Chair, Department of bioinformatics, University of Würzburg


Research Fields Bioinformatics: regulatory and metabolic cellular networks, protein function and structure, regulation in RNA and DNA; experimental verification, often in collaborations.


Professional Activities University: Since 2002 board member Theodor Boveri Institute; Vice-speaker (03-05) and Speaker (05-07) of the biocenter; vice-dean (07-09; 11-13); Dean (09- Sept. 11) of the faculty of biology
German Research Foundation (DFG): Since 2004 Member of Review Board for Bioinformatics; Reviewer for Leibniz Association, for Humboldt Foundation; for bioinformatics and molecular journals, Reviewer for Search Committees at universities (German/ Foreign) and for MPI

Assoc. Editor for BMC Bioinf.; Bioinf. Biol. Insights; Chemtracts; Am. J. of Molecular and Cellular Biology

SEEK ID: https://funginet.hki-jena.de/people/19

Location:  Germany

Expertise: Biochemistry, Integrative Data Analysis, Systems Biology, Host-Pathogen Interaction, Mathematical Modelling, Bioinformatics, Gene Regulatory Network Inference, Metabolic networks

Tools: bioinformatics protein and RNA structure analysis, Systems biological modelling

ORCID: Not specified

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Related items

Julius Maximilians University Würzburg, Biocenter, Department of Bioinformatics

Country:  Germany

City: 97074 Würzburg

Web page: Not specified

Aspergillus fumigatus versus Genus Aspergillus: Conservation, adaptive evolution and specific virulence genes
B1

This repository contains the data of the study "Aspergillus fumigatus versus Genus Aspergillus: Conservation, adaptive evolution and specific virulence genes"

Snapshots: No snapshots

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Genome-wide inference of the Camponotus floridanus protein-protein interaction network using homologous mapping and interacting domain profile pairs.
B1

Abstract (Expand)

Apart from some model organisms, the interactome of most organisms is largely unidentified. High-throughput experimental techniques to determine protein-protein interactions (PPIs) are resource intensive … and highly susceptible to noise. Computational methods of PPI determination can accelerate biological discovery by identifying the most promising interacting pairs of proteins and by assessing the reliability of identified PPIs. Here we present a first in-depth study describing a global view of the ant Camponotus floridanus interactome. Although several ant genomes have been sequenced in the last eight years, studies exploring and investigating PPIs in ants are lacking. Our study attempts to fill this gap and the presented interactome will also serve as a template for determining PPIs in other ants in future. Our C. floridanus interactome covers 51,866 non-redundant PPIs among 6,274 proteins, including 20,544 interactions supported by domain-domain interactions (DDIs), 13,640 interactions supported by DDIs and subcellular localization, and 10,834 high confidence interactions mediated by 3,289 proteins. These interactions involve and cover 30.6% of the entire C. floridanus proteome.

Authors: Shishir K Gupta, Mugdha Srivastava, O. Osmanoglu, Thomas Dandekar

Date Published: 11th Feb 2020

Journal: Sci Rep

Aspergillus fumigatus Challenged by Human Dendritic Cells: Metabolic and Regulatory Pathway Responses Testify a Tight Battle.
B1

Abstract (Expand)

Dendritic cells (DCs) are antigen presenting cells which serve as a passage between the innate and the acquired immunity. Aspergillosis is a major lethal condition in immunocompromised patients caused … by the adaptable saprophytic fungus Aspergillus fumigatus. The healthy human immune system is capable to ward off A. fumigatus infections however immune-deficient patients are highly vulnerable to invasive aspergillosis. A. fumigatus can persist during infection due to its ability to survive the immune response of human DCs. Therefore, the study of the metabolism specific to the context of infection may allow us to gain insight into the adaptation strategies of both the pathogen and the immune cells. We established a metabolic model of A. fumigatus central metabolism during infection of DCs and calculated the metabolic pathway (elementary modes; EMs). Transcriptome data were used to identify pathways activated when A. fumigatus is challenged with DCs. In particular, amino acid metabolic pathways, alternative carbon metabolic pathways and stress regulating enzymes were found to be active. Metabolic flux modeling identified further active enzymes such as alcohol dehydrogenase, inositol oxygenase and GTP cyclohydrolase participating in different stress responses in A. fumigatus. These were further validated by qRT-PCR from RNA extracted under these different conditions. For DCs, we outlined the activation of metabolic pathways in response to the confrontation with A. fumigatus. We found the fatty acid metabolism plays a crucial role, along with other metabolic changes. The gene expression data and their analysis illuminate additional regulatory pathways activated in the DCs apart from interleukin regulation. In particular, Toll-like receptor signaling, NOD-like receptor signaling and RIG-I-like receptor signaling were active pathways. Moreover, we identified subnetworks and several novel key regulators such as UBC, EGFR, and CUL3 of DCs to be activated in response to A. fumigatus. In conclusion, we analyze the metabolic and regulatory responses of A. fumigatus and DCs when confronted with each other.

Authors: Mugdha Srivastava, E. Bencurova, Shishir K Gupta, Esther Weiß, Jürgen Löffler, Thomas Dandekar

Date Published: 14th Jun 2019

Journal: Front Cell Infect Microbiol

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.
B1, B2

Abstract (Expand)

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping … the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage-Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage-C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells.

Authors: Sybille Dühring, Jan Ewald, S. Germerodt, C. Kaleta, Thomas Dandekar, Stefan Schuster

Date Published: 14th Jul 2017

Journal: J R Soc Interface

Optimality principles reveal a complex interplay of intermediate toxicity and kinetic efficiency in the regulation of prokaryotic metabolism.
B2

Abstract (Expand)

A precise and rapid adjustment of fluxes through metabolic pathways is crucial for organisms to prevail in changing environmental conditions. Based on this reasoning, many guiding principles that govern … the evolution of metabolic networks and their regulation have been uncovered. To this end, methods from dynamic optimization are ideally suited since they allow to uncover optimality principles behind the regulation of metabolic networks. We used dynamic optimization to investigate the influence of toxic intermediates in connection with the efficiency of enzymes on the regulation of a linear metabolic pathway. Our results predict that transcriptional regulation favors the control of highly efficient enzymes with less toxic upstream intermediates to reduce accumulation of toxic downstream intermediates. We show that the derived optimality principles hold by the analysis of the interplay between intermediate toxicity and pathway regulation in the metabolic pathways of over 5000 sequenced prokaryotes. Moreover, using the lipopolysaccharide biosynthesis in Escherichia coli as an example, we show how knowledge about the relation of regulation, kinetic efficiency and intermediate toxicity can be used to identify drug targets, which control endogenous toxic metabolites and prevent microbial growth. Beyond prokaryotes, we discuss the potential of our findings for the development of antifungal drugs.

Authors: Jan Ewald, M. Bartl, Thomas Dandekar, Christoph Kaleta

Date Published: 18th Feb 2017

Journal: PLoS Comput Biol

Integrated inference and evaluation of host-fungi interaction networks
FungiNet B - Bioinformatics projects

Abstract (Expand)

Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most … important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host-pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host-fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen-host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi-human and fungi-mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host-fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host-fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host-fungi transcriptome and proteome data.

Authors: Christian Remmele, C. H. Luther, J. Balkenhol, Thomas Dandekar, Tobias Müller, Marcus Dittrich

Date Published: 4th Aug 2015

Journal: Front Microbiol

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