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B1

Overview

Modelling interactions between the host and fungal pathogens by combining metabolic pathway analysis and evolutionary game theory

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

SEEK ID: https://funginet.hki-jena.de/projects/24

Public web page: http://www.funginet.de/project-b1.html

Organisms: Aspergillus fumigatus, Candida albicans

INF PALs: No PALs for this Project

Project created: 21st Jul 2015

Related items

Johannes Balkenhol

Projects: B2, FungiNet B - Bioinformatics projects, FungiNet total, B1

Institutions: Julius Maximilians University Würzburg, Biocenter, Department of Bioinformatics

Andreas Caput

Projects: B1, FungiNet B - Bioinformatics projects, FungiNet total

Institutions: Julius Maximilians University Würzburg, Biocenter, Department of Bioinformatics

Thomas Dandekar project_administrator

Projects: FungiNet B - Bioinformatics projects, FungiNet total, B1, B2

Institutions: Julius Maximilians University Würzburg, Biocenter, Department of Bioinformatics

Wassili Dimitriew

Projects: B1, FungiNet total, FungiNet B - Bioinformatics projects

Institutions: Friedrich Schiller University Jena, Department of Bioinformatics, School for Biology and Pharmacy, Friedrich-Schiller-University

Sybille Dühring : inactive since 2020-09-01

Projects: B1, FungiNet B - Bioinformatics projects, FungiNet total

Institutions: Friedrich Schiller University Jena, Department of Bioinformatics, School for Biology and Pharmacy

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

Quality filtered amino acid sequences of 18 Aspergilli
B1
No description specified

Creator: Shishir K Gupta

Contributor: Shishir K Gupta

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Quality filtered CDS sequences of 18 Aspergilli
B1
No description specified

Creator: Shishir K Gupta

Contributor: Shishir K Gupta

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Nucleotide alignment of single copy orthologs
B1
No description specified

Creators: None

Contributor: Shishir K Gupta

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Amino acid sequences
B1
No description specified

Creators: None

Contributor: Shishir K Gupta

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Ortholog clusters
FungiNet B - Bioinformatics projects, B1

This is the result of OrthoMCL analysis.

Creator: Shishir K Gupta

Contributor: Shishir K Gupta

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Modelling population dynamics in a unicellular social organism community using a minimal model and evolutionary game theory.
B1

Abstract (Expand)

Most unicellular organisms live in communities and express different phenotypes. Many efforts have been made to study the population dynamics of such complex communities of cells, coexisting as … well-coordinated units. Minimal models based on ordinary differential equations are powerful tools that can help us understand complex phenomena. They represent an appropriate compromise between complexity and tractability; they allow a profound and comprehensive analysis, which is still easy to understand. Evolutionary game theory is another powerful tool that can help us understand the costs and benefits of the decision a particular cell of a unicellular social organism takes when faced with the challenges of the biotic and abiotic environment. This work is a binocular view at the population dynamics of such a community through the objectives of minimal modelling and evolutionary game theory. We test the behaviour of the community of a unicellular social organism at three levels of antibiotic stress. Even in the absence of the antibiotic, spikes in the fraction of resistant cells can be observed indicating the importance of bet hedging. At moderate level of antibiotic stress, we witness cyclic dynamics reminiscent of the renowned rock-paper-scissors game. At a very high level, the resistant type of strategy is the most favourable.

Authors: R. Garde, Jan Ewald, A. T. Kovacs, Stefan Schuster

Date Published: 3rd Nov 2020

Journal: Open Biol

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

Trends in mathematical modeling of host-pathogen interactions.
FungiNet total, B1

Abstract (Expand)

Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal … treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.

Authors: Jan Ewald, Patricia Sieber, R. Garde, S. N. Lang, Stefan Schuster, B. Ibrahim

Date Published: 30th Nov 2019

Journal: Cell Mol Life Sci

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

Molecular crypsis by pathogenic fungi using human factor H. A numerical model.
B1

Abstract (Expand)

Molecular mimicry is the formation of specific molecules by microbial pathogens to avoid recognition and attack by the immune system of the host. Several pathogenic Ascomycota and Zygomycota show such … a behaviour by utilizing human complement factor H to hide in the blood stream. We call this type of mimicry molecular crypsis. Such a crypsis can reach a point where the immune system can no longer clearly distinguish between self and non-self cells. Thus, a trade-off between attacking disguised pathogens and erroneously attacking host cells has to be made. Based on signalling theory and protein-interaction modelling, we here present a mathematical model of molecular crypsis of pathogenic fungi using the example of Candida albicans. We tackle the question whether perfect crypsis is feasible, which would imply that protection of human cells by complement factors would be useless. The model identifies pathogen abundance relative to host cell abundance as the predominant factor influencing successful or unsuccessful molecular crypsis. If pathogen cells gain a (locally) quantitative advantage over host cells, even autoreactivity may occur. Our new model enables insights into the mechanisms of candidiasis-induced sepsis and complement-associated autoimmune diseases.

Authors: S. N. Lang, S. Germerodt, C. Glock, Christine Skerka, Peter Zipfel, Stefan Schuster

Date Published: 20th Feb 2019

Journal: PLoS One

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