Publications

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10 Publications visible to you, out of a total of 10

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, J. Ewald, A. T. Kovacs, S. Schuster

Date Published: 3rd Nov 2020

Publication Type: Not specified

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: S. K. Gupta, M. Srivastava, O. Osmanoglu, T. Dandekar

Date Published: 11th Feb 2020

Publication Type: Not specified

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: J. Ewald, P. Sieber, R. Garde, S. N. Lang, S. Schuster, B. Ibrahim

Date Published: 30th Nov 2019

Publication Type: Not specified

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: M. Srivastava, E. Bencurova, S. K. Gupta, E. Weiss, J. Loffler, T. Dandekar

Date Published: 14th Jun 2019

Publication Type: Not specified

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, C. Skerka, P. F. Zipfel, S. Schuster

Date Published: 20th Feb 2019

Publication Type: Not specified

Abstract (Expand)

Alternative splicing (AS) is an important regulatory mechanism in eukaryotes but only little is known about its impact in fungi. Human fungal pathogens are of high clinical interest causing recurrent or life-threatening infections. AS can be well-investigated genome-wide and quantitatively with the powerful technology of RNA-Seq. Here, we systematically studied AS in human fungal pathogens based on RNA-Seq data. To do so, we investigated its effect in seven fungi during conditions simulating ex vivo infection processes and during in vitro stress. Genes undergoing AS are species-specific and act independently from differentially expressed genes pointing to an independent mechanism to change abundance and functionality. Candida species stand out with a low number of introns with higher and more varying lengths and more alternative splice sites. Moreover, we identified a functional difference between response to host and other stress conditions: During stress, AS affects more genes and is involved in diverse regulatory functions. In contrast, during response-to-host conditions, genes undergoing AS have membrane functionalities and might be involved in the interaction with the host. We assume that AS plays a crucial regulatory role in pathogenic fungi and is important in both response to host and stress conditions.

Authors: P. Sieber, K. Voigt, P. Kammer, S. Brunke, S. Schuster, J. Linde

Date Published: 19th Oct 2018

Publication Type: Not specified

Abstract (Expand)

As a part of the complement system, factor H regulates phagocytosis and helps differentiate between a body's own and foreign cells. Owing to mimicry efforts, some pathogenic microorganisms such as Candida albicans are able to bind factor H on their cell surfaces and, thus, become similar to host cells. This implies that the decision between self and foreign is not clear-cut, which leads to a classification problem for the immune system. Here, two different alleles determining the binding affinity of factor H are relevant. Those alleles differ in the SNP Y402H; they are known to be associated with susceptibility to certain diseases. Interestingly, the fraction of both alleles differs in ethnic groups. The game-theoretical model proposed in this article explains the coexistence of both alleles by a battle of the sexes game and investigates the trade-off between pathogen detection and protection of host cells. Further, we discuss the ethnicity-dependent frequencies of the alleles. Moreover, the model elucidates the mimicry efforts by pathogenic microorganisms.

Authors: S. Hummert, C. Glock, S. N. Lang, C. Hummert, C. Skerka, P. F. Zipfel, S. Germerodt, S. Schuster

Date Published: 4th May 2018

Publication Type: Not specified

Abstract (Expand)

The term open reading frame (ORF) is of central importance to gene finding. Surprisingly, at least three definitions are in use. We discuss several molecular biological and bioinformatics aspects, and we recommend using the definition in which an ORF is bounded by stop codons.

Authors: P. Sieber, M. Platzer, S. Schuster

Date Published: 26th Jan 2018

Publication Type: Not specified

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. However, their identification is hampered by the detection of protein communities within large-scale, whole-genome PPINs. A presented successful strategy detects a PPIN's community structure based on the maximal clique enumeration problem (MCE), which is a non-deterministic polynomial time-hard problem. This renders the approach computationally challenging for large PPINs implying the need for new strategies. We present ModuleDiscoverer, a novel approach for the identification of regulatory modules from PPINs and gene expression data. Following the MCE-based approach, ModuleDiscoverer uses a randomization heuristic-based approximation of the community structure. Given a PPIN of Rattus norvegicus and public gene expression data, we identify the regulatory module underlying a rodent model of non-alcoholic steatohepatitis (NASH), a severe form of non-alcoholic fatty liver disease (NAFLD). The module is validated using single-nucleotide polymorphism (SNP) data from independent genome-wide association studies and gene enrichment tests. Based on gene enrichment tests, we find that ModuleDiscoverer performs comparably to three existing module-detecting algorithms. However, only our NASH-module is significantly enriched with genes linked to NAFLD-associated SNPs. ModuleDiscoverer is available at http://www.hki-jena.de/index.php/0/2/490 (Others/ModuleDiscoverer).

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

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: S. Duhring, J. Ewald, S. Germerodt, C. Kaleta, T. Dandekar, S. Schuster

Date Published: 14th Jul 2017

Publication Type: Not specified

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