Abstract (Expand)

BACKGROUND: Understanding the molecular mechanisms of platelet activation and aggregation is of high interest for basic and clinical hemostasis and thrombosis research. The central platelet protein interaction network is involved in major responses to exogenous factors. This is defined by systemsbiological pathway analysis as the central regulating signaling cascade of platelets (CC). RESULTS: The CC is systematically compared here between mouse and human and major differences were found. Genetic differences were analysed comparing orthologous human and mouse genes. We next analyzed different expression levels of mRNAs. Considering 4 mouse and 7 human high-quality proteome data sets, we identified then those major mRNA expression differences (81%) which were supported by proteome data. CC is conserved regarding genetic completeness, but we observed major differences in mRNA and protein levels between both species. Looking at central interactors, human PLCB2, MMP9, BDNF, ITPR3 and SLC25A6 (always Entrez notation) show absence in all murine datasets. CC interactors GNG12, PRKCE and ADCY9 occur only in mice. Looking at the common proteins, TLN1, CALM3, PRKCB, APP, SOD2 and TIMP1 are higher abundant in human, whereas RASGRP2, ITGB2, MYL9, EIF4EBP1, ADAM17, ARRB2, CD9 and ZYX are higher abundant in mouse. Pivotal kinase SRC shows different regulation on mRNA and protein level as well as ADP receptor P2RY12. CONCLUSIONS: Our results highlight species-specific differences in platelet signaling and points of specific fine-tuning in human platelets as well as murine-specific signaling differences.

Authors: J. Balkenhol, K. V. Kaltdorf, E. Mammadova-Bach, A. Braun, B. Nieswandt, M. Dittrich, T. Dandekar

Date Published: 22nd Dec 2020

Journal: BMC Genomics

Abstract (Expand)

OBJECTIVE: The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns. RESULTS: The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.

Authors: L. Urban, Christian Remmele, Marcus Dittrich, R. F. Schwarz, Tobias Müller

Date Published: 24th Feb 2020

Journal: BMC Res Notes

Abstract (Expand)

Stomata are microscopic pores found on the surfaces of leaves that act to control CO2 uptake and water loss. By integrating information derived from endogenous signals with cues from the surrounding environment, the guard cells, which surround the pore, 'set' the stomatal aperture to suit the prevailing conditions. Much research has concentrated on understanding the rapid intracellular changes that result in immediate changes to the stomatal aperture. In this study, we look instead at how stomata acclimate to longer timescale variations in their environment. We show that the closure-inducing signals abscisic acid (ABA), increased CO2, decreased relative air humidity and darkness each access a unique gene network made up of clusters (or modules) of common cellular processes. However, within these networks some gene clusters are shared amongst all four stimuli. All stimuli modulate the expression of members of the PYR/PYL/RCAR family of ABA receptors. However, they are modulated differentially in a stimulus-specific manner. Of the six members of the PYR/PYL/RCAR family expressed in guard cells, PYL2 is sufficient for guard cell ABA-induced responses, whereas in the responses to CO2, PYL4 and PYL5 are essential. Overall, our work shows the importance of ABA as a central regulator and integrator of long-term changes in stomatal behaviour, including sensitivity, elicited by external signals. Understanding this architecture may aid in breeding crops with improved water and nutrient efficiency.

Authors: M. Dittrich, H. M. Mueller, H. Bauer, M. Peirats-Llobet, P. L. Rodriguez, C. M. Geilfus, S. C. Carpentier, K. A. S. Al Rasheid, H. Kollist, E. Merilo, J. Herrmann, T. Muller, P. Ache, A. M. Hetherington, R. Hedrich

Date Published: 28th Aug 2019

Journal: Nat Plants

Abstract (Expand)

Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network's nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the network's nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.

Authors: T. Breitenbach, C. Liang, N. Beyersdorf, T. Dandekar

Date Published: 17th Jul 2019

Journal: PLoS Comput Biol

Abstract (Expand)

Mold specific T-cells have been described as a supportive biomarker to monitor invasive mycoses and mold exposure. This study comparatively evaluated frequencies and cytokine profiles of Aspergillus fumigatus and Mucorales reactive T-cells depending on environmental mold exposure. Peripheral blood mononuclear cells (PBMCs) obtained from 35 healthy donors were stimulated with mycelial lysates of A. fumigatus and three human pathogenic Mucorales species. CD154(+) specific T-cells were quantified by flow cytometry. In a second cohort of 20 additional donors, flow cytometry was complemented by 13-plex cytokine assays. Mold exposure of the subjects was determined using a previously established questionnaire. Highly exposed subjects exhibited significantly greater CD154(+)A. fumigatus and Mucorales specific naive and memory T-helper cell frequencies. Significant correlation (r = 0.48 - 0.79) was found between A. fumigatus and Mucorales specific T-cell numbers. Logistic regression analyses revealed that combined analysis of mold specific T-cell frequencies and selected cytokine markers (A. fumigatus: IL-5 and TNF-alpha, R. arrhizus: IL-17A and IL-13) significantly improves classification performance, resulting in 75-90 % predictive power using 10-fold cross-validation. In conclusion, mold specific T-cell frequencies and their cytokine signatures offer promising potential in the assessment of environmental mold exposure. The cytokines identified in this pilot study should be validated in the clinical setting, e. g. in patients with hypersensitivity pneumonitis.

Authors: L. Page, P. Weis, T. Muller, M. Dittrich, M. Lazariotou, M. Dragan, A. M. Waaga-Gasser, J. Helm, T. Dandekar, H. Einsele, J. Loffler, A. J. Ullmann, S. Wurster

Date Published: 12th Sep 2018

Journal: Int J Med Microbiol

Abstract (Expand)

Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host(-)pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.

Authors: E. Bencurova, S. K. Gupta, E. Sarukhanyan, T. Dandekar

Date Published: 4th Jul 2018

Journal: J Fungi (Basel)

Abstract (Expand)

Invasive infections by the human pathogenic fungus Aspergillus fumigatus start with the outgrowth of asexual, airborne spores (conidia) into the lung tissue of immunocompromised patients. The resident alveolar macrophages phagocytose conidia, which end up in phagolysosomes. However, A. fumigatus conidia resist phagocytic degradation to a certain degree. This is mainly attributable to the pigment 1,8-dihydroxynaphthalene (DHN) melanin located in the cell wall of conidia, which manipulates the phagolysosomal maturation and prevents their intracellular killing. To get insight in the underlying molecular mechanisms, we comparatively analyzed proteins of mouse macrophage phagolysosomes containing melanized wild-type (wt) or nonmelanized pksP mutant conidia. For this purpose, a protocol to isolate conidia-containing phagolysosomes was established and a reference protein map of phagolysosomes was generated. We identified 637 host and 22 A. fumigatus proteins that were differentially abundant in the phagolysosome. 472 of the host proteins were overrepresented in the pksP mutant and 165 in the wt conidia-containing phagolysosome. Eight of the fungal proteins were produced only in pksP mutant and 14 proteins in wt conidia-containing phagolysosomes. Bioinformatical analysis compiled a regulatory module, which indicates host processes affected by the fungus. These processes include vATPase-driven phagolysosomal acidification, Rab5 and Vamp8-dependent endocytic trafficking, signaling pathways, as well as recruitment of the Lamp1 phagolysosomal maturation marker and the lysosomal cysteine protease cathepsin Z. Western blotting and immunofluorescence analyses confirmed the proteome data and moreover showed differential abundance of the major metabolic regulator mTOR. Taken together, with the help of a protocol optimized to isolate A. fumigatus conidia-containing phagolysosomes and a potent bioinformatics algorithm, we were able to confirm A. fumigatus conidia-dependent modification of phagolysosomal processes that have been described before and beyond that, identify pathways that have not been implicated in A. fumigatus evasion strategy, yet.Mass spectrometry proteomics data are available via ProteomeXchange with identifiers PXD005724 and PXD006134.

Authors: H. Schmidt, S. Vlaic, T. Kruger, F. Schmidt, J. Balkenhol, T. Dandekar, R. Guthke, O. Kniemeyer, T. Heinekamp, A. A. Brakhage

Date Published: 7th Mar 2018

Journal: Mol Cell Proteomics

Abstract (Expand)

Understanding optimality principles shaping the evolution of regulatory networks controlling metabolism is crucial for deriving a holistic picture of how metabolism is integrated into key cellular processes such as growth, adaptation and pathogenicity. While in the past the focus of research in pathway regulation was mainly based on stationary states, more recently dynamic optimization has proved to be an ideal tool to decipher regulatory strategies for metabolic pathways in response to environmental cues. In this short review, we summarize recent advances in the elucidation of optimal regulatory strategies and identification of optimal control points in metabolic pathways. We discuss biological implications of the discovered optimality principles on genome organization and provide examples how the derived knowledge can be used to identify new treatment strategies against pathogens. Furthermore, we briefly discuss the variety of approaches for solving dynamic optimization problems and emphasize whole-cell resource allocation models as an important emerging area of research that will allow us to study the regulation of metabolism on the whole-cell level.

Authors: Jan Ewald, M. Bartl, Christoph Kaleta

Date Published: 30th Jul 2017

Journal: Biochem Soc Trans

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

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

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: C. W. Remmele, C. H. Luther, J. Balkenhol, T. Dandekar, T. Muller, M. T. Dittrich

Date Published: 25th Aug 2015

Journal: Front Microbiol

Abstract (Expand)

BACKGROUND: Adjusting the capacity of metabolic pathways in response to rapidly changing environmental conditions is an important component of microbial adaptation strategies to stochastic environments. In this work, we use advanced dynamic optimization techniques combined with theoretical models to study which reactions in pathways are optimally targeted by regulatory interactions in order to minimize the regulatory effort that is required to adjust the flux through a complex metabolic network. Moreover, we analyze how constraints in the speed at which an organism can respond on a proteomic level influences these optimal targets of pathway control. RESULTS: We find that limitations in protein biosynthetic rates have a strong influence. With increasing protein biosynthetic rates the regulatory effort targeting the initial enzyme in a pathway is reduced while the regulatory effort in the terminal enzyme is increased. Studying the impact of allosteric regulation for different pathway topologies, we find that the presence of feedback inhibition by products of metabolic pathways allows organisms to reduce the regulatory effort that is required to control a metabolic pathway in all cases. In a linear pathway this even leads to the case where the sole transcriptional regulatory control of the terminal enzyme is sufficient to control flux through the entire pathway. We confirm the utilization of these pathway regulation strategies through the large-scale analysis of transcriptional regulation in several hundred prokaryotes. CONCLUSIONS: This work expands our knowledge about optimal programs of pathway control. Optimal targets of pathway control strongly depend on the speed at which proteins can be synthesized. Moreover, post-translational regulation such as allosteric regulation allows to strongly reduce the number of transcriptional regulatory interactions required to control a metabolic pathway across different pathway topologies.

Authors: G. M. de Hijas-Liste, E. Balsa-Canto, Jan Ewald, M. Bartl, P. Li, J. R. Banga, Christoph Kaleta

Date Published: 16th May 2015

Journal: BMC Bioinformatics

Abstract (Expand)

In this work, we investigate optimality principles behind synthesis strategies for protein complexes using a dynamic optimization approach. We show that the cellular capacity of protein synthesis has a strong influence on optimal synthesis strategies reaching from a simultaneous to a sequential synthesis of the subunits of a protein complex. Sequential synthesis is preferred if protein synthesis is strongly limited, whereas a simultaneous synthesis is optimal in situations with a high protein synthesis capacity. We confirm the predictions of our optimization approach through the analysis of the operonic organization of protein complexes in several hundred prokaryotes. Thereby, we are able to show that cellular protein synthesis capacity is a driving force in the dissolution of operons comprising the subunits of a protein complex. Thus, we also provide a tested hypothesis explaining why the subunits of many prokaryotic protein complexes are distributed across several operons despite the presumably less precise co-regulation.

Authors: Jan Ewald, M. Kotzing, M. Bartl, Christoph Kaleta

Date Published: 1st May 2015

Journal: Metabolites

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