TY  - JOUR
A1  - Kaltdorf, Martin
A1  - Breitenbach, Tim
A1  - Karl, Stefan
A1  - Fuchs, Maximilian
A1  - Kessie, David Komla
A1  - Psota, Eric
A1  - Prelog, Martina
A1  - Sarukhanyan, Edita
A1  - Ebert, Regina
A1  - Jakob, Franz
A1  - Dandekar, Gudrun
A1  - Naseem, Muhammad
A1  - Liang, Chunguang
A1  - Dandekar, Thomas
T1  - Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis
JF  - Scientific Reports
N2  - The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
KW  - cellular signalling networks
KW  - computer modelling
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313303
VL  - 13
ER  - 
TY  - JOUR
A1  - Sivarajan, Rinu
A1  - Kessie, David Komla
A1  - Oberwinkler, Heike
A1  - Pallmann, Niklas
A1  - Walles, Thorsten
A1  - Scherzad, Agmal
A1  - Hackenberg, Stephan
A1  - Steinke, Maria
T1  - Susceptibility of Human Airway Tissue Models Derived From Different Anatomical Sites to Bordetella pertussis and Its Virulence Factor Adenylate Cyclase Toxin
JF  - Frontiers in Cellular and Infection Microbiology
N2  - To study the interaction of human pathogens with their host target structures, human tissue models based on primary cells are considered suitable. Complex tissue models of the human airways have been used as infection models for various viral and bacterial pathogens. The Gram-negative bacterium Bordetella pertussis is of relevant clinical interest since whooping cough has developed into a resurgent infectious disease. In the present study, we created three-dimensional tissue models of the human ciliated nasal and tracheo-bronchial mucosa. We compared the innate immune response of these models towards the B. pertussis virulence factor adenylate cyclase toxin (CyaA) and its enzymatically inactive but fully pore-forming toxoid CyaA-AC\(^-\). Applying molecular biological, histological, and microbiological assays, we found that 1 µg/ml CyaA elevated the intracellular cAMP level but did not disturb the epithelial barrier integrity of nasal and tracheo-bronchial airway mucosa tissue models. Interestingly, CyaA significantly increased interleukin 6, interleukin 8, and human beta defensin 2 secretion in nasal tissue models, whereas tracheo-bronchial tissue models were not significantly affected compared to the controls. Subsequently, we investigated the interaction of B. pertussis with both differentiated primary nasal and tracheo-bronchial tissue models and demonstrated bacterial adherence and invasion without observing host cell type-specific significant differences. Even though the nasal and the tracheo-bronchial mucosa appear similar from a histological perspective, they are differentially susceptible to B. pertussis CyaA in vitro. Our finding that nasal tissue models showed an increased innate immune response towards the B. pertussis virulence factor CyaA compared to tracheo-bronchial tissue models may reflect the key role of the nasal airway mucosa as the first line of defense against airborne pathogens.
KW  - human nasal epithelial cells
KW  - human tracheo-bronchial epithelial cells
KW  - human airway mucosa tissue models
KW  - adenylate cyclase toxin
KW  - Bordetella pertussis
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-253302
SN  - 2235-2988
VL  - 11
ER  -