92C42 Systems biology, networks
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- 2014 (2)
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- Doctoral Thesis (2)
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- Angiotensin II (1)
- Anpassungsreaktionen (1)
- Atrial fibrillation (1)
- Bacillus subtilis (1)
- Central carbon metabolism (1)
- Connective Tissue Growth Factor (1)
- Dronedarone (1)
- Endothelin (1)
- Irbesartan (1)
- Multi-omics (1)
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In summary, the transcriptome data demonstrated that acute RAP for 7h induces significant changes in the expression of several left atrial genes, including those reflecting ANG II-mediated oxidative stress, tissue remodeling, and energy depletion. Furthermore, the results from the dronedarone study demonstrated that this drug is capable of attenuating most of RAP-induced changes in oxidative stress-related gene expression. Accordingly, the haemodynamic parameters also showed that dronedarone reduced RAP-induced microvascular flow abnormalities. This view is supported by the observation that in the used porcine model of acute AF, dronedarone decreased RAP-dependent PKC phosphorylation, NADPH isoform expression, F2-isoprostane release and IκBα phosphorylation. Additionally, the results of the irbesartan study indicate that ET-1 contributes to AF-dependent atrial fibrosis by synergistic activity with ANG-II to stimulate SGK1 expression and enhance phosphorylation of the SGK1 protein which, in turn, induces CTGF. The latter has been consistently associated with tissue fibrosis. In support of this view, in vitro analyses using HL-1 cells verified CTGF induction after short episodes of RAP and additionally in response to exogenous addition of ET-1. Accordingly, irbesartan was shown to attenuate most of the RAP-dependent changes in atrial or ventricular gene expression.
The soil bacterium Bacillus subtilis is capable of surviving most of the ensuing environmental stress conditions. The dynamic nature of the soil habitat is manifested with varying amounts of nutrients, frequent flooding, drying and variation of other growth parameters like temperature, acidity, aeration etc. In order to survive in these conditions, B. subtilis has evolved to employ very complex adaptational responses. These adaptational responses are often multi-faceted; hence comprehensive understanding of the adaptational responses requires generation and integration of data on multi-omics level. Hence, multi-omics based detailed analysis was performed for the molecules involved in the central carbon metabolism (CCM) and proline biosynthesis pathway. In the current study two major stress conditions were extensively investigated: 1) energy limitation/starvation which is achieved by limiting glucose in the growth medium, 2) osmostress resulting from frequent drying out of soil which is simulated by adding 1.2 M NaCl to the growth medium. In addition to osmostress, the naturally available osmoprotectant glycine betaine (GB) was supplemented to understand the simultaneous influence of osmostress and osmoprotection on cellular physiology. To measure absolute protein abundances by mass spectrometry, a targeted approach (SRM –single reaction monitoring) using stable heavy isotope labeled artificial standard proteins known as QconCATs was optimized and implemented in the current study. The SRM technique in combination with QconCAT provided absolute quantitative data with high dynamic range for the 45 targeted CCM proteins. Transcriptome data was obtained from microarray analysis. The resulting data were integrated with the other omics data sets obtained by metabolome and flux analysis. As part of a joint study conducted by the BaCell-SysMO and BaSysBio consortia which aimed for the genome wide mapping of transcription units and previously unannotated RNAs of B. subtilis by means of tiling array hybridizations, mRNA samples from growth at high and low temperatures (51°C and 16°C) and in the presence of 1.2 M NaCl, shake flask experiments during transition from exponential growth to the stationary phase, and high density batch fermentation. Time course analysis of B. subtilis transitioning from exponential to stationary phase was investigated by high cell density fed-batch fermentation (glucose limitation) and batch fermentation (glucose exhaustion) with glucose as a limiting factor. A multi-omics analysis of the CCM for the batch fermentation was performed and the time course data was integrated and visualized. In conclusion, pathway based multi-omics data were generated, integrated and visualized as a prerequisite for systems biology approaches and for a better understanding of the complex adaptational responses of B. subtilis.