In vitro modulation of inflammatory target gene expression by a polyphenol-enriched fraction of rose oil distillation waste water.

Classical production of rose oil is based on water steam distillation from the flowers of Rosa damascena. During this process, large quantities of waste water accrue which are discharged to the environment, causing severe pollution of both, groundwater and surface water due to a high content of polyphenols. We recently developed a strategy to purify the waste water into a polyphenol-depleted and a polyphenol-enriched fraction RF20-(SP-207). RF20-(SP-207) and sub-fraction F(IV) significantly inhibited cell proliferation and migration of HaCaT cells. Since there is a close interplay between these actions and inflammatory processes, here we focused on the fractions' influence on pro-inflammatory biomarkers. HaCaT keratinocytes were treated with RF20-(SP-207), F(IV) (both at 50µg/mL) and ellagic acid (10µM) for 24h under TNF-α (20ng/mL) stimulated and non-stimulated conditions. Gene expression of IL-1ß, IL-6, IL-8, RANTES and MCP-1 was analyzed by reverse transcriptase polymerase chain reaction (RT-PCR) and cellular protein secretion of IL-8, RANTES and MCP-1 was determined by ELISA based assays. RF20-(SP-207) and F(IV) significantly decreased the expression and cellular protein secretion of IL-1ß, IL-6, IL-8, RANTES and MCP-1. The diminishing effects on inflammatory target gene expression were slightly less pronounced under TNF-α stimulated conditions. In conclusion, the recovered polyphenol fraction RF20-(SP-207) from rose oil distillation waste water markedly modified inflammatory target gene expression in vitro, and, therefore, could be further developed as alternative treatment of acute and chronic inflammation.

Photoconversion and nuclear trafficking cycles determine phytochrome A's response profile to far-red light.

Phytochrome A (phyA) is the only photoreceptor in plants, initiating responses in far-red light and, as such, essential for survival in canopy shade. Although the absorption and the ratio of active versus total phyA are maximal in red light, far-red light is the most efficient trigger of phyA-dependent responses. Using a joint experimental-theoretical approach, we unravel the mechanism underlying this shift of the phyA action peak from red to far-red light and show that it relies on specific molecular interactions rather than on intrinsic changes to phyA's spectral properties. According to our model, the dissociation rate of the phyA-FHY1/FHL nuclear import complex is a principle determinant of the phyA action peak. The findings suggest how higher plants acquired the ability to sense far-red light from an ancestral photoreceptor tuned to respond to red light.

A novel concept combining experimental and mathematical analysis for the identification of unknown interspecies effects in a mixed culture.

Bacteria in natural habitats only occur in consortia together with various other species. Characterization of bacterial species, however, is normally done by laboratory testing of pure isolates. Any interactions that might appear during growth in mixed-culture are obviously missed by this approach. Existing experimental studies mainly focus on two-species mixed cultures with species specifically chosen for their known growth characteristics, and their anticipated interactions. Various theoretical mathematical studies dealing with mixed cultures and possible interspecies effects exist, but often models cannot be validated due to a lack of experimental data. Here, we present a concept for the identification of interspecies effects in mixed cultures with arbitrary and unknown single-species properties. Model structure and parameters were inferred from single-species experiments for the reproduction of mixed-culture experiments by simulation. A mixed culture consisting of the three-species Pseudomonas aeruginosa, Burkholderia cepacia, and Staphylococcus aureus served as a model system. For species-specific enumeration a quantitative terminal restriction length polymorphism (qT-RFLP) assay was used. Based on models fitted to single-species cultivations, the outcome of mixed-culture experiments was predicted. Deviations of simulation results and experimental findings were then used to design additional single-cell experiments, to modify the corresponding growth kinetics, and to update model parameters. Eventually, the resulting mixed-culture dynamics was predicted and compared again to experimental results. During this iterative cycle, it became evident that the observed coexistence of P. aeruginosa and B. cepacia in mixed-culture chemostat experiments cannot be explained on the basis of glucose as the only substrate. After extension of growth kinetics, that is, for use of amino acids as secondary substrates, mixed-culture simulations represented the experimental findings very well. According to the model structure, as motivated by single-species experiments, the growth of P. aeruginosa and B. cepacia on glucose and amino acids could be assumed to be independent of each other. In contrast, both substrates are taken up simultaneously by S. aureus.

An integrative model for phytochrome B mediated photomorphogenesis: from protein dynamics to physiology.

BACKGROUND: Plants have evolved various sophisticated mechanisms to respond and adapt to changes of abiotic factors in their natural environment. Light is one of the most important abiotic environmental factors and it regulates plant growth and development throughout their entire life cycle. To monitor the intensity and spectral composition of the ambient light environment, plants have evolved multiple photoreceptors, including the red/far-red light-sensing phytochromes. METHODOLOGY/PRINCIPAL FINDINGS: We have developed an integrative mathematical model that describes how phytochrome B (phyB), an essential receptor in Arabidopsis thaliana, controls growth. Our model is based on a multiscale approach and connects the mesoscopic intracellular phyB protein dynamics to the macroscopic growth phenotype. To establish reliable and relevant parameters for the model phyB regulated growth we measured: accumulation and degradation, dark reversion kinetics and the dynamic behavior of different nuclear phyB pools using in vivo spectroscopy, western blotting and Fluorescence Recovery After Photobleaching (FRAP) technique, respectively. CONCLUSIONS/SIGNIFICANCE: The newly developed model predicts that the phyB-containing nuclear bodies (NBs) (i) serve as storage sites for phyB and (ii) control prolonged dark reversion kinetics as well as partial reversibility of phyB Pfr in extended darkness. The predictive power of this mathematical model is further validated by the fact that we are able to formalize a basic photobiological observation, namely that in light-grown seedlings hypocotyl length depends on the total amount of phyB. In addition, we demonstrate that our theoretical predictions are in excellent agreement with quantitative data concerning phyB levels and the corresponding hypocotyl lengths. Hence, we conclude that the integrative model suggested in this study captures the main features of phyB-mediated photomorphogenesis in Arabidopsis.

Signatures of gene expression noise in cellular systems.

Noise in gene expression, either due to inherent stochasticity or to varying inter- and intracellular environment, can generate significant cell-to-cell variability of protein levels in clonal populations. To quantify the different sources of gene expression noise, several theoretical studies have been performed using either a quasi-stationary approximation for the emerging master equation or employing a time-dependent description, when cell division is taken explicitly into account. Here, we give an overview of the different origins of gene expression noise which were found experimentally and introduce the basic stochastic modeling approaches. We extend, and apply a time-dependent description of gene expression noise to experimental data. The analysis shows that the induction level of the transcription factor can be employed to discriminate the noise profiles and their characteristic signatures. On the basis of experimentally measured cell distributions, our simulations suggest that transcription factor binding and promoter activation can be modeled independently of each other with sufficient accuracy.

Quantifying origins of cell-to-cell variations in gene expression.

A general dynamic description of protein synthesis was employed to quantify different sources of gene expression noise in cellular systems. To test our approach, we use time-resolved expression data of individual human cells and, from this information, predict the stationary cell-to-cell variation in protein levels in a clonal population. For three of the four human genes investigated, the cellular variations in expression level are not due to fluctuations in promoter activity or transcript copy number, but are almost exclusively a consequence of long-term variations of gene regulatory factors or the global cellular state. Moreover, we show that a dynamic description is much more reliable to discriminate extrinsic and intrinsic sources of noise than it is on grounds of cell-cycle averaged descriptions. The excellent agreement between the theoretical predictions and the experimentally measured noise strengths shows that a quantitative description of gene expression noise is indeed possible on the basis of idealized stochastic processes.