Kinetic modeling of rhamnolipid production by Pseudomonas aeruginosa PAO1 including cell density-dependent regulation.

The production of rhamnolipid biosurfactants by Pseudomonas aeruginosa is under complex control of a quorum sensing-dependent regulatory network. Due to a lack of understanding of the kinetics applicable to the process and relevant interrelations of variables, current processes for rhamnolipid production are based on heuristic approaches. To systematically establish a knowledge-based process for rhamnolipid production, a deeper understanding of the time-course and coupling of process variables is required. By combining reaction kinetics, stoichiometry, and experimental data, a process model for rhamnolipid production with P. aeruginosa PAO1 on sunflower oil was developed as a system of coupled ordinary differential equations (ODEs). In addition, cell density-based quorum sensing dynamics were included in the model. The model comprises a total of 36 parameters, 14 of which are yield coefficients and 7 of which are substrate affinity and inhibition constants. Of all 36 parameters, 30 were derived from dedicated experimental results, literature, and databases and 6 of them were used as fitting parameters. The model is able to describe data on biomass growth, substrates, and products obtained from a reference batch process and other validation scenarios. The model presented describes the time-course and interrelation of biomass, relevant substrates, and products on a process level while including a kinetic representation of cell density-dependent regulatory mechanisms.

Kinetic modeling of the time course of N-butyryl-homoserine lactone concentration during batch cultivations of Pseudomonas aeruginosa PAO1.

Quorum sensing affects the regulation of more than 300 genes in Pseudomonas aeruginosa, influencing growth, biofilm formation, and the biosynthesis of several products. The quorum sensing regulation mechanisms are mostly described in a qualitative character. Particularly, in this study, the kinetics of N-butyryl-homoserine lactone (C4-HSL) and rhamnolipid formation in P. aeruginosa PAO1 were of interest. In this system, the expression of the rhamnolipid biosynthesis genes rhlAB is directly coupled to the C4-HSL concentration via the rhl system. Batch cultivations in a bioreactor with sunflower oil have been used for these investigations. 3-oxo-dodecanoyl-homoserine lactone (3o-C12-HSL) displayed a lipophilic character and accumulated in the hydrophobic phase. Degradation of C4-HSL has been found to occur in the aqueous supernatant of the culture by yet unknown extracellular mechanisms, and production was found to be proportional to biomass concentration rather than by autoinduction mechanisms. Rhamnolipid production rates, as determined experimentally, were shown to correlate linearly with the concentration of autoinducer C4-HSL. These findings were used to derive a simple model, wherein a putative, extracellular protein with C4-HSL degrading activity was assumed (putative C4-HSL acylase). The model is based on data for catalytic efficiency of HSL-acylases extracted from literature (k cat/K m), experimentally determined basal C4-HSL production rates (q C4 - HSL (basal)), and two fitted parameters which describe the formation of the putative acylase and is therefore comparatively simple.

Efficient response to cascading disaster spreading.

We study the effectiveness of recovery strategies for a dynamic model of failure spreading in networks. These strategies control the distribution of resources based on information about the current network state and network topology. In order to assess their success, we have performed a series of simulation experiments. The considered parameters of these experiments are the network topology, the response time delay, and the overall disposition of resources. Our investigations are focused on the comparison of strategies for different scenarios and the determination of the most appropriate strategy. The importance of prompt response and the minimum sufficient quantity of resources are discussed as well.

Growth, innovation, scaling, and the pace of life in cities.

Humanity has just crossed a major landmark in its history with the majority of people now living in cities. Cities have long been known to be society's predominant engine of innovation and wealth creation, yet they are also its main source of crime, pollution, and disease. The inexorable trend toward urbanization worldwide presents an urgent challenge for developing a predictive, quantitative theory of urban organization and sustainable development. Here we present empirical evidence indicating that the processes relating urbanization to economic development and knowledge creation are very general, being shared by all cities belonging to the same urban system and sustained across different nations and times. Many diverse properties of cities from patent production and personal income to electrical cable length are shown to be power law functions of population size with scaling exponents, beta, that fall into distinct universality classes. Quantities reflecting wealth creation and innovation have beta approximately 1.2 >1 (increasing returns), whereas those accounting for infrastructure display beta approximately 0.8 <1 (economies of scale). We predict that the pace of social life in the city increases with population size, in quantitative agreement with data, and we discuss how cities are similar to, and differ from, biological organisms, for which beta<1. Finally, we explore possible consequences of these scaling relations by deriving growth equations, which quantify the dramatic difference between growth fueled by innovation versus that driven by economies of scale. This difference suggests that, as population grows, major innovation cycles must be generated at a continually accelerating rate to sustain growth and avoid stagnation or collapse.