No abstract

No abstract

No abstract

Living systems must adapt quickly and stably to uncertain environments. A common theme in cellular regulation is the presence of multiple feedback loops in the network. An example of such a feedback structure is regulation of tryptophan concentration in Escherichia coli. Here, three distinct feedback mechanisms, namely genetic regulation, mRNA attenuation and enzyme inhibition, regulate tryptophan synthesis. A pertinent question is whether such multiple feedback loops are ''a case of regulatory overkill, or do these di¡erent feedback regulators have distinct functions?'' [Freeman (2000) Nature 295, 313^319]. Another moot question is how robustness to uncertainties can be achieved structurally through biological interactions. Correlation between the feedback structure and robustness can be systematically studied by tools commonly employed in feedback theory. An analysis of feedback strategies in the tryptophan system in E. coli reveals that the network complexity arising due to the distributed feedback structure is responsible for the rapid and stable response observed even in the presence of system uncertainties. ß

Industrial fermentations typically use media that are balanced with multiple substitutable substrates including complex carbon and nitrogen source. Yet, much of the modeling effort to date has mainly focused on defined media. Here, we present a structured model that accounts for growth and product formation kinetics of rifamycin B fermentation in a multi-substrate complex medium. The phenomenological model considers the organism to be an optimal strategist with an in-built mechanism that regulates the sequential and simultaneous uptake of the substrate combinations. This regulatory process is modeled by assuming that the uptake of a substrate depends on the level of a key enzyme or a set of enzymes, which may be inducible. Further, the fraction of flux through a given metabolic branch is estimated using a simple multi-variable constrained optimization. The model has the typical form of Monod equation with terms incorporating multiple limiting substrates and substrate inhibition. Several batch runs were set up with varying initial substrate concentrations to estimate the kinetic parameters for the rifamycin overproducer strain Amycolatopsis mediterranei S699. Glucose and ammonium sulfate (AMS) demonstrated significant substrate inhibition toward growth as well as product formation. The model correctly predicts the experimentally observed regulated simultaneous uptake of the substitutable substrate combinations under different fermentation conditions. The modeling results may have applications in the optimization and control of rifamycin B fermentation while the modeling strategy presented here would be applicable to other industrially important fermentations.