Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to dynamical environments, using a self-replicator model. We formulate dynamical growth maximization as an optimal control problem that can be solved using Pontryagin’s Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-optimal control strategy in dynamical conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for optimizing growth in a changing environment.
31To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes 32 require advanced instrumentation and control tools. Over the years, research on these topics has evolved and 33 followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid
34-mainly industrial -then municipal organic fraction of solid waste and agricultural residues. Time constants of 35 the processes have also changed with respect to the treated waste from minutes or hours to weeks or months.
36Since fast closed loop control is needed for short time constant processes, human operator is now included in the
The industrial exploitation of microalgae is characterized by the production of high value compounds. Optimization of the performance of microalgae culture systems is essential to render the process economically viable. For raceway systems, the task of optimization is rather challenging since the process is by essence periodically forced and, as a consequence, optimization must be carried out in a periodic framework. In this paper, we propose a simple operational criterion for raceway systems that when integrated in a strategy of closed-loop control allows to attain biomass productivities very near to the maximal producitivities. The strategy developed was tested numerically by using a mathematical model of microalgae growth in raceways. The model takes into account the dynamics of environmental variables temperature and light intensity and their influence on microalgae growth.
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