Simulation of Bioreactors for PHB Production from Natural Gas

Abstract

<em>Recently, many economic studies of </em><em>poly(3-hydroxybutyrate) </em><em>PHB production </em><em>on an industrial scale, and the impact of replacing petrochemical polymers by PHB were carried out,</em><em> clearly indicating that the most crucial factors to reduce the cost of producing biopolymers are allotted to the application of microbial production strains capable of high productivity in inexpensive carbon sources, high cell density cultivation methods, cheap yet effective methods </em><em>for the extraction of PHB and other polyhydroxyalkanoates (PHAs), and gene transfer from bacteria</em><em> to plants. We present current strategies to reduce the production price of biological PHA. Because </em><em>an important part of the PHA production cost is related to the cost of carbon source, the article focuses</em><em> on the use of natural gas as an inexpensive and readily available C1-carbon source. Since the first and foremost point in PHA production is biomass growth, we discuss different types of bioreactors to be potentially used for efficient biomass production from natural gas, which facilitates the subsequent selection of the ideal bioreactor for PHA production from this substrate. Nowadays, process simulation software can be used as a powerful tool for analysis, optimization, design, and </em><em>scale up of bioprocesses. Controlling the process design by in silico simulations instead of performing an excessive number of lab-scale experiments to optimize various factors to save </em><em>in time, material and equipment. Simulation of PHA production processes to find the optimal conditions can play a decisive role in increasing the production efficiency. Computational fluid dynamics and mathematical modeling helps us to achieve a better understanding of the role of different nutrients, flow parameters of gaseous substrates, efficient feeding strategies, etc. This finding leads to higher productivity by prediction of parameters e.g. nutrient supply and biomass concentration time profile and their respective yields.</em>