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Due to metabolic engineering advances, it is possible to produce a large number of bio-based chemical compounds. However, the downstream processing is challenging the development at an industrial scale. Selecting the proper recovery and separation method is critical in developing a cost-effective and competitive process. This study is focused on analyzing the production of succinic acid from glycerol through computational methods for strain design and determine the effects on the recovery and purification processes. Here, it was integrated the metabolic phenotype of different mutants obtained through constraint-based reconstruction and analysis modeling into two recoveries and purification processes by using a flash evaporator and a reactive extraction column. Two thousand forty-two mutants, predicted in silico, were phenotypically analyzed. Succinate was the main product; however, were also generated by-products such as acetate, formate, and lactate. Of those, twelve mutants were selected to create feed streams with different compositions and then downstream modeling. These models, after optimization, achieved a recovery rate > 93% and molar purity > 99%. Economic analysis suggests that when engineering a strain, the most important factors to consider are (i) the productivity (> 5 mmol/gDW h-1 of succinic acid) and (ii) the growth rate (> 0.10 gDW h-1). |
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