Metabolic Engineering and Scale-Up Strategies for Upgrading of Renewable Lignin-Derived Feedstocks by Acinetobacter baylyi ADP1


Efficient and sustainable utilization of global resources represents a grand but achievablechallenge. By leveraging biology, we can transform abundant, but recalcitrant resources like lignin to products ranging from fuel to medicine to polymers. Efforts to do so are expansive, but challenges remain, due in no small part to the difficulty in breaking down lignin and in efficiently utilizing the diverse and variable degradation products. However, nature has evolved organisms capable of diverse and efficient catabolism of numerous lignin-derived substrates. One such organism is Acinetobacter baylyi ADP1. As a non-model organism, ADP1 represents both a promising platform for biological transformation and a significant challenge in engineering due to the relative lack of information regarding engineering and scale-up compared to model organisms like E. coli and S. cerevisiae. However, recent developments for ADP1-specific tools alongside engineering towards synthesis of industrially relevant products has demonstrated the suitability of ADP1 as a powerful platform for lignin upgrading. In this dissertation, I describe efforts to engineer and develop growth strategies for ADP1. The work comprises two research projects comprised of one paper each, and suggestions for future work. First, I discuss to my first major project, where I engineer ADP1 to synthesize mevalonate through expression of the heterologous mevalonate pathway. I improve mevalonate production titers by evaluating production from various lignin-derived substrates, eliminating a native, resource-competitive pathway, and implementing fed-batch cultivation. Next, I discuss growth and scale-up strategies specifically for Acinetobacter baylyi ADP1. I identify nutrient limitation as the primary mode of growth limitation in minimal medium and nitrogen as the most limiting nutrient, I implement a targeted nutrient feeding strategy to increase cell density, and I explore strategies to scale ADP1 growth the lab-scale bioreactors while providing adequate aeration. I then pivot to experimental validation of a computational modeling tool for predicting the identity of unknown metabolites in an ADP1 metabolomics data set. Here I develop LCMS methodology for analysis of high priority metabolites and knock out genes predicted to be involved in the synthesis of identified metabolites. These data confirm both the accuracy of the metabolite prediction tool and the metabolic pathways involved in the synthesis of predicted metabolites. Finally, I outline future project directions, specifically (i) enhancing oxygen transfer, (ii) overcoming dilution effects by cell recycle, (iii) utilization of complex and industrially relevant feedstocks, (iv) leveraging bioreactors to achieve finer process control and study consortia dynamics for ADP1, and (v) metabolic engineering towards enhanced cyanophycin production.

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