A Unique Bioengineering Platform for the Efficient Optimization of Metabolic Pathways

Metabolic engineering enables the conversion of microbial cells into factories for the production of drug molecules and other valuable chemical products. Modulation and optimization of metabolic pathways is accomplished by several complementary approaches that influence the presence, catalytic properties and abundance of pathway enzymes.

We have developed a bioengineering platform that is based on the seamless integration of synthetic biology, efficient gene synthesis and modern machine learning to address whole bio-system optimization. The platform enables simultaneous exploration of a large number of variables ranging from synonymous mutations via amino acid substitutions and DNA/protein parts all the way through pathway replacement and genome editing at the chromosomal level while minimizing the sample numbers needed. We manage the large size of possible sequence space by condensing the dimensionality and capturing correlating variables. Causal variables are identified and their relative contribution quantified by iterative rounds of systematic exploration. The technology is generic and broadly applicable in biology and can be used within existing QbD (Quality by Design) processes to capture and interrogate design information much upstream of typical industrial scale QbD.

We will describe several independent unpublished case studies illustrating the efficiency and power of the technology. Examples includes the engineering of polyketide synthase pathways for producing novel compounds, maximizing bio-production yield of commercial small molecules as well as therapeutic proteins, engineering proteins for crystallizability, and altering the carbon feedstock for organisms.