Use of a novel combinatorial genetics platform to rapidly clone, express and select target biocatalytic activities for multigenic metabolic pathway optimization

Replacement of petrochemical processes for manufacturing valuable industrial products and the selection of optimal biosynthetic routes often requires context-dependent evaluation and optimization of multicomponent biosynthetic pathways.  This talk will present the use of Ingenza’s proprietary combinatorial genetics platform (inABLE^®) to rapidly clone, express, select and optimize target activities for many separate enzymatic reactions, from thousands of independent genes derived from metagenomic and phylogenetic discovery approaches.  This includes the characterization of a vast library of hitherto undiscovered genes from rumen microbial flora and the deployment of resulting novel enzyme activities in Saccharomyces to adapt and expand feedstock utilization for increased bioprocess efficiency.  Obvious synergy exists between this approach and versatile, solid phase screening and selection methods using growth-based, crossfeeding or colorimetric methods to identify colonies of interest.  This is illustrated through the rapid identification of critical pathway enzymes, optimal gene coding sequences and enzyme variants from inABLE^®-derived high quality variant libraries for applications in bio-based polymers, chemicals and personal care products.  We will also describe the success of modeling approaches to gene design that, when coupled with our inABLE^® approach towards combinatorial biofabrication, enhance the predictability of heterologous gene expression in diverse hosts.  The technology aims to bring increasing predictability and overcome persistent limitations associated with iterative and empirical processes for microbial strain improvement.  The successful realization of optimal target reactions enables rapid pathway definition and progression to process optimization and scale-up.