Use of a Novel Combinatorial Genetics Platform to Rapidly Clone, Express, Select and Optimize Target Biocatalytic Activities for Multigenic Bio-Based Chemical Production Processes
Thursday, May 1, 2014: 11:25 AM
Grand Ballroom D-E, lobby level (Hilton Clearwater Beach)
Ian Fotheringham, Ingenza, Roslin, United Kingdom
Replacement of petroleum-based products and manufacturing processes with competitive bio-based alternatives is attracting increased attention due to environmental concerns surrounding petroleum sustainability and supply. In addition to replacing existing feedstocks used across a number of applications, bio-based processes have the potential to generate novel products as well as novel functionalities from current products for new applications. Replacement of conventional processes for manufacturing of valuable industrial chemicals and the selection of optimal biosynthetic routes requires the construction, and in most cases subsequent context-dependent evaluation, and optimization of multicomponent biosynthetic pathways to generate intermediates and end products. This talk will present the use of a 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 approaches. Multiple variants of up to ten individual genetic elements are combined in single reactions, generating expression libraries with hundreds or thousands of members in diverse heterologous configurations for assay. 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. The technology aims to bring increasing predictability and overcome typical limitations of the iterative and empirical process of strain improvement. The successful realization of optimal target reactions enables rapid pathway definition and progression to process optimization and scale-up.