Simultaneous, high dimensional strain engineering and process optimisation for increased productivity and robustness

The standard model of bioprocess development is to establish genetics/strain first using screens at the lab scale, then take a set of high producing strains into process development and scaleup.  However, the amount and quality of product a biological system produces is a function of its genetics and the process conditions and medium that we subject it to.  Separating the optimisation genetics and environment relies on the erroneous assumption that there are no significant interactions between genetic and environmental factors.  

Here we present data from high dimensional bioprocess optimisations that investigated up to 30 genetic and process factors simultaneously: rapidly identifying and optimising complex interactions that underlie bioprocess performance.  Optimising these interactions resulted in very large improvements of volumetric productively (10 to 200 fold) in short timeframes.  Our methodologies take advantage of advances in synthetic biology in conjunction with our automation and software solutions enabling parallel execution of 100s of unique experiments.  These experiments make up complex matrices of conditions as defined by cutting edge multifactorial experimental designs.  We have regularly observed interactions between as many as four genetic and process factors, whose optimisation has allowed us harness the underlying complexity of the biology and maximise productivity and process robustness.

Our scaleup strategy transfers our multidimensional models into parallel stirred tank bioreactors (12 reactors run in parallel), before scaling into larger steam in place tanks and technology transfer to our industrial partners.