A Cell-Free Approach to Fine Chemical Pathway Engineering | AIChE

A Cell-Free Approach to Fine Chemical Pathway Engineering

Authors 

Moore, S. - Presenter, Imperial College London
Polizzi, K., Imperial College London

Pathway engineering studies often neglect a key requirement to balance the supply and demand of enzyme loading at the molecular level. Furthermore, toxic intermediates can also hinder growth and promote genetic instability, so fine-tuning of pathway gene expression is essential to hit the metabolic sweet spot of pathway design1.

Our aim is to draw a link between cell-free in vitro kinetics and pathway design in vivo in living cells 2,3. Using the biosynthesis of raspberry ketone (Type III polyketide) as a 5-enzyme model pathway, we have designed a synthetic in vitro pathway to study the effects of enzyme loading and cofactor regeneration on pathway productivity. We have also discovered a reductase enzyme that fluoresces upon binding of a late pathway intermediate, therefore serving as a reporter by measuring product accumulation in real time. Using this fluorescence reporter, we have studied the pathway under massively parallel (384- to 1536-well plate format) experimental conditions with acoustic liquid handling robotics. In summary, the pathway enzyme benzalacetone synthase represents a rate-limiting step in the pathway, whilst low productivity occurs through imbalances in coenzyme A utilisation and cofactor regeneration.

Using this cell-free insight, we have implemented an in vivo pathway using combinatorial pathway refactoring4and natural riboswitch insulators to improve genetic stability and increase benzalacetone synthase levels. We are currently quantifying pathway designs with enzyme-GFP fusions and whole-cell extract LC-MS/MS analysis to correlate enzyme loading to pathway productivity. This will enable us to provide a fingerprint of an optimal enzyme pathway for production of Type III polyketides.

1. Jeschek, M., Gerngross, D. & Panke, S. Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort. Nat. Commun.7, 11163 (2016).

2. Weaver, L. J. et al. A kinetic-based approach to understanding heterologous mevalonate pathway function in E. coli. Biotechnol. Bioeng.112, 111â??9 (2015).

3. Opgenorth, P. H., Korman, T. P. & Bowie, J. U. A synthetic biochemistry module for production of bio-based chemicals from glucose. Nat. Chem. Biol.(2016). doi:10.1038/nchembio.2062

4. Moore, S. J. et al. EcoFlex - A Multifunctional MoClo Kit for E. coli Synthetic Biology. ACS Synth. Biol. (2016). doi:10.1021/acssynbio.6b00031