A Cell-Free Metabolic Engineering Platform for High-Throughput Pathway Prototyping - Reverse Beta-Oxidation in Vitro | AIChE

A Cell-Free Metabolic Engineering Platform for High-Throughput Pathway Prototyping - Reverse Beta-Oxidation in Vitro

Authors 

Vogeli, B. - Presenter, Northwestern University
Jewett, M., Northwestern University
Schulz, L., Northwestern University
Engineered microorganisms offer an attractive approach to produce a large variety of small molecules in a sustainable way, if chemical synthesis is untenable. Implementation and optimization of biosynthetic pathways in industrially relevant heterologous hosts however remains time-consuming and labor-intensive among other challenges. Recent efforts in cell-free metabolic engineering have highlighted its potential for fast high-throughput pathway prototyping and can help speed up pathway design and optimization for subsequent in vivo testing1. Most of these studies have focused on short linear pathways optimizing the combination and ratio of only a couple of heterologous enzymes. Here we extend this approach to the modular and cyclic reverse beta-oxidation pathway (rBOX) capable of producing a large variety of short chain fatty acids and fatty acid derivatives of different chain lengths (>C4). In vivo studies of rBOX pathways often yield a mixture of products and finding the right enzyme homologues and combinations to specifically produce only one target molecule is a challenge2. We use the combination of cell-free protein synthesis and a subsequent mix-and-match of the produced enzyme homologues to rapidly build combinatorial rBOX pathway variants to prototype their substrate spectrum and optimize enzyme ratios. Acoustic liquid-handling robotics allows us to downscale to 4-µL reactions in 96-well plate formats and feasibly screen >50 pathway variants per day to accelerate the search for rBOX enzyme combinations with more specific product spectra. We anticipate this platform will improve cell-free methods for studying biosynthetic pathways in vitro, inform future in vivo engineering efforts of rBOX pathways, and be helpful more broadly for the design and optimization of engineered metabolic pathways.

1Karim et al. bioRxiv 2019 (10.1101/685768)

2Kim et al. Biotechnology and Bioengineering 2018 (10.1002/bit.26540)