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Abstract:
In vitro metabolic systems allow the reconstitution of natural and new-to-nature pathways outside of their cellular context and are of increasing interest in bottom-up synthetic biology, cell-free manufacturing and metabolic engineering. Yet, the analysis of the activity of such in vitro networks is very often restricted by time- and cost-intensive methods. To overcome these limitations, we sought to develop an in vitro transcription (IVT)-based biosensing workflow that is compatible with the complex conditions of in vitro metabolism, such as the CETCH cycle, a 27-component in vitro metabolic system that converts CO2 into glycolate. As proof-of-concept, we constructed a novel glycolate sensor module that is based on the transcriptional repressor GlcR from Paracoccus denitrificans, and established an IVT biosensing workflow that allows to quantify glycolate from CETCH samples in the µM to mM range. We investigate the influence on 13 (shared) cofactors between the two in vitro systems to show that Mg2+, ATP and other phosphorylated metabolites are critical for robust signal output. Our optimized IVT biosensor correlates well with LC-MS-based glycolate quantification of CETCH samples with one or multiple components varied (linear correlation 0.94-0.98), but notably at ~10-fold lowered cost and ~10 times faster turnover time. Our results demonstrate the potential and challenges of IVT-based systems to quantify and prototype the activity of complex reaction cascades and in vitro metabolic networks.
