<b><i>In vitro </i></b><b>transcription-based biosensing of glycolate for prototyping of a complex enzyme cascade</b>

Revised dataset of Barthel et al., 2024, '<i>In vitro</i> transcription-based biosensing of glycolate for prototyping of a complex enzyme cascade'. See abstract below.<br><i>In vitro</i> 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 prototyping of such <i>in vitro</i> networks is very often restricted by time- and cost-intensive analytical methods. To overcome these limitations, we sought to develop an <i>in vitro</i> transcription (IVT)-based biosensing workflow that is compatible with complex conditions. As proof-of-concept, we developed an IVT biosensor for the CETCH cycle, a 27-component <i>in vitro</i> metabolic system that converts CO₂ into glycolate. We constructed a sensor module that is based on the transcriptional repressor GlcR from <i>Paracoccus denitrificans</i>, and established an IVT biosensing workflow that allows to quantify glycolate from CETCH samples in the µM to mM range. We show that free Mg²⁺ and phosphorylated compounds strongly influence IVT activity and are critical for robust signal output. Our optimized IVT biosensor correlates well with LC-MS-based glycolate quantification of CETCH samples with one enzyme varied (Pearson r = 0.9827) or multiple components varied (Pearson r = 0.9446), but notably at ~10-fold lowered cost and ~10 times faster turnover time. Our results demonstrate the potential of IVT-based biosensor systems to break current limitations in biological design-build-test cycles for the prototyping of individual enzymes, complex reaction cascades and <i>in vitro</i> metabolic networks.