An Automated Cell-Free\nWorkflow for Transcription\nFactor Engineering

The design and optimization\nof metabolic pathways, genetic\nsystems,\nand engineered proteins rely on high-throughput assays to streamline\ndesign-build-test-learn cycles. However, assay development is a time-consuming\nand laborious process. Here, we create a generalizable approach for\nthe tailored optimization of automated cell-free gene expression (CFE)-based\nworkflows, which offers distinct advantages over in vivo assays in\nreaction flexibility, control, and time to data. Centered around designing\nhighly accurate and precise transfers on the Echo Acoustic Liquid\nHandler, we introduce pilot assays and validation strategies for each\nstage of protocol development. We then demonstrate the efficacy of\nour platform by engineering transcription factor-based biosensors.\nAs a model, we rapidly generate and assay libraries of 127 MerR and\n134 CadR transcription factor variants in 3682 unique CFE reactions\nin less than 48 h to improve limit of detection, selectivity, and\ndynamic range for mercury and cadmium detection. This was achieved\nby assessing a panel of ligand conditions for sensitivity (to 0.1,\n1, 10 μM Hg and 0, 1, 10, 100 μM Cd for MerR and CadR,\nrespectively) and selectivity (against Ag, As, Cd, Co, Cu, Hg, Ni,\nPb, and Zn). We anticipate that our Echo-based, cell-free approach\ncan be used to accelerate multiple design workflows in synthetic biology.