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A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors.

Brent TownshendJoy S XiangGabriel ManzanarezEric J HaydenChristina D Smolke
Published in: Nature communications (2021)
Biosensors are key components in engineered biological systems, providing a means of measuring and acting upon the large biochemical space in living cells. However, generating small molecule sensing elements and integrating them into in vivo biosensors have been challenging. Here, using aptamer-coupled ribozyme libraries and a ribozyme regeneration method, de novo rapid in vitro evolution of RNA biosensors (DRIVER) enables multiplexed discovery of biosensors. With DRIVER and high-throughput characterization (CleaveSeq) fully automated on liquid-handling systems, we identify and validate biosensors against six small molecules, including five for which no aptamers were previously found. DRIVER-evolved biosensors are applied directly to regulate gene expression in yeast, displaying activation ratios up to 33-fold. DRIVER biosensors are also applied in detecting metabolite production from a multi-enzyme biosynthetic pathway. This work demonstrates DRIVER as a scalable pipeline for engineering de novo biosensors with wide-ranging applications in biomanufacturing, diagnostics, therapeutics, and synthetic biology.
Keyphrases
  • small molecule
  • high throughput
  • gene expression
  • label free
  • living cells
  • single cell
  • machine learning
  • dna methylation
  • deep learning
  • sensitive detection
  • protein protein