Protein engineering of a genetically encoded biosensor for wastewater detection of profen NSAIDs

Abstract

Non-steroidal anti-inflammatory drugs (NSAIDs) are pervasive environmental contaminants due to their frequent and widespread use, multiple paths of release into surface and ground water supply, diversity of the chemical class, and toxicity to aquatic and other non-target species. In particular, the 2-arylpropionic acid ("profen") class of NSAIDs poses significant risks to aquatic ecosystems due to incomplete removal during wastewater treatment. Current monitoring precludes high frequency testing at point sources. Here we present the engineering and application of a genetically encodable, protein-based biosensor for the detection of the NSAIDs ketoprofen and pranoprofen in wastewater effluent. We repurposed the plant hormone receptor PYR1 to bind selectively to profens using computational protein design, deep mutational scanning, and yeast 2 hybrid and yeast surface display screening. The resulting sensor, PYRNSAID, has a nanomolar limit of detection for ketoprofen and panoprofen, and {micro}M sensitivity to the NSAIDs ibuprofen, fenoprofen, tolmetin and diclofenac. We also demonstrated dose responsive-activity of our sensor in simulated wastewater matrices containing the common wastewater contaminants sulfamethoxazole, caffeine, acetaminophen, and 2,4, dichlorophenol using a split Nanoluc luminescence assay. PYRNSAID is the first step towards a scalable, cost-effective alternative for real-time monitoring of pharmaceutical pollution.