Rational design of allosterically regulated toehold mediated strand displacement circuits for sensitive and on-site detection of small molecule metabolites. Issue 23 (4th November 2021)

• Record Type: Journal Article
• Authors: Lin, Haosi; Rodríguez-Serrano, Alan F.; Hsing, I-Ming
• Is Part Of: Analyst. Volume 146:Issue 23(2021)
• Page Start: 7144
• Page End: 7151
• Publication Date: 2021-11-04
• Subjects: Chemistry, Analytic -- Periodicals; 543
• DOI: 10.1039/d1an01488a
• Languages: English
• ISSNs: 0003-2654

Abstract

Abstract : In this paper we established an allosterically-regulated toehold-mediated strand displacement circuit enhanced by a two-cycle design. This system allowed one-step, rapid uric acid detection in user-friendly non-invasive saliva samples. Abstract : Development of small molecule biosensors enables rapid and de-centralized small molecule detection that meets the demands of routine health monitoring and rapid diagnosis. Among them, allosteric transcription factor (aTF)-based biosensors have shown potential in modular design of small molecule detection platforms due to their ligand-regulated DNA binding activity. Here, we expand the capabilities of a biosensor that leverages the aTF-based regulation of toehold-mediated strand displacement (TMSD) circuits for uric acid (UA) detection in non-invasive salivary samples by utilizing the UA-responsive aTF HucR. The impact of the low ligand affinity of the native HucR was addressed by engineering a two-pass TMSD circuit with in silico rational design. This combined strategy achieved enrichment of the output signal and overcame the negative impact of the matrix effect on the sensitivity and overall response of the biosensor when using real samples, which enabled semi-quantitative detection in the normal salivary UA levels. As well, enhancements provided by the two-pass design halved the turnaround time to less than 15 minutes. To sum up, the two-cycle DNA circuit design enabled aTF-based simple, rapid and one-step non-invasive salivary UA detection, showing its potential in metabolite detection for health monitoring.