Signal amplification and optimization of riboswitch-based hybrid inputs by modular and titratable toehold switches

• Published in: Journal of biological engineering Vol. 15; no. 1; p. 11
• Main Authors: Hwang, Yunhee, Kim, Seong Gyeong, Jang, Sungho, Kim, Jongmin, Jung, Gyoo Yeol
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 19.03.2021; BioMed Central; BMC
• Subjects: Biosensor; Coenzyme B12; Enzymes; Genetic circuit; Riboswitch; RNA; Switches; Toehold switch; Riboswitch; Biosensor; Coenzyme B12; Genetic circuit; Toehold switch
• ISSN: 1754-1611; 1754-1611
• DOI: 10.1186/s13036-021-00261-w

Synthetic biological circuits are widely utilized to control microbial cell functions. Natural and synthetic riboswitches are attractive sensor modules for use in synthetic biology applications. However, tuning the fold-change of riboswitch circuits is challenging because a deep understanding of the riboswitch mechanism and screening of mutant libraries is generally required. Therefore, novel molecular parts and strategies for straightforward tuning of the fold-change of riboswitch circuits are needed. In this study, we devised a toehold switch-based modulator approach that combines a hybrid input construct consisting of a riboswitch and transcriptional repressor and de-novo-designed riboregulators named toehold switches. First, the introduction of a pair of toehold switches and triggers as a downstream signal-processing module to the hybrid input for coenzyme B resulted in a functional riboswitch circuit. Next, several optimization strategies that focused on balancing the expression levels of the RNA components greatly improved the fold-change from 260- to 887-fold depending on the promoter and host strain. Further characterizations confirmed low leakiness and high orthogonality of five toehold switch pairs, indicating the broad applicability of this strategy to riboswitch tuning. The toehold switch-based modulator substantially improved the fold-change compared to the previous sensors with only the hybrid input construct. The programmable RNA-RNA interactions amenable to in silico design and optimization can facilitate further development of RNA-based genetic modulators for flexible tuning of riboswitch circuitry and synthetic biosensors.