RNA-based dynamic genetic controllers: development strategies and applications

Abstract

Dynamic regulation of gene expression in response to various molecules is crucial for both basic science and practical applications. RNA is considered an attractive material for creating dynamic genetic controllers because of its specific binding to ligands, structural flexibility, programmability, and small size. Here, we review recent advances in strategies for developing RNA-based dynamic controllers and applications. First, we describe studies that re-engineered natural riboswitches to generate new dynamic controllers. Next, we summarize RNA-based regulatory mechanisms that have been exploited to build novel artificial dynamic controllers. We also discuss computational methods and high-throughput selection approaches for de novo design of dynamic RNA controllers. Finally, we explain applications of dynamic RNA controllers for metabolic engineering and synthetic biology.

Graphical abstract

Figure 1

Re-engineering of natural riboswitches. Shaded box, randomized nucleotides; yellow circle, natural ligand; blue and red polygons, synthetic ligands. (a) Natural riboswitches are re-engineered to orthogonally detect synthetic ligands. Specific nucleotides are chosen based on crystal structure and fully mutagenized. Orthogonal riboswitches are identified from in vivo screening against synthetic analogues. (b) Natural aptamers are utilized as scaffolds for in vitro selection. Nucleotides at the three-way junction of natural aptamers are fully randomized and synthetic aptamers are evolved from in vitro selection. Evolved aptamers retain good in vivo functionality. (c) Expression platforms of natural riboswitches are re-engineered to construct modular platforms. A boundary between an aptamer and expression platform of a natural riboswitch is determined. Isolated expression platform is re-engineered and combined with numerous aptamers to create novel chimeric riboswitches.

Figure 2

RNA-based regulatory mechanisms for developing new dynamic controllers. Red circle and blue hexagon, ligands; black triangle, self-cleavage site. (a) Self-cleaving ribozymes are fused with aptamers to form aptazymes. Hammerhead ribozyme has three stems to which aptamers can be linked through a communication module. Twister ribozyme has two stems that can be combined with two distinct aptamers simultaneously to construct two-input logic gates. (b) Eukaryote-specific translation regulation mechanisms are exploited to create new dynamic RNA controllers. Left: Modulator sequence, anti-anti-IRES sequence (aaIRES), and anti-IRES sequence (aIRES) are designed to sequester the pseudoknot III (PK-III) which is an essential element of IRES system in the absence of ligand. When the ligand is bound to an aptamer, aaIRES and aIRES hybridize, forming PK-III. Middle: Ribosome cannot translate a downstream ORF (dORF) after translating a short ORF (sORF) in the absence of ligand. When the ligand is bound to an aptamer, an essential stem structure is formed, allowing the ribosome to shunt and reinitiate translation of the downstream ORF. Right: −1 programmed ribosomal frameshifting stimulator is formed when the ligand binds the aptamer. The ribosome shifts the reading frame at a slippery sequence. (c)Trans-acting dynamic RNA controllers. Left: A trans-non-coding RNA (ncRNA) is fused with an aptamer. Trans-ncRNA is inactive when ligand is absent because of intramolecular interactions. When the ligand is bound to the aptamer, an active stem-loop structure is formed that can terminate transcription or repress translation. Middle: A single guide RNA (sgRNA) is inactive in the absence of ligand because its spacer sequence hybridizes with an antisense stem. When the ligand is bound to an aptamer, the spacer is released and sgRNA represses gene expression in combination with a catalytically inactive Cas9 (dCas9). Right: An aptazyme is attached to the 5′-end of a sgRNA to sequester a spacer sequence in the absence of ligand. When the ligand is bound to the aptamer, the aptazyme cleaves itself, leaving a free spacer sequence that can repress gene expression.

Figure 3

De novo construction strategies for dynamic RNA controllers. (a) General flowchart of computational methods for designing dynamic RNA controllers. (b) Coupled in vitro–in vivo selection strategy for efficient development of dynamic RNA controllers that can function in vivo.

Figure 4

Applications of dynamic RNA controllers. (a) High-throughput screening and selection of metabolite production. Intracellular or extracellular metabolites can be detected using dynamic RNA controllers. Selection marker genes can control the growth rates of producer cells depending on metabolite production. Otherwise, fluorescence protein genes can be used with a fluorescence-activated cell sorting or single-cell droplet array to screen highly productive strains. (b) Dynamic RNA controllers can regulate gene expression in response to externally added ligands. Expression level of the gene is determined from the concentration of the ligand. RNA-based inducible gene expression is utilized to control T-cell proliferation, mammalian cell cycle, and viral replication and infection.