Conditional Guide RNAs: Programmable Conditional Regulation of CRISPR/Cas Function in Bacterial and Mammalian Cells via Dynamic RNA Nanotechnology

Abstract

A guide RNA (gRNA) directs the function of a CRISPR protein effector to a target gene of choice, providing a versatile programmable platform for engineering diverse modes of synthetic regulation (edit, silence, induce, bind). However, the fact that gRNAs are constitutively active places limitations on the ability to confine gRNA activity to a desired location and time. To achieve programmable control over the scope of gRNA activity, here we apply principles from dynamic RNA nanotechnology to engineer conditional guide RNAs (cgRNAs) whose activity is dependent on the presence or absence of an RNA trigger. These cgRNAs are programmable at two levels, with the trigger-binding sequence controlling the scope of the effector activity and the target-binding sequence determining the subject of the effector activity. We demonstrate molecular mechanisms for both constitutively active cgRNAs that are conditionally inactivated by an RNA trigger (ON → OFF logic) and constitutively inactive cgRNAs that are conditionally activated by an RNA trigger (OFF → ON logic). For each mechanism, automated sequence design is performed using the reaction pathway designer within NUPACK to design an orthogonal library of three cgRNAs that respond to different RNA triggers. In E. coli expressing cgRNAs, triggers, and silencing dCas9 as the protein effector, we observe a median conditional response of ≈4-fold for an ON → OFF "terminator switch" mechanism, ≈15-fold for an ON → OFF "splinted switch" mechanism, and ≈3-fold for an OFF → ON "toehold switch" mechanism; the median crosstalk within each cgRNA/trigger library is <2%, ≈2%, and ≈20% for the three mechanisms. To test the portability of cgRNA mechanisms prototyped in bacteria to mammalian cells, as well as to test generalizability to different effector functions, we implemented the terminator switch in HEK 293T cells expressing inducing dCas9 as the protein effector, observing a median ON → OFF conditional response of ≈4-fold with median crosstalk of ≈30% for three orthogonal cgRNA/trigger pairs. By providing programmable control over both the scope and target of protein effector function, cgRNA regulators offer a promising platform for synthetic biology.

Figure 1

Programmable regulators. (a) A conditional guide RNA (cgRNA) changes conformation in response to a programmable trigger X to conditionally direct the activity of a protein effector to a programmable target Y. Top: a constitutively active cgRNA is conditionally inactivated by X (ON → OFF logic). Bottom: a constitutively inactive cgRNA is conditionally activated by X (OFF → ON logic). (b) Molecular logic of programmable regulation using a standard gRNA (“not Y”) vs programmable conditional regulation using a cgRNA (“if X then not Y”). In this conceptual illustration, the standard gRNA silences Y in all tissues, while the cgRNA silences Y only in tissues where and when X is expressed, exerting spatiotemporal control over regulation. (c) A standard guide RNA (gRNA) is constitutively active, directing the function of protein effector dCas9 to a target gene Y; different dCas9 variants implement different functions (edit, silence, induce, bind). From 5′ to 3′, a standard gRNA comprises a target-binding region, a Cas9 handle recognized by the protein effector, and a terminator region.

Figure 2

Constitutively active terminator switch cgRNAs (ON → OFF logic) with silencing dCas9 in bacteria. (a) Conditional logic: if not X then not Y. (b) cgRNA mechanism: the constitutively active cgRNA is inactivated by hybridization of RNA trigger X. Rational sequence design of cgRNA terminator region (domains “d–e–f” comprising 6 nt linker, 4 nt stem, 30 nt loop) and complementary trigger region (domains “f*–e*–d*”). (c) Expression of RNA trigger X (40 nt unstructured + synthetic terminator hairpin) toggles the cgRNA from ON → OFF, leading to an increase in fluorescence. Single-cell fluorescence intensities via flow cytometry. Induced expression (aTc) of silencing dCas9 and constitutive expression of mRFP target gene Y and either: standard gRNA (ideal ON state), cgRNA (ON state), cgRNA + RNA trigger X (OFF state; trigger expression is IPTG-induced), no-target gRNA that lacks target-binding region (ideal OFF state). Autofluorescence (AF): cells with no mRFP. (d) Programmable conditional regulation using 3 orthogonal cgRNAs (A, B, C). Left: raw fluorescence depicting ON → OFF conditional response to cognate trigger (fold change = OFF/ON = [cognate trigger–AF]/[no trigger–AF]). Right: normalized fluorescence depicting orthogonality between noncognate cgRNA/trigger pairs (crosstalk = [noncognate trigger–no trigger]/[cognate trigger–no trigger]). Bar graphs depict mean ± estimated standard error calculated based on the mean single-cell fluorescence over 20 000 cells for each of N = 3 replicate wells (fold change and crosstalk calculated with uncertainty propagation).

Figure 3

Constitutively active splinted switch cgRNAs (ON → OFF logic) with silencing dCas9 in bacteria. (a) Conditional logic: if not X then not Y. (b) cgRNA mechanism: the constitutively active cgRNA is inactivated by hybridization of RNA trigger X. Rational sequence design of the 35 nt Cas9 handle loop (domain “d”) and an extended 35 nt terminator hairpin loop (domain “e”). (c) Expression of RNA trigger X (70 nt unstructured + synthetic terminator hairpin) toggles the cgRNA from ON → OFF, leading to an increase in fluorescence. Single-cell fluorescence intensities via flow cytometry. Induced expression (aTc) of silencing dCas9 and constitutive expression of sfGFP target gene Y and either: standard gRNA (ideal ON state), cgRNA (ON state), cgRNA + RNA trigger X (OFF state), or no-target gRNA that lacks target-binding region (ideal OFF state). Autofluorescence (AF): cells with no sfGFP. (d) Programmable conditional regulation using 3 orthogonal cgRNAs (A, B, C). Left: raw fluorescence depicting ON → OFF conditional response to cognate trigger (fold change = OFF/ON = [cognate trigger–AF]/[no trigger–AF]). Right: normalized fluorescence depicting orthogonality between noncognate cgRNA/trigger pairs (crosstalk = [noncognate trigger–no trigger]/[cognate trigger–no trigger]). Bar graphs depict mean ± estimated standard error calculated based on the mean single-cell fluorescence over 20 000 cells for each of N = 3 replicate wells (fold change and crosstalk calculated with uncertainty propagation).

Figure 4

Constitutively inactive toehold switch cgRNAs (OFF → ON logic) with silencing dCas9 in bacteria. (a) Conditional logic: if X then not Y. (b) cgRNA mechanism: the constitutively inactive cgRNA is activated by hybridization of RNA trigger X. Rational sequence design of the toehold (domain “d”; 15 nt) and loop (domain “e”; 8 nt) flanking the sequestration domain “u*” (20 nt). (c) Expression of RNA trigger X (35 nt unstructured + synthetic terminator hairpin) toggles the cgRNA from OFF → ON, leading to a decrease in fluorescence. Single-cell fluorescence intensities via flow cytometry. Induced expression (aTc) of silencing dCas9 and constitutive expression of mRFP target gene Y and either: no-target gRNA that lacks target-binding region (ideal OFF state), cgRNA (OFF state), cgRNA + RNA trigger X (ON state), or standard gRNA (ideal ON state). Autofluorescence (AF): cells with no mRFP. (d) Programmable conditional regulation using 3 orthogonal cgRNAs (A, B, C). Left: raw fluorescence depicting OFF → ON conditional response to cognate trigger (fold change = OFF/ON = [no trigger–AF]/[cognate trigger–AF]). Right: normalized fluorescence depicting orthogonality between noncognate cgRNA/trigger pairs (crosstalk = [noncognate trigger–no trigger]/[cognate trigger–no trigger]). Bar graphs depict mean ± estimated standard error calculated based on the mean single-cell fluorescence over 20 000 cells for each of N = 3 replicate wells (fold change and crosstalk calculated with uncertainty propagation).

Figure 5

Constitutively active terminator switch cgRNAs (ON → OFF logic) with inducing dCas9 in mammalian cells. (a) Conditional logic: if not X then Y. See Figure 2b for cgRNA mechanism: the constitutively active cgRNA is inactivated by hybridization of RNA trigger X (note that the mammalian cgRNA and trigger do not include the depicted synthetic terminator hairpins). (b) Expression of RNA trigger X (40 nt + hU6 terminator) toggles the cgRNA from ON → OFF, leading to a decrease in fluorescence. Single-cell fluorescence intensities via flow cytometry. Transfection of plasmids expressing inducing dCas9-VPR, dTomato target gene Y, and either: standard gRNA (ideal ON state), cgRNA (ON state), cgRNA + RNA trigger X (OFF state), or no-target gRNA that lacks target-binding region (ideal OFF state). Background (BACK): characterized using no-target gRNA control. (c) Programmable conditional regulation using 3 orthogonal cgRNAs (Q, R, S). Left: raw fluorescence depicting ON → OFF conditional response to cognate trigger (fold change = ON/OFF = [no trigger–BACK]/[cognate trigger–BACK]). Right: normalized fluorescence depicting orthogonality between noncognate cgRNA/trigger pairs (crosstalk = [noncognate trigger–no trigger]/[cognate trigger–no trigger]). Bar graphs depict mean ± estimated standard error calculated based on the mean single-cell fluorescence over 426–7714 cells for each of N = 3 replicate wells (fold change and crosstalk calculated with uncertainty propagation).

Figure 6

Computational cgRNA sequence design using NUPACK.^, (a) Target test tubes for design of 3 orthogonal cgRNAs A, B, and C (terminator switch mechanism of Figure 2). Left: elementary step tubes. Reactants tube (Step 0): cgRNA and trigger. Products tube (Step 1): cgRNA:trigger complex. Each target test tube contains a set of desired “on-target” complexes (each with the depicted target secondary structure and a target concentration of 10 nM) corresponding to the on-pathway hybridization products for a given step and a set of undesired “off-target” complexes (all complexes of up to 2 strands, each with a target concentration of 0 nM; not depicted) corresponding to on-pathway reactants and off-pathway hybridization crosstalk for a given step. To design 3 orthogonal systems, there are two elementary step tubes for each system A, B, and C. Right: global crosstalk tube. Contains the depicted on-target complexes corresponding to reactive species generated during Steps 0 and 1 (each with the depicted target secondary structure and a target concentration of 10 nM) as well as off-target complexes (all complexes of up to 2 strands, each with a target concentration of 0 nM; not depicted) corresponding to off-pathway interactions between these reactive species. To design 3 orthogonal systems, the global crosstalk tube contains a set of on-targets and off-targets for each system A, B, and C. (b) Analysis of design quality.^, Left: tubes depict the target structure and predicted concentration for each on-target complex with nucleotides shaded to indicate the probability of adopting the depicted base-pairing state at equilibrium. For this design, all on-targets are predicted to form with quantitative yield at the 10 nM target concentration, but some nucleotides have unwanted base-pairing interactions (nucleotides not shaded dark red). Right: computational orthogonality study. Predicted equilibrium concentration of each cgRNA:trigger complex for the 3 orthogonal systems of Figure 2 (one cgRNA species and one RNA trigger species per tube). RNA at 37 °C in 1 M Na⁺.