Engineered dCas9 with reduced toxicity in bacteria: implications for genetic circuit design

Abstract

Large synthetic genetic circuits require the simultaneous expression of many regulators. Deactivated Cas9 (dCas9) can serve as a repressor by having a small guide RNA (sgRNA) direct it to bind a promoter. The programmability and specificity of RNA:DNA basepairing simplifies the generation of many orthogonal sgRNAs that, in theory, could serve as a large set of regulators in a circuit. However, dCas9 is toxic in many bacteria, thus limiting how high it can be expressed, and low concentrations are quickly sequestered by multiple sgRNAs. Here, we construct a non-toxic version of dCas9 by eliminating PAM (protospacer adjacent motif) binding with a R1335K mutation (dCas9*) and recovering DNA binding by fusing it to the PhlF repressor (dCas9*_PhlF). Both the 30 bp PhlF operator and 20 bp sgRNA binding site are required to repress a promoter. The larger region required for recognition mitigates toxicity in Escherichia coli, allowing up to 9600 ± 800 molecules of dCas9*_PhlF per cell before growth or morphology are impacted, as compared to 530 ± 40 molecules of dCas9. Further, PhlF multimerization leads to an increase in average cooperativity from n = 0.9 (dCas9) to 1.6 (dCas9*_PhlF). A set of 30 orthogonal sgRNA-promoter pairs are characterized as NOT gates; however, the simultaneous use of multiple sgRNAs leads to a monotonic decline in repression and after 15 are co-expressed the dynamic range is <10-fold. This work introduces a non-toxic variant of dCas9, critical for its use in applications in metabolic engineering and synthetic biology, and exposes a limitation in the number of regulators that can be used in one cell when they rely on a shared resource.

Figure 1.

Design and evaluation of a dCas9 – transcription factor fusion. (A) A schematic of targeted repression by dCas9-sgRNA complex bound to the promoter region of a fluorescent reporter gene (RFP, red fluorescent protein). (B) A detailed schematic of the fused protein bound to a promoter is shown. DBD is the DNA-binding domain that is fused to dCas9. GGN is the PAM site. R1335K is the mutation that reduces the PAM recognition ability of dCas9. (C) The impact of changes to the fused protein and promoter on the response. The fold-repression is calculated as the ratio of uninduced to induced (1 mM IPTG) cells (Methods). All constructs other than the first are based on dCas9* (R1335K). F and R represent the forward and reverse orientations of the Zif268 operator. ΔHNH refers to the deletion of this domain. L88 shows the impact of a longer linker. The size of the spacer between the -35 and operator sequence is shown as SN, where N is the number of bp. Sequences and plasmid maps are shown in Supplementary Figure S12 and Supplementary Table S2. SrpR, HlyIIR and BM3RI are all TetR-family repressors that were tested as alternatives to PhlF. (D) The growth impact of dCas9 and dCas9*_PhlF is compared to the pSZ_Backbone plasmid (Supplementary Figure S12) as a control. Protein expression is controlled using the aTc-inducible system and the x-axis is shown in units of fluorescence for the pTet promoter, measured separately (Supplementary Figure S1). The dashed line shows 2.5 ng/ml aTc, used in E for morphology studies. The arrows point to the inducer levels (0.7 ng/ml and 2.5 ng/ml) where the protein concentrations are determined in Figure 1G. Media and growth conditions are provided in the Materials and Methods. (E) Microscopic images of E. coli strains expressing PhlF, dCas9 or dCas9*_PhlF variants and a control (Backbone) are shown, under identical conditions as used for the growth curves. The scale bars are 5 μm. The corresponding FSC-A/SSC-A distribution of each strain was measured by flow cytometry (Materials and Methods). (F) The fold-repression of the construct (pSZ_PhlF plasmid in Supplementary Figure S12 and the pPhlF_S6 promoter from Supplementary Table S2) is shown as a function of dCas9*_PhlF expression. The sgRNA is under the control of the pTac promoter and all data are for 1 mM IPTG. The x-axis is the same as described in D. The line shows a fit to a Hill equation. For B–F, the data are shown as the mean of three experiments performed on different days and the error bars are the standard deviation. (G) A representative immunoblotting assay is shown for calculating the number of dCas9 per cell. The dashed lines show the interpolation used to estimate concentrations. The calculation is described in the Methods and the numbers presented in the text are based on three experiments performed on different days (Supplementary Figure S3).

Figure 2.

NOT gates based on dCas9*_PhlF. (A) The schematic of the gate is shown. The input and output to the gate are pTac and p9. Part sequences and plasmid maps are provided in Supplementary Figure S12 and Supplementary Table S3. (B) The response curves of dCas9-based NOT gates are shown (Methods). The input is the activity of the pTac promoter as a function of IPTG concentration, measured separately (Supplementary Figure S1). The concentration of dCas9*_PhlF was maintained by adding 2.5 ng/ml aTc and 0.7 ng/ml for dCas9. (C) The response functions of 30 NOT gated based on orthogonal pairs of sgRNAs and promoters. The sequences are provided in Supplementary Figure S11. The data were fit to Equation (1) and the resulting parameters are provided in Supplementary Table S1. (D) Evaluation of cascades of different length. The detailed parts used in the genetic systems are shown in Supplementary Figure S13. The color of the gate indicates the sgRNA:promoter pair used (blue: sgRNA2, light blue: sgRNA8, green: sgRNA9, orange: sgRNA3). The input to the gate is the vanillic acid inducible promoter (pVan) and the x-axis is the activity of this promoter at different levels of inducer, measured separately (Supplementary Figure S1). The color of the data corresponds to the last gate of the cascade. The fits to the data are the responses predicted by combining the response functions of each layer of the cascade. The response functions of the individual gates and the predicted propagation of the signal through the cascade are shown at the bottom (Methods). All of the data in this Figure are shown as the mean of three experiments performed on different days and the error bars are the standard deviation.

Figure 3.

The impact of simultaneous expression of multiple sgRNAs. (A) Expression of sgRNA9 was fully induced (10 mM choline, activating pBetI) to measure fold-repression of promoter p9 (orange), while the expression level of sgRNA10 (green) was induced by adding different levels of vanillic acid. The activity of the pVan promoter was measured separately as a function of vanillic acid concentration (Supplementary Figure S1). The detailed parts used in the genetic systems are shown in Supplementary Figure S13. Solid lines are model prediction results. (B) The impact of expressing multiple sgRNAs simultaneously. The repression fold change of promoter p9 was measured with or without the addition 100 μM vanillic acid. The constructs containing different numbers of sgRNAs are shown to the right. The sequences corresponding to the promoters and terminators are provided in Supplementary Table S3. The sgRNAs are labeled sgN where N corresponds to the sequences in Supplementary Figure S11. The horizontal line marks 10-fold repression, roughly the minimum required for useful NOT gates. For dCas9*_PhlF, the fit parameters for Equations (11) and (12) are β = 3.0 × 10⁻¹¹ Ms⁻¹, α₁ = 7.6 × 10⁻¹² Ms⁻¹, α_x = 2.3 × 10⁻¹¹ Ms⁻¹, K = 1.7 × 10⁻⁸ M, n = 0.9. For dCas9, the fit parameters are: β = 3.0 × 10⁻¹¹ Ms⁻¹, α₁ = 7.6 × 10⁻¹² Ms⁻¹, α_x = 2.3 × 10⁻¹¹ Ms⁻¹, K = 2.9 × 10⁻⁹ M, n = 1.1, In both parts, the data are shown as the mean of three experiments performed on different days and the error bars are the standard deviation.