A protein-RNA specificity code enables targeted activation of an endogenous human transcript

Abstract

Programmable protein scaffolds that target DNA are invaluable tools for genome engineering and designer control of transcription. RNA manipulation provides broad new opportunities for control, including changes in translation. PUF proteins are an attractive platform for that purpose because they bind specific single-stranded RNA sequences by using short repeated modules, each contributing three amino acids that contact an RNA base. Here, we identified the specificities of natural and designed combinations of those three amino acids, using a large randomized RNA library. The resulting specificity code reveals the RNA binding preferences of natural proteins and enables the design of new specificities. Using the code and a translational activation domain, we designed a protein that targets endogenous cyclin B1 mRNA in human cells, increasing sensitivity to chemotherapeutic drugs. Our study provides a guide for rational design of engineered mRNA control, including translational stimulation.

Figure 1. RNA recognition by the PUF proteins

(A) The structure of C. elegans FBF-2 bound to RNA . RNA recognition is modular; each PUF repeat contributes an RNA recognition helix. (Inset) Three amino acid residues (referred to as a Tripartite Recognition Motif or TRM) form edge-on contacts (red lines) and stacking interactions (blue lines) with RNA bases (not all atoms are shown). By convention, the two edge-on residues are given in the same order in which they are found in the primary sequence (SE), followed by a dash and the stacking residue (H). (B) Abundance of natural TRMs inferred from sequence alignment. Pie charts represent TRM enrichment as a function of PUF repeat (R8-R1) based on 94 proteins.

Figure 2. A quantitative TRM recognition code

(A) Experimental overview. TRM substitutions are introduced in PUF repeat 7 of FBF-2. The predicted site of variation is base +2 in the RNA sequence. TRM mutants are analyzed using the SEQRS technique (see text). (B) Hierarchical clustering reveals three classes of TRM binding specificity. Left, highly enriched 10-mer sequences for each TRM were identified (Y-axis) and the enrichment values were used to cluster similar binding profiles for each mutant (X-axis). For each TRM, the data were normalized to the maximum enrichment value. Right, three clusters were identified empirically and a representative motif was generated. (C) Sequence logos for members of cluster A reveal a common specificity consistent with the results from clustering (Top). The innermost ring contains sequences perfectly matched to a given seed motif, while subsequent rings contain increasing numbers of mismatches from that seed motif. SSLs for three representative TRMs reveal non-equivalent differences in overall specificity (Bottom). (D) Enrichment at position +2 of the PUF binding element. The relative enrichment for G (yellow), U (red), A (green), and C (blue). TRMs previously described as preferential C-binders, SR–Y, AR–Y, and CR–Y, are italicized^,. The remaining synthetic combinations are underlined.

Figure 3. Prediction and distribution of specificity in nature

(A) Predictions of specificity in vitro. Prediction of specificity of uncharacterized PUF proteins from Dictyostelium dictyostelium. Motifs depicting specificities were generated from primary sequence (predicted) and compared to experimentally determined motifs by SEQRS (observed). (B) Prediction of and occupancy in vivo. Frequency plots represent predicted specificity from TRM data, a previously described SEQRS analysis of PUM2, an in vivo binding motif derived from photo-crosslinking, or a mock where G bases were replaced with C bases ^,. (C) The distribution of specificity in natural PUF proteins. The black line denotes a smoothed fit to the observed data. Both TRM repeats and RNA bases have been subjected to extensive mutagenesis in prior work for Puf3p, FBF-2, and Puf4p . That data is compiled in the right panel (“Relative mutability”), and reveals the average tolerance of the base or TRM to substitution for each repeat.

Figure 4. Modifications of PUF scaffolds using the TRM code

TRM variants are denoted as colored circles and RNAs as colors in bar charts according to the key. RNA sequences are provided for variant sites. Red nucleotides indicate sites that differ from the wild-type sequence. Binding activity measurements were conducted in the yeast-three hybrid system. (A) Replacement of TRMs in the PUM2 scaffold yields protein mutants with novel specificity. Most specificity mutants possessed binding activities comparable to that of the wild-type protein and RNA binding element. Error bars, s.d. (n = 3 independent colonies). (B) Mutations in FBF-2 yield altered specificity. Error bars, s.d. (n = 3 independent colonies). (C) Additivity of specificity mutations in PUM2. Sites of comparison between TRMs are highlighted in blue. Error bars, s.d. (n = 3 independent colonies).

Figure 5. Engineered specificity of PUF proteins

(A) Sequence motifs of wild-type (WT) and redesigned (neo-PUF) proteins. The targeted recognition site possesses a single substitution at position seven of the binding element. (B) Analysis of RNA binding activity in a yeast three-hybrid assay. RNA binding for wild-type (blue) and neo-PUF (orange) measurements for an empty vector, positive control gld-1 RNA element, and the cyclin B1 targeting element are shown. Error bars, s.d. (n = 3 independent colonies). (C) Binding enrichment values for the neo-PUF and the wild-type proteins were calculated for the in vitro consensus sequence HUGURWWWU and subtracted (Wt-Neo) . On the vertical axis are arrayed 384 sequences – a subset of the 4 possible 10-mers analyzed computationally – arranged in logical order by sequence. A subset of the sequences shown on the right, posses sequences altered at positions +7 and +9. The plots indicate the degree of enrichment either for the wild-type or neo-PUF proteins. Values are shaded as in A, with positive enrichments shaded green to red and negative enrichments shaded light to dark blue.

Figure 6. Manipulation of translation using a modified PUF scaffold

(A) Effects of a neo-activator on Cyclin B1 levels in U2OS cells measured by western blotting. (right - quantification). Error bars, s.d. (n = 3 cell cultures) * P < 0.05, ** P < 0.05, by two-tailed Student's t test. (B) Immunofluorescence of Cyclin B1 expression in U2OS cells expressing the Neo-activator (right - quantification). Error bars, s.d. (n = 3 cell cultures) * P < 0.05, ** P < 0.05 by two-tailed Student's t test. Slides were observed under the same microscope using identical parameters (scale bar = 100 μm). (C) Viability assays. Viability was quantified 24 hours post-treatment. Normalized cell death is shown for two M-phase targeting drugs . Cyclin B1 was overexpressed as a positive control. Error bars, s.d. (n = 3 cell cultures) * P < 0.05, ** P < 0.05 by two-tailed Student's t test.