Hidden specificity in an apparently nonspecific RNA-binding protein

Abstract

Nucleic-acid-binding proteins are generally viewed as either specific or nonspecific, depending on characteristics of their binding sites in DNA or RNA. Most studies have focused on specific proteins, which identify cognate sites by binding with highest affinities to regions with defined signatures in sequence, structure or both. Proteins that bind to sites devoid of defined sequence or structure signatures are considered nonspecific. Substrate binding by these proteins is poorly understood, and it is not known to what extent seemingly nonspecific proteins discriminate between different binding sites, aside from those sequestered by nucleic acid structures. Here we systematically examine substrate binding by the apparently nonspecific RNA-binding protein C5, and find clear discrimination between different binding site variants. C5 is the protein subunit of the transfer RNA processing ribonucleoprotein enzyme RNase P from Escherichia coli. The protein binds 5' leaders of precursor tRNAs at a site without sequence or structure signatures. We measure functional binding of C5 to all possible sequence variants in its substrate binding site, using a high-throughput sequencing kinetics approach (HITS-KIN) that simultaneously follows processing of thousands of RNA species. C5 binds different substrate variants with affinities varying by orders of magnitude. The distribution of functional affinities of C5 for all substrate variants resembles affinity distributions of highly specific nucleic acid binding proteins. Unlike these specific proteins, C5 does not bind its physiological RNA targets with the highest affinity, but with affinities near the median of the distribution, a region that is not associated with a sequence signature. We delineate defined rules governing substrate recognition by C5, which reveal specificity that is hidden in cellular substrates for RNase P. Our findings suggest that apparently nonspecific and specific RNA-binding modes may not differ fundamentally, but represent distinct parts of common affinity distributions.

Fig. 1. Processing of ptRNA with randomized leader sequences

(a) ptRNA processing reaction by RNase P. (b) Structure of the RNase P holoenzyme . (c) Sequences of non-initiator ptRNA^Met leaders (reference: black; randomized: red). The tRNA body is omitted for clarity. The arrow indicates the cleavage site. (d) Timecourses of RNase P processing of ptRNA^Met82 (black), and ptRNA^Met(-3-8N) (red), in the presence (filled circles), and in the absence of C5 (open circles). The solid lines are fits to the integrated rate equation for a biphasic first order reaction. (e) PAGE of reactions processed for Illumina sequencing. (f) Distributions of species for individual timepoints, ranked from fastest to slowest. Distributions are normalized to t = 0.

Fig. 2. Discrimination of C5 between different ptRNA^Met leader sequences

(a) Relative rate constants (^rk) for processing of all ptRNA leader sequence variants, ranked from slow to fast. Relative rate constants are averaged from four values (two timepoints of two experiments) and shown for only sequences where data from all four measurements passed quality control criteria (Extended Data Tab. 1). The line at ^rk = 1 marks the reference sequence. (b) Correlation of relative rate constants from two independent biological replicates (red line: linear fit through the data, R²: correlation coefficient). (c) Correlation between relative rate constants obtained by PAGE and by the HiTS-Kin approach for selected sequence variants. Error bars represent the standard deviation of multiple individual experiments. (d) Distribution of relative rate constants for processing of ptRNA^Met(-3-8N) sequence variants by C5 (black) and apparent affinities for DNA binding by the transcription factor Arid3a, indicated as Z-scores based on published microarray data . The Z-score is not identical to ^rk values, but accurately reflects affinity-based ranking of all sequences (triangles: ^rk values for genomic leader sequences of ptRNA^Met). (e) Plot of all sequence variants ranked from slowest to fastest processed. The bracket marks of 0.3% of sequence variants with the largest relative rate constants. (f) Sequence logo for this fraction.

Fig. 3. Rules for sequence discrimination by C5

(a) Correlation between observed ^rk and values calculated with the best fit of the data to models of increasing complexity. Logarithmic ^rk values are used because of their correspondence to differences in binding energies . R² expresses the correlation of each model with measured processing rate constants. (b) Functional coupling between two base positions. Yellow squares show promotion of processing (high linear coefficients), black squares indicate small or no effects, blue squares mark inhibition of processing.