Solution structure of RNase P RNA

Abstract

The ribonucleoprotein enzyme ribonuclease P (RNase P) processes tRNAs by cleavage of precursor-tRNAs. RNase P is a ribozyme: The RNA component catalyzes tRNA maturation in vitro without proteins. Remarkable features of RNase P include multiple turnovers in vivo and ability to process diverse substrates. Structures of the bacterial RNase P, including full-length RNAs and a ternary complex with substrate, have been determined by X-ray crystallography. However, crystal structures of free RNA are significantly different from the ternary complex, and the solution structure of the RNA is unknown. Here, we report solution structures of three phylogenetically distinct bacterial RNase P RNAs from Escherichia coli, Agrobacterium tumefaciens, and Bacillus stearothermophilus, determined using small angle X-ray scattering (SAXS) and selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) analysis. A combination of homology modeling, normal mode analysis, and molecular dynamics was used to refine the structural models against the empirical data of these RNAs in solution under the high ionic strength required for catalytic activity.

FIGURE 1.

Bacterial RNAse P RNA structures. (A) Crystal structures of RNase P RNA from B. stearothermophilus (B-type) and T. maritima (A-type). Paired elements of the structure (P1, P2, etc.) are labeled in the order of their occurrence from the 5′-end. (B) Secondary structure of the B-type RNase P RNA (B. stearothermophilus). Dashed lines mark independently folding structural domains. Solid lines indicate long-range docking interactions. Helical elements of the structure are labeled and colored according to A. (C) Secondary structures of the A-type RNase P RNAs, from E. coli and A. tumefaciens.

FIGURE 2.

Sample preparation for SAXS experiments. (A) Chromatographic profiles of RNA samples prepared by different techniques. RNA from A. tumefaciens (“Atu”), B. stearothermophilus (“Bst”), or E. coli (“Eco”) was prepared by refolding from denatured state (“annealed”), nondenaturing method according to Batey and Kieft (2007) (“native”) or by transcription at elevated ionic strength and nondenaturing purification (“HS native”), and analyzed by high-resolution gel-filtration chromatography on Shodex KW 803. Absorbance at 254 nm is plotted versus retention time. (B) Kratky plot representation of the scattering data from RNA samples prepared by HS native method.

FIGURE 3.

(Top) All-atom models of the RNase P RNA variants. RNA models were generated in silico by taking into account available crystallographic and phylogenetic information. Elements of the structure are colored according to Figure 1. (Middle) Agreement between theoretical scattering profiles calculated from the models (red line) and experimental SAXS data (open circles). (Bottom) Distribution of the residuals (I_data/I_model) vs. q.

FIGURE 4.

Conformational pools for ensemble optimization. (A) All-atom models of Bst and Eco RNase P RNA perturbed along five lowest elastic normal modes. Ribbon diagrams of the 50 endpoints of perturbation trajectories are shown on the left, colored according to Figure 1. R_g and D_max frequency distributions plotted on a relative scale illustrate spread of these values in the pools of the 1051 conformations used for ensemble optimization (“Pool freq.”). R_g and D_max distributions in a typical optimized ensemble of 10 conformations that fit the experimental data best (Fig. 5) are also shown (“Sel. Freq.”). (Far right) Dependence of the goodness-of-fit parameter χ² on the size of optimized ensemble n (n = 0 corresponds to the unperturbed models shown in Fig. 3). (B) Conformational pools for ensemble optimization of Atu RNA. (Top) Ribbon diagrams of the 50 endpoints of perturbations along elastic normal modes (“NMA”) are compared with the endpoints of 104 torsion molecular dynamics trajectories (“MD”) and to 65 conformations selected at random from a pool of 12,684 conformations obtained by filtering the MD pool to exclude conformations with unrealistic R_g and D_max (“Filtered”). (Bottom) R_g and D_max frequency distributions plotted on absolute scale illustrate spread of these values in the conformational pools prepared by NMA perturbations (“NMA”, 1051 conformations), torsion MD simulations (“MD”, 52,000 conformations), or filtered pool combined with the NMA-perturbed pool (13,735 conformations). R_g and D_max distributions in a typical optimized ensemble of 10 conformations that fit experimental data best (Fig. 5) are also shown on relative scale (“EOM”). (Far right) Dependence of the goodness-of-fit parameter χ² on the size of optimized ensemble n for selections from a pool of 1051 NMA-perturbed conformations (“NMA”) compared with the selections from a pool of 13,735 filtered MD conformations (“Filtered”); n = 0 corresponds to the unperturbed model shown in Figure 3.

FIGURE 5.

Representative conformational ensembles that fit SAXS data best. Typical optimized ensembles of indicated size selected for Bst and Eco RNA from the pools of 1051 NMA-perturbed conformations and for Atu RNA from a pool of 13,735 filtered MD-perturbed conformations. For each RNA, minimal ensembles that fit experimental data best are shown on the right, superimposed onto the unperturbed model from Figure 3 (black ribbon).