No abstract

We present a molecular-level model for the origin and evolution of the translation system, using a 3D comparative method. In this model, the ribosome evolved by accretion, recursively adding expansion segments, iteratively growing, subsuming, and freezing the rRNA. Functions of expansion segments in the ancestral ribosome are assigned by correspondence with their functions in the extant ribosome. The model explains the evolution of the large ribosomal subunit, the small ribosomal subunit, tRNA, and mRNA. Prokaryotic ribosomes evolved in six phases, sequentially acquiring capabilities for RNA folding, catalysis, subunit association, correlated evolution, decoding, energy-driven translocation, and surface proteinization. Two additional phases exclusive to eukaryotes led to tentacle-like rRNA expansions. In this model, ribosomal proteinization was a driving force for the broad adoption of proteins in other biological processes. The exit tunnel was clearly a central theme of all phases of ribosomal evolution and was continuously extended and rigidified. In the primitive noncoding ribosome, proto-mRNA and the small ribosomal subunit acted as cofactors, positioning the activated ends of tRNAs within the peptidyl transferase center. This association linked the evolution of the large and small ribosomal subunits, protomRNA, and tRNA.RNA evolution | translation | origin of life | A-minor interactions T he ribosome retains interpretable molecular records of a world of primordial molecules (1) from around 4 billion years ago (2-9). The records are maintained in rRNA secondary and 3D structures, which are fully conserved throughout the tree of life, and in rRNA sequences, which are more variable (SI Appendix, Fig. S1). Here we use information within ribosomes from each major branch of the tree of life to reconstruct much of the emergence of the universal translational machinery. Large Ribosomal Subunit EvolutionPreviously, we reported a 3D comparative method that revealed a molecular level chronology of the evolution of the large ribosomal subunit (LSU) rRNA (10). Insertion fingerprints are evident when comparing 3D structures of LSU rRNAs of various sizes from various species. These insertion fingerprints mark sites where rRNA expands, recording growth steps on a molecular level.Within the common core of the LSU rRNA, insertion fingerprints were used to identify ancient growth sites. We showed that insertion fingerprints provide a roadmap from the first steps in the formation of the peptidyl transferase center (PTC) (10) located in the ancient heart of the LSU (2-6), culminating in the common core.Small Ribosomal Subunit, LSU, tRNA, and mRNA Evolution Here, using the 3D comparative method, we establish a comprehensive and coherent model for the evolution of the entire ribosome. This model covers the LSU rRNA, small ribosomal subunit (SSU) rRNA, tRNA, and mRNA. The evolution of each of these components is reconciled at the molecular level to a common chronology. This evolutionary model, which we call the "accretion model," ...

The origins and evolution of the ribosome, 3-4 billion years ago, remain imprinted in the biochemistry of extant life and in the structure of the ribosome. Processes of ribosomal RNA (rRNA) expansion can be "observed" by comparing 3D rRNA structures of bacteria (small), yeast (medium), and metazoans (large). rRNA size correlates well with species complexity. Differences in ribosomes across species reveal that rRNA expansion segments have been added to rRNAs without perturbing the preexisting core. Here we show that rRNA growth occurs by a limited number of processes that include inserting a branch helix onto a preexisting trunk helix and elongation of a helix. rRNA expansions can leave distinctive atomic resolution fingerprints, which we call "insertion fingerprints." Observation of insertion fingerprints in the ribosomal common core allows identification of probable ancestral expansion segments. Conceptually reversing these expansions allows extrapolation backward in time to generate models of primordial ribosomes. The approach presented here provides insight to the structure of pre-last universal common ancestor rRNAs and the subsequent expansions that shaped the peptidyl transferase center and the conserved core. We infer distinct phases of ribosomal evolution through which ribosomal particles evolve, acquiring coding and translocation, and extending and elaborating the exit tunnel.RNA evolution | C value | origin of life | translation | phylogeny T he translation system, one of life's universal processes, synthesizes all coded protein in living systems. Our understanding of translation has advanced over the last decade and a half with the explosion in sequencing data and by the determination of 3D structures (1-4). X-ray crystallography and cryoelectron microscopy (cryo-EM) have provided atomic resolution structures of ribosomes from all three domains of life. Eukaryotic ribosomal structures are now available from protists (5), fungi (6), plants (7), insects, and humans (8). Here we describe an atomic level model of the evolution of ribosomal RNA (rRNA) from the large ribosomal subunit (LSU). Our evolutionary model is grounded in patterns of rRNA growth in relatively recent ribosomal expansions, for which there is an extensive, atomicresolution record.The common core LSU rRNA (9, 10), which is approximated here by the rRNA of Escherichia coli, is conserved over the entire phylogenetic tree, in sequence, and especially in secondary structure (11) and 3D structure (12). By contrast, the surface regions and the sizes of ribosomes are variable (13,14). Most of the size variability is found in eukaryotic LSUs (Fig. 1). The integrated rRNA size in the LSU follows the trend Bacteria ≤ Archaea < Eukarya. The added rRNA in eukaryotes interacts with eukaryotic-specific proteins (5, 8, 9) (SI Appendix, Fig. S1 and Dataset S1).Bacterial and archaeal LSU rRNAs are composed entirely of the common core, with only subtle deviations from it. By contrast, eukaryotic LSU rRNAs are expanded beyond the common core. Sacccharomyce...

Hfq, a bacterial RNA-binding protein, was recently shown to contain the Sm1 motif, a characteristic of Sm and LSm proteins that function in RNA processing events in archaea and eukaryotes. In this report, comparative structural modeling was used to predict a three-dimensional structure of the Hfq core sequence. The predicted structure aligns with most major features of the Methanobacterium thermoautotrophicum LSm protein structure. Conserved residues in Hfq are positioned at the same structural locations responsible for subunit assembly and RNA interaction in Sm proteins. A highly conserved portion of Hfq assumes a structural fold similar to the Sm2 motif of Sm proteins. The evolution of the Hfq protein was explored by conducting a BLAST search of microbial genomes followed by phylogenetic analysis. Approximately half of the 140 complete or nearly complete genomes examined contain at least one gene coding for Hfq. The presence or absence of Hfq closely followed major bacterial clades. It is absent from high-level clades and present in the ancient Thermotogales-Aquificales clade and all proteobacteria except for those that have undergone major reduction in genome size. Residues at three positions in Hfq form signatures for the beta/gamma proteobacteria, alpha proteobacteria and low GC Gram-positive bacteria groups.

Accurate secondary structures are important for understanding ribosomes, which are extremely large and highly complex. Using 3D structures of ribosomes as input, we have revised and corrected traditional secondary (2°) structures of rRNAs. We identify helices by specific geometric and molecular interaction criteria, not by co-variation. The structural approach allows us to incorporate non-canonical base pairs on parity with Watson-Crick base pairs. The resulting rRNA 2° structures are up-to-date and consistent with three-dimensional structures, and are information-rich. These 2° structures are relatively simple to understand and are amenable to reproduction and modification by end-users. The 2° structures made available here broadly sample the phylogenetic tree and are mapped with a variety of data related to molecular interactions and geometry, phylogeny and evolution. We have generated 2° structures for both large subunit (LSU) 23S/28S and small subunit (SSU) 16S/18S rRNAs of Escherichia coli, Thermus thermophilus, Haloarcula marismortui (LSU rRNA only), Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. We provide high-resolution editable versions of the 2° structures in several file formats. For the SSU rRNA, the 2° structures use an intuitive representation of the central pseudoknot where base triples are presented as pairs of base pairs. Both LSU and SSU secondary maps are available (http://apollo.chemistry.gatech.edu/RibosomeGallery). Mapping of data onto 2° structures was performed on the RiboVision server (http://apollo.chemistry.gatech.edu/RiboVision).

Hfq is a RNA-binding protein in Escherichia coli that plays an essential role in post-transcriptional regulation of mRNAs by facilitating pairing of noncoding RNAs (ncRNAs) to mRNA target sites. Recent work has provided evidence that E. coli Hfq has two distinct RNA-binding surfaces. In this study, a comparative sequence-structure analysis of hfq genes in bacterial genomes was employed to identify conserved residues that may be involved in binding RNA. A covariance of residue properties at neighboring positions 12 and 39 and conserved surface residues with high propensities at binding sites of RNA-binding proteins suggested several sites for Hfq-RNA interactions. On the basis of these predictions, eight mutant Hfq proteins were produced and their interactions were examined with the 38 nucleotide (nt) domain II of DsrA ncRNA (DsrA(DII)) and A(18) by a gel-mobility shift assay, fluorescence anisotropy, and fluorescence quenching. Mutations on the proximal surface of Hfq had a small affect on Hfq binding to A(18) (

Temperature-gradient gel electrophoresis (TGGE) was employed to determine the thermal stabilities of 48 DNA fragments that differ by single base pair mismatches. The approach provides a rapid way for studying how specific base mismatches effect the stability of a long DNA fragment. Homologous 373 bp DNA fragments differing by single base pair substitutions in their first melting domain were employed. Heteroduplexes were formed by melting and reannealing pairs of DNAs, one of which was 32P-labeled on its 5'-end. Product DNAs were separated based on their thermal stability by parallel and perpendicular temperature-gradient gel electrophoresis. The order of stability was determined for all common base pairs and mismatched bases in four different nearest neighbor environments; d(GXT).d(AYC), d(GXG).d(CYC), d(CXA).d(TYG), and d(TXT).d(AYA) with X,Y = A, T, C, or G. DNA fragments containing a single mismatch were destabilized by 1 to 5 degrees C with respect to homologous DNAs with complete Watson-Crick base pairing. Both the bases at the mismatch site and neighboring stacking interactions influence the destabilization caused by a mismatch. G.T, G.G and G.A mismatches were always among the most stable mismatches for all nearest neighbor environments examined. Purine.purine mismatches were generally more stable than pyrimidine.pyrimidine mispairs. Our results are in very good agreement with data where available from solution studies of short DNA oligomers.

The regions upstream from forty-three procaryotic promoters were examined for nucleotide distributions which have been associated with DNA curvature. The analysis procedure assigned a DNA curvature score based on the phasing of the 5' and 3' ends of An and Tn tracts, n greater than or equal to 3. The weighting scheme for the curvature score was based on recent studies which showed that tracts of An and Tn periodically phased with the helix repeat cause DNA curvature. Results show that promoters which have high transcription initiation rates in vivo tend to have high curvature scores in their upstream regions. Regions downstream from the transcription start-point do not have sequences correlated with DNA curvature. Four promoters which have been shown to have upstream activation regions have curvature scores above 1.5 in their -40 to -150 regions. The correlations observed lend support to the hypothesis that DNA curvature is associated with upstream activation of transcription.