Sávio Torres de Farias

Preferred codons and amino acid couples in hyperthermophiles

BackgroundMost organisms grow at temperatures from 20 to 50°C but some prokaryotes, including Archaea and Bacteria, are capable of withstanding higher temperatures, from 60 to >100°C. What makes these cells so resistant to heat? Their biomolecules must be sufficiently stable, especially proteins, to work under these extreme conditions, but the bases for thermostability remains elusive.ResultsThe preferential usage of certain couples of amino acids and codons in thermal adaptation was investigated, by comparative proteome analysis, using 28 complete genomes from 18 mesophiles, 4 thermophiles, and 6 hyperthermophiles. In the hyperthermophiles proteomes, whenever the percent of Glu (E) and Lys (K) Increased, the percent of Gln (Q) and His (H) decreased, so that the E+K/Q+H ratio was > 4,5; in the mesophiles proteomes, it was < 2,5 and in the thermophiles an intermediary value was observed. The E+K/Q+H ratios for chaperonins, potentially thermostable proteins, were higher than their proteome ratios whereas, for DNA ligases, not necessarily thermostable, they followed the proteome ones. Analysis of codon usage revealed that hyperthermophiles preferred AGR codons for Arg in detriment of CGN codons, which were preferred by mesophiles.ConclusionsThe results suggested that the E+K/Q+H ratio may provide a useful mark for distinguishing hyperthermophilic, thermophilic and mesophilic prokaryotes and that the high percent of the amino acid couple E+K, consistently associated to the low percent of the pair Q+H, could contribute to protein thermostability. Second, the preference for AGR codons for Arg was a signature of all hyperthermophilics so far analyzed.

Origin and evolution of the Peptidyl Transferase Center from proto‐tRNAs

We tested the hypothesis of Tamura (2011) [3] that molecules of tRNA gave origin to ribosomes, particularly to the Peptidyl Transferase Center (PTC) of the 23S ribosomal RNA. We reconstructed the ancestral sequences from all types of tRNA and compared them in their sequences with the current PTC of 23S ribosomal RNA from different organisms. We built an ancestral sequence of proto‐tRNAs that showed a remarkable overall identity of 50.53% with the catalytic site of PTC. We conclude that the Peptidyl Transferase Center was indeed originated by the fusion of ancestral sequences of proto‐tRNA.

Structure of the genetic code suggested by the hydropathy correlation between anticodons and amino acid residues.

The correlation between hydropathies of anticodons and amino acids, detected by other authors utilizing scales of amino acid molecules in solution, was improved with the utilization of scales of amino acid residues in proteins. Three partitions were discerned in the correlation plot with the principal dinucleotides of anticodons (pDiN, excluding the wobble position). (a) The set of outliers of the correlation: Gly-CC, Pro-GG, Ser-GA and Ser-CU. The amino acids are consistently small, hydro-apathetic, stabilizers of protein N-ends, preferred in aperiodic protein conformations and belong to synthetases class II. The pDiN sequences are representative of the homogeneous sector (triplets NRR and NYY), distinguished from the mixed sector (triplets NRY and NYR), that depict a 70% correspondence to the synthetases class II and I, respectively. The triplet pairs proposed to be responsible for the coherence in the set of outliers are of the palindromic kind, where the lateral bases are the same, CCC: GGG and AGA: UCU. This suggests that UCU previously belonged to Ser, adding to other indications that the attribution of Arg to YCU was due to an expansion of the Arg-tRNA synthetase specificity. The other attributions produced two correlation sets. (b) One corresponds to the remaining pDiN of the homogeneous sector, containing both synthetase classes; its regression line overlapped the one formed by the remaining attributions to class II. (c) The other contains the pDiN of the mixed sector and produced steeper slopes, especially with the class I attributions. It is suggested that the correlation was established when the amino acid composition of the protein synthetases became progressively enriched and that the set of outliers were the earliest to have been fixed.

Evolution of transfer RNA and the origin of the translation system.

The origin of the translation system is at the center of discussions about the evolution of biological systems. In this context, molecules of transfer RNA (tRNA) are highlighted due to its ability to convey the information contained in nucleic acids with the functional information contained in the proteins. Despite many characteristics shared among tRNAs in various organisms, suggesting a monophyletic origin for this group of molecules, recent discussions have proposed a polyphyletic origin for this group, thus indicating that the shared features are products of evolutionary convergence (Di Giulio, 2013). The main arguments in favor of the model for polyphyletic origin of tRNAs, is based on the theory of exons and suggests that the introns played an important role uniting mini exons or genes, which enabled that minigenes with independent origins were grouped in a single transcription unit at the start of the biological system (Di Giulio, 2012a). Genes for tRNAs have one of the most conserved introns that we know, which would represent a remnant of the process that gave rise to this molecule, being the anticodon loop initially a minigene that was attached to the other loop or hairpin that gave origin to the modern structure of tRNAs (Di Giulio, 2012b). An evidence of this model was found in Nanoarchaeum equitans, where a single tRNA is encoded by two genes that are united after the transcription (Randau et al., 2005). Podar et al. (2013), analyzed the genome of N. equitans and suggested that the organization of genes in this organism is a derived character, being consequence of a process of genomic reduction that is associated with their lifestyle (Podar et al., 2013). Thus, the tRNAs would be monophyletic, having a single ancestor that gave origin to the diversity known today, as suggested by Lacey and Staves (1990).

A self-referential model for the formation of the genetic code

A model for the formation of the genetic code is presented where protein synthesis is directed initially by tRNA dimers. Proteins that are resistant to degradation and efficient RNA-binders protect the RNAs. Replication becomes elongational producing poly-tRNAs from which the mRNAs and ribosomes are derived. Attributions are successively fixed to tRNAs paired through the perfect palindromic anticodons, with the same bases at the extremities (5′ANA: UNU 3′; GNG: CNC; principal dinucleotides, pDiN). The 5′ degeneracy is then developed. The first pairs to be encoded correspond to the hydropathy correlation outliers (Gly-CC: Pro-GG and Ser-GA: Ser-CU) and to the sector of homogeneous pDiN, composed by two pyrimidines or two purines. These amino acids are preferred in the N-ends of proteins, stabilizers of proteins against catabolism and strong RNA-binders. The next pairs complete the sector of homogeneous pDiN (Asp, Glu-UC: Leu-AG and Asn, Lys-UU: Phe-AA). This set of nine amino acids forms the protein cores with the predominant aperiodic conformation. Next enter the pairs with mixed pDiN (one purine and one pyrimidine), the RY attributions composing the protein N-ends and the YR attributions the C-ends. The last pair contains the main punctuation signs (Ile, Met, iMet-AU: Tyr, Stop-UA). The model indicates that genetic information emerged during the process of formation of the coding/decoding system and that genes were defined by the proteins. Stable proteins constructed the nucleoprotein system by binding to the RNAs that produced them. In this circular rationale, genes are memories in a metabolic system for production of proteins that stabilize it. The simplicity and the highly deterministic character of the process suggest that the Last Universal Common Ancestor populations could be composed, in early stages, of lineages bearing similar genetic codes.

Suggested phylogeny of tRNAs based on the construction of ancestral sequences

The origin and evolution of life on the planet is one of the most intriguing challenges in life sciences and, for some researchers, it is centered in the origin of the genetic code. Many hypotheses about the origin and evolution of tRNA have been proposed and in this work a new suggestion is proposed based on the reconstruction of tRNA ancestor sequences. Ancestral sequences of 22 types of tRNA molecules were built by maximum likelihood from 9758 sequences currently reported from different organisms. Phylogenetic analysis showed that the main force for evolutionary diversification of tRNA molecules was a change in the second base of the anticodon. The data revealed that diversification is not correlated with the characteristic of the specified amino acid, indicating that the correlation between tRNA and amino acid was given indirectly, and possibly should have been mediated by proto-aminoacyl-tRNA synthetases.

Three-Dimensional Algebraic Models of the tRNA Code and 12 Graphs for Representing the Amino Acids

Three-dimensional algebraic models, also called Genetic Hotels, are developed to represent the Standard Genetic Code, the Standard tRNA Code (S-tRNA-C), and the Human tRNA code (H-tRNA-C). New algebraic concepts are introduced to be able to describe these models, to wit, the generalization of the 2n-Klein Group and the concept of a subgroup coset with a tail. We found that the H-tRNA-C displayed broken symmetries in regard to the S-tRNA-C, which is highly symmetric. We also show that there are only 12 ways to represent each of the corresponding phenotypic graphs of amino acids. The averages of statistical centrality measures of the 12 graphs for each of the three codes are carried out and they are statistically compared. The phenotypic graphs of the S-tRNA-C display a common triangular prism of amino acids in 10 out of the 12 graphs, whilst the corresponding graphs for the H-tRNA-C display only two triangular prisms. The graphs exhibit disjoint clusters of amino acids when their polar requirement values are used. We contend that the S-tRNA-C is in a frozen-like state, whereas the H-tRNA-C may be in an evolving state.

tRNA Core Hypothesis for the Transition from the RNA World to the Ribonucleoprotein World

Herein we present the tRNA core hypothesis, which emphasizes the central role of tRNAs molecules in the origin and evolution of fundamental biological processes. tRNAs gave origin to the first genes (mRNA) and the peptidyl transferase center (rRNA), proto-tRNAs were at the core of a proto-translation system, and the anticodon and operational codes then arose in tRNAs molecules. Metabolic pathways emerged from evolutionary pressures of the decoding systems. The transitions from the RNA world to the ribonucleoprotein world to modern biological systems were driven by three kinds of tRNAs transitions, to wit, tRNAs leading to both mRNA and rRNA.

Self-Referential Formation of the Genetic System

Formation of the genetic code is considered a part of the process of establishing precise nucleoprotein associations. The process is initiated by tRNA dimers paired through the perfect palindromic anticodons, which are at the same time codons for each other; the amino acid acceptor ends produce the transferase function, in a manner similar to the reaction occurring in ribosomes. The connections between nucleic acids and proteins are bidirectional, forming a self-feeding system. In one direction, proteins that are resistant to degradation and efficient RNA-binders stabilize the tRNAs that are specifically involved with their production; in the other direction, these tRNAs become fixed with the correspondences which are the amino acid codes. Replication of the stabilized tRNAs becomes elongational, forming polytRNAs, the precursors of the mRNA strings (genes), and of ribosomes. The linear order in the gene sequences follows the temporal succession of the encoding of tRNA pairs. The whole encoding process is oriented by the tRNA pairs. The core sequence of proteins shows the predominant aperiodic conformation and the anticodonic principal dinucleotides (pDiN) are composed of two purines or two pyrimidines: (1a) Gly / Pro; (1b) Ser / Ser; (2a) Asp, Glu / Leu; (2b) Asn, Lys / Phe. Members of the following pairs, with pDiN composed of a purine and a pyrimidine [(3a) Ala / Arg; (3b) Val / His, Gln; (3c) Thr / Cys, Trp; (4) Ile, Met / Tyr, and iMet / Stop], are added, respectively, to the mRNA heads / tails. It is indicated that: (a) The Last Universal Common Ancestor populations could, at some early stages, be composed of lineages bearing similar genetic codes, due to the simple and highly deterministic character of the process; (b) Genetic information was created during the process of formation of the coding/decoding subsystem, inside a proto-metabolic system already producing some amino acids and tRNA-like precursors; (c) Genes were defined by the proteins that stabilized the system, as memories for their production.

A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.

Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP—Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.