Evolution of the genetic code: partial optimization of a random code for robustness to translation error in a rugged fitness landscape

Background  

The standard genetic code table has a distinctly non-random structure, with similar amino acids often encoded by codons series that differ by a single nucleotide substitution, typically, in the third or the first position of the codon. It has been repeatedly argued that this structure of the code results from selective optimization for robustness to translation errors such that translational misreading has the minimal adverse effect. Indeed, it has been shown in several studies that the standard code is more robust than a substantial majority of random codes. However, it remains unclear how much evolution the standard code underwent, what is the level of optimization, and what is the likely starting point.     

A four-column theory for the origin of the genetic code: tracing the evolutionary pathways that gave rise to an optimized code

Background  

The arrangement of the amino acids in the genetic code is such that neighbouring codons are assigned to amino acids with similar physical properties. Hence, the effects of translational error are minimized with respect to randomly reshuffled codes. Further inspection reveals that it is amino acids in the same column of the code (i.e. same second base) that are similar, whereas those in the same row show no particular similarity. We propose a 'four-column' theory for the origin of the code that explains how the action of selection during the build-up of the code leads to a final code that has the observed properties.     

On the origin of the translation system and the genetic code in the RNA world by means of natural selection, exaptation, and subfunctionalization

Background  

The origin of the translation system is, arguably, the central and the hardest problem in the study of the origin of life, and one of the hardest in all evolutionary biology. The problem has a clear catch-22 aspect: high translation fidelity hardly can be achieved without a complex, highly evolved set of RNAs and proteins but an elaborate protein machinery could not evolve without an accurate translation system. The origin of the genetic code and whether it evolved on the basis of a stereochemical correspondence between amino acids and their cognate codons (or anticodons), through selectional optimization of the code vocabulary, as a "frozen accident" or via a combination of all these routes is another wide open problem despite extensive theoretical and experimental studies. Here we combine the results of comparative genomics of translation system components, data on interaction of amino acids with their cognate codons and anticodons, and data on catalytic activities of ribozymes to develop conceptual models for the origins of the translation system and the genetic code.     

The optimality of the standard genetic code assessed by an eight-objective evolutionary algorithm

Background

The standard genetic code (SGC) is a unique set of rules which assign amino acids to codons. Similar amino acids tend to have similar codons indicating that the code evolved to minimize the costs of amino acid replacements in proteins, caused by mutations or translational errors. However, if such optimization in fact occurred, many different properties of amino acids must have been taken into account during the code evolution. Therefore, this problem can be reformulated as a multi-objective optimization task, in which the selection constraints are represented by measures based on various amino acid properties.

Results

To study the optimality of the SGC we applied a multi-objective evolutionary algorithm and we used the representatives of eight clusters, which grouped over 500 indices describing various physicochemical properties of amino acids. Thanks to that we avoided an arbitrary choice of amino acid features as optimization criteria. As a consequence, we were able to conduct a more general study on the properties of the SGC than the ones presented so far in other papers on this topic. We considered two models of the genetic code, one preserving the characteristic codon blocks structure of the SGC and the other without this restriction. The results revealed that the SGC could be significantly improved in terms of error minimization, hereby it is not fully optimized. Its structure differs significantly from the structure of the codes optimized to minimize the costs of amino acid replacements. On the other hand, using newly defined quality measures that placed the SGC in the global space of theoretical genetic codes, we showed that the SGC is definitely closer to the codes that minimize the costs of amino acids replacements than those maximizing them.

Conclusions

The standard genetic code represents most likely only partially optimized systems, which emerged under the influence of many different factors. Our findings can be useful to researchers involved in modifying the genetic code of the living organisms and designing artificial ones.

     

Comparison of translation loads for standard and alternative genetic codes

Background  

The (almost) universality of the genetic code is one of the most intriguing properties of cellular life. Nevertheless, several variants of the standard genetic code have been observed, which differ in one or several of 64 codon assignments and occur mainly in mitochondrial genomes and in nuclear genomes of some bacterial and eukaryotic parasites. These variants are usually considered to be the result of non-adaptive evolution. It has been shown that the standard genetic code is preferential to randomly assembled codes for its ability to reduce the effects of errors in protein translation.     

An extension of the coevolution theory of the origin of the genetic code

Background  

The coevolution theory of the origin of the genetic code suggests that the genetic code is an imprint of the biosynthetic relationships between amino acids. However, this theory does not seem to attribute a role to the biosynthetic relationships between the earliest amino acids that evolved along the pathways of energetic metabolism. As a result, the coevolution theory is unable to clearly define the very earliest phases of genetic code origin. In order to remove this difficulty, I here suggest an extension of the coevolution theory that attributes a crucial role to the first amino acids that evolved along these biosynthetic pathways and to their biosynthetic relationships, even when defined by the non-amino acid molecules that are their precursors.     

Sequence similarity is more relevant than species specificity in probabilistic backtranslation

Background  

Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species.     

Frequent occurrence of recognition Site-like sequences in the restriction endonucleases

Background  

There are two different theories about the development of the genetic code. Woese suggested that it was developed in connection with the amino acid repertoire, while Crick argued that any connection between codons and amino acids is only the result of an "accident". This question is fundamental to understand the nature of specific protein-nucleic acid interactions.     

A general model of codon bias due to GC mutational bias

Background

In spite of extensive research on the effect of mutation and selection on codon usage, a general model of codon usage bias due to mutational bias has been lacking. Because most amino acids allow synonymous GC content changing substitutions in the third codon position, the overall GC bias of a genome or genomic region is highly correlated with GC3, a measure of third position GC content. For individual amino acids as well, G/C ending codons usage generally increases with increasing GC bias and decreases with increasing AT bias. Arginine and leucine, amino acids that allow GC-changing synonymous substitutions in the first and third codon positions, have codons which may be expected to show different usage patterns.

Principal Findings

In analyzing codon usage bias in hundreds of prokaryotic and plant genomes and in human genes, we find that two G-ending codons, AGG (arginine) and TTG (leucine), unlike all other G/C-ending codons, show overall usage that decreases with increasing GC bias, contrary to the usual expectation that G/C-ending codon usage should increase with increasing genomic GC bias. Moreover, the usage of some codons appears nonlinear, even nonmonotone, as a function of GC bias. To explain these observations, we propose a continuous-time Markov chain model of GC-biased synonymous substitution. This model correctly predicts the qualitative usage patterns of all codons, including nonlinear codon usage in isoleucine, arginine and leucine. The model accounts for 72%, 64% and 52% of the observed variability of codon usage in prokaryotes, plants and human respectively. When codons are grouped based on common GC content, 87%, 80% and 68% of the variation in usage is explained for prokaryotes, plants and human respectively.

Conclusions

The model clarifies the sometimes-counterintuitive effects that GC mutational bias can have on codon usage, quantifies the influence of GC mutational bias and provides a natural null model relative to which other influences on codon bias may be measured.     

Protein disorder prediction by condensed PSSM considering propensity for order or disorder

Background  

More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that disordered regions of a protein can be predicted by its primary structure, the amino acid sequence. One observation that has been widely accepted is that ordered regions usually have compositional bias toward hydrophobic amino acids, and disordered regions are toward charged amino acids. Recent studies further show that employing evolutionary information such as position specific scoring matrices (PSSMs) improves the prediction accuracy of protein disorder. As more and more machine learning techniques have been introduced to protein disorder detection, extracting more useful features with biological insights attracts more attention.     

An analysis of nucleotide and amino acid variability in the barcode region of cytochrome c oxidase I (cox1) in fishes

The 655 bp cytochrome c oxidase subunit I barcode region of single specimens of 388 species of fishes (four Holocephali, 61 Elasmobranchii and 323 Actinopterygii) was examined. All but two (Urolophus cruciatus and Urolophus sufflavus) showed different cox1 nucleotide sequences (99.5% species discrimination); the two that could not be resolved are suspected to hybridize. Most of the power of cox1 nucleotide sequence analysis for species identification comes from the degenerate nature of the genetic code and the highly variable nature of the third codon position of amino acids. Variation at the third codon position is bimodally distributed, and the more variable mode is dominated by amino acids with four or six codons, while the less variable mode is dominated by amino acids with two codons. The ratio of nonsynonymous to synomymous changes is much less than one, indicating that this gene is subject to strong purifying selection. Consequently, cox1 amino acid sequence diversity is much less than nucleotide sequence diversity and has very poor species resolution power. Fourteen of the 16 amino acid residues recognized as having important functions in the region of cox1 sequenced were completely conserved over all 388 species (and the bovine cox1 sequence), with one fish species varying at one of these sites, and three fish at another site. No significant differences in amino acid conservation were observed between residues in helices, strands and turns. Patterns of nucleotide and amino acid variability were very similar between elasmobranchs and actinopterygians.     

Optimality of the genetic code with respect to protein stability and amino-acid frequencies

Background

The genetic code is known to be efficient in limiting the effect of mistranslation errors. A misread codon often codes for the same amino acid or one with similar biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question quantitatively, by estimating the fraction of randomly generated codes that do better than the genetic code in respect of overall robustness. We extended these results by investigating the role of amino-acid frequencies in the optimality of the genetic code.

Results

We found that taking the amino-acid frequency into account decreases the fraction of random codes that beat the natural code. This effect is particularly pronounced when more refined measures of the amino-acid substitution cost are used than hydrophobicity. To show this, we devised a new cost function by evaluating in silico the change in folding free energy caused by all possible point mutations in a set of protein structures. With this function, which measures protein stability while being unrelated to the code's structure, we estimated that around two random codes in a billion (10⁹) are fitter than the natural code. When alternative codes are restricted to those that interchange biosynthetically related amino acids, the genetic code appears even more optimal.

Conclusions

These results lead us to discuss the role of amino-acid frequencies and other parameters in the genetic code's evolution, in an attempt to propose a tentative picture of primitive life.     

The evolutionary differentiation of two histone H2A.Z variants in chordates (H2A.Z-1 and H2A.Z-2) is mediated by a stepwise mutation process that affects three amino acid residues

Background  

The histone H2A family encompasses the greatest number of core histone variants of which the replacement variant H2A.Z is currently one of the most heavily studied. No clear mechanism for the functional variability that H2A.Z imparts to chromatin has yet been proposed. While most of the past studies have referred to H2A.Z generically as a single protein, in vertebrates it is a mixture of two protein forms H2A.Z-1 (previously H2A.Z) and H2A.Z-2 (previously H2A.F/Z or H2A.V) that differ by three amino acids.     

On origin of genetic code and tRNA before translation

Background  

Synthesis of proteins is based on the genetic code - a nearly universal assignment of codons to amino acids (aas). A major challenge to the understanding of the origins of this assignment is the archetypal "key-lock vs. frozen accident" dilemma. Here we re-examine this dilemma in light of 1) the fundamental veto on "foresight evolution", 2) modular structures of tRNAs and aminoacyl-tRNA synthetases, and 3) the updated library of aa-binding sites in RNA aptamers successfully selected in vitro for eight amino acids.     

A quantitative measure of error minimization in the genetic code

Summary We have calculated the average effect of changing a codon by a single base for all possible single-base changes in the genetic code and for changes in the first, second, and third codon positions separately. Such values were calculated for an amino acid's polar requirement, hydropathy, molecular volume, and isoelectric point. For each attribute the average effect of single-base changes was also calculated for a large number of randomly generated codes that retained the same level of redundancy as the natural code. Amino acids whose codons differed by a single base in the first and third codon positions were very similar with respect to polar requirement and hydropathy. The major differences between amino acids were specified by the second codon position. Codons with U in the second position are hydrophobic, whereas most codons with A in the second position are hydrophilic. This accounts for the observation of complementary hydropathy. Single-base changes in the natural code had a smaller average effect on polar requirement than all but 0.02% of random codes. This result is most easily explained by selection to minimize deleterious effects of translation errors during the early evolution of the code.     

The rate of the molecular clock and the cost of gratuitous protein synthesis

Background  

The nature of the protein molecular clock, the protein-specific rate of amino acid substitutions, is among the central questions of molecular evolution. Protein expression level is the dominant determinant of the clock rate in a number of organisms. It has been suggested that highly expressed proteins evolve slowly in all species mainly to maintain robustness to translation errors that generate toxic misfolded proteins. Here we investigate this hypothesis experimentally by comparing the growth rate of Escherichia coli expressing wild type and misfolding-prone variants of the LacZ protein.     

Do universal codon-usage patterns minimize the effects of mutation and translation error?

Background

Do species use codons that reduce the impact of errors in translation or replication? The genetic code is arranged in a way that minimizes errors, defined as the sum of the differences in amino-acid properties caused by single-base changes from each codon to each other codon. However, the extent to which organisms optimize the genetic messages written in this code has been far less studied. We tested whether codon and amino-acid usages from 457 bacteria, 264 eukaryotes, and 33 archaea minimize errors compared to random usages, and whether changes in genome G+C content influence these error values.

Results

We tested the hypotheses that organisms choose their codon usage to minimize errors, and that the large observed variation in G+C content in coding sequences, but the low variation in G+U or G+A content, is due to differences in the effects of variation along these axes on the error value. Surprisingly, the biological distribution of error values has far lower variance than randomized error values, but error values of actual codon and amino-acid usages are actually greater than would be expected by chance.

Conclusion

These unexpected findings suggest that selection against translation error has not produced codon or amino-acid usages that minimize the effects of errors, and that even messages with very different nucleotide compositions somehow maintain a relatively constant error value. They raise the question: why do all known organisms use highly error-minimizing genetic codes, but fail to minimize the errors in the mRNA messages they encode?

     

Composition Profiler: a tool for discovery and visualization of amino acid composition differences

Background  

Composition Profiler is a web-based tool for semi-automatic discovery of enrichment or depletion of amino acids, either individually or grouped by their physico-chemical or structural properties.     

Do anticodons of misacylated tRNAs preferentially mismatch codons coding for the misloaded amino acid?

Background  

Accurate amino acid insertion during peptide elongation requires tRNAs loaded by cognate amino acids and that anticodons match codons. However, tRNA misloading does not necessarily cause misinsertions: misinsertion is avoided when anticodons mismatch codons coding for misloaded amino acids.     

Hierarchical amino acid utilization and its influence on fermentation dynamics: rifamycin B fermentation using Amycolatopsis mediterranei S699, a case study

Background  

Industrial fermentation typically uses complex nitrogen substrates which consist of mixture of amino acids. The uptake of amino acids is known to be mediated by several amino acid transporters with certain preferences. However, models to predict this preferential uptake are not available. We present the stoichiometry for the utilization of amino acids as a sole carbon and nitrogen substrate or along with glucose as an additional carbon source. In the former case, the excess nitrogen provided by the amino acids is excreted by the organism in the form of ammonia. We have developed a cybernetic model to predict the sequence and kinetics of uptake of amino acids. The model is based on the assumption that the growth on a specific substrate is dependent on key enzyme(s) responsible for the uptake and assimilation of the substrates. These enzymes may be regulated by mechanisms of nitrogen catabolite repression. The model hypothesizes that the organism is an optimal strategist and invests resources for the uptake of a substrate that are proportional to the returns.