Evolution of the Genetic Code by Incorporation of Amino Acids that Improved or Changed Protein Function

Fifty years have passed since the genetic code was deciphered, but how the genetic code came into being has not been satisfactorily addressed. It is now widely accepted that the earliest genetic code did not encode all 20 amino acids found in the universal genetic code as some amino acids have complex biosynthetic pathways and likely were not available from the environment. Therefore, the genetic code evolved as pathways for synthesis of new amino acids became available. One hypothesis proposes that early in the evolution of the genetic code four amino acids—valine, alanine, aspartic acid, and glycine—were coded by GNC codons (N = any base) with the remaining codons being nonsense codons. The other sixteen amino acids were subsequently added to the genetic code by changing nonsense codons into sense codons for these amino acids. Improvement in protein function is presumed to be the driving force behind the evolution of the code, but how improved function was achieved by adding amino acids has not been examined. Based on an analysis of amino acid function in proteins, an evolutionary mechanism for expansion of the genetic code is described in which individual coded amino acids were replaced by new amino acids that used nonsense codons differing by one base change from the sense codons previously used. The improved or altered protein function afforded by the changes in amino acid function provided the selective advantage underlying the expansion of the genetic code. Analysis of amino acid properties and functions explains why amino acids are found in their respective positions in the genetic code.     

An Analysis of the Metabolic Theory of the Origin of the Genetic Code

A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature. Received: 8 August 1996 / Accepted: 26 December 1996     

The complementarity of the chemical parameters of amino acids and anticodons in the genetic code

Chemical language of the genetic code is suggested in which elementary information code units are presented by functional groups of amino acids and nucleotides. Using this language, the existence of correspondence and conformity of chemical parameters of amino acids and of central nucleotides of their anticodons was demonstrated. These findings confirm the idea that the genetic code is determined by chemical properties of amino acids and nucleotides and that this determination is the result of direct specific interactions between amino acids and nucleotide triplets at the stage of the origin of the code. The data obtained reveal primary role of anticodon triplets in the origin of the code. Key role of the central nucleotide in triplets for amino acid coding is confirmed.     

A hardware interpretation of the evolution of the genetic code

A quantitative rationale for the evolution of the genetic code is developed considering the principle of minimal hardware. This principle defines an optimal code as one that minimizes for a given amount of information encoded, the product of the number of physical devices used by the average complexity of each device. By identifying the number of different amino acids, number of nucleotide positions per codon and number of base types that can occupy each such position with, respectively, the amount of information, number of devices and the complexity, we show that optimal codes occur for 3, 7 and 20 amino acids with codons having a single, two and three base positions per codon, respectively. The advantage of a code of exactly 4 symbols is deduced, as well as a plausible evolutionary pathway from a code of doublets to triplets. The present day code of 20 amino acids encoded by 64 codons is shown to be the most optimal in an absolute sense. Using a tetraplet code further evolution to a code in which there would be 55 amino acids is in principle possible, but such a code would deviate slightly more than the present day code from the minimal hardware configuration. The change from a triplet code to a tetraplet code would occur at about 32 amino acids. Our conclusions are independent of, but consistent with, the observed physico-chemical properties of the amino acids and codon structures. These correlations could have evolved within the constrains imposed by the minimal hardware principle.     

Selection, history and chemistry: the three faces of the genetic code.

The genetic code might be a historical accident that was fixed in the last common ancestor of modern organisms. 'Adaptive', 'historical' and 'chemical' arguments, however, challenge such a 'frozen accident' model. These arguments propose that the current code is somehow optimal, reflects the expansion of a more primitive code to include more amino acids, or is a consequence of direct chemical interactions between RNA and amino acids, respectively. Such models are not mutually exclusive, however. They can be reconciled by an evolutionary model whereby stereochemical interactions shaped the initial code, which subsequently expanded through biosynthetic modification of encoded amino acids and, finally, was optimized through codon reassignment. Alternatively, all three forces might have acted in concert to assign the 20 'natural' amino acids to their present positions in the genetic code.     

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.     

The Historical Factor: The Biosynthetic Relationships Between Amino Acids and Their Physicochemical Properties in the Origin of the Genetic Code

Two forces are in general, hypothesized to have influenced the origin of the organization of the genetic code: the physicochemical properties of amino acids and their biosynthetic relationships. In view of this, we have considered a model incorporating these two forces. In particular, we have studied the optimization level of the physicochemical properties of amino acids in the set of amino acid permutation codes that respects the biosynthetic relationships between amino acids. Where the properties of amino acids are represented by polarity and molecular volume we obtain indetermination percentages in the organization of the genetic code of approximately 40%. This indicates that the contingent factor played a significant role in structuring the genetic code. Furthermore, this result is in agreement with the genetic code coevolution hypothesis, which attributes a merely ancillary role to the properties of amino acids while it suggests that it was their biosynthetic relationships that organized the code. Furthermore, this result does not favor the stereochemical models proposed to explain the origin of the genetic code. On the other hand, where the properties of amino acids are represented by polarity alone, we obtain an indetermination percentage of at least 21.5%. This might suggest that the polarity distances played an important role and would therefore provide evidence in favor of the physicochemical hypothesis of genetic code origin. Although, overall, the analysis might have given stronger support to the latter hypothesis, this did not actually occur. The results are therefore discussed in the context of the different theories proposed to explain the origin of the genetic code. Received: 10 September 1996 / Accepted: 3 March 1997     

Genetic code preferentially conserves long-range interactions among the amino acids

The physical properties of amino acids were investigated in order to evaluate their possible relationship to the assignment of codons for amino acids in the genetic code. A comparison of the interconversion probability between amino acids and the distances between the amino acids for individual physical properties revealed a striking hierarchy among the physical properties. Surprisingly, it is the long-range/solvent interactions and not the short-range/stereochemical properties which are preferentially conserved in the genetic code.     

Hidden symmetry of the genetic code and laws of amino acid interaction]

Natural amino acids having common antiamino acids are divided into families and groups according to the algorithm of the genetic code (a-n-n-a, amino acid-codon-anticodon-antiamino acid). Members of these groups are placed symmetrically in the structure of the genetic code. In the course of evolution, those point mutations are predominantly accepted retained. In homologous proteins of phylogenetically related organisms which lend to amino acids belonging to one family or group and having common antiamino acids. This assumption is in agreement with L. B. Mekler's theory (1969) of the amino acid interaction code a-a.     

Structuring of the genetic code took place at acidic pH

I have observed that in multiple regression the number of codons specifying amino acids in the genetic code is positively correlated with the isoelectric point of amino acids and their molecular weight. Therefore basic amino acids are, on average, codified in the genetic code by a larger number of codons, which seems to imply that the genetic code originated in an acidic 'intracellular' environment. Moreover, I compare the proteins from Picrophilus torridus and Thermoplasma volcanium, which have different intracellular pH and I define the ranks of acidophily for the amino acids. A simple index of acidophily (AI), which can be easily obtained from acidophily ranks, can be associated to any protein and, therefore, can also be associated to the genetic code if the number of synonymous codons attributed to the amino acids in the code is assumed to be the frequency with which the amino acids appeared in ancestral proteins. Finally, the sampling of the variable AI among organisms having an intracellular pH less than or equal to 6.6 and those having a non-acidic intracellular pH leads to the conclusion that the value of the genetic code's AI is not typical of proteins of the latter organisms. As the genetic code's AI value is also statistically not different from that of proteins of the organisms having an acidic intracellular pH, this supports the hypothesis that the structuring of the genetic code took place in acidic pH conditions.     

Stability of the genetic code and optimal parameters of amino acids

The standard genetic code is known to be much more efficient in minimizing adverse effects of misreading errors and one-point mutations in comparison with a random code having the same structure, i.e. the same number of codons coding for each particular amino acid. We study the inverse problem, how the code structure affects the optimal physico-chemical parameters of amino acids ensuring the highest stability of the genetic code. It is shown that the choice of two or more amino acids with given properties determines unambiguously all the others. In this sense the code structure determines strictly the optimal parameters of amino acids or the corresponding scales may be derived directly from the genetic code. In the code with the structure of the standard genetic code the resulting values for hydrophobicity obtained in the scheme “leave one out” and in the scheme with fixed maximum and minimum parameters correlate significantly with the natural scale. The comparison of the optimal and natural parameters allows assessing relative impact of physico-chemical and error-minimization factors during evolution of the genetic code. As the resulting optimal scale depends on the choice of amino acids with given parameters, the technique can also be applied to testing various scenarios of the code evolution with increasing number of codified amino acids. Our results indicate the co-evolution of the genetic code and physico-chemical properties of recruited amino acids.     

Physico-chemical basis of the genetic code origin: stereochemical analysis of interactions of amino acids and nucleotides based on the progene hypothesis

A progene hypothesis has been proposed earlier to explain the mechanism of origin of the self-reproducing genetic system. Progenes (precursors of the genetic system) are mixed anhydrides of an amino acid and deoxyribotrinucleotide at the 3'-gamma-terminal phosphate (NpNpNppp-AA); they are produced from dinucleotides (NpNp) and 3'-gamma-aminoacylnucleotidylates (Nppp-AA) as a result of specific interaction between amino acid and dinucleotide. The postulated mechanism of progene formation accounts for the selection of substances, including chirality, the origin of the genetic code as well as for the mechanisms of formation, self-reproduction and evolution of the simpliest genetic system ("gene--polypeptide"). A stereochemical analysis of the progene formation mechanism has allowed us to support the main statements of the hypothesis that relate to the origin of the genetic code and to selection of substances. Atomic groups that could be responsible for the specificity of interaction between dinucleotides and amino acids in progene formation have been revealed. Stereochemical evidence for the physicochemical basis of the origin of the existing genetic code have been produced: 1) a special role of the second nucleotide in the codon is demonstrated in amino acid coding by the progene hypothesis principle; 2) an advantage of T against U in such coding is demonstrated; 3) for 16 amino acids out of 20 an agreement has been obtained between the optimal dinucleotide as revealed by the stereochemical analysis and the codon dinucleotides; 4) an explanation for the third nucleotide selection mechanism is offered. A restoration of the prebiotic code, based on these results, has indicated that the code contains 32 codons, is statistical and group-wise. It encodes 7 groups of isofunctional amino acids: 3 overlapping groups of non-polar amino acids 1) medium-size hydrophobic amino acids (chiefly Val, n-Val and a-But), 2) small and medium-size non-polar amino acids (chiefly Ala Val, n-Val a-But and Gly), 3) small non-polar amino acids (Gly, Ala, a-But) and 4 groups of polar amino acids--1) hydroxy--+dicarbonic (Asp, Glu, Ser and Thr), 2) dicarbonic (Asp and Glu), 3) hydroxy (Ser and Thr) and 4) basic (Arg and Lys). The code includes about 20 amino acids among which are 15-17 canonical and a few common non-canonical. The prebiotic code explains many properties of the existing genetic code and is capable of evolving into the latter by way of a gradual replacement of the physicochemical coding mechanism by the enzymatic coding mechanism.     

Evolution of the aminoacyl-tRNA synthetases and the origin of the genetic code

The aminoacyl-tRNA synthetases exist as two enzyme families which were apparently generated by divergent evolution from two primordial synthetases. The two classes of enzymes exhibit intriguing familial relationships, in that they are distributed nonrandomly within the codon-amino acid matrix of the genetic code. For example, all XCX codons code for amino acids handled by class II synthetases, and all but one of the XUX codons code for amino acids handled by class I synthetases. One interpretation of these patterns is that the synthetases coevolved with the genetic code. The more likely explanation, however, is that the synthetases evolved in the context of an already-established genetic code—a code which developed earlier in an RNA world. The rules which governed the development of the genetic code, and led to certain patterns in the coding catalog between codons and amino acids, would also have governed the subsequent evolution of the synthetases in the context of a fixed code, leading to patterns in synthetase distribution such as those observed. These rules are (1) conservative evolution of amino acid and adapter binding sites and (2) minimization of the disruptive effects on protein structure caused by codon meaning changes.     

The evolution of the structures of amino acid families]

Natural amino acids possessing common antiamino acids are divided into groups and families according to the genetic code algorithm a-n-n-a (amino acid-codon-anticodon-antiamino acid). In an attempt to study structural evolution of amino acid families, artificial genetic code models were constructed. It is suggested that after inclusion of asparaginase and glutamine into the coding system, one of the two natural amino acid families is split into two parts ("half-families").     

Protein evolution drives the evolution of the genetic code and vice versa

A model for the developmental pathway of the genetic code, grounded on group theory and the thermodynamics of codon-anticodon interaction is presented. At variance with previous models, it takes into account not only the optimization with respect to amino acid attributes but, also physicochemical constraints and initial conditions. A 'simple-first' rule is introduced after ranking the amino acids with respect to two current measures of chemical complexity. It is shown that a primeval code of only seven amino acids is enough to build functional proteins. It is assumed that these proteins drive the further expansion of the code. The proposed primeval code is compared with surrogate codes randomly generated and with another proposal for primeval code found in the literature. The departures from the 'universal' code, observed in many organisms and cellular compartments, fit naturally in the proposed evolutionary scheme. A strong correlation is found between, on one side, the two classes of aminoacyl-tRNA synthetases, and on the other, the amino acids grouped by end-atom-type and by codon type. An inverse of Davydov's rules, to associate the amino acid end atoms (O/N and non-O/non-N) of 18 amino acids with codons containing a weak base (A/U), extended to the 20 amino acids, is derived.     

On the organizational dynamics of the genetic code

The organization of the canonical genetic code needs to be thoroughly illuminated. Here we reorder the four nucleotides-adenine, thymine, guanine and cytosine-according to their emergence in evolution, and apply the organizational rules to devising an algebraic representation for the canonical genetic code. Under a framework of the devised code, we quantify codon and amino acid usages from a large collection of 917 prokaryotic genome sequences, and associate the usages with its intrinsic structure and classification schemes as well as amino acid physicochemical properties. Our results show that the algebraic representation of the code is structurally equivalent to a content-centric organization of the code and that codon and amino acid usages under different classification schemes were correlated closely with GC content, implying a set of rules governing composition dynamics across a wide variety of prokaryotic genome sequences. These results also indicate that codons and amino acids are not randomly allocated in the code, where the six-fold degenerate codons and their amino acids have important balancing roles for error minimization. Therefore, the content-centric code is of great usefulness in deciphering its hitherto unknown regularities as well as the dynamics of nucleotide, codon, and amino acid compositions.     

The relationship between the biosynthetic paths to the amino acids and their coding

The genetic code could not have been fixed until the means for biosynthesis of the amino acids was at hand. The biosynthetic enzymes could not be optimized until the genetic code ceased to be rearranged. Therefore the development of the code and the development of the biosynthesis of the amino acids occurred concurrently. The present day biosynthetic pathways of amino acids, examined from this point of view, help to explain the present set of coded amino acids, in particular the absence of norvaline, norleucine, homoserine, ornithine, and alpha-aminobutyric acid. An order of development of biosyntheses is also proposed. Lysine was first, followed by valine and isoleucine. The more common primordial amino acids did not need biosyntheses so early. The central pathways of metabolism probably developed in response to a need for amino acid biosynthesis.     

Physicochemical Optimization in the Genetic Code Origin as the Number of Codified Amino Acids Increases

We have assumed that the coevolution theory of genetic code origin (Wong JT, Proc Natl Acad Sci USA 72:1909–1912, 1975) is essentially correct. This theory makes it possible to identify at least 10 evolutionary stages through which genetic code organization might have passed prior to reaching its current form. The calculation of the minimization level of all these evolutionary stages leads to the following conclusions. (1) The minimization percentages increased linearly with the number of amino acids codified in the codes of the various evolutionary stages when only the sense changes are considered in the analysis. This seems to favor the physicochemical theory of genetic code origin even if, as discussed in the paper, this observation is also compatible with the coevolution theory. (2) For the first seven evolutionary stages of the genetic code, this trend is less clear and indeed is inverted when we consider the global optimisation of the codes due to both sense changes and synonymous changes. This inverse correlation between minimization percentages and the number of amino acids codified in the codes of the intermediate stages seems to favor neither the physicochemical nor the stereochemical theories of genetic code origin, as it is in the early and intermediate stages of code development that these theories would expect minimization to have played a crucial role, and this does not seem to be the case. However, these results are in agreement with the coevolution theory, which attributes a role to the physicochemical properties of amino acids that, while important, is nevertheless subordinate to the mechanism which concedes codons from the precursor amino acids to the product amino acids as the primary factor determining the evolutionary structuring of the genetic code. The results are therefore discussed in the context of the various theories proposed to explain genetic code origin. Received: 25 October 1998 / Accepted: 19 February 1999     

Some aspects of the organization and evolution of the genetic code

In this paper, I define a measure of the relative position of each amino acid in the genetic code by means of a 21-dimensional vector describing its potential for mutation, in a single step, to each of the other amino acids, or to a chain termination codon. This measure allows us to make a systematic investigation of the type and number of the physicochemical properties of the amino acids that were involved in evolution. The polar character and size of amino acids are identified in this analysis as properties that played a leading role in the evolutionary history of the genetic code. The application of cluster analysis and discriminant analysis reveals the characteristics of the structural organization of the genetic code. Finally, I suggest the existence of a relationship between the molecular weight of the amino acids and the number of synonymous codons.