Some pungent arguments against the physico-chemical theories of the origin of the genetic code and corroborating the coevolution theory

Theories of the origin of the genetic code: Strong corroboration for the coevolution theory

I analyzed all the theories and models of the origin of the genetic code, and over the years, I have considered the main suggestions that could explain this origin. The conclusion of this analysis is that the coevolution theory of the origin of the genetic code is the theory that best captures the majority of observations concerning the organization of the genetic code. In other words, the biosynthetic relationships between amino acids would have heavily influenced the origin of the organization of the genetic code, as supported by the coevolution theory. Instead, the presence in the genetic code of physicochemical properties of amino acids, which have also been linked to the physicochemical properties of anticodons or codons or bases by stereochemical and physicochemical theories, would simply be the result of natural selection. More explicitly, I maintain that these correlations between codons, anticodons or bases and amino acids are in fact the result not of a real correlation between amino acids and codons, for example, but are only the effect of the intervention of natural selection. Specifically, in the genetic code table we expect, for example, that the most similar codons - that is, those that differ by only one base - will have more similar physicochemical properties. Therefore, the 64 codons of the genetic code table ordered in a certain way would also represent an ordering of some of their physicochemical properties. Now, a study aimed at clarifying which physicochemical property of amino acids has influenced the allocation of amino acids in the genetic code has established that the partition energy of amino acids has played a role decisive in this. Indeed, under some conditions, the genetic code was found to be approximately 98% optimized on its columns. In this same work, it was shown that this was most likely the result of the action of natural selection. If natural selection had truly allocated the amino acids in the genetic code in such a way that similar amino acids also have similar codons - this, not through a mechanism of physicochemical interaction between, for example, codons and amino acids - then it might turn out that even different physicochemical properties of codons (or anticodons or bases) show some correlation with the physicochemical properties of amino acids, simply because the partition energy of amino acids is correlated with other physicochemical properties of amino acids. It is very likely that this would inevitably lead to a correlation between codons (or anticodons or bases) and amino acids. In other words, since the codons (anticodons or bases) are ordered in the genetic code, that is to say, some of their physicochemical properties should also be ordered by a similar order, and given that the amino acids would also appear to have been ordered in the genetic code by selection natural, then it should inevitably turn out that there is a correlation between, for example, the hydrophobicity of anticodons and that of amino acids. Instead, the intervention of natural selection in organizing the genetic code would appear to be highly compatible with the main mechanism of structuring the genetic code as supported by the coevolution theory. This would make the coevolution theory the only plausible explanation for the origin of the genetic code.

The time of appearance of the genetic code

I support the hypothesis that the origin of the genetic code occurred simultaneously with the evolution of cellularity. That is to say, I favour the hypothesis that the origin of the genetic code is a very, very late event in the history of life on Earth. I corroborate this hypothesis with observations favouring the progenote's stage for the Last Universal Common Ancestor (LUCA), for the ancestor of bacteria and that of archaea. Indeed, these progenotic stages would imply that - at that time - the origin of the genetic code was still ongoing simply because this origin would fall within the very definition of progenote. Therefore, if the evolution of cellularity had truly been coeval with the origin of the genetic code - at least in its terminal part - then this would favour theories such as the coevolution theory of the origin of the genetic code because this theory would postulate that this origin must have occurred in extremely complex protocellular conditions and not concerning stereochemical or physicochemical interactions having to do with other stages of the origin of life. In this sense, the coevolution theory would be corroborated while the stereochemical and physicochemical theories would be damaged. Therefore, the origin of the genetic code would be linked to the origin of the cell and not to the origin of life as sometimes asserted. Therefore, I will discuss the late hypothesis of the origin of the genetic code in the context of the theories proposed to explain this origin and more generally of its implications for the early evolution of life.

The error minimization of the genetic code would have been determined by natural selection and not by a neutral evolution

I discuss the mechanisms by which the error minimization observed in the genetic code would have been produced; that is, the ability of the genetic code to buffer, for example, the deleterious effects of translation errors. Here, I analyse whether the error minimization was produced by the intervention of natural selection or whether it is an emergent, that is, neutral property; in other words, whether it is a by-product of another mechanism that was structuring the genetic code. In particular, I criticize Massey's simulations (2008) - favouring the neutral hypothesis - which, containing elements of natural selection, would render his conclusions at least partly tautological. Furthermore, I criticize some of Koonin's (2017) interpretations regarding Massey's simulations. Finally, I criticize the opinion of Janzen et al. (2022) according to which their self-aminoacylating ribozyme system would have been capable of generating an error minimization of the genetic code as its emergent property. That is to say, I criticize, more generally, a neutral origin of error minimization. Indeed, any mechanism for structuring the genetic code would be capable of generating, in theory, such an emergent property. The problem is that to demonstrate this, it would be necessary to show that the level of optimization achieved by the genetic code would be that expected under the neutral hypothesis, the one that Janzen et al. (2022) instead they did not make. Therefore, their view is only a hypothesis and is very far from being corroborated by their results. Instead, in the literature there is a strong evidence that the level of optimization achieved by the genetic code is so high that it would imply, per se, an intervention of natural selection in the origin of error minimization of the genetic code. On the other hand, this level of optimization would be very far from what might have been produced by a neutral process.

The structure of the genetic code as an optimal graph clustering problem

The standard genetic code (SGC) is the set of rules by which genetic information is translated into proteins, from codons, i.e. triplets of nucleotides, to amino acids. The questions about the origin and the main factor responsible for the present structure of the code are still under a hot debate. Various methodologies have been used to study the features of the code and assess the level of its potential optimality. Here, we introduced a new general approach to evaluate the quality of the genetic code structure. This methodology comes from graph theory and allows us to describe new properties of the genetic code in terms of conductance. This parameter measures the robustness of codon groups against the potential changes in translation of the protein-coding sequences generated by single nucleotide substitutions. We described the genetic code as a partition of an undirected and unweighted graph, which makes the model general and universal. Using this approach, we showed that the structure of the genetic code is a solution to the graph clustering problem. We presented and discussed the structure of the codes that are optimal according to the conductance. Despite the fact that the standard genetic code is far from being optimal according to the conductance, its structure is characterised by many codon groups reaching the minimum conductance for their size. The SGC represents most likely a local minimum in terms of errors occurring in protein-coding sequences and their translation.

Factors in Protobiomonomer Selection for the Origin of the Standard Genetic Code

Natural selection of specific protobiomonomers during abiogenic development of the prototype genetic code is hindered by the diversity of structural, spatial, and rotational isomers that have identical elemental composition and molecular mass (M), but can vary significantly in their physicochemical characteristics, such as the melting temperature T_m, the T_m:M ratio, and the solubility in water, due to different positions of atoms in the molecule. These parameters differ between cis- and trans-isomers of dicarboxylic acids, spatial monosaccharide isomers, and structural isomers of α-, β-, and γ-amino acids. The stable planar heterocyclic molecules of the major nucleobases comprise four (C, H, N, O) or three (C, H, N) elements and contain a single -C=C bond and two nitrogen atoms in each heterocycle involved in C-N and C=N bonds. They exist as isomeric resonance hybrids of single and double bonds and as a mixture of tautomer forms due to the presence of -C=O and/or -NH₂ side groups. They are thermostable, insoluble in water, and exhibit solid-state stability, which is of central importance for DNA molecules as carriers of genetic information. In M-T_m diagrams, proteinogenic amino acids and the corresponding codons are distributed fairly regularly relative to the distinct clusters of purine and pyrimidine bases, reflecting the correspondence between codons and amino acids that was established in different periods of genetic code development. The body of data on the evolution of the genetic code system indicates that the elemental composition and molecular structure of protobiomonomers, and their M, T_m, photostability, and aqueous solubility determined their selection in the emergence of the standard genetic code.

On the Origin of Frameshift-Robustness of the Standard Genetic Code

The standard genetic code (SGC) has been extensively analyzed for the biological ramifications of its nonrandom structure. For instance, mismatch errors due to point mutation or mistranslation have an overall smaller effect on the amino acid polar requirement under the SGC than under random genetic codes (RGCs). A similar observation was recently made for frameshift errors, prompting the assertion that the SGC has been shaped by natural selection for frameshift-robustness-conservation of certain amino acid properties upon a frameshift mutation or translational frameshift. However, frameshift-robustness confers no benefit because frameshifts usually create premature stop codons that cause nonsense-mediated mRNA decay or production of nonfunctional truncated proteins. We here propose that the frameshift-robustness of the SGC is a byproduct of its mismatch-robustness. Of 564 amino acid properties considered, the SGC exhibits mismatch-robustness in 93-133 properties and frameshift-robustness in 55 properties, respectively, and that the latter is largely a subset of the former. For each of the 564 real and 564 randomly constructed fake properties of amino acids, there is a positive correlation between mismatch-robustness and frameshift-robustness across one million RGCs; this correlation arises because most amino acid changes resulting from a frameshift are also achievable by a mismatch error. Importantly, the SGC does not show significantly higher frameshift-robustness in any of the 55 properties than RGCs of comparable mismatch-robustness. These findings support that the frameshift-robustness of the SGC need not originate through direct selection and can instead be a site effect of its mismatch-robustness.

The Mutational Robustness of the Genetic Code and Codon Usage in Environmental Context: A Non-Extremophilic Preference?

The genetic code was evolved, to some extent, to minimize the effects of mutations. The effects of mutations depend on the amino acid repertoire, the structure of the genetic code and frequencies of amino acids in proteomes. The amino acid compositions of proteins and corresponding codon usages are still under selection, which allows us to ask what kind of environment the standard genetic code is adapted to. Using simple computational models and comprehensive datasets comprising genomic and environmental data from all three domains of Life, we estimate the expected severity of non-synonymous genomic mutations in proteins, measured by the change in amino acid physicochemical properties. We show that the fidelity in these physicochemical properties is expected to deteriorate with extremophilic codon usages, especially in thermophiles. These findings suggest that the genetic code performs better under non-extremophilic conditions, which not only explains the low substitution rates encountered in halophiles and thermophiles but the revealed relationship between the genetic code and habitat allows us to ponder on earlier phases in the history of Life.

Basic principles of the genetic code extension

Compounds including non-canonical amino acids (ncAAs) or other artificially designed molecules can find a lot of applications in medicine, industry and biotechnology. They can be produced thanks to the modification or extension of the standard genetic code (SGC). Such peptides or proteins including the ncAAs can be constantly delivered in a stable way by organisms with the customized genetic code. Among several methods of engineering the code, using non-canonical base pairs is especially promising, because it enables generating many new codons, which can be used to encode any new amino acid. Since even one pair of new bases can extend the SGC up to 216 codons generated by a six-letter nucleotide alphabet, the extension of the SGC can be achieved in many ways. Here, we proposed a stepwise procedure of the SGC extension with one pair of non-canonical bases to minimize the consequences of point mutations. We reported relationships between codons in the framework of graph theory. All 216 codons were represented as nodes of the graph, whereas its edges were induced by all possible single nucleotide mutations occurring between codons. Therefore, every set of canonical and newly added codons induces a specific subgraph. We characterized the properties of the induced subgraphs generated by selected sets of codons. Thanks to that, we were able to describe a procedure for incremental addition of the set of meaningful codons up to the full coding system consisting of three pairs of bases. The procedure of gradual extension of the SGC makes the whole system robust to changing genetic information due to mutations and is compatible with the views assuming that codons and amino acids were added successively to the primordial SGC, which evolved minimizing harmful consequences of mutations or mistranslations of encoded proteins.

A tRNA- and Anticodon-Centric View of the Evolution of Aminoacyl-tRNA Synthetases, tRNAomes, and the Genetic Code

Pathways of standard genetic code evolution remain conserved and apparent, particularly upon analysis of aminoacyl-tRNA synthetase (aaRS) lineages. Despite having incompatible active site folds, class I and class II aaRS are homologs by sequence. Specifically, structural class IA aaRS enzymes derive from class IIA aaRS enzymes by in-frame extension of the protein N-terminus and by an alternate fold nucleated by the N-terminal extension. The divergence of aaRS enzymes in the class I and class II clades was analyzed using the Phyre2 protein fold recognition server. The class I aaRS radiated from the class IA enzymes, and the class II aaRS radiated from the class IIA enzymes. The radiations of aaRS enzymes bolster the coevolution theory for evolution of the amino acids, tRNAomes, the genetic code, and aaRS enzymes and support a tRNA anticodon-centric perspective. We posit that second- and third-position tRNA anticodon sequence preference (C>(U~G)>A) powerfully selected the sectoring pathway for the code. GlyRS-IIA appears to have been the primordial aaRS from which all aaRS enzymes evolved, and glycine appears to have been the primordial amino acid around which the genetic code evolved.

The influence of different types of translational inaccuracies on the genetic code structure

BACKGROUND

The standard genetic code is a recipe for assigning unambiguously 21 labels, i.e. amino acids and stop translation signal, to 64 codons. However, at early stages of the translational machinery development, the codons did not have to be read unambiguously and the early genetic codes could have contained some ambiguous assignments of codons to amino acids. Therefore, the goal of this work was to obtain the genetic code structures which could have evolved assuming different types of inaccuracy of the translational machinery starting from unambiguous assignments of codons to amino acids.

RESULTS

We developed a theoretical model assuming that the level of uncertainty of codon assignments can gradually decrease during the simulations. Since it is postulated that the standard code has evolved to be robust against point mutations and mistranslations, we developed three simulation scenarios assuming that such errors can influence one, two or three codon positions. The simulated codes were selected using the evolutionary algorithm methodology to decrease coding ambiguity and increase their robustness against mistranslation.

CONCLUSIONS

The results indicate that the typical codon block structure of the genetic code could have evolved to decrease the ambiguity of amino acid to codon assignments and to increase the fidelity of reading the genetic information. However, the robustness to errors was not the decisive factor that influenced the genetic code evolution because it is possible to find theoretical codes that minimize the reading errors better than the standard 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.

A Non-neutral Origin for Error Minimization in the Origin of the Genetic Code

Massey (J Mol Evol 67:510-516, 2008; J Theor Biol 408:237-242, 2016; Nat Comput. https://doi.org/10.1007/s11047-017-9669-3, 2018) claims that the error minimization of the genetic code is derived by means of a neutral process and was not due to the action of natural selection. Here, I argue that this neutralist hypothesis of the origin of error minimization is not based directly on any neutral process but it could be only indirectly. On the contrary, it has been natural selection that has acted during the origin of the genetic code determining the property that similar amino acids are coded by similar codons within the genetic code table.

Optimization of the standard genetic code according to three codon positions using an evolutionary algorithm

Many biological systems are typically examined from the point of view of adaptation to certain conditions or requirements. One such system is the standard genetic code (SGC), which generally minimizes the cost of amino acid replacements resulting from mutations or mistranslations. However, no full consensus has been reached on the factors that caused the evolution of this feature. One of the hypotheses suggests that code optimality was directly selected as an advantage to preserve information about encoded proteins. An important feature that should be considered when studying the SGC is the different roles of the three codon positions. Therefore, we investigated the robustness of this code regarding the cost of amino acid replacements resulting from substitutions in these positions separately and the sum of these costs. We applied a modified evolutionary algorithm and included four models of the genetic code assuming various restrictions on its structure. The SGC was compared both with the codes that minimize the objective function and those that maximize it. This approach allowed us to place the SGC in the global space of possible codes, which is a more appropriate and unbiased comparison than that with randomly generated codes because they are characterized by relatively uniform amino acid assignments to codons. The SGC appeared to be well optimized at the global scale, but its individual positions were not fully optimized because there were codes that were optimized for only one codon position and simultaneously outperformed the SGC at the other positions. We also found that different code structures may lead to the same optimality and that random codes can show a tendency to minimize costs under some of the genetic code models. Our results suggest that the optimality of SGC could be a by-product of other processes.

Intrinsic Properties of tRNA Molecules as Deciphered via Bayesian Network and Distribution Divergence Analysis

The identity/recognition of tRNAs, in the context of aminoacyl tRNA synthetases (and other molecules), is a complex phenomenon that has major implications ranging from the origins and evolution of translation machinery and genetic code to the evolution and speciation of tRNAs themselves to human mitochondrial diseases to artificial genetic code engineering. Deciphering it via laboratory experiments, however, is difficult and necessarily time- and resource-consuming. In this study, we propose a mathematically rigorous two-pronged in silico approach to identifying and classifying tRNA positions important for tRNA identity/recognition, rooted in machine learning and information-theoretic methodology. We apply Bayesian Network modeling to elucidate the structure of intra-tRNA-molecule relationships, and distribution divergence analysis to identify meaningful inter-molecule differences between various tRNA subclasses. We illustrate the complementary application of these two approaches using tRNA examples across the three domains of life, and identify and discuss important (informative) positions therein. In summary, we deliver to the tRNA research community a novel, comprehensive methodology for identifying the specific elements of interest in various tRNA molecules, which can be followed up by the corresponding experimental work and/or high-resolution position-specific statistical analyses.

Genetic Code Optimization for Cotranslational Protein Folding: Codon Directional Asymmetry Correlates with Antiparallel Betasheets, tRNA Synthetase Classes

A new codon property, codon directional asymmetry in nucleotide content (CDA), reveals a biologically meaningful genetic code dimension: palindromic codons (first and last nucleotides identical, codon structure XZX) are symmetric (CDA = 0), codons with structures ZXX/XXZ are 5'/3' asymmetric (CDA = - 1/1; CDA = - 0.5/0.5 if Z and X are both purines or both pyrimidines, assigning negative/positive (-/+) signs is an arbitrary convention). Negative/positive CDAs associate with (a) Fujimoto's tetrahedral codon stereo-table; (b) tRNA synthetase class I/II (aminoacylate the 2'/3' hydroxyl group of the tRNA's last ribose, respectively); and (c) high/low antiparallel (not parallel) betasheet conformation parameters. Preliminary results suggest CDA-whole organism associations (body temperature, developmental stability, lifespan). Presumably, CDA impacts spatial kinetics of codon-anticodon interactions, affecting cotranslational protein folding. Some synonymous codons have opposite CDA sign (alanine, leucine, serine, and valine), putatively explaining how synonymous mutations sometimes affect protein function. Correlations between CDA and tRNA synthetase classes are weaker than between CDA and antiparallel betasheet conformation parameters. This effect is stronger for mitochondrial genetic codes, and potentially drives mitochondrial codon-amino acid reassignments. CDA reveals information ruling nucleotide-protein relations embedded in reversed (not reverse-complement) sequences (5'-ZXX-3'/5'-XXZ-3').

Optimization of amino acid replacement costs by mutational pressure in bacterial genomes

Mutations are considered a spontaneous and random process, which is important component of evolution because it generates genetic variation. On the other hand, mutations are deleterious leading to non-functional genes and energetically costly repairs. Therefore, one can expect that the mutational pressure is optimized to simultaneously generate genetic diversity and preserve genetic information. To check if empirical mutational pressures are optimized in these ways, we compared matrices of nucleotide mutation rates derived from bacterial genomes with their best possible alternatives that minimized or maximized costs of amino acid replacements associated with differences in their physicochemical properties (e.g. hydropathy and polarity). It should be noted that the studied empirical nucleotide substitution matrices and the costs of amino acid replacements are independent because these matrices were derived from sites free of selection on amino acid properties and the amino acid costs assumed only amino acid physicochemical properties without any information about mutation at the nucleotide level. Obtained results indicate that the empirical mutational matrices show a tendency to minimize costs of amino acid replacements. It implies that bacterial mutational pressures can evolve to decrease consequences of amino acid substitutions. However, the optimization is not full, which enables generation of some genetic variability.