An Autotrophic Origin for the Coded Amino Acids is Concordant with the Coevolution Theory of the Genetic Code

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.

Biophysical Interactions Underpin the Emergence of Information in the Genetic Code

The genetic code conceals a 'code within the codons', which hints at biophysical interactions between amino acids and their cognate nucleotides. Yet, research over decades has failed to corroborate systematic biophysical interactions across the code. Using molecular dynamics simulations and NMR, we have analysed interactions between the 20 standard proteinogenic amino acids and 4 RNA mononucleotides in 3 charge states. Our simulations show that 50% of amino acids bind best with their anticodonic middle base in the -1 charge state common to the backbone of RNA, while 95% of amino acids interact most strongly with at least 1 of their codonic or anticodonic bases. Preference for the cognate anticodonic middle base was greater than 99% of randomised assignments. We verify a selection of our results using NMR, and highlight challenges with both techniques for interrogating large numbers of weak interactions. Finally, we extend our simulations to a range of amino acids and dinucleotides, and corroborate similar preferences for cognate nucleotides. Despite some discrepancies between the predicted patterns and those observed in biology, the existence of weak stereochemical interactions means that random RNA sequences could template non-random peptides. This offers a compelling explanation for the emergence of genetic information in biology.

A biophysical basis for the emergence of the genetic code in protocells

The origin of the genetic code is an abiding mystery in biology. Hints of a 'code within the codons' suggest biophysical interactions, but these patterns have resisted interpretation. Here, we present a new framework, grounded in the autotrophic growth of protocells from CO₂ and H₂. Recent work suggests that the universal core of metabolism recapitulates a thermodynamically favoured protometabolism right up to nucleotide synthesis. Considering the genetic code in relation to an extended protometabolism allows us to predict most codon assignments. We show that the first letter of the codon corresponds to the distance from CO₂ fixation, with amino acids encoded by the purines (G followed by A) being closest to CO₂ fixation. These associations suggest a purine-rich early metabolism with a restricted pool of amino acids. The second position of the anticodon corresponds to the hydrophobicity of the amino acid encoded. We combine multiple measures of hydrophobicity to show that this correlation holds strongly for early amino acids but is weaker for later species. Finally, we demonstrate that redundancy at the third position is not randomly distributed around the code: non-redundant amino acids can be assigned based on size, specifically length. We attribute this to additional stereochemical interactions at the anticodon. These rules imply an iterative expansion of the genetic code over time with codon assignments depending on both distance from CO₂ and biophysical interactions between nucleotide sequences and amino acids. In this way the earliest RNA polymers could produce non-random peptide sequences with selectable functions in autotrophic protocells.

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.

Genetic codes optimized as a traveling salesman problem

The Standard Genetic Code (SGC) is robust to mutational errors such that frequently occurring mutations minimally alter the physio-chemistry of amino acids. The apparent correlation between the evolutionary distances among codons and the physio-chemical distances among their cognate amino acids suggests an early co-diversification between the codons and amino acids. Here we formulated the co-minimization of evolutionary distances between codons and physio-chemical distances between amino acids as a Traveling Salesman Problem (TSP) and solved it with a Hopfield neural network. In this unsupervised learning algorithm, macromolecules (e.g., tRNAs and aminoacyl-tRNA synthetases) associating codons with amino acids were considered biological analogs of Hopfield neurons associating "tour cities" with "tour positions". The Hopfield network efficiently yielded an abundance of genetic codes that were more error-minimizing than SGC and could thus be used to design artificial genetic codes. We further argue that as a self-optimization algorithm, the Hopfield neural network provides a model of origin of SGC and other adaptive molecular systems through evolutionary learning.

Match fitness landscapes for macromolecular interaction networks: Selection for translational accuracy and rate can displace tRNA-binding interfaces of non-cognate aminoacyl-tRNA synthetases

Advances in structural biology of aminoacyl-tRNA synthetases (aaRSs) have revealed incredible diversity in how aaRSs bind their tRNA substrates. The causes of this diversity remain mysterious. We developed a new class of highly rugged fitness landscape models called match landscapes, through which genes encode the assortative interactions of their gene products through the complementarity and identifiability of their structural features. We used results from coding theory to prove bounds and equalities on fitness in match landscapes assuming additive interaction energies, macroscopic aminoacylation kinetics including proofreading, site-specific modifiers of interaction, and selection for translational accuracy in multiple, perfectly encoded site-types. Using genotypes based on extended Hamming codes we show that over a wide array of interface sizes and numbers of encoded cognate pairs, selection for translational accuracy alone is insufficient to displace the tRNA-binding interfaces of aaRSs. Yet, under combined selection for translational accuracy and rate, site-specific modifiers are selected to adaptively displace the tRNA-binding interfaces of non-cognate aaRS-tRNA pairs. We describe a remarkable correspondence between the lengths of perfect RNA (quaternary) codes and the modal sizes of small non-coding RNA families.

Genetic Code Evolution Investigated through the Synthesis and Characterisation of Proteins from Reduced-Alphabet Libraries

The universal genetic code of 20 amino acids is the product of evolution. It is believed that earlier versions of the code had fewer residues. Many theories for the order in which amino acids were integrated into the code have been proposed, considering factors ranging from prebiotic chemistry to codon capture. Several meta-analyses combined these theories to yield a feasible consensus chronology of the genetic code's evolution, but there is a dearth of experimental data to test the hypothesised order. We used combinatorial chemistry to synthesise libraries of random polypeptides that were based on different subsets of the 20 standard amino acids, thus representing different stages of a plausible history of the alphabet. Four libraries were comprised of the five, nine, and 16 most ancient amino acids, and all 20 extant residues for a direct side-by-side comparison. We characterised numerous variants from each library for their solubility and propensity to form secondary, tertiary or quaternary structures. Proteins from the two most ancient libraries were more likely to be soluble than those from the extant library. Several individual protein variants exhibited inducible protein folding and other traits typical of intrinsically disordered proteins. From these libraries, we can infer how primordial protein structure and function might have evolved with the genetic code.

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.

The last universal common ancestor between ancient Earth chemistry and the onset of genetics

All known life forms trace back to a last universal common ancestor (LUCA) that witnessed the onset of Darwinian evolution. One can ask questions about LUCA in various ways, the most common way being to look for traits that are common to all cells, like ribosomes or the genetic code. With the availability of genomes, we can, however, also ask what genes are ancient by virtue of their phylogeny rather than by virtue of being universal. That approach, undertaken recently, leads to a different view of LUCA than we have had in the past, one that fits well with the harsh geochemical setting of early Earth and resembles the biology of prokaryotes that today inhabit the Earth's crust.

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

Self-Referential Encoding on Modules of Anticodon Pairs-Roots of the Biological Flow System

The proposal that the genetic code was formed on the basis of (proto)tRNA Dimer-Directed Protein Synthesis is reviewed and updated. The tRNAs paired through the anticodon loops are an indication on the process. Dimers are considered mimics of the ribosomes-structures that hold tRNAs together and facilitate the transferase reaction, and of the translation process-anticodons are at the same time codons for each other. The primitive protein synthesis system gets stabilized when the product peptides are stable and apt to bind the producers therewith establishing a self-stimulating production cycle. The chronology of amino acid encoding starts with Glycine and Serine, indicating the metabolic support of the Glycine-Serine C1-assimilation pathway, which is also consistent with evidence on origins of bioenergetics mechanisms. Since it is not possible to reach for substrates simpler than C1 and compounds in the identified pathway are apt for generating the other central metabolic routes, it is considered that protein synthesis is the beginning and center of a succession of sink-effective mechanisms that drive the formation and evolution of the metabolic flow system. Plasticity and diversification of proteins construct the cellular system following the orientation given by the flow and implementing it. Nucleic acid monomers participate in bioenergetics and the polymers are conservative memory systems for the synthesis of proteins. Protoplasmic fission is the final sink-effective mechanism, part of cell reproduction, guaranteeing that proteins don't accumulate to saturation, which would trigger inhibition.