Synonymous genes explore different evolutionary landscapes

Abstract

The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other through single mutation. Thus, synonymous DNA sequences should access different regions of the protein sequence space through a limited number of mutations, and this may deeply influence the evolution of natural proteins. Here, we demonstrate that this feature can be of value for manipulating protein evolvability. We designed an algorithm that, starting from an input gene, constructs a synonymous sequence that systematically includes the codons with the most different evolutionary perspectives; i.e., codons that maximize accessibility to amino acids previously unreachable from the template by point mutation. A synonymous version of a bacterial antibiotic resistance gene was computed and synthesized. When concurrently submitted to identical directed evolution protocols, both the wild type and the recoded sequence led to the isolation of specific, advantageous phenotypic variants. Simulations based on a mutation isolated only from the synthetic gene libraries were conducted to assess the impact of sub-functional selective constraints, such as codon usage, on natural adaptation. Our data demonstrate that rational design of synonymous synthetic genes stands as an affordable improvement to any directed evolution protocol. We show that using two synonymous DNA sequences improves the overall yield of the procedure by increasing the diversity of mutants generated. These results provide conclusive evidence that synonymous coding sequences do experience different areas of the corresponding protein adaptive landscape, and that a sequence's codon usage effectively constrains the evolution of the encoded protein.

Figure 1. Standard genetic code and codon evolutionary landscapes.

Every codon can access nine other codons by single mutation, which corresponds to only 5.8 proximal aa on average due to the code redundancy. These evolutionary perspectives are highlighted in yellow and blue and for the arginine codons CGG and CGT, respectively (green indicates codons accessible from both). Amino acids reachable by only one of the two codons are bold and underlined.

Figure 2. Evolutionary landscape comparison of the aac_WT and aac_ELP synonymous genes.

aac_ELP has been designed by the ELP software to maximize evolutionary perspective divergence from aac_WT when subjected to single mutation. The 184 successive positions along AAC(6′) are represented as columns. Each row stands for an aa, as indicated by the one-letter code in first column. Intersection between aa and position are coloured according to the following code: black, aa encoded at that position; blue, aa specifically accessible by aac_WT; red, aa specifically accessible by aac_ELP; yellow, aa directly accessible from both aac genes; grey, aa inaccessible from either aac genes through single mutation. Blue and red patterns, denoting different evolutionary perspectives, are widely and evenly distributed along the sequence. The histogram on the bottom summarizes the number of aa directly accessible only by aac_WT (blue squares) or aac_ELP (red squares) for each position. Mutations isolated in this study are indicated above the diagram and corresponding positions are black lined. Mutations' outcomes are highlighted with bright green borders. Asterisks denote mutations isolated together.

Figure 3. Comparison of the amino acid substitutions identified in alleles sampled from the mutant libraries before selection.

This diagram is reminiscent of Figure 2. The 184 successive positions along the AAC(6′)-Ib protein are represented as columns. Each row stands for an aa, as indicated by the one-letter code in first column. Black cells show the WT sequence, other coloured cells highlight the substitutions identified by sequencing 297 aac_WT and 267 aac_ELP alleles, independent and randomly chosen before any selection. The color code is the following: blue, observed substitution only directly accessible from aac_WT; red, observed substitution only directly accessible from aac_ELP; yellow, observed substitution directly accessible from both genes; green, observed substitution resulting from a double mutation in the same codon. Overall, we identified 524 substitutions out of which 110 were only accessible from one of the version of the gene and not the other. The mutations specific of each gene versions were only observed from the cognate template. The histogram on the bottom summarizes the number of aa substitution specific to each version that were sampled at each position (aac_WT, blue squares; aac_ELP, red squares). The shaded area recalls the theoretical pattern as shown in Figure 4.

Figure 4. Impact of the low-usage leucine codon CTA on L55Q evolutionary pathways.

The L55Q mutation has only been isolated from aac_ELP libraries and has never been described in natural isolates. In aac_WT, L55 is encoded by TTA. Panel A: two main pathways can be followed to access Gln under selection, one with a single CTA intermediate, which might be associated with a lower fitness (top, selective pathway) and the other with two neutral intermediates (bottom, neutral pathway). Every genotype presented in these schematic landscapes has been constructed and assessed for growth on isepamicin. The colouring scheme, with darker colours associated with lower fitness, derives from these results except for the weakly used codon CTA for which the putative fitness effect was not measurable. Panel B: Monte-Carlo simulations of the evolution of TTA alleles populations were carried out, assuming various fitness f of CTA. s denotes the selective coefficient associated with the CTA codon. The cumulative number of simulations where CAA (top, selective pathway) or CAG (bottom, neutral pathway) reached fixation is plotted over time in generations (2,000 repetitions). Even weak selective coefficient against CTA (e.g. 5 10⁻⁴) greatly affects the use of the selective pathway. Although longer, the neutral pathway is preferred over the selective one from selective coefficients as low as 2.5 10⁻³.