The fundamental tradeoff in genomes and proteomes of prokaryotes established by the genetic code, codon entropy, and physics of nucleic acids and proteins

Abstract

Background: Mutations in nucleotide sequences provide a foundation for genetic variability, and selection is the driving force of the evolution and molecular adaptation. Despite considerable progress in the understanding of selective forces and their compositional determinants, the very nature of underlying mutational biases remains unclear.

Results: We explore here a fundamental tradeoff, which analytically describes mutual adjustment of the nucleotide and amino acid compositions and its possible effect on the mutational biases. The tradeoff is determined by the interplay between the genetic code, optimization of the codon entropy, and demands on the structure and stability of nucleic acids and proteins.

Conclusion: The tradeoff is the unifying property of all prokaryotes regardless of the differences in their phylogenies, life styles, and extreme environments. It underlies mutational biases characteristic for genomes with different nucleotide and amino acid compositions, providing foundation for evolution and adaptation.

Figure 1

Distribution of the GC _CB and GC _NCB content and the derived theoretical limits for 1364 prokaryotic genomes. A, the highest (red) and lowest (green) limits on nucleotide composition obtained by replacing natural codons with synonymous GC-richest and GC-poorest ones. B, the theoretical limits (red and green) on amino acid composition (GC_NCB), see also Additional file 1: Figure S1.

Figure 2

The tradeoff between nucleotide and amino acid compositions. Theoretical model. Black circles represent the genomes. The lower (green) and upper (red) limits for GC_CB are calculated in the same way as in Figure 1a. The tradeoff describes the relation between the two components of GC depicted by an orange curve (with the coefficients a = 20.82, b = −16.28, c = −49.4, r = 0.255). The colored circles illustrate three pairs of genomes with the same GC_NAT (45 percent – magenta, 51 – yellow, and 63 – blue) obtained by combining the GC_CB and GC_NCB in different proportions (see Additional file 1: Table S7 for details).

Figure 3

Simulations of the tradeoff dynamics via random nucleotide mutations. A, B, simulations for two genomes (Nocardiopsis dassonvillei subs. dassonvillei DSM 43111, GC_NAT = 72.7; and Streptobacillus moniliformis DSM 12112, GC_NAT = 26.3) with distorted codon bias. A, changes in the GC_CB/GC_NCB pairs related to the tradeoff. B, the increase of the genomes’ codon entropy in relation to the distribution of entropies in all genomes. C and D, simulations of mutations in 1364 natural genomes; the simulation starts at points marked by filled circles and continues along the lines. The traces are colored by average amino acid depth C, changes in the GC_CB/GC_NCB pairs related to the tradeoff. D, behavior of the codon entropy.

Figure 4

Environmental factors in relation to the tradeoff: A, Temperature; B, Habitat; C, Aerobicity; D, Domain of Life.

Figure 5

Limits of the codon entropy in genomes with the natural amino acid composition preserved. A, Natural nucleotide composition (black); synonymous codons substituted with the GC-richest ones (red) and the GC-poorest ones (green); synonymous codons were used uniformly (blue), GC_NCB. B, Natural nucleotide composition (black); reduced synonymous codons (orange) – in cases when there are several synonymous codons with the same GC saturation, only one codon was used.

Figure 6

Dependence of the purine/pyrimidine ratio (A) and the average amino acid depth (B) on the GC content of protein-coding sequences.

Figure 7

Dependence of the purine-purine RpR (A) pyrimidine-pyrimidine YpY (B), pyrimidine-purine YpR (C), purine-pyrimidine RpY (D) dinucleotides on the genomic GC _NAT .

Figure 8

Dependence of the adenine-adenine ApA (A), guanine-guanine GpG (B), adenine-guanine ApG (C), guanine-adenine GpA (D) dinucleotides on the genomic GC _NAT .