Genes optimized by evolution for accurate and fast translation encode in Archaea and Bacteria a broad and characteristic spectrum of protein functions

The Code of Silence: Widespread Associations Between Synonymous Codon Biases and Gene Function

Some mutations in gene coding regions exchange one synonymous codon for another, and thus do not alter the amino acid sequence of the encoded protein. Even though they are often called 'silent,' these mutations may exhibit a plethora of effects on the living cell. Therefore, they are often selected during evolution, causing synonymous codon usage biases in genomes. Comparative analyses of bacterial, archaeal, fungal, and human cancer genomes have found many links between a gene's biological role and the accrual of synonymous mutations during evolution. In particular, highly expressed genes in certain functional categories are enriched with optimal codons, which are decoded by the abundant tRNAs, thus enhancing the speed and accuracy of the translating ribosome. The set of genes exhibiting codon adaptation differs between genomes, and these differences show robust associations to organismal phenotypes. In addition to selection for translation efficiency, other distinct codon bias patterns have been found in: amino acid starvation genes, cyclically expressed genes, tissue-specific genes in animals and plants, oxidative stress response genes, cellular differentiation genes, and oncogenes. In addition, genomes of organisms harboring tRNA modifications exhibit particular codon preferences. The evolutionary trace of codon bias patterns across orthologous genes may be examined to learn about a gene's relevance to various phenotypes, or, more generally, its function in the cell.

Inferring gene function from evolutionary change in signatures of translation efficiency

Background

The genetic code is redundant, meaning that most amino acids can be encoded by more than one codon. Highly expressed genes tend to use optimal codons to increase the accuracy and speed of translation. Thus, codon usage biases provide a signature of the relative expression levels of genes, which can, uniquely, be quantified across the domains of life.

Results

Here we describe a general statistical framework to exploit this phenomenon and to systematically associate genes with environments and phenotypic traits through changes in codon adaptation. By inferring evolutionary signatures of translation efficiency in 911 bacterial and archaeal genomes while controlling for confounding effects of phylogeny and inter-correlated phenotypes, we linked 187 gene families to 24 diverse phenotypic traits. A series of experiments in Escherichia coli revealed that 13 of 15, 19 of 23, and 3 of 6 gene families with changes in codon adaptation in aerotolerant, thermophilic, or halophilic microbes. Respectively, confer specific resistance to, respectively, hydrogen peroxide, heat, and high salinity. Further, we demonstrate experimentally that changes in codon optimality alone are sufficient to enhance stress resistance. Finally, we present evidence that multiple genes with altered codon optimality in aerobes confer oxidative stress resistance by controlling the levels of iron and NAD(P)H.

Conclusions

Taken together, these results provide experimental evidence for a widespread connection between changes in translation efficiency and phenotypic adaptation. As the number of sequenced genomes increases, this novel genomic context method for linking genes to phenotypes based on sequence alone will become increasingly useful.

scnRCA: a novel method to detect consistent patterns of translational selection in mutationally-biased genomes

Codon usage bias (CUB) results from the complex interplay between translational selection and mutational biases. Current methods for CUB analysis apply heuristics to integrate both components, limiting the depth and scope of CUB analysis as a technique to probe into the evolution and optimization of protein-coding genes. Here we introduce a self-consistent CUB index (scnRCA) that incorporates implicit correction for mutational biases, facilitating exploration of the translational selection component of CUB. We validate this technique using gene expression data and we apply it to a detailed analysis of CUB in the Pseudomonadales. Our results illustrate how the selective enrichment of specific codons among highly expressed genes is preserved in the context of genome-wide shifts in codon frequencies, and how the balance between mutational and translational biases leads to varying definitions of codon optimality. We extend this analysis to other moderate and fast growing bacteria and we provide unified support for the hypothesis that C- and A-ending codons of two-box amino acids, and the U-ending codons of four-box amino acids, are systematically enriched among highly expressed genes across bacteria. The use of an unbiased estimator of CUB allows us to report for the first time that the signature of translational selection is strongly conserved in the Pseudomonadales in spite of drastic changes in genome composition, and extends well beyond the core set of highly optimized genes in each genome. We generalize these results to other moderate and fast growing bacteria, hinting at selection for a universal pattern of gene expression that is conserved and detectable in conserved patterns of codon usage bias.

High level of intergenera gene exchange shapes the evolution of haloarchaea in an isolated Antarctic lake

Deep Lake in Antarctica is a globally isolated, hypersaline system that remains liquid at temperatures down to -20 °C. By analyzing metagenome data and genomes of four isolates we assessed genome variation and patterns of gene exchange to learn how the lake community evolved. The lake is completely and uniformly dominated by haloarchaea, comprising a hierarchically structured, low-complexity community that differs greatly to temperate and tropical hypersaline environments. The four Deep Lake isolates represent distinct genera (∼85% 16S rRNA gene similarity and ∼73% genome average nucleotide identity) with genomic characteristics indicative of niche adaptation, and collectively account for ∼72% of the cellular community. Network analysis revealed a remarkable level of intergenera gene exchange, including the sharing of long contiguous regions (up to 35 kb) of high identity (∼100%). Although the genomes of closely related Halobacterium, Haloquadratum, and Haloarcula (>90% average nucleotide identity) shared regions of high identity between species or strains, the four Deep Lake isolates were the only distantly related haloarchaea to share long high-identity regions. Moreover, the Deep Lake high-identity regions did not match to any other hypersaline environment metagenome data. The most abundant species, tADL, appears to play a central role in the exchange of insertion sequences, but not the exchange of high-identity regions. The genomic characteristics of the four haloarchaea are consistent with a lake ecosystem that sustains a high level of intergenera gene exchange while selecting for ecotypes that maintain sympatric speciation. The peculiarities of this polar system restrict which species can grow and provide a tempo and mode for accentuating gene exchange.

On the limitations of using ribosomal genes as references for the study of codon usage: a rebuttal

In a recent paper published in PLOS ONE, Wang et al. challenge our finding that the identity of optimal codons in different genomes follows a set of clear rules. Here we provide a rebuttal of their paper and demonstrate that the results of our original PLOS Genetics paper stand. This provides us with an opportunity to bring up an aspect of how codon usage has been studied that should be of general interest. The Wang et al. study, as well as many other studies, used ribosomal genes as a reference set for the study of patterns of codon usage. We discuss here the assumptions that are made in order to justify using ribosomal genes to study codon bias, suggest that this practice can at times be problematic, and discuss its limitations.

Genomic analysis reveals Lactobacillus sanfranciscensis as stable element in traditional sourdoughs

Sourdough has played a significant role in human nutrition and culture for thousands of years and is still of eminent importance for human diet and the bakery industry. Lactobacillus sanfranciscensis is the predominant key bacterium in traditionally fermented sourdoughs.

The genome of L. sanfranciscensis TMW 1.1304 isolated from an industrial sourdough fermentation was sequenced with a combined Sanger/454-pyrosequencing approach followed by gap closing by walking on fosmids. The sequencing data revealed a circular chromosomal sequence of 1,298,316 bp and two additional plasmids, pLS1 and pLS2, with sizes of 58,739 bp and 18,715 bp, which are predicted to encode 1,437, 63 and 19 orfs, respectively. The overall GC content of the chromosome is 34.71%. Several specific features appear to contribute to the ability of L. sanfranciscensis to outcompete other bacteria in the fermentation. L. sanfranciscensis contains the smallest genome within the lactobacilli and the highest density of ribosomal RNA operons per Mbp genome among all known genomes of free-living bacteria, which is important for the rapid growth characteristics of the organism. A high frequency of gene inactivation and elimination indicates a process of reductive evolution. The biosynthetic capacity for amino acids scarcely availably in cereals and exopolysaccharides reveal the molecular basis for an autochtonous sourdough organism with potential for further exploitation in functional foods. The presence of two CRISPR/cas loci versus a high number of transposable elements suggests recalcitrance to gene intrusion and high intrinsic genome plasticity.

Quantification of codon selection for comparative bacterial genomics

Background

Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).

Results

This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (e.g. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.

Conclusions

The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.