Dataset Information

Convergent evolution of AUA decoding in bacteria and archaea.

ABSTRACT: Deciphering AUA codons is a difficult task for organisms, because AUA and AUG specify isoleucine (Ile) and methionine (Met), separately. Each of the other purine-ending sense co-don sets (NNR) specifies a single amino acid in the universal genetic code. In bacteria and archaea, the cytidine derivatives, 2-lysylcytidine (L or lysidine) and 2-agmatinylcytidine (agm(2)C or agmatidine), respectively, are found at the first letter of the anticodon of tRNA(Ile) responsible for AUA codons. These modifications prevent base pairing with G of the third letter of AUG codon, and enable tRNA(Ile) to decipher AUA codon specifically. In addition, these modifications confer a charging ability of tRNA(Ile) with Ile. Despite their similar chemical structures, L and agm(2)C are synthesized by distinctive mechanisms and catalyzed by different classes of enzymes, implying that the analogous decoding systems for AUA codons were established by convergent evolution after the phylogenic split between bacteria and archaea-eukaryotes lineages following divergence from the last universal common ancestor (LUCA).

SUBMITTER: Suzuki T

PROVIDER: S-EPMC4615378 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Convergent evolution of AUA decoding in bacteria and archaea.

Suzuki Tsutomu T Numata Tomoyuki T

RNA biology 20140101 12

Deciphering AUA codons is a difficult task for organisms, because AUA and AUG specify isoleucine (Ile) and methionine (Met), separately. Each of the other purine-ending sense co-don sets (NNR) specifies a single amino acid in the universal genetic code. In bacteria and archaea, the cytidine derivatives, 2-lysylcytidine (L or lysidine) and 2-agmatinylcytidine (agm(2)C or agmatidine), respectively, are found at the first letter of the anticodon of tRNA(Ile) responsible for AUA codons. These modifi ...[more]

PMID: 25629511

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Project description:Distantly related organisms may evolve similar traits when exposed to similar environments or engaging in certain lifestyles. Several members of the Lactobacillaceae (LAB) family are frequently isolated from the floral niche, mostly from bees and flowers. In some floral LAB species (henceforth referred to as bee-associated), distinctive genomic (e.g., genome reduction) and phenotypic (e.g., preference for fructose over glucose or fructophily) features were recently documented. These features are found across distantly related species, raising the hypothesis that specific genomic and phenotypic traits evolved convergently during adaptation to the floral environment. To test this hypothesis, we examined representative genomes of 369 species of bee-associated and non-bee-associated LAB. Phylogenomic analysis unveiled seven independent ecological shifts towards the floral niche in LAB. In these bee-associated LAB, we observed pervasive, significant reductions of genome size, gene repertoire, and GC content. Using machine leaning, we could distinguish bee-associated from non-bee-associated species with 94% accuracy, based on the absence of genes involved in metabolism, osmotic stress, or DNA repair. Moreover, we found that the most important genes for the machine learning classifier were seemingly lost, independently, in multiple bee-associated lineages. One of these genes, adhE, encodes a bifunctional aldehyde-alcohol dehydrogenase associated with the evolution of fructophily, a rare phenotypic trait that was recently identified in many floral LAB species. These results suggest that the independent evolution of distinctive phenotypes in bee-associated LAB has been largely driven by independent loss of the same set of genes.ImportanceSeveral lactic acid bacteria (LAB) species are intimately associated with bees and exhibit unique biochemical properties with potential for food applications and honeybee health. Using a machine-learning based approach, our study shows that adaptation of LAB to the bee environment was accompanied by a distinctive genomic trajectory deeply shaped by gene loss. Several of these gene losses occurred independently in distantly related species and are linked to some of their unique biotechnologically relevant traits, such as the preference of fructose over glucose (fructophily). This study underscores the potential of machine learning in identifying fingerprints of adaptation and detecting instances of convergent evolution. Furthermore, it sheds light onto the genomic and phenotypic particularities of bee-associated bacteria, thereby deepening the understanding of their positive impact on honeybee health.

Dataset Information

Convergent evolution of AUA decoding in bacteria and archaea.

Publications

Convergent evolution of AUA decoding in bacteria and archaea.

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