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Environmental Shaping of Ribosomal RNA Nucleotide Composition

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Abstract

Ribosomal RNA (rRNA) is one of the most important macromolecules in the cell. It is well established that high-temperature environmental conditions destabilize rRNA, leading to a selection for G+C-rich stabilizing structures. Our knowledge about the nucleotide composition effect of other environmental conditions, however, is limited. In the present work, I addressed this by correlating the rRNA nucleotide composition to known environmental habitats for bacteria. The bacterial phyla Firmicutes, Actinobacteria, and Proteobacteria were chosen for in-depth analyses due to the abundance of information available in the databases. Major differences in nucleotide composition were identified between these phyla. In addition to the G+C→A+T gradients, a main gradient of G+A→C+T was identified for Firmicutes, while a G+T→A+C gradient was identified for Actinobacteria. With respect to correlation to environmental conditions, the Firmicutes showed a main structure of high G+C being correlated to thermophilic conditions, high A+T to anaerobic conditions, and high C+T to halophilic conditions. The main patterns detected for Firmicutes can be explained by structural stability for high G+C, chemical instability of G under aerobic conditions, and structural stability by purine/pyrimidine skew for halophilic conditions. On the contrary, the correlations for Actinobacteria cannot easily be explained by chemical and/or structural stability. This may indicate interference with factors not included in my work. Finally, I found a main correlation between high A+T and endosymbiosis for Proteobacteria. High A+T probably reflects adaptation to cell internal growth. Further support for environmentally driven nucleotide composition shaping was found and that polyphyletic bacteria were associated with the same environment/nucleotide correlations. My conclusion is that environmental conditions and habitats have a major effect on rRNA nucleotide composition but that the effects may differ between the bacterial phyla.

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Acknowledgments

This work was supported by Hedmark Sparebank and a research levy on certain agriculture products in Norway. A great thank is also given to Monika Zimonja for revising the statistical treatments.

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Authors and Affiliations

  1. Hedmark University College, Hamar, 2306, Norway

    Knut Rudi

  2. NOFIMA Food, 1430, Ås, Norway

    Knut Rudi

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  1. Knut Rudi
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Correspondence to Knut Rudi.

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ESM 1

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Figure S1

Principal component analyses for mononucleotide frequency data for SSU (black circles) and LSU (red squares). The generation of normalized frequency data and the PCA were conducted using the Phylomode program, and plotted using MINITAB. The nucleotide gradients are marked (PDF 35.9 KB).

Table S1

ANOVA of dinucleotide composition in LSU and SSU for global data. 1 p values significant A+T the 5% level are marked (PDF 16.4 KB).

Table S2

Pearson’s correlation analysis for pair-wise comparisons of LSU and SSU PCs1. 1Pairs with significant correlation (p < 0.05) are highlighted. 2The Pearson correlation coefficient and the corresponding p value are shown (PDF 40.7 KB).

Table S3

ANOVA of dinucleotide thermodynamic properties in LSU and SSU for global data. 1The thermodynamic parameters used have previously been described by Santalucia and Hicks6. 2 p values significant A+T, the 5% level are marked (PDF 25.5 KB).

Table S4

ANOVA for bacterial SSU dinucleotide composition. 1 p values significant A+T, the 5% level are marked (PDF 31.7 KB).

Table S5

ANOVA of genome, SSU and LSU dinucleotide composition. 1p-values significant A+T, the 5% level are marked (PDF 26.8 KB).

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Rudi, K. Environmental Shaping of Ribosomal RNA Nucleotide Composition. Microb Ecol 57, 469–477 (2009). https://doi.org/10.1007/s00248-008-9446-z

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  • DOI: https://doi.org/10.1007/s00248-008-9446-z

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