Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles

Abstract

Errors that occur during transcription have received much less attention than the mutations that occur in DNA because transcription errors are not heritable and usually result in a very limited number of altered proteins. However, transcription error rates are typically several orders of magnitude higher than the mutation rate. Also, individual transcripts can be translated multiple times, so a single error can have substantial effects on the pool of proteins. Transcription errors can also contribute to cellular noise, thereby influencing cell survival under stressful conditions, such as starvation or antibiotic stress. Implementing a method that captures transcription errors genome-wide, we measured the rates and spectra of transcription errors in Escherichia coli and in endosymbionts for which mutation and/or substitution rates are greatly elevated over those of E. coli Under all tested conditions, across all species, and even for different categories of RNA sequences (mRNA and rRNAs), there were no significant differences in rates of transcription errors, which ranged from 2.3 × 10(-5) per nucleotide in mRNA of the endosymbiont Buchnera aphidicola to 5.2 × 10(-5) per nucleotide in rRNA of the endosymbiont Carsonella ruddii The similarity of transcription error rates in these bacterial endosymbionts to that in E. coli (4.63 × 10(-5) per nucleotide) is all the more surprising given that genomic erosion has resulted in the loss of transcription fidelity factors in both Buchnera and Carsonella.

Keywords: RNA polymerase fidelity; base substitutions; transcription errors.

Fig. S1.

Nucleic acid information processing genes that are present in E. coli compared with their retention or loss in B. aphidicola and C. ruddii. Colored circles indicate retention of the corresponding gene; white circles indicate loss of the corresponding gene from the specified genome.

Fig. 1.

Frequency of transcription errors in E. coli. Points are color-coded according to growth condition (n = 2 for each condition); horizontal bars represent means of each column. No significant differences in transcription error frequencies were detected between any of the tested parameters.

Fig. S2.

Frequency of transcription errors along the E. coli genome. Shaded rectangles represent transcription error rates of all errors over the eight E. coli samples in nonoverlapping 50-kb windows. Horizontal lines represent the genome-wide mean transcription error rate (black) and 2 SDs from the mean (red). Positions of replication origin and terminus are shown.

Fig. S3.

Association between numbers of transcription errors and sequence coverage. Error numbers computed for nonoverlapping 50-kb windows across the E. coli genome in all eight samples.

Fig. S4.

Transcription error frequencies in E. coli genes transcribed on the leading or lagging strands. Points are color-coded according to growth condition, and horizontal bars represent means of each column. There is no significant difference between the transcription error frequencies for genes encoded on the two strands (Wilcoxon test, P > 0.90; n = 8).

Fig. 2.

Transcription error frequencies by substitution type in E. coli. Points are color-coded according to growth condition, and horizontal bars represent mean values for each class of base substitution. (A) Transcription error frequencies for individual substitutions. C→U is the most common transcription error, displaying a significantly higher error rate than each of the other substitutions. (B) Effect of base composition (G/C or A/U) on transcription error frequencies. Errors occur at significantly higher frequencies when the original nucleotide is a G or C. Removal of C→U errors from the analysis (right column) demonstrates that the significant effect does not depend on the most abundant type of error. (C) Transcription error frequencies grouped according to base composition G/C or A/U of resulting substitutions. Transcription errors resulting in A or U occur at significantly higher levels than those resulting in G or C. Removal of C→U errors from the analysis (right column) demonstrates that the significant effect does not depend on the most abundant type of error. Comparisons were made by pairwise Wilcoxon tests (n = 8 for each test), subjected to Bonferroni correction: *P < 0.05; **P < 0.01.

Fig. 3.

Transcription error frequencies in divergent bacterial taxa. Points are color-coded according to growth condition or source of RNA (see Key), and horizontal bars represent means of each column. (A) Transcription error frequencies in E. coli mRNA (n = 8), B. aphidicola mRNA (n = 2), B. aphidicola rRNA (n = 2), and C. ruddii rRNA (n = 1). (B) Transcription error frequencies by substitution type in bacterial endosymbionts. No significant differences were detected for any pairwise comparisons.

Fig. S5.

Effect of sequencing errors and data quality on the estimation of transcription error frequencies. Transcription error frequencies for the combined E. coli replicates were calculated at increasing average base quality scores between 10 and 40 to demonstrate the effect of sequencing errors and low quality bases on error frequencies. Overall transcription error frequency (A) and the transcription error frequency for each nucleotide substitution (B) level off in the quality-score range of 18–20, indicating that use of data in this range and beyond exclude sequencing artifacts from estimates of transcription error rates. There were insufficient bases in the transcriptome that attained average quality scores >38 for inclusion in this analysis.