Rapid, accurate, computational discovery of Rho-independent transcription terminators illuminates their relationship to DNA uptake

Abstract

Background: In many prokaryotes, transcription of DNA to RNA is terminated by a thymine-rich stretch of DNA following a hairpin loop. Detecting such Rho-independent transcription terminators can shed light on the organization of bacterial genomes and can improve genome annotation. Previous computational methods to predict Rho-independent terminators have been slow or limited in the organisms they consider.

Results: We describe TransTermHP, a new computational method to rapidly and accurately detect Rho-independent transcription terminators. We predict the locations of terminators in 343 prokaryotic genomes, representing the largest collection of predictions available. In Bacillus subtilis, we can detect 93% of known terminators with a false positive rate of just 6%, comparable to the best-known methods. Outside the Firmicutes division, we find that Rho-independent termination plays a large role in the Neisseria and Vibrio genera, the Pasteurellaceae (including the Haemophilus genus) and several other species. In Neisseria and Pasteurellaceae, terminator hairpins are frequently formed by closely spaced, complementary instances of exogenous DNA uptake signal sequences. We quantify the propensity for terminators to include these sequences. In the process, we provide the first discussion of potential uptake signals in Haemophilus ducreyi and Mannheimia succiniciproducens, and we discuss the preference for a particular configuration of uptake signal sequences within terminators.

Conclusion: Our new fast and accurate method for detecting transcription terminators has allowed us to identify and analyze terminators in many new genomes and to identify DNA uptake signal sequences in several species where they have not been previously reported. Our software and predictions are freely available.

Figure 1

Schematic of the terminator motif for which TransTermHP searches. The terminators consist of a short stem-loop hairpin followed by a thymine-rich region on their 3' side. For the results reported here, TransTermHP was restricted to find terminators for which each side of the stem is ≥ 4 nt, the length of the loop is ≥ 3 nt and ≤ 13 nt, and the total length of the stem-loop was ≤ 59 nt.

Figure 2

Performance of TransTermHP in B. subtilis. Receiver operator characteristic (ROC) curve showing the percentage of positive regions for which TransTermHP finds a terminator for various low false positive rates (circles), using a data set derived from experimentally verified operons [3]. The reported performance of the method described by de Hoon et al. [3] on this set after training is also shown (triangle). TransTermHP performs comparably without fitting parameters to the data set.

Figure 3

Stem lengths for high-confidence terminators in six organisms. These six organisms exhibit quite different distributions of stem lengths, with Neisseria having, on average, the longest stems, and the H. ducreyi and V. cholerae having the shortest. Because the statistics are computed using only high-confidence terminators, they may be skewed toward longer stem lengths.

Figure 4

Extended motif for H. ducreyi and H. influenzae. (a) A sequence logo [26,27] created from the regions surrounding occurrences of USS motifs in H. influenzae. Position +1 is the first position following the USS motif. The previously reported extended motif is shown above the letters. (b) A sequence logo created from the regions surrounding occurrences of the conjectured USS motif in H. ducreyi. A gap of two nucleotides has been introduced to align the H. ducreyi motif with the H. influenzae motif. (An alternative alignment places position -4 in H. ducreyi across from position -6 in H. influenzae.) Examining the frequencies, we can derive a consensus pattern as follows. We mark a position with a 'w' if more than 70% of the occurrences contain an A or a T (expected frequency of an A or T = 60%). We mark a column with a 'y' or 'r' if more than 60% of the occurrences have a T or a C (for 'y') or A or a G (for 'r'). The expected frequency for either case is 50%. The 'rwwwwnnnn' from positions +2 to +11 matches the previously identified extended motif for H. influenzae, though the rwwww motif is not as clear. The subsequent 'nnrwwwww' from the extended H. influenzae motif is not exactly matched in H. ducreyi but there is a general bias toward A and T residues extending to about +25.

Figure 5

Bias toward +- configuration by separation distance. For each of four Pasteurellacaea, the height of the bar gives the total number of paired USS motifs separated by the given distance. The orange (lower) portion of the bar gives the number of pairs in the +- configuration. In H. influenzae, local peaks around approximately 8 and approximately 19-22 are due to the preservation of the extended USS motif. The distribution of distances is different for H. ducreyi, which has a peak of pairs (all in the +- configuration) at separations of 27 to 30, and the preference for the +- motif is not apparent until larger separation distances.