Dynamic insights on transcription initiation and RNA processing during bacterial adaptation.

Transcription initiation and RNA processing govern gene expression and enable bacterial adaptation by reshaping the RNA landscape. The aim of this study was to simultaneously observe these two fundamental processes in a transcriptome responding to an environmental signal. A controlled σE system in E. coli was coupled to our previously described tagRNA-seq method to yield process kinetics information. Changes in transcription initiation frequencies (TIF) and RNA processing frequencies (PF) were followed using 5' RNA tags. Changes in TIF showed a binary increased/decreased pattern that alternated between transcriptionally activated and repressed promoters, providing the bacterial population with transcriptional oscillation. PF variation fell into three categories of cleavage activity: (i) constant and independent of RNA levels, (ii) increased once RNA has accumulated, and (iii) positively correlated to changes in TIF. This work provides a comprehensive and dynamic view of major events leading to transcriptomic reshaping during bacterial adaptation. It unveils an interplay between transcription initiation and the activity of specific RNA cleavage sites. This study utilized a well-known genetic system to analyze fundamental processes and can serve as a blueprint for comprehensive studies that exploit the RNA metabolism to decipher and understand bacterial gene expression control.

Landscape of RNA polyadenylation in E. coli.

Polyadenylation is thought to be involved in the degradation and quality control of bacterial RNAs but relatively few examples have been investigated. We used a combination of 5΄-tagRACE and RNA-seq to analyze the total RNA content from a wild-type strain and from a poly(A)polymerase deleted mutant. A total of 178 transcripts were either up- or down-regulated in the mutant when compared to the wild-type strain. Poly(A)polymerase up-regulates the expression of all genes related to the FliA regulon and several previously unknown transcripts, including numerous transporters. Notable down-regulation of genes in the expression of antigen 43 and components of the type 1 fimbriae was detected. The major consequence of the absence of poly(A)polymerase was the accumulation of numerous sRNAs, antisense transcripts, REP sequences and RNA fragments resulting from the processing of entire transcripts. A new algorithm to analyze the position and composition of post-transcriptional modifications based on the sequence of unencoded 3΄-ends, was developed to identify polyadenylated molecules. Overall our results shed new light on the broad spectrum of action of polyadenylation on gene expression and demonstrate the importance of poly(A) dependent degradation to remove structured RNA fragments.

The bulk and the tail of minimal absent words in genome sequences.

Minimal absent words (MAW) of a genomic sequence are subsequences that are absent themselves but the subwords of which are all present in the sequence. The characteristic distribution of genomic MAWs as a function of their length has been observed to be qualitatively similar for all living organisms, the bulk being rather short, and only relatively few being long. It has been an open issue whether the reason behind this phenomenon is statistical or reflects a biological mechanism, and what biological information is contained in absent words. In this work we demonstrate that the bulk can be described by a probabilistic model of sampling words from random sequences, while the tail of long MAWs is of biological origin. We introduce the concept of a core of a MAW, which are sequences present in the genome and closest to a given MAW. We show that in E. faecalis, E. coli and yeast the cores of the longest MAWs, which exist in two or more copies, are located in highly conserved regions the most prominent example being ribosomal RNAs. We also show that while the distribution of the cores of long MAWs is roughly uniform over these genomes on a coarse-grained level, on a more detailed level it is strongly enhanced in 3' untranslated regions (UTRs) and, to a lesser extent, also in 5' UTRs. This indicates that MAWs and associated MAW cores correspond to fine-tuned evolutionary relationships, and suggest that they can be more widely used as markers for genomic complexity.

Detection and quantitative estimation of spurious double stranded DNA formation during reverse transcription in bacteria using tagRNA-seq.

Standard RNA-seq has a well know tendency to generate "ghost" antisense reads due to formation of spurious second strand cDNA in the sequencing process. We recently reported on a novel variant of RNA-seq coined "tagRNA-seq" introduced for the purpose of distinguishing primary from processed transcripts in bacteria. Incidentally, the additional information provided by the tags is also very suitable for detection of true anti-sense RNA transcripts and quantification of spurious antisense signals in a sample. We briefly explain how to perform such a detection and illustrate on previously published datasets.

Whole-genome mapping of 5' RNA ends in bacteria by tagged sequencing: a comprehensive view in Enterococcus faecalis.

Enterococcus faecalis is the third cause of nosocomial infections. To obtain the first snapshot of transcriptional organizations in this bacterium, we used a modified RNA-seq approach enabling to discriminate primary from processed 5' RNA ends. We also validated our approach by confirming known features in Escherichia coli. We mapped 559 transcription start sites (TSSs) and 352 processing sites (PSSs) in E. faecalis. A blind motif search retrieved canonical features of SigA- and SigN-dependent promoters preceding transcription start sites mapped. We discovered 85 novel putative regulatory RNAs, small- and antisense RNAs, and 72 transcriptional antisense organizations. Presented data constitute a significant insight into bacterial RNA landscapes and a step toward the inference of regulatory processes at transcriptional and post-transcriptional levels in a comprehensive manner.

SEK: sparsity exploiting k-mer-based estimation of bacterial community composition.

MOTIVATION: Estimation of bacterial community composition from a high-throughput sequenced sample is an important task in metagenomics applications. As the sample sequence data typically harbors reads of variable lengths and different levels of biological and technical noise, accurate statistical analysis of such data is challenging. Currently popular estimation methods are typically time-consuming in a desktop computing environment. RESULTS: Using sparsity enforcing methods from the general sparse signal processing field (such as compressed sensing), we derive a solution to the community composition estimation problem by a simultaneous assignment of all sample reads to a pre-processed reference database. A general statistical model based on kernel density estimation techniques is introduced for the assignment task, and the model solution is obtained using convex optimization tools. Further, we design a greedy algorithm solution for a fast solution. Our approach offers a reasonably fast community composition estimation method, which is shown to be more robust to input data variation than a recently introduced related method. AVAILABILITY AND IMPLEMENTATION: A platform-independent Matlab implementation of the method is freely available at http://www.ee.kth.se/ctsoftware; source code that does not require access to Matlab is currently being tested and will be made available later through the above Web site.