E. coli. We discuss why transcription elongation complexes pause at certain template sites and how auxiliary host and phage transcription factors affect elongation and termination. The connection between translation and transcription elongation is described. Finally we present an overview indicating where progress has been made and where it has not.This article will review our current understanding of transcription elongation and termination in  E. coli. Because of the large scope of the article, we have largely confined ourselves to recent manuscripts. Older references have, in general, been omitted except when necessary or when they consist of our own work.This article will review our current understanding of transcription elongation and termination in RNA synthesis by bacterial RNA polymerases, although processive, does not proceed at a uniform rate. Template sequences can induce pausing or backtracking—movement of the transcription elongation complex (TEC) towards the promoter. Forward or backward movement of TEC does not entail loss of energy. The RNA:DNA hybrid, 9 nt in the post-translocated state and 10 nt in the pre-translocated state, is maintained independently of the direction of RNAP movement.Translocation speed and direction is also influenced by accessory transcription factors. NusG and NusA suppress or enhance pausing, respectively. UvrD can push TEC backwards to reveal damaged DNA, and Mfd can push it forward as part of the transcription-coupled repair process. The GreA/B proteins can rescue backtracked TEC by removing extruded RNA and restoring the 3'- end of the nascent transcript to the TEC active center. Backtracking is also suppressed when TEC is coupled to translating ribosomes, which present a barrier to retrograde translocation. Phage functions affect transcription elongation. λ N protein accelerates transcription by inhibiting pausing, whereas HK022 arrests transcription by preventing TEC translocation.Transcription terminates at the ends of operons or under certain conditions, within genes. Termination can be template-encoded and factor-independent (intrinsic termination), or require accessory factors, such as Rho, Mfd and DksA.There has been considerable progress in understanding these aspects of transcription elongation, although areas of controversy remain. We will summarize the new findings and try to smooth out the contradictions in the following pages.E. coli RNAP is not uniform. RNA synthesis is characterized by pauses, some of which may be brief and resolved spontaneously, whereas others may lead to TEC backtracking. Backtracked TEC can restart when acted upon by GreA/B factors, which restore the 3'- end of the nascent transcript to the active center. Pausing may regulate gene expression, as in the case of attenuation or phage λ gene Q antitermination. In this section we will discuss recent advances in understanding the mechanism and specificity of pausing.The rate of transcription elongation by Elongation rate and pausing are determined by template sequence and RNA structure  and involve at least two components of the RNAP catalytic center, the bridge helix (BH) and trigger loop (TL). Elongation is proposed to occur in two steps. First, the TL folds in response to NTP binding. Mutational analyses indicate that this conformational change in the TL can be rate-limiting, and reflects the ability of the incoming NTP to bind to TEC. The second step is the incorporation of the NTP and the release of pyrophosphate. Kinetic conformational changes in the TL, however, do not account for pause recovery, since the TL remains unfolded during a pause .Pausing not associated with backtracking is frequent, occurring on average every 100 bases of DNA . The paui.e., movement of TEC towards the promoter by one bp, with associated displacement of the 3' ribonucleotide from the active center.Zenkin and his coworkers  analyzedin vivo analysis of TEC occupancy on the E. coli chromosome defined almost 20,000 pause sites [et al. [in vitro and pauses with equal efficiency on the various templates. However, the mutant RNAP is more likely than wild-type enzyme to be in the pretranslocated register on the G+1 template, i.e., more likely to pause. This observation is curious, and does not fit readily with the above model.A genome-wide se sites . Analysi [et al.  This seqE. coli and Bacillus subtilis [Interestingly, the pause-inducing consensus sequence is enriched at translation start sites in both subtilis . It is cPauses also occur at sites resembling the promoter sequence to which the RNAP sigma 70 subunit binds ,7. SigmaIntrinsic termination occurs at specific template sequences - an inverted repeat followed by a run of A residues. Termination is driven by formation of a short stem-loop structure in the nascent RNA chain. RNA synthesis arrests and TEC dissociates at the 7th and 8th U of the run. Formation of the stem-loop dissociates the weak rU:dA hybrid. Stem-loop formation is hindered by upstream complementary RNA sequences that compete with the downstream portion of the stem, as well as by RNA: protein interactions in the RNA exit channel. Intrinsic termination depends critically upon timing. Hairpin folding and transcription of the termination point must be coordinated, so that the complete hairpin is formed by the time RNAP transcribes the termination point. The size of the stem, the sequence of the stem and the length of the loop all affect termination efficiency see .et al. [Nedialkov et al.  have stuE. coli first identified for its role in transcription termination at Rho-dependent terminators [E. coli transcripts [rho is highly conserved and nearly ubiquitous in bacteria [rho is regulated by Rho-dependent transcription termination at a Rho termination site located upstream of the structural gene [Transcription termination factor Rho is an essential protein in minators , and is nscripts . rho is bacteria . Rho is bacteria  with RNAbacteria , and conbacteria . Transcrral gene .rut sites (rho utilization) and release sites [rut site RNA, is stimulated to hydrolyze ATP, and then translocates along the RNA in a 5' to 3' direction while maintaining an interaction with rut [Rho-dependent terminators are comprised of se sites . Rho binwith rut ,19, untiwith rut .et al. [E. coli Rho factor will efficiently terminate transcription of Saccharomyces cerevisiae RNA pol II [RNA binds to two distinct sites in Rho, termed primary and secondary . The priet al.  propose et al. , howeverA pol II .rut sites are likewise not highly conserved. They consist of unstructured RNA that is C-rich and G-poor compared to the flanking sequences [in vivo requires the NusG transcription factor [D = 0.2 μM; [in vitro [Rho-dependent terminators, unlike intrinsic terminators, lack an easily identifiable motif. equences ,27,28. Cequences . Releaseequences ,29. Effin factor . NusG bin factor  and shifn factor ,33,34. R 0.2 μM; ) but Nusin vitro .rut binding site [et al. [rut element is required for Rho association with RNAP, and suggest that the ChIP-chip data does not reflect a relevant interaction between Rho and TEC. Single molecule studies show no evidence that Rho directly binds to RNAP [et al. [in vitro. The reason for the above discrepancy remains unclear.ChIP-chip analysis reveals that Rho associates with the TEC throughout transcription, rather than only after synthesis of an untranslated ing site . Kalyani [et al.  instead  to RNAP , however [et al.  did deteE. coli occurs predominantly within the “foreign” DNA  that makes up ~14% of the genome of E. coli MG1655 [E. coli is essential to suppress expression of toxic genes in this horizontally-acquired DNA [nusA or nusG mutations in a strain deleted of all horizontally transferred DNA, rho cannot be deleted in this strain. Washburn and Gottesman proposed that Rho is essential to prevent collisions between TEC and the replisome [Rho-dependent termination in i MG1655 . Efficieired DNA . Althougeplisome . Rho tereplisome .et al. [rho could be deleted in a −rac strain expressing the RNA-DNA helicase uvsW. This model assumes that both Rho and UvsW prevent or remove potentially lethal R-loops. Nevertheless, rnhA deletion mutants are healthy despite extensive accumulation of R-loops. Nor are rnhA mutants more dependent on rho for survival than wild-type [et al. [The RNA-DNA helicase activity of Rho can unwind extensive RNA-DNA hybrids. Harinarayanan and Gowrishankar  suggest et al.  found thild-type ,44. Perh [et al. , demonstet al. [nusG resulted in the accumulation of antisense transcripts. The antisense transcripts are untranslated, thus allowing Rho access to termination sites. Surprisingly, nusA does not contribute to termination of the antisense transcripts, despite the similarities in transcription patterns in nusG, nusA and cells treated with the Rho inhibitor bicyclomycin [in vivo is unclear.Peters et al.  found thclomycin . WhetherrpoB8, 5-fold higher Km for ATP) and are more efficient at Rho-dependent termination. Conversely, fast mutants have an increased affinity for NTPs  and are less efficiently terminated. Enhanced termination was observed in vitro when the transcription rate was slowed by limiting NTP concentrations. This “kinetic coupling” model might explain the correlation between TEC pausing and Rho termination sites.The efficiency of Rho termination is dependent on the rate of transcription elongation . Slow RNhns deletion mutations increase Rho dependency [E. coli sequences, which favors H-NS binding.The histone-like nucleoid-structuring protein H-NS contributes to Rho-dependent termination. pendency ,44, and pendency . This ispendency . HorizonTEC are accompanied by transcriptional cofactors that affect the rate of elongation and specify loci of transcription termination. Among these are NusA, NusG, and the ppGpp cofactor, DksA.E. coli NusG is composed of two domains connected by a flexible linker. It affects transcription elongation through a variety of mechanisms. The NusG-NTD directly suppresses pausing and thus enhances the overall rate of transcription elongation [The 21kDa ongation . Structuongation . Single ongation .The NusG-CTD KOW domain interacts with NusE/S10, thus linking TEC to the lead ribosome. Coupling of transcription to translation suppresses backtracking and possible clashes with the replisome . The NusIn vivo, it is not known whether NusG associates first with RNAP, with ribosomes or simultaneously to both. Genome-wide surveys suggest that NusG associates with TEC only after significant elongation has occurred [E. coli NusG paralogue, RfaH, appears to link ribosomes to TEC early after transcription initiation [occurred . This isitiation .in vivo calculated/reported numbers for NusG [The for NusG  is one sfor NusG ). This iHowever, ribosomal stalling at rare codons or induced by amino acid analogues can uncouple transcription from translation and induce intragenic Rho-dependent termination. The stalled ribosome is attacked by tmRNA, which competes for binding with NusG-CTD to S10 and releases the impacted ribosome .E. coli. The cryptic rac prophage carries a constitutive promoter and a downstream kil gene whose expression is lethal to the bacterial host. Rho-dependent termination prevents transcription extension from the promoter to kil. Deletion of the rac prophage allows E. coli to support a nusG deletion, although the mutant strain grows poorly and dies in stationary phase [Activation of Rho explains why NusG is essential in wild-type ry phase .B. subtilis NusG stimulates pausing at two regulatory sites in the untranslated leader of the B. subtilis trp operon that participate in transcription attenuation and translational control mechanisms, respectively. To induce pausing, B. subtilis NusG makes sequence-specific contacts with a T-rich sequence in the nontemplate DNA strand within the paused transcription bubble [E. coli NusG homologue, RfaH, makes similar contacts with the template ops element. Pausing at ops may allow RfaH to link to the lead ribosome and couple transcription to translation in ops-bearing operons [Oddly, n bubble . The E.  operons .E. coli NusA protein was originally identified genetically as a required component of the phage λ N antitermination complex, and biochemically as a factor that stimulated lacZ gene expression in vitro [vice versa. NusA enhances pausing as well as termination at intrinsic termination sites. Paradoxically, it also suppresses transcription termination as part of the λ N or rrn antitermination complexes. NusA is thought to provoke termination when present in 1:1 stochiometry with RNAP, and antitermination—as part of the NusBEG/λ N complex—when the stoichiometry is 2:1. Numerous studies place NusA near the RNA exit channel [in vitro . RNAP is channel . Gusarov channel  proposed channel . Thus, dpL and λ pR promoters and the first termination signals in their operons. NusA binds to the NUT SPACER sequence within NUT. However, NusA binding to RNA is dependent on its association with TEC. NusA binds to TEC via two distinct domains, the NTD and an acidic domain in the CTD (AR2). The C-terminal domain (CTD) of the RNAP α-subunit (αCTD) interacts with the acidic CTD 2 (AR2) of NusA, releasing the autoinhibitory blockade of the NusA S1-KH1-KH2 motif and allowing NusA to bind RNA. The solution conformation of the AR2:αCTD complex shows that the αCTD residues that interface with AR2 are identical to those that recognize UP promoter elements. This is consistent with a role for NusA in transcription initiation of operons carrying UP elements, although evidence for such an activity has yet to be unearthed [The NusABEG/λN antitermination complex forms at the NUT sequences of λ nascent transcript. These sequences lie in the phage chromosome between the λnearthed .Earlier studies suggested that the binding of NusA-NTD and σ70 to RNAP were mutually exclusive. However, recent structural data shows association of NusA-NTD and the β-flap tip helix, a site distinct from that of the major σ70 region 2 binding site, the CH region of the β' subunit. Nevertheless, NusA might compete with the weak binding of σ70 region 4 to the β-flap tip .rac prophage [Unlike NusG, complete deletions of NusA cannot be constructed. A NusA truncation that retains the NusA-NTD can be introduced into strain MDS42, which lacks all horizontally transmitted elements, including the cryptic prophage . This isprophage .dnaK. It was then shown to disrupt RNAP open complexes at rrn promoters under the influence of ppGpp and NTP [DksA was originally isolated as a suppressor of a chaperone mutation,  and NTP . DksA andksA growth defect. At other genetic loci, however, DksA and GreA act oppositely. The biochemical basis of these interactions remains to be elucidated [tna operon [The critical difference between DksA and GreA/B lies in a few residues at the tip of the coiled coil. These residues contact the RNAP active center . There iucidated . Like Dka operon .in vitro. Although wild-type DksA has little or no effect on the rate of RNA synthesis with wild-type RNAP, a DksA mutant with enhanced affinity for RNAP slows elongation in a ppGpp-independent fashion, although this effect is stimulated by ppGpp. Similarly, wild-type DksA retards RNA synthesis by an RNAP mutant with increased sensitivity to DksA, again independently of ppGpp. The template used in these studies lacked paused sites, suggesting that DksA does not slow transcription elongation by stimulating pausing. Finally, DksA stimulates termination at the intrinsic rrnB T1 terminator [The fact that ppGpp inhibits RNA chain extension prompted experiments to test if DksA also acted on TEC rminator .In vivo, mutational studies implicate DksA in preventing transcription-replication conflicts. DksA protects cells against UV and other DNA damage, which inhibit transcription elongation [et al. [ongation . DksA prongation . Amino aongation . This isongation ,64. Tehr [et al.  propose in vitro studies, has not been ruled out [dksA mutants to the DNA cross-linker, mitomycin C, is suppressed by a second mutation in greA [in vitro and in vivo observations will be, we are afraid, the task of future generations.A genome wide survey of TEC occupancy in the presence or absence of DksA supports the notion that DksA suppresses replisome clashes by acting on backtracked TEC. ChIP-chip experiments reveal that DksA is enriched both at promoters and in downstream regions, colocalizing with RNAP across the entire chromosome. DksA suppresses TEC stalling induced by amino acid starvation globally, possibly by blocking backtracking . An alteuled out . Genetic in greA . Since bin vivo specifically on the λ chromosome. It is directed to TEC by binding to the NUT sequence of the λ nascent transcript via its N-terminal arginine rich motif (ARM), and remains attached to TEC during transcription of the λ early genes. λ N and NusA, B, E and G form an antitermination complex that modifies TEC. The mechanism of action of λ N remains controversial. In vitro, λ N alone can accelerate transcription elongation and suppress transcription termination at Rho-dependent and intrinsic termination sites. However, E. coli NusA factor significantly improves λ N efficiency. Gusarov and Nudler [et al. [in vitro. This result suggests that λ N does, in fact, stabilize the RNA:DNA hybrid, particularly at the 5' end. Stabilization is proposed to disfavor dissociation of RNA from the DNA template, thereby suppressing both termination and slippage. In contrast, Gusarov and Nudler [λ N suppresses transcription termination d Nudler  found th [et al.  concluded Nudler  suggest nut elements. The arrested TEC is released by the host Mfd factor, thus prematurely terminating transcription on the λ chromosome [nun mutations, and HK022 nun mutants lysogenize with normal frequency. The specificity of Nun exclusion is unique; other phage exclusion systems are active against a broad range of superinfecting phage [HK022 blocks the growth of phage λ by arresting transcription at pause sites distal to the λ romosome . Nun binng phage .nut is dispensable for function of both proteins in vitro . Furromosome . Toxicitromosome ,78. In vin vitro is a substrate for subsequent Nun arrest, although the site of arrest differs depending on the location of the pause [TEC paused by nucleotide deprivation he pause ,80. Mutahe pause ,81,82. Nhe pause ,80.Our understanding of transcription elongation has accelerated over the past few years. To a large extent, this reflects the application of structural biology to the elongation reaction, which, in turn, has informed the genetics, allowing construction of relevant mutant RNAPs and auxiliary factors. Nevertheless, we lack a satisfactory mechanistic explanation for the activities of many transcription factors, e.g., Rho, DksA, λ N and HK022 Nun remain obscure. This is likely to be so only in the short term, we expect, as more sophisticated structural and biochemical approaches are applied to determining how genes are transcribed.


Transposable elements (TEs) are major structural components of eukaryotic genomes; however, mobilization of TEs generally has negative effects on the host genome. To counteract this threat, host cells have evolved genetic and epigenetic mechanisms that keep TEs silenced. One such mechanism involves the Piwi-piRNA complex, which represses TEs in animal gonads either by cleaving TE transcripts in the cytoplasm or by directing specific chromatin modifications at TE loci in the nucleus. Most Piwi-interacting RNAs (piRNAs) are derived from genomic piRNA clusters. There has been remarkable progress in our understanding of the mechanisms underlying piRNA biogenesis. However, little is known about how a specific locus in the genome is converted into a piRNA-producing site. In this review, we will discuss a possible link between chromatin boundaries and piRNA cluster formation. Both DNA transposons and retrotransposons have non-autonomous subtypes and defective copies, which require the reverse transcriptase and endonuclease supplied by the autonomous type to jump around the genome.Large fractions of eukaryotic genomes comprise transposable elements (TEs), which are repetitive DNA elements that can mobilize to take up new chromosomal locations within a genome. TEs act as insertional mutagens that can alter gene expression or rearrange chromosomes. Therefore, they can cause disease and may even drive evolution -4. TEs aDrosophila harbors around 100 different TEs, and the only conserved and universal property shared by them is the ability of transposition [in trans. Thus, piRNA clusters are genetic elements that regulate the activity of TEs. However, relatively little is known about how piRNA clusters are formed. In this review, we emphasize the role of chromatin boundaries in piRNA cluster formation. To this end, we briefly review our current knowledge of piRNAs and piRNA clusters. We then discuss a possible link between chromatin boundaries and piRNA clusters, and propose some models as to how piRNA clusters are formed in chromatin boundaries.As an example, position . Thus, tposition -10. In aposition ,12. MostDrosophila PIWI genes  have revealed that mutations in these genes affect germline development [RNA interference (RNAi) and related pathways are cellular pathways in which small ncRNAs of 20 to 35 nucleotides (nt) guide Argonaute-containing effector complexes, termed RNA-induced silencing complexes (RISCs), to RNA targets by means of base-pairing, and promote the inactivation of homologous sequences -16. Theyelopment -20. TEs elopment .Drosophila genome, 142 regions have been identified as piRNA clusters [Drosophila, the flamenco locus produces a major fraction of piRNAs in somatic support cells in the ovary [gypsy, idefix, and ZAM TEs [flamenco in which the P-element is inserted in the 5′ region and those lacking flamenco partial genomic sequence lose the ability to regulate TEs [flamenco locus are processed into piRNAs. This linear biogenesis of piRNAs from precursor transcripts has been called the ‘primary piRNA processing pathway’  and small interfering RNAs (siRNAs), piRNAs in most animals are processed in a Dicer-independent manner from single-stranded precursors, which are transcribed mostly from genomic piRNA clusters ,23. A laclusters . Althougclusters . The piRclusters . Among ahe ovary . This lo ZAM TEs ,27. piRNlate TEs ,26,28,29 TE loci -34. This-piRISCs ,35,36. Tflamenco piRNA cluster, many piRNA clusters in the Drosophila germline are transcribed from both strands, and both precursor transcripts are processed into piRNAs [Compared with the situation in somatic support cells, the piRNA biogenesis in germline cells in the fly ovary is more complex. In contrast to the unidirectional o piRNAs ,25. Thero piRNAs ,37,38. Ao piRNAs ,37 -sequencing analysis of H3K9me3, the most established marker for heterochromatic regions, revealed that the promoter and its surrounding region of flamenco, a unistrand piRNA cluster, is fairly devoid of this repressive histone mark, which may explain the active transcription of the locus by RNA polymerase II [Although many factors that are required for piRNA production are shared between these two types of clusters, there are some differences between them. Rhino , Cutoff (a homolog of the yeast decapping nuclease and transcription termination factor Rai1), and Deadlock (which acts as a linker between Rhino and Cutoff), are all required for piRNA production only in germline cells of the oocyte ,55-57. Ierase II . By contBombyx mori tissue cultured cell line BmN4, a portion of piRNAs are derived from TEs [In the from TEs . piRNA cfrom TEs , suggestThese findings suggest that piRNA clusters are highly transcribed units within heterochromatic regions, and raise the question of how this kind of special location in the genome has been selected for piRNA clusters to produce piRNAs.In the mouse, over 90% of piRNA reads have been mapped to roughly 100 genomic regions, ranging from a few kb to over 100 kb in length. Most mouse clusters show profound strand asymmetry, with reads arising from only one strand within a cluster . When piRNAs map to both strands within one piRNA cluster, the transcription units are arranged in a divergent manner  ,43 and tCaenorhabditis elegans has two PIWI proteins, PRG-1 and PRG-2. PRG-1 is required in germline maintenance, and interacts with a class of small RNAs, called 21U-RNAs [C. elegans. As their name implies, they are characterized by a first U bias, and their length is exclusively 21 nt, which is shorter than that of piRNA species in other organisms [cis motif located around 40 bp upstream of the 21U-RNA encoding site [C. elegans is produced from an independent transcription unit.21U-RNAs ,64. By drganisms . The vasrganisms . These ring site . The coning site ,66. In aing site . MoreoveTetrahymena thermophila has a unique genome processing mechanism, called ‘programmed DNA elimination’. Most ciliated protozoans, including T. thermophila, exhibit nuclear dimorphism, with a germline micronucleus (Mic) and somatic macronucleus (Mac) [Tetrahymena PIWI proteins and are, therefore, T. thermophila piRNAs [Tetrahymena[us (Mac) . The gena piRNAs . Twi1-sca piRNAs . Strikina piRNAs . scnRNAstrahymena. Recent trahymena. BecauseP-element is a DNA transposon that has been used for insertional mutagenesis to isolate specific alleles in Drosophila[P-element insertion sites in the genome. Analysis of 100,000 transposition events identified that P-element insertion preferentially occurs immediately 5′ to genes or within 5′ exons [piggyBac, another TE that is also often used for mutagenesis, also shows a high preference of insertion at or near promoter regions of genes [A prerequisite for genomic regions to act as TE traps is that they must be frequent and non-deleterious sites for TE insertion. TEs jump around the genome by transposition, but this appears to occur in a non-random manner . The P-erosophila,75. Beca5′ exons . piggyBaof genes . These rTf1 is a retrotransposon prevailing in the specific yeast genome. Tf1 insertion predominantly occurs closer to the 5′ end of genes, in regions known to have relatively open chromatin [A fission yeast TE termed hromatin ,79. ThesCis-regulatory elements are located at chromatin boundaries, and have different compositions of trans-acting proteins. They limit the spreading of heterochromatin domains into regions of actively transcribed genes (and vice versa) and prevent adventitious interactions between enhancers and promoters when located between them (acting as “insulators”) [Drosophila, between constitutive heterochromatin and euchromatin are not fixed but stochastic, as evident in position effect variegation (PEV), in which the heritable inactivating influence of the heterochromatin on a neighboring gene can spread in some, but not all, cells of the same cell type [In addition to gene promoters and their neighboring regions, chromatin boundaries are also known to have relatively open chromatin structures. A chromatin boundary can act as a buffer between two functional chromatin domains by resisting the proliferation of epigenetic changes that are characteristic of each, thus genes present in one domain are not affected by regulatory sequences present in a different domain -84 Figu. Cis-reglators”) ,84 , abdominal A (abd-A), and Abdominal B (Abd-B). It has been shown that nine body segments are defined by the combination of expression level of the three genes. Boundary elements demarcate the BX-C region into nine parts, making possible the differential expression pattern of the three genes. Interestingly, the preferential deposition sites of H3.3 match well with the BX-C boundary elements, such as Fab-7, Fab-8, and Mcp [Drosophila[In addition to histone modifications, replacement of core histones with their variants appears to contribute to boundary formation. The ENCODE project revealed that specific histone variants are highly abundant at chromatin boundaries. For example, H2A.Z is an evolutionarily conserved H2A variant present in all eukaryotes , which eeposited ,98. The eposited . The reg and Mcp   produced from the flam locus was reported [flam was found to be constitutively spliced [flam locus. Therefore, there could be a certain mechanism that suppresses transcription termination and poly(A) addition for the flam transcripts. Therefore, the transcript itself is sending some message that it is different from other transcript.Another model is that transcripts from piRNA clusters have some special property allowing them to be processed into piRNA, and this property is used by the piRNA-producing machinery to distinguish piRNA transcripts from the vast majority of other transcripts. This special property can be either altered splicing, characteristic 3′-end processing, or specific eoformans. These anscripts ,107,109.reported . Further spliced . In addiRecent genome-wide ChIP analyses have revealed the locations on the genome where specific transcription and epigenetic factors sit. Cross-linking immunoprecipitation (CLIP) methods have also revealed specific binding sites on transcripts for RNA-binding proteins. There is no doubt that these types of analysis will propel this field forward and expand our knowledge of how piRNA clusters are formed and how transcripts from the clusters are specifically processed into piRNAs. In addition, other methods that are complementary to ChIP and CLIP should also be applied to piRNA research. For example, we do not have a comprehensive understanding of the repertoire of proteins that bind to piRNA clusters or to the transcript from piRNA cluster. Taking advantage of specific DNA-protein interactions, such as LexA with LexA-binding sites, LacI with LacO repeats and modified transcription activator-like effector (TALE), recent studies have successfully immunopurified a chromatin locus of interest and identified associated proteins -113. A cChIP: Chromatin immunoprecipitation; CLIP: Cross-linking immunoprecipitation; IES: Internal eliminated sequence; LINE: Long interspersed repetitive element; miRNA: microRNA; NDR: Nucleosome-depleted region; Nt: Nucleotide; PEV: Position effect variegation; piRNA: Piwi-interacting RNA; RISC: RNA-induced silencing complex; scnRNA: Scan RNA; SINE: Short interspersed repetitive element; siRNA: Small interfering RNA; TALE: Transcription activator-like effector; TE: Transposable element; tRNA: Transfer RNA.The authors declare that they have no competing interests.SY and HS designed the structure of the review, and wrote the paper along with MCS. All authors commented on the manuscript, and read and approved the final manuscript.


Due to the absence of transcription initiation regulation of protein coding genes transcribed by RNA polymerase II, posttranscriptional regulation is responsible for the majority of gene expression changes in trypanosomatids. Therefore, cataloging the abundance of mRNAs (transcriptome) and the level of their translation (translatome) is a key step to understand control of gene expression in these organisms.Trypanosoma cruzi, in both the non-infective (epimastigote) and infective (metacyclic trypomastigote) insect’s life stages using RNA-seq and ribosome profiling. The observed steady state transcript levels support constitutive transcription and maturation implying the existence of distinctive posttranscriptional regulatory mechanisms controlling gene expression levels at those parasite stages. Meanwhile, the downregulation of a large proportion of the translatome indicates a key role of translation control in differentiation into the infective form. The previously described proteomic data correlate better with the translatomes than with the transcriptomes and translational efficiency analysis shows a wide dynamic range, reinforcing the importance of translatability as a regulatory step. Translation efficiencies for protein families like ribosomal components are diminished while translation of the transialidase virulence factors is upregulated in the quiescent infective metacyclic trypomastigote stage.Here we assess the extent of regulation of the transcriptome and the translatome in the Chagas disease causing agent, Trypanosoma cruzi life cycle. Translation upregulation of virulence factors and downregulation of ribosomal proteins indicates different degrees of control operating to prepare the parasite for an infective life form. Taking together our results show that translational regulation, in addition to regulation of steady state level of mRNA, is a major factor playing a role during the parasite differentiation.A large subset of genes is modulated at the translation level in two different stages of The online version of this article (doi:10.1186/s12864-015-1563-8) contains supplementary material, which is available to authorized users. Trypanosoma cruzi is the causative agent of Chagas’ disease a serious ailment that affects millions of people in Latin America, against which there is no prevention, vaccine or effective chemotherapeutic agent [ic agent .T. cruzi has a complex life cycle characterized by several developmental forms present in vertebrate and invertebrate hosts. Replicative epimastigote and amastigote forms in arthropod and mammal hosts, respectively, alternate with the infective and non-proliferative metacyclic trypomastigotes in the insect vector and bloodstream trypomastigotes in the infected mammal [d mammal . The intd mammal . UnderstT. cruzi, most genes are transcribed by RNA Polymerase II which generates polycistronic transcripts in a run-through fashion. Although transcription starts at defined locations, no sequence signals defining a classical eukaryotic promoter have been found at those sites [T. cruzi this was confirmed using microarrays [Trypanosomatids probably belong to the earliest diverging branches of the eukaryotic lineage ,5 and arse sites -9. In cose sites . There ise sites ,12, howeroarrays . Thereforoarrays . In addiroarrays . Single roarrays -17, thusin vivo [Trypanosoma brucei are accumulating [T. cruzi clearly drive forward carrying out genome-wide approaches in this parasite. As reviewed in Kramer 2012 [T. cruzi an intracellular stage), vector transmission , targeted host tissues (being T. brucei restricted to bloodstream), and immune evasion system (presenting T. brucei antigenic variation), and even molecular processes (such as absence of RNAi in T. cruzi).Next-generation sequencing (NGS) technologies have permitted not only the accurate determination of mRNA steady state levels but also the genome-wide analysis of processes such as transcription initiation, mRNA maturation, degradation and more recently translation. Specifically, deep sequencing of ribosome protected mRNA fragments, ribosome profiling, has provided a highly accurate measurement of the translation process in vivo , for a rin vivo . Althougmulating ,20-23, kmer 2012 , remarkaT. cruzi differentiation.In an effort to contribute to understand gene expression regulation processes occurring during the differentiation from the non-infective epimastigote (E) to the infective metacyclic trypomastigote forms (MT) we comprehensively monitored the steady state transcript abundances and translation profiles using RNA-seq and ribosome profiling. Our results strongly support previous indications of genome-wide constitutive transcription and uncover general pre mRNA maturation. In addition we reveal translation control as a key mechanism generating the gene expression changes that occur in Trypanosoma cruzi. The general procedure is shown in the Additional file T. cruzi epimastigotes and in vitro differentiated metacyclic trypomastigotes by standard protocols in the SOLiD platform. In parallel, ribosome footprints, obtained in triplicates by digestion of polysomal fractions that were previously separated through sucrose cushions, were sequenced in the same platform for both stages. After quality filtering, reads from both were mapped to the T. cruzi reference genome and read counts per gene were calculated. Normalization was performed to account for sequencing depth and transcript length, resulting in an expression estimate for each gene  and MT (9092) stages , including a high number of them  common to both transcriptomes  mapping was assessed. In contrast to transcriptome derived reads, RFPs aligned mainly to annotated CDS segments while marginally to inter CDS regions  superfamily are the most overrepresented among the ones with an efficiency FC (MT/E) higher than 2   are the most overrepresented among the ones with an efficiency FC (MT/E) lower than 0.5 , being almost all common to both stages (approx. 98%)  Figure . Our resT.cruzi [T. cruzi genome are translated in the epimastigote (approx. 74%) than in the metacyclic trypomastigote (approx. 58%) stage + mRNA and the RFP fractions of both stages . Three biological replicates with 2.5 × 109 epimastigotes each were used. Metacyclic trypomastigotes were obtained as previously described [7 parasites ml−1) were harvested by centrifugation at 7000 × g for 5 min at 25°C and subjected to nutritional stress for 2 h at 28°C in TAU medium  at a density of 5 × 108 parasites ml−1. The epimastigotes were subsequently used to inoculate cell culture flasks containing TAU3AAG  at a density of 5 × 106 cells mL−1 at 28°C. Metacyclic trypomastigotes were purified by DEAE-51 chromatography from the TAU3AAG culture supernatant after 72 h of incubation. Three biological replicates of 5 × 109 parasites each with greater than 99% metacyclic cells were used.Epimastigotes of c strain  were culescribed ,52. BrieMessenger RNA was purified using poly(A)+ mRNA selection, and sequenced using standard SOLiD RNA-seq procedures. Ribosome protected footprints were generated through nuclease treatment of cell extract in the presence of cycloheximide. The drug was added to a concentration of 100 μg/ml and incubated for 10 minutes at 28°C, and was present at this concentration in all downstream steps according Ingolia and cols. with minor modifications . The polT. cruzi CL Brener Esmeraldo-Like annotated transcripts V5.0 was used as reference ("http://tritrypdb.org/"). Alignment settings for color space reads were the following: maximum number of mismatches: 2; minimum length fraction: 0.9; minimum similarity fraction: 0.8 and maximum number of hits for a read: 10  with Q phred score larger than 13. A range between 25 and 40 nt was selected for the footprints lengths, while 18 to 50 nt was set for the transcriptome reads , TcS25 TcCLB.503907.10 , and trans-sialidase TcGP82 TcCLB.510307.230 . RT-PCR was carried out from ribosome-free, monosomal and polysomal fractions extracted from both epimastigotes and metacyclic trypomastigotes of the Dm20c strain.Independent experimental verification of the expression levels obtained in our transcriptome and translatome experiments was performed for a set of differentially expressed Sucrose density gradient of epimastigotes and metacyclic trypomastigotes extracts were prepared as previously described ,54 and RQuantitative proteomic data were obtained from a label free MS-based approach .To categorize gene lists into overrepresented functional related groups, DAVID  functional annotation clustering tool was used . Groups The data sets supporting the results of this article are available in the Sequence Read Archive repository, Project ID: PRJNA260933.


Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific analysis of genomic processes. We applied dsHMM to yeast using strand specific transcription data, nucleosome data, and protein binding data for a set of 11 factors associated with the regulation of transcription.The resulting annotation recovers the mRNA transcription cycle  while correctly predicting strand-specificity and directionality of the transcription process. We find that pre-initiation complex formation is an essentially undirected process, giving rise to a large number of bidirectional promoters and to pervasive antisense transcription. Notably, 12% of all transcriptionally active positions showed simultaneous activity on both strands. Furthermore, dsHMM reveals that antisense transcription is specifically suppressed by Nrd1, a yeast termination factor. HMMs were successfully used for dissecting the genome into ‘chromatin states’  or ‘tranet al.  showed tIn the present work we introduce double-stranded hidden Markov models (dsHMMs), which explicitly model the forward and reverse DNA strand by two Markov chains running in opposite directions. Therefore dsHMMs are able to disentangle the two strands at every single position of the genome. dsHMMs capture the biology of directed genomic processes such as transcription, which often occur at the same position on both strands. We illustrate the use of dsHMMs on a data set comprised of strand-specific expression, nucleosome occupancy and ChIP-chip data of 11 factors involved in yeast transcription. We present the first strand-specific map of transcription states in yeast. Our results confirm the role of Nrd1 in a non-canonical pathway of transcription termination, which predominately occurs in antisense direction of stable gene transcripts and is mainly involved in the termination of CUTs ,18.P be a set of genome-wide experiments (‘tracks’) which give rise to a sequence of observables j at position t. The observables are emitted by two independent, homogeneous Markov chains of hidden variables running in opposite direction, the forward chain ot is conditionally independent of all other observations, given the hidden state pair A is ergodic, and that π is its unique steady state distribution. A dsHMM can then be transformed into a standard HMM with state space Let s(o) = P(o∣s), P = B∪E+∪E−, where E+ and E− are disjoint copies from a set E. We assume that s which is built from ‘strand-specific’, multivariate Gaussian emission distributions i. Let s+ ‘dominates’ over s−, and vice versa, let s bys, s .It remains to find a sparse parametrization of the emission distributions ψne νs by\documentne νs by\documentet al.  for strand-specific genome annotation Figure . Figure In contrast to the standard HMM the bdHMM correctly recognizes directionality and distinguishes between the beginning and the end of active regions Figure . The bdHThe dsHMM model assumes that the observed sequence of states is emitted by two Markov chains, a forward and a backward chain that run in opposite direction Figure , the modWe learned a dsHMM with 20 states (i.e. 400 state pairs) on strand specific expression data, nucleosome occupancy data and on ChIP–chip data of 11 factors involved in yeast transcription . As already stated by other authors , we emphet al. . State 5 is interpreted as a termination state  and transcriptional activity data . These data comprised transcription factors necessary for all phases of transcription, various modifications of both Pol II and nucleosomes. It was shown that the hidden states of the learned model accurately recovered the different phases of the transcription cycle. Each phase is characterized by typical protein binding patterns. Consequently, the trained dsHMM has successfully captured the important biological characteristics of the transcription process. The separate modeling of the two DNA strands finds bidirectional promoters and distinguishes between the canonical and the Nrd1 assisted transcription termination pathways. Most remarkably the Nrd1 pathway is most frequently annotated in antisense direction to coding genes and peaks shortly before TSS and after the pA site of these coding genes. This suggest the role of Nrd1 as the main factor for the suppression of antisense transctiption .Formally the dsHMM operates on hidden state pairs which grow quadratically in the number of strand specific states. By introducing natural symmetry constraints, we ensure that the number of parameters is the same as in a standard HMM. While this is uncritical for the transition matrix  as opposed to the relative scale of microarray measurements used in this study. Further we did not learn or update the covariance structure for each state but rather conservatively fixed the covariance structure of the emission distribution to the empirical covariance structure of the whole data.So far, we have only included data of some transcription factors, various modifications of Pol II and nucleosomes into the model. It is tempting to include data of different activating and repressing histone modifications. This will help to elucidate the interplay between transcription factors and chromatin marks. A promising application is the annotation of plant genomes, as plant Pol4 and Pol5 establish a transcriptional feedback to chromatin structure . dsHMM cSupplementary Data are available at NAR online.


Staphylococcus aureus is a major pathogen that colonizes about 20% of the human population. Intriguingly, this Gram-positive bacterium can survive and thrive under a wide range of different conditions, both inside and outside the human body. Here, we investigated the transcriptional adaptation of S. aureus HG001, a derivative of strain NCTC 8325, across experimental conditions ranging from optimal growth in vitro to intracellular growth in host cells. These data establish an extensive repertoire of transcription units and non-coding RNAs, a classification of 1412 promoters according to their dependence on the RNA polymerase sigma factors SigA or SigB, and allow identification of new potential targets for several known transcription factors. In particular, this study revealed a relatively low abundance of antisense RNAs in S. aureus, where they overlap only 6% of the coding genes, and only 19 antisense RNAs not co-transcribed with other genes were found. Promoter analysis and comparison with Bacillus subtilis links the small number of antisense RNAs to a less profound impact of alternative sigma factors in S. aureus. Furthermore, we revealed that Rho-dependent transcription termination suppresses pervasive antisense transcription, presumably originating from abundant spurious transcription initiation in this A+T-rich genome, which would otherwise affect expression of the overlapped genes. In summary, our study provides genome-wide information on transcriptional regulation and non-coding RNAs in S. aureus as well as new insights into the biological function of Rho and the implications of spurious transcription in bacteria. Staphylococcus aureus can survive under a wide range of conditions, both inside and outside the human body. The goal of this study was to determine how S. aureus adapts to such different conditions and, additionally, we wanted to identify general factors governing the staphylococcal transcriptome architecture. Therefore, we performed a precise analysis of all RNA transcripts of S. aureus across experimental conditions ranging from in vitro growth in different media to internalization by eukaryotic host cells. We systematically mapped all transcription units, annotated non-coding RNAs, and assigned promoters controlled by particular RNA polymerase sigma factors and transcription factors. By a comparison with data available for the related Gram-positive bacterium Bacillus subtilis, we made key observations concerning the abundance and origin of antisense RNAs. Intriguingly, these findings support the view that many antisense RNAs in a bacterium like B. subtilis could be byproducts of spurious promoter recognition by condition-specific alternative sigma factors. We also report that the transcription termination factor Rho prevents widespread antisense transcription, presumably caused by pervasive transcription initiation in the A+T-rich genome of S. aureus. Altogether our study presents new perspectives on the biological significance of antisense and pervasive transcription in bacteria.The major human pathogen  Staphylococcus aureus causes human infections that range from superficial skin infections to life-threatening diseases such as pneumonia, endocarditis, osteomyelitis, bacteremia and sepsis [S. aureus´ host range is not limited to humans; it also infects many animals [S. aureus (MRSA) [S. aureus relies on a wide range of virulence factors, whose expression is coordinated by a complex gene regulatory network. They facilitate the escape from host immune responses and adaptation to diverse environmental conditions  ,7. The viewed in ,9).Bacillus subtilis exposed to a wide range of nutritional and environmental conditions established one of the most comprehensive repertoires of transcription units in a prokaryote [B. subtilis antisense RNAs could be attributed to transcription initiated by alternative sigma factors and to imperfect control of transcription termination. This raised the possibility that many antisense transcripts may not have a functional role but are spurious transcripts generated by imperfect transcription termination and unintended transcription initiation, the latter being presumably less deleterious and more frequent when linked to alternative condition-dependent sigma factors [Escherichia coli and Salmonella enterica [Physiological adaptation of a bacterium is coordinated largely at the transcriptional level where molecules such as RNA polymerase sigma factors, transcription factors, and regulatory RNAs, are involved in a variety of mechanisms to modulate mRNA synthesis, processing and degradation. Genome-wide transcriptome studies analyzing bacterial transcription globally and in a quantitative manner across various environmental conditions have provided deep insights into the bacterial transcriptome architecture –13. In penterica  and in aenterica . Howeverenterica ,19.B. subtilis data set as an example, the approach provides at least three useful pieces of information that jointly contribute to the discrimination between direct and indirect regulatory effects. First, the observed co-expression patterns can complement results obtained in more targeted experiments [The availability of large-scale transcriptome data for a particular organism has also proven a very useful resource, complementing sequence-based genome annotation, for the respective research community. Indeed, the information on the genetic regulatory network of an organism provided by the characterization of the wild-type global transcriptome across a wide range of conditions is complementary to more classical studies analyzing particular mutants. The greatest asset of such an approach is its unbiased nature, which does not focus on preselected regulatory circuits and conditions. Simultaneously, it allows comprehensive and precise mapping of all transcriptome parts such as transcription units, non-coding RNA species, and transcription start sites. Taking the aforementioned eriments . Second,eriments . Third, eriments . This iseriments .B. subtilis, S. aureus is a low G+C Gram-positive bacterium but has a smaller genome (~2.8 Mbp) than B. subtilis (~4.2Mbp) and a markedly different partitioning of its promoter space since only three alternative sigma factors are encoded by its genome. In contrast, the B. subtilis genome encodes 17 alternative sigma factors, 14 of which are known to be activated in response to environmental conditions or during developmental processes . In S. escribed ,25. Seve. aureus –31. In S factors . The roln models –37, and . aureus –41. Alon. aureus . Intrins. aureus . Rho is . aureus . Unlike . aureus ,46 and m. aureus ,48.S. aureus HG001 by strand-specific tiling array hybridizations. This strain was derived from S. aureus NCTC 8325, a model strain widely used in genetic and regulatory studies, but in HG001, in contrast to its parent, the SigB-activating phosphatase RsbU is active [in vitro growth to interaction with host cells. The data thus obtained were analyzed in silico, including the systematic mapping of transcription units, annotation of non-coding RNAs, the classification of promoters according to their dependency on SigA and SigB, and the prediction of potentially new transcription factor target sites. In particular, a Fur-dependent sRNA postulated to represent the S. aureus functional analog of FsrA/RyhB was identified. Our findings contribute to a better understanding of the pathogenicity of this organism, in particular the complex regulation of genes encoding virulence factors and the adaptation of S. aureus to infection-mimicking conditions. Antisense RNAs were of particular interest because of the small number of alternative sigma factors present in S. aureus. This class of RNAs was indeed found to be relatively rare in S. aureus, overlapping only 6% of the annotated coding genes. Global analysis of the role of Rho-dependent termination in S. aureus revealed a remarkable overall increase in antisense transcription in the absence of Rho, which had an impact on expression of overlapping genes. Nonetheless, the lack of Rho triggered only slight changes to the growth behavior compared to the respective wild-type strain.In the present study we have analyzed the condition-dependent transcriptome of s active . The invS. aureus HG001 [TSB), minimal medium (CDM), cell culture media , and in human plasma (plasma)  as well as 2 hours (t2) and 4 hours (t4) after entry into stationary phase. In addition, S. aureus was grown in the presence of the cationic antimicrobial peptide colistin (colist) and sub-inhibitory concentrations of the following clinically most relevant antibiotics: flucloxacillin (fluc), vancomycin (vanc), ciprofloxacin (cipro), clindamycin (clind), erythromycin (ery), linezolid (line), and trimethoprim-sulfamethoxazole (T/Smx). Cell culture infection experiments were performed with the human bronchial epithelial cell line S9 and the human monocyte cell line THP-1. Staphylococci internalized by eukaryotic host cells were isolated from samples taken 2/ 2.5 hours (intTHP1-2h and intS9-2h) and 6/ 6.5 hours (intTHP1-6h and intS9-6h) post infection. The following additional samples were taken: i) non-adherent bacteria at multiplicity of infection (MOI) of 25 or 50 retrieved from the supernatant of S9 cells after 1 hour of infection (nonad25-1h and nonad50-1h); ii) bacteria after 1, 2.5, and 6.5 hours of incubation in the infection medium at 37°C and 5% CO2 without agitation ; iii) bacteria after 2.5 hours of anaerobic incubation in pMEM medium at 37°C (anaer-2h); and iv) bacteria grown in RPMI medium with fetal calf serum (FCS) (RPMI/FCS), the pre-culture condition for the THP-1 experiments.The transcriptome of us HG001  was analS. aureus Expression Data Browser at http://genome.jouy.inra.fr/aeb/ provides the condition-dependent transcription profiles, mapping of transcription units and the new annotation of transcribed segments along the chromosome. Transcription profiles for selected genomic regions are presented in The S. aureus strains during growth in RPMI medium revealed that amino acids are largely taken up during the exponential growth phase [srrA) and negative correlation with genes induced by oxidative stress  was observed, so that this axis might reflect the difference between aerobic and anaerobic conditions. This interpretation is supported by the position of the anaerobic growth condition (anaer-2h) on the axis 3. S. aureus grown in the presence of sub-inhibitory concentrations of several clinically relevant antibiotics exhibited overall minor gene expression changes . This approach allowed assessing the general relationships between the 156 RNA samples in terms of expression profiles composed of aggregated values for all annotated genes and newly discovered RNA features . The perth phase . In the  changes .S. aureus is faced with in human plasma (plasma-exp and plasma-t4), as illustrated by high expression levels of iron-regulated genes during growth in both conditions. The virulence factor genes showed a great diversity of expression profiles and all of them were expressed under at least one of the growth conditions  as well as the positions of abrupt signal increases and decreases . The 1523 RNA 5’-ends  derived The TRs outside of annotated CDSs and RNA genes were assigned to 1192 RNA segments (S1 to S1192) according to their structural relationship with neighboring genes  including RNAIII [S. aureus has been predicted and/or experimentally identified by different global approaches, mostly for S. aureus N315 [et al. [S. aureus by mapping the 186 intergenic transcripts, including 25 antisense RNAs (ASRNAs), of N315 reported by Beaume et al. [S. aureus NCTC 8325, at least under the conditions tested.Our study identified nearly all (48/50) of the (predicted) non-coding RNAs of database , includig RNAIII  and SprDg RNAIII . In addieus N315 –62. The  [et al. . We thercis-acting 5’-regulatory region . Of these, three are generic RNAs  and 11 correspond to intergenic transcripts of N315 [bona fide sRNAs. Searching against all experimentally confirmed sRNAs of S. aureus [S. aureus in human plasma, and S414 and S774 appeared further down-regulated in the stationary phase. Expression of these seven potential sRNAs was also examined by Northern blot analysis. For six of them , the presence of a transcript with the predicted size was confirmed for exponentially growing and stationary phase cells in three cultivation media .B. subtilis, using similar criteria to define ASRNAs but with a higher number of different biological conditions, the rate of ASRNAs was 100 per Mbp, the proportion of overlapped genes reached 13%, and RNAs classified as Indep and Indep-NT accounted for 21% (88/423) of the ASRNAs [S. aureus than in B. subtilis.ASRNAs accounted for 145 of the 1192 RNA features identified by our study  and occude novo identification of sigma factor regulons [S. aureus up-shifts identified in our study  when compared to B. subtilis (~60-fold) [B. subtilis). Furthermore, unlike in B. subtilis, the predicted SigB promoters form distinct clusters in the promoter tree summarizing the pairwise correlations of promoter activities  , mainly tivities , which utivities . Analysitivities . On avertivities . A recenS9 cells . In our S. aureus, which are involved in diverse biological functions. Among the predicted SigB regulon members were also the known SigB-dependent sRNA RsaA (S210/S211) [Based on the repertoire of transcription units defined by our study, 249 annotated protein-coding genes were found to be preceded by a SigB binding site, out of which 163 (65%) were considered as SigB-regulated by (one of) the previous studies (Table D in 10/S211)  involved10/S211)  and a neS. aureus is clearly lower than the total contribution of alternative sigma factors to antisense transcription in B. subtilis. In this organism 50% (213/423) of the ASRNAs were predicted to be transcribed by one of the alternative sigma factors and the percentage raised to 68% (60/88) for the ASRNAs classified as Indep or Indep-NT. Many of the ASRNAs in B. subtilis are transcribed from sporulation sigma factors that do not have counterparts in S. aureus. However, even SigB-generated ASRNAs occurred at lower rates in S. aureus than in B. subtilis (6.7 Mbp-1 versus 12 Mbp-1), and this was much more pronounced for the subset of ASRNAs belonging to the categories Indep and Indep-NT (0.35 Mbp-1 in S. aureus vs. 3.8 Mbp-1 in B. subtilis). In contrast, SigA-dependent ASRNAs tended to occur at similar rates in the two organisms with 39 Mbp-1 in S. aureus vs. 57 Mbp-1 in B. subtilis and 5.7 Mbp-1 vs. 4.7 Mbp-1 for the categories Indep and Indep-NT. The comparatively low frequency of ASRNAs in S. aureus appears thus as the combined outcome of the small number of alternative sigma factors and of the small contribution of SigB to antisense transcription in this organism.Considering the ASRNAs, 12% (18/145) were identified as transcribed from SigB-dependent promoters, and the percentage dropped to 5% (1/19) for ASRNAs belonging to categories Indep and Indep-NT. In contrast, 75% (109/145) of the ASRNAs were identified as transcribed from SigA-dependent promoters. The remaining fraction consisted of ASRNAs that lacked an identified promoter. Interestingly, the proportion of ASRNAs identified as SigB-dependent in Coordinated regulation of promoter activities is summarized in the promoter correlation tree and the associated clustering: 1242 up-shifts (82%) belonged to 16 activity clusters with ≥15 members defined by a cutoff on average Pearson correlation set to 0.6 . The larS. aureus, several iron uptake systems are known to be controlled by Fur [fhuD1, opp-1 operon, mntABC) or iron release from heme (isdI). Of these, the mntABC operon encoding a manganese transporter is a potential new member of the S. aureus Fur regulon. For the other genes, Fur-dependent regulation has already been reported but with different localization of the Fur box  with a size of ~180 nt that was also confirmed by Northern blot analysis . Targetiewed in  revealedS. aureus. Most down-shift sites were also found associated with predicted intrinsic terminators in B. subtilis, where the transcription termination factor Rho was shown to be involved in termination of a particular class of TUs lacking a defined 3’-end. These TUs were characterized by slowly decreasing expression, apparently due to the lack of an efficient intrinsic terminator  [S. aureus, only 19 TUs lacked a defined termination site . The 3’PT and AS segments were also about twice less frequent than in B. subtilis .Specific sequence elements, typically encoding a hairpin structure followed by a U-rich tract, direct dissociation of the RNA polymerase from the DNA template at intrinsic termination sites. Applying a 30 bp distance cut-off, these elements were searched using the TransTermHP software . They wendep-NT) , and therho-deletion on the growth of S. aureus [rho-deletion mutant. Chromosomal regions with Rho-dependent changes in transcript levels were mapped by comparing the normalized tiling array transcription profiles of the Δrho mutant and the parental strain HG001 harvested during exponential growth and four hours after entry into stationary phase in TSB and RPMI medium. In both media, growth of the S. aureus Δrho mutant was almost identical to that of the parental strain, except reaching a slightly lower final OD  possessed 3’-extensions in the Δl strain , supportrho mutant than in the parental strain in at least one of the four conditions  accounted for only a very small fraction of the increase in transcript levels detected in absence of Rho and we therefore decided to analyze all chromosomal regions where normalized transcript levels were 4-fold higher in the Δrho mutant would result from extensions beyond the transcript 3’-ends due to read-through of Rho-dependent terminators. However, our analysis (Text D in It was expected that most of the up-regulated regions in the Δrho mutant was the higher expression of coding genes sometimes followed by (often long) downstream extensions  for the 292 annotated genes (sense level) with log2 expression signal ≤8 in the wild-type, as compared to 1.11  for the 2453 antisense transcripts of annotated genes with log2 expression signal ≤8. Therefore, the absence of Rho seems to impact less on sense strands than antisense strands even after accounting for the potential masking effect of the coding transcripts  than B. subtilis (56.5%) and E. coli (49.2%). We therefore wanted to examine to what extent different genome compositions may lead to a different rate of random occurrence of the TATAAT hexamer that corresponds to the canonical core of the -10 box for the housekeeping sigma factor  in the three genomes . The TATAAT hexamer was indeed much more frequent (0.905 Kbp-1) in the antisense strand of protein-coding genes in the S. aureus genome than in the B. subtilis (0.332 Kbp-1) or E. coli genome (0.091 Kbp-1). In each of these three genomes the TATAAT hexamer was also less frequent on the sense strand than on the antisense strand . This possibly reflects, at least partly, the fact that the hexamer TATAAT cannot start at the second position of a codon within a gene since it contains the TAA stop codon. The extent of differential abundances of the TATAAT hexamer between and within genomes seems thus consistent with the idea that nucleotide composition may contribute to shape the patterns of pervasive transcription initiation counteracted by Rho.rho mutant during exponential growth in RPMI medium  that was much weaker in the wild-type (r = -0.30), but also statistically significant   in the ΔI medium , 153  . In partrho mutant based on the tiling array signals may originate from long RNA molecules or from overlapping small molecules resulting from degradation of longer transcripts [rho mutant, mainly as a result of read-through transcription at TU ends. For all six antisense transcripts, the analysis confirmed the presence of large-size RNA molecules that were specific for the mutant samples (rho mutant. In a fourth case (3’PT transcript S931), the obtained size matched the position of a marked drop in the tiling array signal. For a ~9 Kb long transcribed region downstream of S234 and a ~11 Kb long region downstream of S596, Northern blot analysis detected transcripts with different sizes, all larger than 2 Kb.In principle, the increased transcript levels observed outside of annotated genes in the Δnscripts . To disc samples . In threrho mutant were detected. The second probe, specific to the antisense region, showed only the longer transcript.The example in S. aureus HG001 was systematically analyzed under a broad range of experimental conditions to allow for an extensive mapping of TUs, annotation of non-coding RNAs and further insights into the transcriptional regulatory network of S. aureus. Almost 90% of the annotated genes were expressed in at least one growth condition but only 110 CDSs (3.9%) were always found to be highly expressed , and half (55/110) belong to the set of 351 genes of S. aureus NCTC 8325 identified as essential for survival and growth in vitro [perR, rex, icaR), and proteins involved in oxidative stress management  whose generally high expression might provide a molecular basis for the rather high level of oxidative stress resistance of S. aureus, a reflection of the frequent encounter of oxidative stress in the interaction with its host/ natural environments.Using a genomic tiling array approach, the transcriptome of xpressed , which iin vitro   were assigned to SigB, which controls the general stress regulon. A relatively small fraction (about 12%) of the genes supposed to be controlled by SigB in S. aureus [B. subtilis SigB regulon. Besides roughly 30% of genes with unknown function, the S. aureus SigB regulon contains genes involved in cell envelope composition, membrane transport processes, intermediary metabolism, and virulence. Our study identified 86 new protein-coding genes in the SigB regulon that are of particular interest for further investigation.SigA or SigB binding sites could be assigned to 1412 of the 1523 transcription signal up-shifts detected, which led to the identification of 145 SigB-dependent promoters. In  factors  and 170 . aureus  have homS. aureus and B. subtilis where SigB is released from its inhibitory complex with the anti-sigma factor RsbW by the competitive binding of the unphosphorylated form of the antagonist protein RsbV to RsbW [B. subtilis are not conserved in S. aureus whose genome encodes neither RsbP nor the stressosome that controls the activity of RsbU [S. aureus is still not well understood. RsbU may be constitutively active making SigB activity sensitive to the availability of core RNA polymerase [S. aureus compared to B. subtilis. Unlike in B. subtilis, the induction of SigB-dependent promoters in S. aureus is not restricted to a narrow range of stress conditions but is instead generally associated with the stationary phase and perhaps a general redistribution of RNA-polymerase activity. Indeed, the average expression level downstream of SigB-dependent promoters was higher than for SigA-dependent promoters in half of the conditions of our study. In addition, the S. aureus SigB regulon exhibits a substantial basal activity in non-induced conditions not seen in B. subtilis where SigB-dependent promoters are strictly turned off in the absence of stress. It was also interesting to note that while genes of the SigB regulon grouped in a single specific expression cluster in B. subtilis, this was not the case in S. aureus where SigB-regulated genes exhibited a substantial diversity of expression patterns, some of which very similar to genes transcribed from SigA-dependent promoters. Altogether, these differences are certainly associated with distinct physiological roles of SigB in the two species as also suggested by the widely different gene content.Activation of SigB involves the same primary partner switching mechanism in  to RsbW . However of RsbU . How andlymerase . Our datcitB, fdhA, addB, ilvD, and miaB) and heme biosynthesis enzymes (ctaA and hemE) as well as of tricarboxylic acid (TCA) cycle genes citZ (encoding citrate synthase) and sdhCA (encoding succinate dehydrogenase subunits). Iron-responsive sRNAs exist in many bacteria including B. subtilis [E. coli RyhB [S. aureus, Fur-mediated regulation was also shown to involve changes in the levels of central carbon metabolism proteins; three TCA cycle enzymes  were observed in lower amounts under conditions of iron starvation [In addition to searching for so far unknown SigB controlled genes and new insights into the regulatory role of SigB, we exploited our tiling array data set with respect to the prediction of new transcription factor target genes including the iron-responsive regulator Fur. This analysis identified an sRNA (S596) supposed to be controlled by the Fur repressor, which is apparently a functional analog of FsrA/RyhB. It is predicted to repress, amongst others, the expression of genes encoding iron-sulfur-cluster containing proteins (subtilis  and typioli RyhB . In S. aarvation . In addiarvation ).S. aureus to the host during colonization and infection. In particular, expression of virulence factor genes is tightly controlled by multiple regulatory systems involving two-component systems , transcription factors , the alternative sigma factor SigB and sRNAs  [in vivo infection has recently been characterized [2O2 and sub-inhibitory concentrations of α-defensins [Our data highlight the diversity of expression patterns for virulence related genes across conditions. This observation reflects the functional heterogeneity of this pool of genes that encompasses biological functions such as cell adhesion, toxin production, and escape of the immune system. However, for the proteins classified as virulence factors, which often have multiple roles in pathogenesis, the knowledge of the exact function and regulation of their encoding genes is not always complete. Indeed, a complex regulatory network mediates the adaptation of D, RsaA) ,64. WithD, RsaA) ,84 and icterized . The hosefensins .eap, fnbA and fnbB . The Extracellular fibrinogen-binding protein (Efb) interacts with complement protein C3b and attracts fibrinogen to the surface of S. aureus, thus masking C3b and opsonizing antibodies from recognition by phagocytic receptors [S. aureus in human blood [efb, sbi, chp, and scn showed a partially different expression pattern compared to other SaeRS-dependent genes reflects the expression of virulence factors in adaptation to the host environment, suggesting the involvement of additional regulators.The global view on the condition-dependent expression of virulence related genes pointed to interesting observations. A noticeably high number of virulence factor genes (37/47), in particular SaeRS-dependent genes, were upregulated after internalization by human THP-1 macrophages and S9 bronchial epithelial cells, including and fnbB . Extraceocytosis , were moeceptors . It was an blood ,91. The S. aureus HG001 inside eukaryotic cells, using the human lung epithelial cell lines A549 and S9 and the kidney cell line HEK 293 [S. aureus internalized by human THP-1 macrophages or S9 bronchial epithelial cells  is comparable to growing rather than stationary phase cells. More specifically, our data revealed that S. aureus is challenged with reduced amino acid availability and iron limitation upon internalization by these eukaryotic cells. Furthermore, the PCA results  transcripts without major negative impact on fitness [S. aureus where SigB and SigH (which is not active in the strain used [B. subtilis.ASRNAs are less frequent and less often initiated from their own promoter (categories Indep and Indep-NT) in  fitness . This poain used ) are thei.e. genome-wide, cellular function of Rho has been almost exclusively studied in E. coli [S. aureus, we identified only 19 TUs with heterogeneous and often antisense 3’-extensions due to the complete absence of a defined termination site. Our results confirmed the Rho-dependence of this particular class of TUs already identified in B. subtilis [S. aureus is therefore mostly independent of Rho.The global,  E. coli –106 in w E. coli  and has  E. coli ,108. In subtilis . Beyond B. subtilis and E. coli had already revealed that Rho plays a major role in suppressing or limiting antisense transcription but Rho-dependent transcripts initiated from promoters undetected in control conditions represented only a limited number of loci [B. subtilis, where Rho is also dispensable [E. coli, where rho is an essential gene, Rho-dependent transcripts were mapped by treatment with the Rho inhibitor bicyclomycin. Antisense transcription suppressed by Rho was identified for 1555 genes  and was shown to arise mostly (~60%) from continuation of transcription at the end of genes into oppositely oriented downstream genes, but a substantial fraction (~40%) was also generated by transcription from antisense promoters within genes, i.e. by extension of bona fide antisense RNAs [Nevertheless, a massive up-regulation of expression on the antisense strand of the protein-coding genes was found in an isogenic mutant deficient for the termination factor Rho, which substantiates the role of Rho in suppressing pervasive antisense transcription initiation. Previous studies in  of loci ,13. Indepensable , the impnse RNAs .S. aureus in absence of Rho is therefore very different from what was reported from E. coli and B. subtilis. Our comparison of the frequency of canonical promoter -10 box hexamer TATAAT between S. aureus, B. subtilis and E. coli suggests that pervasive antisense transcription from cryptic low level promoters may be directly linked to the higher A+T composition of the S. aureus genome. The precise mode of action of Rho has not been studied in Gram-positive bacteria, but what is known from Gram-negative bacteria suggests that Rho is particularly well suited to terminate transcription of ASRNAs since the absence of ribosomes may facilitate its loading and contact with the elongation complex. Interestingly, pervasive transcription initiation certainly also occurs on the sense strand [rho deletion had less impact on the expression of the sense strand. The higher abundance of the TATAAT hexamer on the antisense strand could at least partly explain why Rho-dependent termination seems to target mostly antisense transcripts in S. aureus.The pattern of antisense transcription observed in e strand  and probet al. [E. coli that the increase in antisense transcription caused by the inhibition of Rho did not affect sense transcription. In contrast, our study revealed an effect of elevated antisense transcription on sense transcript levels in Rho-deficient conditions in S. aureus. Moreover, the mutant antisense levels of down-regulated genes were found to be mostly higher than the sense levels detected in the wild-type . Peet al.  reportedild-type . This obrho deletion has no clear effect on the growth rate despite its role in control of pervasive antisense transcription: The genes whose expression tends to be higher (in particular housekeeping genes) are less impacted by antisense transcription.Importantly, these results disclosing the context in which antisense transcription impacts on sense transcription directly suggest an explanation for the observation that S. aureus and the direct comparison to those obtained with the same technology on B. subtilis reveal additional pieces of information on the biological interpretation of pervasive antisense transcripts. Indeed, the data tend to indicate that the pattern of pervasive antisense transcription may be a simple by-product of genome and transcriptome characteristics such as: A+T-composition, multiplicity of promoter motifs recognized by sigma factors, and balance between the evolutionary forces of mutation, drift and negative selection whose stringency is presumably lower for condition-dependent promoters. From such a perspective, pervasive antisense transcription would not be the product of an evolution for a biological function either at the individual level (e.g. cis-regulation of sense gene) or at the global level. Furthermore, the data also disambiguate the notions of biological effect and biological function, since we show that pervasive transcription although certainly spurious would have an effect on sense transcription if not suppressed by specific mechanisms such as Rho-dependent termination.Our results obtained on wild-type and Rho-deficient S. aureus research, the present study has provided a detailed inventory of transcription units and non-coding RNAs of S. aureus HG001, along with a classification of SigA- and SigB-dependent promoters, and targets for major transcription factors. It is anticipated that this compendium, which can be queried through an online genome browser, will serve as a major lead for future studies on this important pathogen’s very diverse lifestyles inside and around the human host.In the context of S. aureus was grown with shaking at 37°C in the various cultivation media and in human plasma. Samples were collected by centrifugation with half volume of killing buffer . Pellets were frozen in liquid nitrogen and stored at -80°C until RNA preparation. The details of the medium compositions are provided in the supplemental material  and methionine (1 mM) [no acids . The cele (1 mM) .S. aureus was pre-cultured in TSB till early-exponential phase (OD600 of 0.5), after which the culture was diluted 10-fold using TSB supplemented with the respective antibiotics.Sub-inhibitory antibiotic concentrations were as follows: flucloxacillin 0.02 μg/mL, vancomycin 0.63 μg/mL, ciprofloxacin 0.10 μg/mL, clindamycin 0.01 μg/mL, erythromycin 0.05 μg/mL, linezolid 0.10 μg/mL, and trimethoprim-sulfamethoxazole 0.75 μg/mL. In these experiments, 2 in a humidified incubator. During this time bacteria were internalized by the S9 cells. After 1 hour of infection, lysostaphin was added to kill remaining extracellular bacteria. After 1.5 and 5.5 hours of incubation (2.5 and 6.5 hours post infection) samples were taken and internalized staphylococci were isolated for RNA preparation. For the experiments with THP-1 cells, bacteria were pre-grown in RPMI medium with FCS, added to the host cells and incubated at 37°C and 5% CO2 in a humidified incubator.For the experiments with S9 cells  database (accession numbers GSE70040-43).in vitro transcription (IVT) with T7 RNA polymerase and gene-specific PCR products as template. Primer sequences are listed in Table A in Northern blot analysis was carried out as described previously . The digB. subtilis [B. subtilis with transcription start sites mapped by a differential RNA-seq approach [B. subtilis) of the actual transcription start site. New transcripts (i.e. unannotated in GenBank: CP000253) were detected where the lower boundary of the 95% equal-tailed credibility interval for the smoothed trajectory reached 10-fold the chromosome median. These segments were further split according to breakpoints to avoid aggregation of regions with different transcription levels and extended on their 5’ and 3’ extremities according to a more permissive expression cut-off (5-fold the chromosome median) to avoid over-segmentation in regions with expression levels close to the 10-fold cut-off. Promoter activity was measured as the smoothed signal downstream the position of the corresponding up-shift and a promoter tree was built by hierarchical clustering based on estimated pairwise correlation coefficients. Downstream each up-shift, a transcription unit (TU) was defined as the maximum continuous region where the expression level remains at least 5-fold higher than the chromosome median before dropping below this level or encountering another up-shift in at least one RNA sample. Aggregated log2-scale expression values for annotated genes and newly detected segments were obtained as the median of the smoothed signal for probes lying entirely within the considered region. For most analyses gene-level values were quantile-normalized to make them more comparable between hybridizations.Detection of new transcribed segments, 5’-ends , 3’-ends , delineation of TUs, and computation of gene expression values, were performed exactly as described for subtilis ; the maisubtilis  to obtaisubtilis . The repsubtilis  by a comapproach , which rrho-mutant data is available in Text D in A detailed description of the methods used to analyze the ΔStaphylococcaceae for the transcription factors listed for S. aureus N315. For WalR and GraR, not present in RegPrecise, we used the binding sites listed in [S. aureus in RegPrecise we considered only the occurrences with the same orientation as the up-shifts, except for WalR for which we took both strands into account. We compared the position of signal down-shifts to predictions of intrinsic terminators available at http://transterm.cbcb.umd.edu/tt/ that were made from the sequence alone with the software TranstermHP [The classification of promoters based on the presence of sigma factor binding site motifs around the up-shifts  was performed with the software ‘treemm’  that alsisted in ,120,121.nstermHP .S. aureus Expression Data Browser at http://genome.jouy.inra.fr/aeb/ can be accessed through the study website http://genome.jouy.inra.fr/aeb/supplementary_data.html. The website also provides links to access the data sets deposited in GEO (records GSE70040-43).The S1 Data(PDF)Click here for additional data file.S1 FigS. aureus by S9 bronchial epithelial cells or THP-1 macrophages and related conditions, i.e. 2.5 hours of anaerobic incubation in pMEM medium at 37°C, 1 hour of incubation in the infection medium at 37°C and 5% CO2 without agitation, and non-adherent bacteria retrieved from the supernatant of S9 cells after 1 hour of infection (green bars).Gene expression levels  are displayed for the following conditions: exponential growth and stationary phase in different cultivation media and human plasma (blue bars); growth in the presence of sub-inhibitory concentrations of various antibiotics in TSB (red bars) and RPMI medium (orange bars); internalization of (PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.S9 Table(XLSX)Click here for additional data file.S10 Table(XLSX)Click here for additional data file.S11 Table(XLSX)Click here for additional data file.