<i>Staphylococcus aureus </i>Transcriptome Architecture:From Laboratory to Infection-Mimicking Conditions

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

Dual Role of the Oligopeptide Permease Opp3 during Growth of Staphylococcus aureus in Milk▿

Staphylococcus aureus RN6390 presents a diauxic growth in milk, due to amino acid limitation. Inactivation of the oligopeptide permease Opp3 (dedicated to the nitrogen nutrition of the strain) not only affects the growth of the strain but also results in reduced expression levels of three major extracellular proteases

The WalKR system controls major staphylococcal virulence genes and is involved in triggering the host inflammatory response

International audienceThe WalKR two-component system is essential for the viability of Staphylococcus aureus, playing a central role in controlling cell wall metabolism. We produced a constitutively active form of WalR in S. aureus through a phosphomimetic amino acid replacement (WalR(c), D55E). The strain displayed significantly increased biofilm formation and alpha-hemolytic activity. Transcriptome analysis was used to determine the full extent of the WalKR regulon, revealing positive regulation of major virulence genes involved in host matrix interactions (efb, emp, fnbA, and fnbB), cytolysis (hlgACB, hla, and hlb), and innate immune defense evasion (scn, chp, and sbi), through activation of the SaeSR two-component system. The impact on pathogenesis of varying cell envelope dynamics was studied using a murine infection model, showing that strains producing constitutively active WalRc are strongly diminished in their virulence due to early triggering of the host inflammatory response associated with higher levels of released peptidoglycan fragments. Indeed, neutrophil recruitment and proinflammatory cytokine production were significantly increased when the constitutively active walR(c) allele was expressed, leading to enhanced bacterial clearance. Taken together, our results indicate that WalKR play an important role in virulence and eliciting the host inflammatory response by controlling autolytic activity

A nickel ABC-transporter of Staphylococcus aureus is involved in urinary tract infection

The oligopeptide transport systems Opp belong to the nickel/peptide/opine PepT subfamily of ABC-transporters. The opportunist pathogen Staphylococcus aureus encodes four putative Opps and one orphean substrate binding protein Opp5A. Here, we report that the Opp2 permease complex (Opp2BCDF) and Opp5A are involved in nickel uptake and then renamed them NikBCDE and NikA respectively. S. aureus carries also a high-affinity nickel transporter NixA belonging to the NiCoT family of secondary transporters. The activity of these two nickel transporters determine that of urease, a multimeric nickel-dependent enzyme mainly involved in the neutralization of acidic environments. However, only the Nik system was responsible for the neutralization and deposit of pH-dependent crystals in human urine. Inactivation of the nik genes affected bacterial colonization of mouse urinary tract, as well as the 50% infective dose levels compared with the parental and nixA strains. Finally, complementation of the nik mutations restored bacterial colonization. Together, our results suggest a role for the Nik system in the urinary tract infection by S. aureus, probably due to the urease-mediated pH increase of the urine

Promoter tree, sigma-factor and TFBS predictions.

<p>From top to bottom, the figure includes the following elements: A promoter tree built by hierarchical clustering of promoter activities across RNA samples based on pairwise correlations. The classification of up-shifts according to the type of sigma-factor binding sites identified (black bars for SigA, orange bars for SigB, gray bars for lack of sigma-factor binding site identification). The clusters of size ≥15 promoters obtained when splitting the tree at an average Pearson correlation coefficient 0.6. The TFBSs identified by MAST search. Here, the different transcription factors are listed on the left-hand side of the plot along with the counts for three different categories of up-shifts. The color codes used for counts and symbols are: blue for sites predicted by MAST search and included in the training (RegPrecise) set, red for sites in the training set but not identified by our MAST search, green for sites predicted by MAST search but not listed in the training set thus representing newly identified potential TFBSs.</p

Summary of the new transcription segments.

<p>Summary of the new transcription segments.</p

Context and impact of elevated antisense expression levels in the Δ<i>rho</i> mutant.

<p><b>(A)</b> Transcription profiles for selected regions showing different effects of <i>rho</i> deletion, from left to right: 1) flattening of the downstream drift expression patterns typical of regions lacking defined termination sites (3’PT and 3’NT); 2) & 3) expression of regions for which no promoters are detected in the wild-type; 4) & 5) transcriptional read-through at defined termination sites; 6) higher transcript levels of coding genes. For the first two regions we show the transcription profiles for the four growth conditions examined, with wild-type profiles in black and Δ<i>rho</i> mutant profiles in condition-specific colors, as well as the 30 representative wild-type profiles. As seen in these examples, the impact of <i>rho</i> deletion tends to be stronger in RPMI than in TSB medium and in exponential growth than in stationary phase. Some degree of decrease of sense transcript levels, which may be caused by elevated antisense levels, is seen in these examples. <b>(B)</b> Sense versus antisense transcription levels in the wild-type and in the Δ<i>rho</i> mutant for exponential growth in RPMI. Each annotated gene is represented by a point. There is a strong negative correlation between sense and antisense expression in the Δ<i>rho</i> mutant (Pearson correlation coefficient r = -0.73) that is also visible but much weaker in the wild-type (r = -0.30). Indeed, antisense levels tend to increase genome-wide in the Δ<i>rho</i> mutant, except for the antisense strand of the most highly expressed genes. The most down-regulated genes (expression level in the Δ<i>rho</i> mutant is ≤50% of the wild-type) are highlighted in blue; they face antisense transcripts with particularly elevated levels in the Δ<i>rho</i> mutant. Horizontal and vertical lines indicate the medians (global in gray, most down-regulated genes in blue).</p

Transcriptional landscape reconstruction leads to a new annotation of the <i>S</i>. <i>aureus</i> HG001 genome.

<p>Panels <b>(A-G)</b> show examples of the different categories of transcription segments outside annotated CDSs and RNA genes. Each panel shows from top-to-bottom (i) the original GenBank annotation, (ii) a selection of 30 representative expression profiles (horizontal black lines show for each strand the chromosome median, and the associated 5-fold and 10-fold cut-offs) colored according to the position of the hybridization in 3D PCA, (iii) the detected up-shifts, the associated transcription units, and the down-shift positions, (iv) the new annotation with unannotated expressed segments colored according to the classification based on the transcriptional context. The different categories of terminal regions are <b>5’UTR</b> (green boxes) and three classes of 3’ regions: <b>3’UTR</b> (red) ending with a defined termination site, <b>3’NT</b> (orange) without defined termination site, and <b>3’PT</b> (old yellow) downstream a site of partial termination. Two categories of intergenic regions are distinguished: <b>intra</b> (dark blue) for strictly intracistronic regions, and <b>inter</b> (light blue) for regions where the downstream gene can be transcribed from its own promoter. Finally, depending of the presence or absence of a defined termination site, independent segments decompose into two categories: <b>indep</b> (black) and <b>indep-NT</b> (brown). Transcription segments overlapping (≥100bp or ≥50%) GenBank annotated genes on the opposite strand are referred to as antisense (<b>AS</b>).</p

Northern blot analysis of a Δ<i>rho</i> mutant-specific antisense transcript facing a tri-cistronic transcription unit starting with SAOUHSC_00972.

<p><b>(A)</b> Transcription profiles of the genomic region assayed. <i>S</i>. <i>aureus</i> wild-type (black lines) and Δ<i>rho</i> mutant (colored lines) were grown in RPMI and TSB medium. <b>(B)</b> Northern blot analysis of the same RNA samples (5 μg per lane) using RNA probes (indicated by red bars) directed against SAOUHSC_00975 and the antisense strand of SAOUHSC_00974. The SAOUHSC_00975 probe detected the 0.5-kb mRNA in both strains and the longer read-through transcript in the Δ<i>rho</i> mutant. The antisense specific probe detected only the 2.5-kb transcript specific to the mutant samples.</p