The reduction in small ribosomal subunit abundance in ethanol-stressed cells of Bacillus subtilis is mediated by a SigB-dependent antisense RNA

One of the best-characterized general stress responses in bacteria is the sigma(B)-mediated stress response of the Gram-positive soil bacterium Bacillus subtilis. The sigma(B) regulon contains approximately 200 protein-encoding genes and 136 putative regulatory RNAs. One of these sigma(B)-dependent RNAs, named S1136-S1134, was recently mapped as being transcribed from the S1136 promoter on the opposite strand of the essential rpsD gene, which encodes the ribosomal primary-binding protein S4. Accordingly, S1136-S1134 transcription results in an rpsD-overlapping antisense RNA (asRNA). Upon exposure of B. subtilis to ethanol, the S1136 promoter was found to be induced, while rpsD transcription was downregulated. By quantitative PCR, we show that the activation of transcription from the S1136 promoter is directly responsible for the downregulation of rpsD upon ethanol exposure. We also show that this downregulation of rpsD leads to a reduced level of the small (30S) ribosomal subunit upon ethanol stress. The activation of the S1136 promoter thus represents the first example of antisense transcription-mediated regulation in the general stress response of B. subtilis and implicates the reduction of ribosomal protein abundance as a new aspect in the sigma(B)-dependent stress response. We propose that the observed reduction in the level of the small ribosomal subunit, which contains the ribosome-decoding center, may protect B. subtilis cells against misreading and spurious translation of possibly toxic aberrant peptides under conditions of ethanol stress. (C) 2015 Elsevier B.V. All rights reserved.</p

Regulatory RNAs in Bacillus subtilis:a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression

Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5= untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNAmediated gene regulation in B. subtilis mostly involves elements at the 5= ends of mRNA molecules. These can include 5= secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis

Small regulatory RNA-induced growth rate heterogeneity of Bacillus subtilis

Isogenic bacterial populations can consist of cells displaying heterogeneous physiological traits. Small regulatory RNAs (sRNAs) could affect this heterogeneity since they act by fine-tuning mRNA or protein levels to coordinate the appropriate cellular behavior. Here we show that the sRNA RnaC/S1022 from the Gram-positive bacterium Bacillus subtilis can suppress exponential growth by modulation of the transcriptional regulator AbrB. Specifically, the post-transcriptional abrB-RnaC/S1022 interaction allows B. subtilis to increase the cell-to-cell variation in AbrB protein levels, despite strong negative autoregulation of the abrB promoter. This behavior is consistent with existing mathematical models of sRNA action, thus suggesting that induction of protein expression noise could be a new general aspect of sRNA regulation. Importantly, we show that the sRNA-induced diversity in AbrB levels generates heterogeneity in growth rates during the exponential growth phase. Based on these findings, we hypothesize that the resulting subpopulations of fast- and slow-growing B. subtilis cells reflect a bet-hedging strategy for enhanced survival of unfavorable conditions

Overview of metabolite changes explained by different community members of the bee gut microbiota.

<p>(A) Bar graphs show the fraction of the metabolic changes explained by mono-colonizations and hive bees for substrates (240 ions) and products (132 ions). The category “Total” indicates the total number of ions explained by mono-colonizations, thus excluding hive bees. Heatmap representation of enrichment <i>P</i> values (one-sided Fisher’s exact test <i>P</i> < 0.05) are provided for compound categories enriched in one or several mono-colonizations. (B–E) Z-score transformed ion intensities of selected substrate and product ions are shown for all treatment groups. (B) Four glycosylated flavonoid substrates. (C) Two substrates from the outer pollen wall. (D) Two products corresponding to host-derived metabolites. (E) Succinate, one of the major fermentation products. Groups depicted in color highlight treatment groups displaying a significant difference compared to MD bees in the same direction as the CL versus MD difference (one-way analysis of variance [ANOVA], Tukey honest significant difference [HSD] post hoc test at 99% confidence, <i>P</i> ≤ 0.05). Plots for all 372 ions are provided in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s008" target="_blank">S8 Data</a>. Ba, <i>B</i>. <i>apis</i> mono-colonized; Bi, <i>B</i>. <i>asteroides</i> mono-colonized; CL, colonized with the reconstituted microbiota; F4, Firm-4 mono-colonized; F5, Firm-5 mono-colonized; Fp, <i>F</i>. <i>perrara</i> mono-colonized; Ga, <i>G</i>. <i>apicola</i> mono-colonized; Hive, hive bees; MD, microbiota-depleted; Sa, <i>S</i>. <i>alvi</i> mono-colonized. The numerical results of the full enrichment analysis, bar graphs, and mono-colonization plots are provided in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s003" target="_blank">S3 Data</a>, <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s001" target="_blank">S1 Data</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s008" target="_blank">S8 Data</a>, respectively.</p

Summary of the metabolic activities of the bee gut microbiota identified in this study.

<p>(A) Schematic representation of the bee gut depicting the crop, midgut, and hindgut. The hindgut is divided into the ileum and the rectum, where the highest bacterial densities are found. Bacteria in the ileum are shown in magenta and orange (mostly Proteobacteria), and those in the rectum are shown in green and blue (mostly <i>Lactobacilli</i> and <i>Bifidobacteria</i>). Pollen grains are shown in yellow. (B) Pollen is likely predigested in the midgut, where bacterial levels are relatively low [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.ref045" target="_blank">45</a>]. Here, the host absorbs accessible pollen-derived compounds such as simple sugars (glucose or fructose) and amino acids [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.ref046" target="_blank">46</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.ref047" target="_blank">47</a>]. Nondigested pollen compounds enter the hindgut, where bacterial density is higher. We found nucleosides, various carboxylic acids (e.g., citrate, malate, and fumarate), and aromatic compounds (such as quinate) from pollen to be utilized by bee gut bacteria. In the posterior part of the hindgut (rectum), three community members (Firm-5, Firm-4, and <i>B</i>. <i>asteroides</i>) metabolize major components of the outer pollen wall, including flavonoids, phenolamides, and ω-hydroxy acids. The metabolic activities of the microbiota lead to the accumulation of fermentation products and intermediates of aromatic compound degradation. Some of the bacterial products may be utilized by other community members, as exemplified by the cross-feeding between <i>G</i>. <i>apicola</i> and <i>S</i>. <i>alvi</i>, or absorbed by the host. In addition, the gut symbiont <i>B</i>. <i>asteroides</i> seems to increase the production of several host metabolites (juvenile hormone derivatives and prostaglandins) that have key functions in immunity and physiology.</p

Metabolite changes between microbiota-depleted (MD) and colonized (CL) bees.

<p>An Orthogonal Projection of Least Squares-Differentiation Analysis (OPLS-DA) based S-plot of metabolite changes shows the ions responsible for CL and MD separation. The inset shows OPLS-DA separation between CL and MD along the component that was used for correlating ion intensities. Experiment 2 data (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s002" target="_blank">S2A Data</a>) was used for this plot, and annotated ions that were not robustly significantly different between CL and MD in both experiments are plotted in grey. Ions with a first annotation belonging to an enriched category (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s003" target="_blank">S3A Data</a>) are plotted in color, except for the category “amino acids and derivatives”, which did not meet the significance threshold for enrichment but was deemed relevant. The “purine nucleosides and analogues” and “pyrimidine nucleosides and analogues” categories were combined into “nucleosides and analogs” for coloring only. The boxed areas show the <i>m/z</i> [M-H⁺]^- of the ion and the first annotation name of the most discriminatory ions, sorted by covariance. Asterisks indicate ions with ambiguous annotations. The numerical data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s001" target="_blank">S1 Data</a>. Conjug., conjugates; Deriv., derivatives; FC, fold change; int., intensity.</p

Recapitulation of flavonoid degradation patterns by gut bacteria during in vitro growth in pollen-conditioned medium.

<p>(A) Line graphs show the growth of each community member in control medium and pollen-conditioned medium based on colony-forming unit (CFU) counts at time points 0 h and 16 h. Values are the mean of five replicates, with error bars indicating standard deviation. **<i>P</i> < 0.01, ***<i>P</i> < 0.001 (Welch’s <i>t</i> test). Volcano plots of significance (Welch’s <i>t</i> test Benjamini and Hochberg adjusted [BH adj.] <i>P</i> value) versus log2(fold change) show metabolic changes in pollen-conditioned medium at time point 16 h relative to 0 h. Ions identified as pollen derived are highlighted in black. Ions annotated as glycosylated flavonoids, flavonoid aglycones (non-glycosylated flavonoids), or putative flavonoid breakdown products are shown in color when they displayed log2(fold changes) ≥ |1|. Other annotated ions are plotted in grey. (B) Model for the metabolism of flavonoids in the bee gut. Flavonoids are deglycosylated by specific bee gut bacteria, resulting in the release of flavonoid aglycones. The sugar residues are likely fermented into organic acids. Accumulation of several intermediates of aromatic compound degradation pathways, both in vivo and in vitro, suggests that the aglycone may be broken down further. The numerical values of the line graphs and the volcano plots can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s001" target="_blank">S1 Data</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s009" target="_blank">S9 Data</a>, respectively.</p

Bacterial colonization levels in the guts of microbiota-depleted (MD), colonized (CL), and hive bees.

<p>(A) Total bacterial loads in the gut of 10-d-old MD bees (<i>n</i> = 21), CL bees (<i>n</i> = 18), and hive bees (<i>n</i> = 16) were assessed by quantitative PCR (qPCR) with universal bacterial 16S rRNA primers. (B) The bacterial loads of the seven predominant community members used for experimental colonizations were assessed by qPCR with species-specific 16S rRNA primers for the same bees as shown in panel A. Black lines show median values. Samples with <10⁵ bacterial cells per gut are shown below the red line, which we consider the threshold of detection. Primer characteristics are summarized in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s022" target="_blank">S2 Table</a>. n.s., not significant; *<i>P</i> < 0.05; **<i>P</i> < 0.01; and ***<i>P</i> < 0.001 (Wilcoxon Rank Sum test, Benjamini and Hochberg adjusted [BH adj.]). The numerical data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s001" target="_blank">S1 Data</a>.</p

Overview of the experimental setup to characterize metabolic activities of the honey bee gut microbiota.

<p>Newly emerged adult bees were either kept microbiota-depleted (MD), colonized with a reconstituted community of the seven predominant species of the bee gut microbiota (CL), or mono-colonized with one of the seven species separately. Bees received sterilized bee pollen and sugar water as diet. Ten days after colonization, metabolites were extracted from the honey bee guts and subjected to untargeted metabolomics to (1) reveal overall metabolic changes in CL versus MD bees and (2) identify which community member could explain these metabolic changes in the gut. As a control, we additionally analyzed 10-d-old hive bees that were colonized by the native microbiota under natural conditions in the colony (not shown in this figure). To recapitulate findings in vitro, individual community members were cultured in pollen-conditioned medium, and metabolic changes in this medium were profiled using untargeted metabolomics. MS, mass spectrometry; Q-TOF, quadrupole-time of flight.</p

Cross-feeding between <i>G</i>. <i>apicola</i> and <i>S</i>. <i>alvi</i>.

<p>(A) Evidence for cross-feeding of pyruvate in the honey bee gut. Z-score transformed ion intensities revealed that the ion annotated as pyruvate accumulated in bees mono-colonized with <i>G</i>. <i>apicola</i> but was depleted in hive bees, CL bees, and bees mono-colonized with <i>S</i>. <i>alvi</i> and Firm-5. (B) Growth improvement of <i>S</i>. <i>alvi</i> in <i>G</i>. <i>apicola-</i>conditioned medium. <i>S</i>. <i>alvi</i> was grown in pollen-conditioned medium in the presence (black line) or absence (dashed line) of <i>G</i>. <i>apicola</i> culture supernatant (50%, v/v). Growth was determined based on OD₆₀₀ at time points 0 h, 16 h, 36 h, and 72 h. n.s., not significant; * <i>P</i> < 0.05 (Welch’s <i>t</i> test, Benjamini and Hochberg adjusted [BH adj.]). (C) Six potentially cross-fed ions that accumulated during in vitro growth of <i>G</i>. <i>apicola</i> (left subpanel) and were consumed by <i>S</i>. <i>alvi</i> when it was grown in the presence <i>G</i>. <i>apicola</i> culture supernatant (right subpanel). Data from panels B and C come from the same experiment. Smoothed lines are added for interpretation purposes only in panel C and are dashed in the left subpanel because they are drawn through two points only. Error bars represent the standard deviation based on three replicate cultures. Chemical structures of the first annotation of each ion are shown. Asterisks indicate ions with ambiguous annotations. The numerical data of panel A can be retrieved from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s008" target="_blank">S8 Data</a>. All other values are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2003467#pbio.2003467.s001" target="_blank">S1 Data</a>.</p