Stochasticity in the enterococcal sex pheromone response revealed by quantitative analysis of transcription in single cells

<div><p>In <i>Enterococcus faecalis</i>, sex pheromone-mediated transfer of antibiotic resistance plasmids can occur under unfavorable conditions, for example, when inducing pheromone concentrations are low and inhibiting pheromone concentrations are high. To better understand this paradox, we adapted fluorescence <i>in situ</i> hybridization chain reaction (HCR) methodology for simultaneous quantification of multiple <i>E</i>. <i>faecalis</i> transcripts at the single cell level. We present direct evidence for variability in the minimum period, maximum response level, and duration of response of individual cells to a specific inducing condition. Tracking of induction patterns of single cells temporally using a fluorescent reporter supported HCR findings. It also revealed subpopulations of rapid responders, even under low inducing pheromone concentrations where the overall response of the entire population was slow. The strong, rapid induction of small numbers of cells in cultures exposed to low pheromone concentrations is in agreement with predictions of a stochastic model of the enterococcal pheromone response. The previously documented complex regulatory circuitry controlling the pheromone response likely contributes to stochastic variation in this system. In addition to increasing our basic understanding of the biology of a horizontal gene transfer system regulated by cell-cell signaling, demonstration of the stochastic nature of the pheromone response also impacts any future efforts to develop therapeutic agents targeting the system. Quantitative single cell analysis using HCR also has great potential to elucidate important bacterial regulatory mechanisms not previously amenable to study at the single cell level, and to accelerate the pace of functional genomic studies.</p></div

Visualization of pheromone induced and constitutive transcripts by fluorescence <i>in situ</i> hybridization chain reaction (HCR).

<p>Fluorescence images demonstrating simultaneous labeling of multiple transcripts in <i>E</i>. <i>faecalis</i> cells by fluorescence <i>in situ</i> hybridization chain reaction (HCR). Purple, <i>E</i>. <i>faecalis</i> cell envelope labeled with Alexa Fluor 647: wheat germ agglutinin (AF647: WGA) conjugate highlighting the outsides of individual cells. Blue, Hoechst 33342 DNA label also highlighting individual cells. Red, HCR labeled <i>ptsI</i> transcripts (Alexa Fluor 546). Green, HCR labeled <i>lacZ</i> transcripts (Alexa Fluor 488). <b>(A)</b> <i>E</i>. <i>faecalis</i> cells containing pBK2 30 minutes after addition of 10 ng ml^-1 <b><i>C</i></b>. Images are maximum intensity projections of Airyscan stacks and show z-axis projections. <b>(B)</b> <i>E</i>. <i>faecalis</i> cells containing pBK2 without addition of <b><i>C</i></b>. Images are a single z-plane of an Airyscan processed image. The punctate green HCR <i>lacZ</i> signal observed without addition of <b><i>C</i></b> is weak and much less intense than the signal observed after addition of <b><i>C</i></b>. This signal is visible in this figure due to intentional over exposure and the Min/Max brightness and contrast adjustment. Notably, these puncta are generally localized outside of cells and appear different than true signal observed with addition of <b><i>C</i></b> or the red HCR <i>ptsI</i> signal. See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006878#pgen.1006878.s004" target="_blank">S4 Fig</a> for further documentation. Scale bars, 5 μm.</p

Analysis of the induction response using either HCR or a GFP reporter demonstrates heterogeneity within responding populations over time.

<p><b>(A)</b> Time course showing <i>lacZ</i> expression in <i>E</i>. <i>faecalis</i> upon induction with 10 ng ml^-1 <b><i>C</i></b>. Times (left to right): 0, 15, 30, 60, and 120 minutes after <b><i>C</i></b> addition. Green, HCR labeled <i>lacZ</i> transcripts (pseudo colored Alexa Fluor 546). Blue, Hoechst 33342 DNA label highlighting individual cells. <b>(B)</b> Time course of GFP expression in <i>E</i>. <i>faecalis</i> upon induction with 5 ng ml^-1 <b><i>C</i></b>. Times (left to right): 70, 90, 110, 130, and 150 minutes after <b><i>C</i></b> addition. Green, GFP. Blue, Hoechst 33342. <b>(C)</b>, <b>(D)</b>, and <b>(E)</b>: 3D distributions reflecting the fraction of cells induced over time as measured by HCR, GFP expression, or predicted by the stochastic model respectively. Relative intensity or Q_L of induced cells was normalized to the threshold value and reflects varied levels of induction. <b>(C)</b>, Induction of <i>lacZ</i> RNA over time from pBK2 plasmid upon addition of 5 ng ml^-1 <b><i>C</i></b> in a <b><i>C</i></b>^{<b><i>-</i></b>} host as shown by relative HCR fluorescent intensity per cell. <b>(D)</b> Induction of fluorescent GFP over time from pCIE-GFP plasmid upon addition of 5 ng ml^-1 <b><i>C</i></b> in a <b><i>C</i></b>^{<b><i>-</i></b>} host as shown by relative fluorescent intensity per cell. <b>(E)</b> 3D distributions of the induced expression of the Q_L transcript upon addition of 5 ng ml^-1 <b><i>C</i></b> in a population of cells over time simulated using the stochastic mathematical model. The fraction induced reflects the proportion of cells with the depicted levels of Q_L out of the total cell population. Scale bars, 3.9 μm <b>(A)</b> and 20 μm <b>(B)</b>.</p

Model of induction of the pCF10 conjugative plasmid and reporter systems.

<p><b>(A)</b> The Q_L transcript from the pCF10 plasmid encodes the proteins that mediate conjugation and is induced upon signaling by <b><i>C</i></b> pheromone (green stars) from potential recipient cells. The <b><i>I</i></b> inhibitory peptide (red stars) counteracts <b><i>C</i></b> and is produced by plasmid-containing cells from a short transcript from the P_Q promoter (red). PrgX complexes (green circles) repress the P_Q promoter whereby PrgX-<b><i>C</i></b> complexes allow induction of Q_L transcription and PrgX or PrgX-<b><i>I</i></b> complexes inhibit transcription of Q_L. <b>(B)</b> The pBK2 and pCIE-GFP reporter plasmid constructs have the same P_Q/ Q_L regulatory region as pCF10. However, either <i>lacZ</i> for pBK2 or <i>gfp</i> for pCIE-GFP have been inserted in place of the conjugation genes.</p

Distribution of induction times for <i>E</i>. <i>faecalis</i> cells exposed to exogenous <i>C</i> and <i>I</i> show early responders in tested conditions by GFP and model analysis.

<p><b>(A)</b> Experimentally obtained time distributions showing the fraction of cells crossing the GFP induction threshold. The experiment in the far right panel mimics high donor density by the presence of a high concentration of <b><i>I</i></b> (50 ng ml^-1). <b>(B)</b> Predicted time distributions of the fraction of cells crossing the induction threshold determined by stochastic simulations. (<b>A</b>) and (<b>B</b>): Induction time refers to the time window during which an individual cell became induced and fraction induced refers to the fraction of cells that became induced in that time window. Black arrows indicate the time at which the first cell within the observed population became induced.</p

Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by <i>Saccharomyces cerevisiae</i>

<div><p>The inability of native <i>Saccharomyces cerevisiae</i> to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram <i>S</i>. <i>cerevisiae</i> to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved <i>S</i>. <i>cerevisiae</i> strains depends upon epistatic interactions among genes encoding a xylose reductase (<i>GRE3</i>), a component of MAP Kinase (MAPK) signaling (<i>HOG1</i>), a regulator of Protein Kinase A (PKA) signaling (<i>IRA2</i>), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (<i>ISU1</i>). Interestingly, the mutation in <i>IRA2</i> only impacted anaerobic xylose consumption and required the loss of <i>ISU1</i> function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in <i>HOG1</i> and <i>ISU1</i> unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.</p></div

Genetic differences between parental and evolved strains.

<p>Genetic differences between parental and evolved strains.</p

Genetic differences between parental and evolved strains.

<p>Genetic differences between parental and evolved strains.</p

Proposed model for how the evolved mutations impact biochemical pathways for xylose metabolism.

<p>Text, shapes and arrows in green signify upregulated activities compared to the activities in the parental strain (in black). Under aerobic or anaerobic conditions, the parent strain consumes low amounts of xylose due to insufficient biochemical activities (<b>A</b>). Under aerobic conditions, the evolved <i>hog1</i>^{<i>M282fs</i>} and <i>isu1</i>^<i>H138Y</i> mutations enhance activities (signified in green) of the pentose phosphate and lower glycolytic pathways, as well as respiration, thereby permitting significantly greater growth on and metabolism of xylose (<b>B</b>). Loss of <i>HOG1</i> function caused reduced expression of <i>GRE3</i> and other targets that impair xylose metabolism. Under anaerobic conditions (<b>C</b>), the evolved <i>ira2</i>^{<i>E2928Stop</i>} mutation causes activation of PKA, which in turn activates glycolytic enzymes. This, along with the disabling <i>gre3</i>^<i>A46T</i> mutation, enables the fermentation of xylose into ethanol.</p

Mutations in <i>ISU1</i> enhance respiration of xylose.

<p>Engineered and evolved strains were cultured in aerobic YPX media and analyzed for intracellular protein and metabolite concentrations. Average Log₂ intracellular concentrations of mitochondrial translation and respiration proteins (<b>A</b>) or hexose transporters and glucose-repressed proteins (<b>B</b>) from mutant strains relative to the Y22-3^MR parent are shown. White boxes indicate strains for which no corresponding peptides were detected. Relative protein concentrations were calculated from three independent biological replicates. Y22-3^MR <i>hog1Δ isu1Δ</i> strains were cultured in YP-Ethanol (<b>C</b>), YPD (<b>D</b>) or YPX (<b>E</b>) media and then treated with DMSO control or 0.5 μg/mL Antimycin A. Shaded areas represent the time during which DMSO or Antimycin A were present in the cultures. Average cell density, sugar and ethanol concentration with standard deviations from three independent biological replicates are reported.</p