qRT-PCR based verification of putative EcpR1 target genes displaying changes in transcript levels upon overproduction of EcpR1 as detected by global transcriptome profiling.

<p>Log₂ change in transcript amount normalized to levels of the SMc01852 mRNA. Errors represent the standard deviation of three replicates. Positions of microarray reporter oligonucleotides relative to the start codon are given in brackets for 5’-UTR regions.</p><p>*Description of gene product or associated gene product.</p><p>qRT-PCR based verification of putative EcpR1 target genes displaying changes in transcript levels upon overproduction of EcpR1 as detected by global transcriptome profiling.</p

A Stress-Induced Small RNA Modulates Alpha-Rhizobial Cell Cycle Progression

<div><p>Mechanisms adjusting replication initiation and cell cycle progression in response to environmental conditions are crucial for microbial survival. Functional characterization of the <i>trans</i>-encoded small non-coding RNA (<i>trans</i>-sRNA) EcpR1 in the plant-symbiotic alpha-proteobacterium <i>Sinorhizobium meliloti</i> revealed a role of this class of riboregulators in modulation of cell cycle regulation. EcpR1 is broadly conserved in at least five families of the Rhizobiales and is predicted to form a stable structure with two defined stem-loop domains. In <i>S</i>. <i>meliloti</i>, this <i>trans</i>-sRNA is encoded downstream of the <i>divK-pleD</i> operon. <i>ecpR1</i> belongs to the stringent response regulon, and its expression was induced by various stress factors and in stationary phase. Induced EcpR1 overproduction led to cell elongation and increased DNA content, while deletion of <i>ecpR1</i> resulted in reduced competitiveness. Computationally predicted EcpR1 targets were enriched with cell cycle-related mRNAs. Post-transcriptional repression of the cell cycle key regulatory genes <i>gcrA</i> and <i>dnaA</i> mediated by mRNA base-pairing with the strongly conserved loop 1 of EcpR1 was experimentally confirmed by two-plasmid differential gene expression assays and compensatory changes in sRNA and mRNA. Evidence is presented for EcpR1 promoting RNase E-dependent degradation of the <i>dnaA</i> mRNA. We propose that EcpR1 contributes to modulation of cell cycle regulation under detrimental conditions.</p></div

Elongated cell phenotype induced by <i>ecpR1</i> overexpression.

<p><b>(A)</b> Northern blot detection of EcpR1 RNA variants in Rm4011 strains carrying either pSKControl⁺ (Control⁺), pSKEcpR1⁺ (EcpR1⁺), or pSKEcpR1-2⁺ (EcpR1-2⁺) 4 hours after induction with IPTG. Below, relative hybridization signals derived from the 101 nt EcpR1 species are plotted. The wild type level of EcpR1 in Control⁺ cells (OD₆₀₀ of ~0.9) has been normalized to 1 (dashed line) and the sRNA levels in other conditions are correlated to that value. Mean results from three experiments are shown. Error bars indicate the standard deviation. <b>(B)</b> Cell morphology, <b>(C)</b> motility assay, <b>(D)</b> cell length, and <b>(E)</b> DNA content of <i>S</i>. <i>meliloti</i> strains overexpressing <i>ecpR1</i> or the SmelC812 control antisense RNA gene. The 2011<i>visN</i> mutant was used as negative control for swimming motility. 1C and 2C indicate one and two genome equivalents, respectively. Bars correspond to 2 μm in <i>B</i> and 5 mm in <i>C</i>. Error bars in <i>D</i> represent standard errors (n = 100 cells).</p

Hfq and RNase E activities are dispensable for EcpR1 overproduction-related cell elongation and post-transcriptional repression of <i>gcrA</i>.

<p><b>(A)</b> Northern blot analysis of EcpR1 stability in Rm2011 and <i>hfq</i> mutant strains grown to early stationary phase (OD₆₀₀ of 1.2, t = 0) and upon transcription arrest with Rf at indicated time points (in min). <b>(B)</b> Cell morphology of 2011<i>hfq</i> and 2011<i>rne</i>::<i>Tn5</i> mutants overexpressing either <i>ecpR1</i> (EcpR1⁺) or the control RNA gene SmelC812 (Control⁺) upon IPTG induction. Bars represent 2 μm. <b>(C)</b> Percentage of fluorescence in EcpR1 overproduction strains relative to the respective control strain overproducing SmelC812 in the Rm4011<i>ecpR1</i> or Rm4011<i>ecpR1 rne675</i> background co-transformed with plasmids carrying p<i>PgcrA-gcrA-egfp</i> or p<i>dnaA-154+162-egfp</i> translational fusions. <b>(D)</b> qRT-PCR analysis of <i>gcrA</i> and <i>dnaA</i> transcript abundance in Rm4011<i>ecpR1</i> EcpR1⁺ after transcription arrest with Rifampicin for 5 minutes. Values were normalized to the SMc01852 transcript and the levels in the IPTG induced control strain overexpressing the SmelC812 RNA gene. Results from three independent experiments are shown. Error bars indicate the standard deviation.</p

<i>ecpR1</i> genomic locus and transcriptional regulation.

<p><b>(A)</b> Secondary structure of the dominant EcpR1 101 nt variant with a minimum free energy of -50.20 kcal/mol. Nucleotide positions relative to the second 5’-end are denoted. SL, stem loop domain. The 13 nt region predicted to bind the <i>gcrA</i> mRNA is boxed. Below, chromosomal region including the <i>ecpR1</i> gene and RNAseq coverage profile of the EcpR1 sRNA in <i>S</i>. <i>meliloti</i> Rm1021. Genome coordinates of the full length <i>ecpR1</i> variant are denoted. Black and grey areas represent coverages from samples enriched for processed and primary transcripts, respectively [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005153#pgen.1005153.ref021" target="_blank">21</a>]. Detected EcpR1 5’-ends are depicted by arrows and the dominant 101 nt EcpR1 variant used for structure prediction is marked by the bar. <b>(B)</b> Schematic representation of the fragments included in the <i>ecpR1</i> transcriptional fusions and fluorescence values of stationary phase Rm2011 wild type and derivative cells harbouring the indicated constructs: 5’1, pP<i>ecpR1</i>_5’1; 5’2, pP<i>ecpR1</i>_5’2; 5’2-Pσ70, pP<i>ecpR1</i>_5’2-Pσ70; 5’1–204, pP<i>ecpR1</i>_5’1–204. Specific activities were normalized to OD₆₀₀ to yield fluorescence units per unit of optical density (F/OD). Shown are means and standard deviation values of at least three independent measurements of three transconjugants grown in six independent cultures. <b>(C)</b> qRT-PCR analysis and Northern blot detection of EcpR1 transcript abundance in Rm2011 and the <i>relA</i> mutant under different growth and stress conditions in TY (left) and MOPS minimal and MOPSlim medium (MM, right). 40°C, heat stress; NaCl, 0.4 mM sodium chloride (osmotic stress); H₂O₂, 10mM hydrogen peroxide (oxidative stress); -O₂, microoxic conditions; 20°C, cold stress; -C and -N, growth in MM until OD₆₀₀ of 0.9 and then MM depleted for 1 hour for carbon or nitrogen. qRT-PCR values were normalized to the SMc01852 transcript and the levels of EcpR1 in Rm2011 growing in TY rich medium at OD₆₀₀ of 0.6 (left) or MOPS minimal medium at OD₆₀₀ of 0.9 (right, dashed line). Plots underneath the Northern blots represent relative hybridization signal intensities. The basal level of EcpR1 in Rm2011 growing in TY rich medium at OD₆₀₀ of 0.6 or MOPS minimal medium at OD₆₀₀ of 0.9 (right) has been normalized to 1 (dashed line) and the sRNA levels in other conditions have been correlated to this value. Mean results from three experiments are shown. Error bars indicate the standard deviation. Exposure times were optimized for each panel.</p

qRT-PCR based verification of putative EcpR1 target genes displaying expression changes in 2011<i>ecpR1</i> vs. Rm2011 wild type growing in MOPS or MOPSlim media.

<p>Log₂ change in transcript amount normalized to levels of the SMc01852 mRNA. Errors represent the standard deviation of three replicates. Positions of microarray reporter oligonucleotides relative to the start codon are given in brackets for 5’-UTR regions.</p><p>*Description of gene product or associated gene product.</p><p>qRT-PCR based verification of putative EcpR1 target genes displaying expression changes in 2011<i>ecpR1</i> vs. Rm2011 wild type growing in MOPS or MOPSlim media.</p

Lack of <i>ecpR1</i> reduces competitiveness of Rm2011.

<p>Mean percentage of <i>egfp</i>-labeled cells 1 and 4 weeks after mixing 2011<i>mCherry</i> with either 2011<i>egfp</i> or 2011<i>ecpR1 egfp</i> cells at a 1:1 ratio in MOPS (A) or MOPSlim media (B). Every week the mixed population was diluted 1000-fold in fresh media. The percentage of <i>egfp</i>-labeled cells was determined by microscopy. Error bars indicate the standard deviation of 3 biological replicates.</p

EcpR1 post-transcriptionally represses <i>gcrA</i> (A) and <i>dnaA</i> (B).

<p>Schematic representations of the genomic regions and the fragments (indicated by bars) translationally fused to <i>egfp</i>. Positions are denoted relative to the AUG; A is +1. Grey boxes indicate potential EcpR1-binding sites. Vertical arrows mark the regions covered by the oligonucleotide probes displaying altered signal intensities in the microarray hybridizations after <i>ecpR1</i> overexpression (see details in text). Means of relative fluorescence intensity values of Rm4011<i>ecpR1</i> co-transformed with the <i>ecpR1</i> or control SmelC812 overexpression plasmid, and the indicated reporter plasmid are shown below. The standard deviation represents at least three independent determinations of three double transconjugants grown in six independent cultures. Specific activities were normalized to the levels of the strain carrying the vector with the control RNA gene without IPTG added to yield percent relative fluorescence (% F).</p

presentation_1.pdf

<p>Time-lapse imaging of cell colonies in microfluidic chambers provides time series of bioimages, i.e., biomovies. They show the behavior of cells over time under controlled conditions. One of the main remaining bottlenecks in this area of research is the analysis of experimental data and the extraction of cell growth characteristics, such as lineage information. The extraction of the cell line by human observers is time-consuming and error-prone. Previously proposed methods often fail because of their reliance on the accurate detection of a single cell, which is not possible for high density, high diversity of cell shapes and numbers, and high-resolution images with high noise. Our task is to characterize subpopulations in biomovies. In order to shift the analysis of the data from individual cell level to cellular groups with similar fluorescence or even subpopulations, we propose to represent the cells by two new abstractions: the particle and the patch. We use a three-step framework: preprocessing, particle tracking, and construction of the patch lineage. First, preprocessing improves the signal-to-noise ratio and spatially aligns the biomovie frames. Second, cell sampling is performed by assuming particles, which represent a part of a cell, cell or group of contiguous cells in space. Particle analysis includes the following: particle tracking, trajectory linking, filtering, and color information, respectively. Particle tracking consists of following the spatiotemporal position of a particle and gives rise to coherent particle trajectories over time. Typical tracking problems may occur (e.g., appearance or disappearance of cells, spurious artifacts). They are effectively processed using trajectory linking and filtering. Third, the construction of the patch lineage consists in joining particle trajectories that share common attributes (i.e., proximity and fluorescence intensity) and feature common ancestry. This step is based on patch finding, patching trajectory propagation, patch splitting, and patch merging. The main idea is to group together the trajectories of particles in order to gain spatial coherence. The final result of CYCASP is the complete graph of the patch lineage. Finally, the graph encodes the temporal and spatial coherence of the development of cellular colonies. We present results showing a computation time of less than 5 min for biomovies and simulated films. The method, presented here, allowed for the separation of colonies into subpopulations and allowed us to interpret the growth of colonies in a timely manner.</p

Small RNA sX13: A Multifaceted Regulator of Virulence in the Plant Pathogen <i>Xanthomonas</i>

<div><p>Small noncoding RNAs (sRNAs) are ubiquitous posttranscriptional regulators of gene expression. Using the model plant-pathogenic bacterium <i>Xanthomonas campestris</i> pv. <i>vesicatoria</i> (<i>Xcv</i>), we investigated the highly expressed and conserved sRNA sX13 in detail. Deletion of <i>sX13</i> impinged on <i>Xcv</i> virulence and the expression of genes encoding components and substrates of the Hrp type III secretion (T3S) system. qRT-PCR analyses revealed that sX13 promotes mRNA accumulation of HrpX, a key regulator of the T3S system, whereas the mRNA level of the master regulator HrpG was unaffected. Complementation studies suggest that sX13 acts upstream of HrpG. Microarray analyses identified 63 sX13-regulated genes, which are involved in signal transduction, motility, transcriptional and posttranscriptional regulation and virulence. Structure analyses of <i>in vitro</i> transcribed sX13 revealed a structure with three stable stems and three apical C-rich loops. A computational search for putative regulatory motifs revealed that sX13-repressed mRNAs predominantly harbor G-rich motifs in proximity of translation start sites. Mutation of sX13 loops differentially affected <i>Xcv</i> virulence and the mRNA abundance of putative targets. Using a GFP-based reporter system, we demonstrated that sX13-mediated repression of protein synthesis requires both the C-rich motifs in sX13 and G-rich motifs in potential target mRNAs. Although the RNA-binding protein Hfq was dispensable for sX13 activity, the <i>hfq</i> mRNA and Hfq::GFP abundance were negatively regulated by sX13. In addition, we found that G-rich motifs in sX13-repressed mRNAs can serve as translational enhancers and are located at the ribosome-binding site in 5% of all protein-coding <i>Xcv</i> genes. Our study revealed that sX13 represents a novel class of virulence regulators and provides insights into sRNA-mediated modulation of adaptive processes in the plant pathogen <i>Xanthomonas</i>.</p></div