17 research outputs found

    What makes the lac-pathway switch: identifying the fluctuations that trigger phenotype switching in gene regulatory systems

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    Multistable gene regulatory systems sustain different levels of gene expression under identical external conditions. Such multistability is used to encode phenotypic states in processes including nutrient uptake and persistence in bacteria, fate selection in viral infection, cell cycle control, and development. Stochastic switching between different phenotypes can occur as the result of random fluctuations in molecular copy numbers of mRNA and proteins arising in transcription, translation, transport, and binding. However, which component of a pathway triggers such a transition is generally not known. By linking single-cell experiments on the lactose-uptake pathway in E. coli to molecular simulations, we devise a general method to pinpoint the particular fluctuation driving phenotype switching and apply this method to the transition between the uninduced and induced states of the lac genes. We find that the transition to the induced state is not caused only by the single event of lac-repressor unbinding, but depends crucially on the time period over which the repressor remains unbound from the lac-operon. We confirm this notion in strains with a high expression level of the repressor (leading to shorter periods over which the lac-operon remains unbound), which show a reduced switching rate. Our techniques apply to multi-stable gene regulatory systems in general and allow to identify the molecular mechanisms behind stochastic transitions in gene regulatory circuits.Comment: Version

    Microscale insights into pneumococcal antibiotic mutant selection windows

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    The human pathogen Streptococcus pneumoniae shows alarming rates of antibiotic resistance emergence. The basic requirements for de novo resistance emergence are poorly understood in the pneumococcus. Here we systematically analyse the impact of antibiotics on S. pneumoniae at concentrations that inhibit wild type cells, that is, within the mutant selection window. We identify discrete growth-inhibition profiles for bacteriostatic and bactericidal compounds, providing a predictive framework for distinction between the two classifications. Cells treated with bacteriostatic agents show continued gene expression activity, and real-time mutation assays link this activity to the development of genotypic resistance. Time-lapse microscopy reveals that antibiotic-susceptible pneumococci display remarkable growth and death bistability patterns in response to many antibiotics. We furthermore capture the rise of subpopulations with decreased susceptibility towards cell wall synthesis inhibitors (heteroresisters). We show that this phenomenon is epigenetically inherited, and that heteroresistance potentiates the accumulation of genotypic resistance

    Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

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    Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.</p

    High-throughput CRISPRi phenotyping identifies new essential genes in Streptococcus pneumoniae.

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    Genome-wide screens have discovered a large set of essential genes in the opportunistic human pathogen &lt;i&gt;Streptococcus pneumoniae&lt;/i&gt; However, the functions of many essential genes are still unknown, hampering vaccine development and drug discovery. Based on results from transposon sequencing (Tn-seq), we refined the list of essential genes in &lt;i&gt;S. pneumoniae&lt;/i&gt; serotype 2 strain D39. Next, we created a knockdown library targeting 348 potentially essential genes by CRISPR interference (CRISPRi) and show a growth phenotype for 254 of them (73%). Using high-content microscopy screening, we searched for essential genes of unknown function with clear phenotypes in cell morphology upon CRISPRi-based depletion. We show that SPD_1416 and SPD_1417 (renamed to MurT and GatD, respectively) are essential for peptidoglycan synthesis, and that SPD_1198 and SPD_1197 (renamed to TarP and TarQ, respectively) are responsible for the polymerization of teichoic acid (TA) precursors. This knowledge enabled us to reconstruct the unique pneumococcal TA biosynthetic pathway. CRISPRi was also employed to unravel the role of the essential Clp-proteolytic system in regulation of competence development, and we show that ClpX is the essential ATPase responsible for ClpP-dependent repression of competence. The CRISPRi library provides a valuable tool for characterization of pneumococcal genes and pathways and revealed several promising antibiotic targets

    Functionality of a next generation biosynthetic bacterial 6-phytase in enhancing phosphorus availability to weaned piglets fed a corn-soybean meal-based diet without added inorganic phosphate

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    The utility of a next generation biosynthetic bacterial 6-phytase (PhyG) in restoring bone ash, bone phosphorus (P) content and performance in piglets depleted in P was evaluated. A total of 9 treatments were tested as follows. Treatment 1, a negative control (NC) diet; treatments 2, 3, 4, NC supplemented with 250, 500 or 1,000 FTU/kg of PhyG; treatments 5, 6, NC supplemented with 500 or 1,000 FTU/kg of a commercial Buttiauxella sp phytase (PhyB); treatments 7, 8, 9, NC supplemented with monocalcium phosphate (MCP) to provide 0.7, 1.4 and 1.8 g/kg digestible P, equating to a digestible P content of 1.8, 2.5 and 2.9 g/kg. The latter constituting the positive control (PC) diet with adequate P and calcium (Ca). The NC was formulated without inorganic P (1.1 g digestible P/kg) and reduced in Ca (5.0 g/kg). Additional limestone was added to treatments 7 to 9 to maintain Ca-to-P ratio between 1.2 and 1.3. A total of 162 crossed Pietrain × (Large White × Landrace) 21-d-old piglets (50% males and 50% females) were fed adaptation diets until 42 d old and then assigned to pens with 2 pigs/pen and 9 pens/treatment in a completely randomized block design. Piglets were fed mash diets based on corn and soybean meal ad libitum for 28 d. At the end of the study, one piglet perpen was euthanized and the right feet collected for determination of bone strength, bone ash and mineral content. Compared with the PC, the NC group had reduced average daily gain (ADG) and increased feed conversion ratio (FCR) during all growth phases and overall, and at d 28 (70 d old) NC pigs had bones with reduced ash, Ca and P content (P < 0.05). The PhyG at 250 FTU/kg improved bone ash vs. NC. Increasing PhyG dose linearly or quadratically improved bone ash, ADG and FCR (P < 0.05). At ≥ 500 FTU/kg, both PhyG and PhyB maintained ADG and FCR equivalent to PC. Linear regression analysis was done to compare the measured response parameters to increasing digestible P from MCP. Based on this analysis it was shown that PhyG and PhyB at 1,000 FTU/kg could replace 1.83 and 1.66 g/kg digestible P from MCP in the diet, respectively, on average across metacarpi bone ash, ADG or FCR. These findings suggest that the biosynthetic phytase is highly effective in the tested dietary setting.info:eu-repo/semantics/publishedVersio

    Gene Expression Platform for Synthetic Biology in the Human Pathogen Streptococcus pneumoniae

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    The human pathogen Streptococcus pneumoniae (pneumococcus) is a bacterium that owes its success to complex gene expression regulation patterns on both the cellular and the population level. Expression of virulence factors enables a mostly hazard-free presence of the commensal, in balance with the host and niche competitors. Under specific circumstances, changes in this expression can result in a more aggressive behavior and the reversion to the invasive form as pathogen. These triggering conditions are very difficult to study due to the fact that environmental cues are often unknown or barely possible to simulate outside the host (in vitro). An alternative way of investigating expression patterns is found in synthetic biology approaches of reconstructing regulatory networks that mimic an observed behavior with orthogonal components. Here, we created a genetic platform suitable for synthetic biology approaches in S. pneumoniae and characterized a set of standardized promoters and reporters. We show that our system allows for fast and easy cloning with the BglBrick system and that reliable and robust gene expression after integration into the S. pneumoniae genome is achieved. In addition, the cloning system was extended to allow for direct linker-based assembly of ribosome binding sites, peptide tags, and fusion proteins, and we called this new generally applicable standard "BglFusion". The gene expression platform and the methods described in this study pave the way for employing synthetic biology approaches in S. pneumoniae

    Switching off: the phenotypic transition to the uninduced state of the lactose uptake pathway

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    The lactose uptake-pathway of E. coli is a paradigmatic example of multistability in gene-regulatory circuits. In the induced state of the lac-pathway, the genes comprising the lac-operon are transcribed, leading to the production of proteins which import and metabolize lactose. In the uninduced state, a stable repressor-DNA loop frequently blocks the transcription of the lac-genes. Transitions from one phenotypic state to the other are driven by fluctuations, which arise from the random timing of the binding of ligands and proteins. This stochasticity affects transcription and translation, and ultimately molecular copy numbers. Our aim is to understand the transition from the induced to the uninduced state of the lac-operon. We use a detailed computational model to show that repressor-operator binding/unbinding, fluctuations in the total number of repressors, and inducer-repressor binding/unbinding all play a role in this transition. Based on the timescales on which these processes operate, we construct a minimal model of the transition to the uninduced state and compare the results with simulations and experimental observations. The induced state turns out to be very stable, with a transition rate to the uninduced state lower than 2×1092 \times 10^{-9} per minute. In contrast to the transition to the induced state, the transition to the uninduced state is well described in terms of a 2D diffusive system crossing a barrier, with the diffusion rates emerging from a model of repressor unbinding.Comment: 10 pages, 6 figures. For SI contact corresponding autho

    Population dynamics of bacterial communities.

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    <p>(<b>a</b>) Simulated growth trajectories for Cm<sup>R</sup> and Cm<sup>S</sup> populations subject to antibiotic stress and resource competition. (<b>b</b>) Dynamic of intracellular Cm (<i>y</i><sub>r</sub> and <i>y</i><sub>s</sub>) and growth-limiting resource (<i>z</i>). Simulation time is scaled relative to the mean residence time of cells in a chemostat, which is equal to the generation time at steady state. At low population densities, the Cm<sup>R</sup> strain can grow, whereas Cm<sup>S</sup> cannot, due to a high concentration of Cm. However, the invasion of Cm<sup>R</sup> lowers antibiotic stress, generating permissive conditions for the growth of Cm<sup>S</sup> cells. The chemostat is then rapidly colonized by both strains (shortly after <i>t</i> = 180) until the resource becomes limiting. From that moment onwards, total cell density changes little, while the relative frequencies of the two strains continue to shift. Eventually, a stable equilibrium is reached, at which the cost and benefit of CAT expression (i.e., reduced growth rate efficiency for Cm<sup>R</sup> cells versus their lower intracellular Cm concentration) balance out. Inset (<b>c</b>), The dark-red dot pinpoints the parameter set used in the simulation shown in <b>a</b> and <b>b</b>: <i>r</i> = 20.0, <i>η</i> = 0.9, <i>k</i><sub>z</sub> = 4.0, <i>c</i> = 1.0, <i>p</i> = 50.0, <i>h</i><sub>Y</sub> = 0.25/<i>Y</i><sub>0</sub>, <i>k</i><sub>Y</sub> = 2.5/<i>Y</i><sub>0</sub>, <i>d</i> = 30.0/<i>Y</i><sub>0</sub> and <i>Y</i><sub>0</sub> = 0.8. These parameters were selected to lie in a restricted area of parameter space (highlighted in red) where stable coexistence between Cm<sup>S</sup> and Cm<sup>R</sup> cells is observed Alternative model outcomes, which were identified by a numerical bifurcation analysis (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s007" target="_blank">S1 Text</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s004" target="_blank">S4 Fig</a>), include establishment of Cm<sup>S</sup> only (area S), establishment of Cm<sup>R</sup> only (area R), no bacterial growth (area N), and competition-induced extinction (area E, where Cm<sup>S</sup> bacteria first outcompete Cm<sup>R</sup> bacteria and subsequently are cleared by the antibiotic; see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s005" target="_blank">S5 Fig</a>).</p

    Experimental setup to determine passive resistance.

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    <p>Antibiotic-susceptible cells (Ab<sup>S</sup>) constitutively expressing <i>luc</i> are grown together with antibiotic-resistant cells (Ab<sup>R</sup>, which do not express <i>luc</i>). Only when the concentration of the antibiotic in the medium is reduced by enzymatic deactivation of resistant cells will the genetically antibiotic-susceptible cells be able to grow and produce light.</p

    Cross-protection in a mouse pneumonia model.

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    <p>(<b>a</b>) Eight-wk-old female CD1 mice were infected intratracheally with Cm<sup>S</sup> pneumococci or an equivalent amount of Cm<sup>S</sup> + Cm<sup>R</sup> pneumococci in a one-to-one ratio. One h post infection, mice were treated with one intraperitoneal injection of Cm 75 mg kg<sup>−1</sup> followed by two additional doses spaced 5 h apart. Control mice received an injection of the vehicle alone. <i>n</i> = 14 for Cm<sup>S</sup> control; 13 for Cm<sup>S</sup> Cm-treated; 13 for Cm<sup>S</sup> + Cm<sup>R</sup> control; and 14 for Cm<sup>S</sup> + Cm<sup>R</sup> Cm-treated. Data plotted as average and s.e.m. of two independent experiments combined. Dashed line ‘inoc’ denotes the initial inoculum. <i>*p < 0</i>.<i>05</i>; one-way ANOVA with Tukey's multiple comparison post-test. (<b>b</b>) Bacterial colonies recovered from the Cm<sup>S</sup> + Cm<sup>R</sup> control and Cm<sup>S</sup> + Cm<sup>R</sup> Cm-treated mice were individually picked and used to inoculate THY media in 96-well plates. These 96-well plates were then used to inoculate 96-well plates with THY media containing either 15 μg ml<sup>−1</sup> Cm or 100 μg ml<sup>−1</sup> kanamycin to determine whether or not the original bacterial colony was Cm<sup>S</sup> or Cm<sup>R</sup>. n = 9 for Cm<sup>S</sup> + Cm<sup>R</sup> control and 14 for Cm<sup>S</sup> + Cm<sup>R</sup> Cm-treated. Data plotted as average and s.e.m. of two independent experiments combined. <i>*p</i> = 0.04; Mann–Whitney <i>U</i> test (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s008" target="_blank">S1 Data</a>).</p
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