Article

Quantifying the Integration of Quorum-Sensing Signals with Single-Cell Resolution

Department of Physics, Princeton University, Princeton, NJ, USA.
PLoS Biology (Impact Factor: 9.34). 04/2009; 7(3):e68. DOI: 10.1371/journal.pbio.1000068
Source: PubMed

ABSTRACT

Author Summary

Although bacteria are unicellular, the individual cells communicate with each other via small diffusible molecules. This communication process, known as quorum sensing, allows groups of bacteria to track the density of the population they are in, synchronize gene expression across the population, and thereby carry out collective activities similar to those of cells in multi-cellular organisms. Many bacterial species use multiple signaling molecules, but it remains a mystery why multiple signals are required and how the information encoded in them is integrated by bacteria. To explore these questions, we studied a model quorum-sensing bacterium Vibrio harveyi. Using single-cell fluorescence microscopy, we quantified quorum-sensing responses and analyzed the mechanism of integration of multiple signals. Surprisingly, we found that information from two distinct signals is combined strictly additively, with precisely equal weight from each signal. Our results revealed a coherent response across the population with little cell-to-cell variation, allowing the entire population of bacterial cells to reliably distinguish multiple environmental states. We argue that multiple signals and multiple response states could be used to distinguish distinct stages in the development of a bacterial community.

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    • "It indicates that s 2 p =hpi 2 is approximately constant after reaching about one third of the maximal expression, i.e. from this point on the standard deviation increases proportional to the mean. The obtained CV % 0.17 is about half of that obtained previously for V. harveyi autoinducer reporter systems[25]. The scaling of the fractional noise with the mean is often used to distinguish between intrinsic and extrinsic noise contributions. "
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    ABSTRACT: Monitoring gene expression dynamics on the single cell level provides important information on cellular heterogeneity and stochasticity, and potentially allows for more accurate quantitation of gene expression processes. We here study bacterial senders and receivers genetically engineered with components of the quorum sensing system derived from Aliivibrio fischeri on the single cell level using microfluidics-based bacterial chemostats and fluorescence video microscopy. We track large numbers of bacteria over extended periods of time, which allows us to determine bacterial lineages and filter out subpopulations within a heterogeneous population. We quantitatively determine the dynamic gene expression response of receiver bacteria to varying amounts of the quorum sensing inducer N-3-oxo-C6-homoserine lactone (AHL). From this we construct AHL response curves and characterize gene expression dynamics of whole bacterial populations by investigating the statistical distribution of gene expression activity over time. The bacteria are found to display heterogeneous induction behavior within the population. We therefore also characterize gene expression in a homogeneous bacterial subpopulation by focusing on single cell trajectories derived only from bacteria with similar induction behavior. The response at the single cell level is found to be more cooperative than that obtained for the heterogeneous total population. For the analysis of systems containing both AHL senders and receiver cells, we utilize the receiver cells as 'bacterial sensors' for AHL. Based on a simple gene expression model and the response curves obtained in receiver-only experiments, the effective AHL concentration established by the senders and their 'sending power' is determined.
    Full-text · Article · Jan 2016 · PLoS ONE
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    • "Detection of AI-2 Activity AI-2 activity was measured as previously described (Taga and Xavier, 2011) using the V. harveyi AI-2 reporter strain TL26 (DluxN DluxS DcqsS; Long et al., 2009). To determine AI-2 activity in mouse cecal extracts, the cecal contents were homogenized at a 10% weight/volume concentration in 0.1 M MOPS (pH 7). "
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    ABSTRACT: The mammalian gut microbiota harbors a diverse ecosystem where hundreds of bacterial species interact with each other and their host. Given that bacteria use signals to communicate and regulate group behaviors (quorum sensing), we asked whether such communication between different commensal species can influence the interactions occurring in this environment. We engineered the enteric bacterium, Escherichia coli, to manipulate the levels of the interspecies quorum sensing signal, autoinducer-2 (AI-2), in the mouse intestine and investigated the effect upon antibiotic-induced gut microbiota dysbiosis. E. coli that increased intestinal AI-2 levels altered the composition of the antibiotic-treated gut microbiota, favoring the expansion of the Firmicutes phylum. This significantly increased the Firmicutes/Bacteroidetes ratio, to oppose the strong effect of the antibiotic, which had almost cleared the Firmicutes. This demonstrates that AI-2 levels influence the abundance of the major phyla of the gut microbiota, the balance of which is known to influence human health. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Preview · Article · Mar 2015 · Cell Reports
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    • "To test the predictions of the model, we constructed three V. harveyi strains that report on target mRNA levels by integrating a luxR, a luxM, or a luxO 5 0 UTR translational GFP fusion under a constitutive promoter onto the chromosome. We used mCherry oriented in the opposite direction to normalize for cellular protein (Long et al., 2009). We measured GFP and mCherry fluorescence after we induced Qrr production by adding a quorum-sensing antagonist (see Experimental Procedures) (Shao et al., 2013). "
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    ABSTRACT: Quorum sensing is a cell-cell communication process that bacteria use to transition between individual and social lifestyles. In vibrios, homologous small RNAs called the Qrr sRNAs function at the center of quorum-sensing pathways. The Qrr sRNAs regulate multiple mRNA targets including those encoding the quorum-sensing regulatory components luxR, luxO, luxM, and aphA. We show that a representative Qrr, Qrr3, uses four distinct mechanisms to control its particular targets: the Qrr3 sRNA represses luxR through catalytic degradation, represses luxM through coupled degradation, represses luxO through sequestration, and activates aphA by revealing the ribosome binding site while the sRNA itself is degraded. Qrr3 forms different base-pairing interactions with each mRNA target, and the particular pairing strategy determines which regulatory mechanism occurs. Combined mathematical modeling and experiments show that the specific Qrr regulatory mechanism employed governs the potency, dynamics, and competition of target mRNA regulation, which in turn, defines the overall quorum-sensing response. Copyright © 2015 Elsevier Inc. All rights reserved.
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