Optimal census by quorum sensing

Experience-dependent modulation of collective behavior in larval zebrafish

Complex group behavior can emerge from simple inter-individual interactions. Commonly, these interactions are considered static and hardwired and little is known about how experience and learning affect collective group behavior. Young larvae use well described visuomotor transformations to guide interindividual interactions and collective group structure. Here, we use naturalistic and virtual-reality (VR) experiments to impose persistent changes in population density and measure their effects on future visually evoked turning behavior and the resulting changes in group structure. We find that neighbor distances decrease after exposure to higher population densities, and increase after the experience of lower densities. These adaptations develop slowly and gradually, over tens of minutes and remain stable over many hours. Mechanistically, we find that larvae estimate their current group density by tracking the frequency of neighbor-evoked looming events on the retina and couple the strength of their future interactions to that estimate. A time-varying state-space model that modulates agents' social interactions based on their previous visual-social experiences, accurately describes our behavioral observations and predicts novel aspects of behavior. These findings provide concrete evidence that inter-individual interactions are not static, but rather continuously evolve based on past experience and current environmental demands. The underlying neurobiological mechanisms of experience dependent modulation can now be explored in this small and transparent model organism.

Maximal information transmission is compatible with ultrasensitive biological pathways

Cells are often considered input-output devices that maximize the transmission of information by converting extracellular stimuli (input) via signaling pathways (communication channel) to cell behavior (output). However, in biological systems outputs might feed back into inputs due to cell motility, and the biological channel can change by mutations during evolution. Here, we show that the conventional channel capacity obtained by optimizing the input distribution for a fixed channel may not reflect the global optimum. In a new approach we analytically identify both input distributions and input-output curves that optimally transmit information, given constraints from noise and the dynamic range of the channel. We find a universal optimal input distribution only depending on the input noise, and we generalize our formalism to multiple outputs (or inputs). Applying our formalism to Escherichia coli chemotaxis, we find that its pathway is compatible with optimal information transmission despite the ultrasensitive rotary motors.

Negative feedback increases information transmission, enabling bacteria to discriminate sublethal antibiotic concentrations

In the cell, noise constrains information transmission through signaling pathways and regulatory networks. There is growing evidence that the channel capacity of cellular pathways is limited to a few bits, questioning whether cells quantify external stimuli or rely on threshold detection and binary on/off decisions. Here, using fluorescence microscopy and information theory, we analyzed the ability of the transcriptional regulator TetR to sense and quantify the antibiotic tetracycline. The results showed that noise filtering by negative feedback increased information transmission up to 2 bits, generating a graded response able to discriminate different antibiotic concentrations. This response matched the antibiotic subinhibitory selection window, suggesting that information transmission through TetR is optimized to quantify sublethal antibiotic levels. Noise filtering by negative feedback may thus boost the discriminative power of cellular sensors, enabling signal quantification.

Small RNA-Based Regulation of Bacterial Quorum Sensing and Biofilm Formation

Quorum sensing is a vital property of bacteria that enables community-wide coordination of collective behaviors. A key example of such a behavior is biofilm formation, in which groups of bacteria invest in synthesizing a protective, joint extracellular matrix. Quorum sensing involves the production, release, and subsequent detection of extracellular signaling molecules called autoinducers. The architecture of quorum-sensing signal transduction pathways is highly variable among different species of bacteria, but frequently involves posttranscriptional regulation carried out by small regulatory RNA molecules. This review illustrates the diverse roles small trans-acting regulatory RNAs can play, from constituting a network's core to auxiliary roles in adjusting the rate of autoinducer synthesis, mediating cross talk among different parts of a network, or integrating different regulatory inputs to trigger appropriate changes in gene expression. The emphasis is on describing how the study of small RNA-based regulation in quorum sensing and biofilm formation has uncovered new general properties or expanded our understanding of bacterial riboregulation.

Positive Autoregulation of an Acyl-Homoserine Lactone Quorum-Sensing Circuit Synchronizes the Population Response

Many proteobacteria utilize acyl-homoserine lactone quorum-sensing signals. At low population densities, cells produce a basal level of signal, and when sufficient signal has accumulated in the surrounding environment, it binds to its receptor, and quorum-sensing-dependent genes can be activated. A common characteristic of acyl-homoserine lactone quorum sensing is that signal production is positively autoregulated. We have examined the role of positive signal autoregulation in Pseudomonas aeruginosa. We compared population responses and individual cell responses in populations of wild-type P. aeruginosa to responses in a strain with the signal synthase gene controlled by an arabinose-inducible promoter so that signal was produced at a constant rate per cell regardless of cell population density. At a population level, responses of the wild type and the engineered strain were indistinguishable, but the responses of individual cells in a population of the wild type showed greater synchrony than the responses of the engineered strain. Although sufficient signal is required to activate expression of quorum-sensing-regulated genes, it is not sufficient for activation of certain genes, the late genes, and their expression is delayed until other conditions are met. We found that late gene responses were reduced in the engineered strain. We conclude that positive signal autoregulation is not a required element in acyl-homoserine lactone quorum sensing, but it functions to enhance synchrony of the responses of individuals in a population. Synchrony might be advantageous in some situations, whereas a less coordinated quorum-sensing response might allow bet hedging and be advantageous in other situations.

There are many quorum-sensing systems that involve a transcriptional activator, which responds to an acyl-homoserine lactone signal. In all of the examples studied, the gene coding for signal production is positively autoregulated by the signal, and it has even been described as essential for a quorum-sensing response. We have used the opportunistic pathogen Pseudomonas aeruginosa as a model to show that positive autoregulation is not required for a robust quorum-sensing response. We also show that positive autoregulation of signal production enhances the synchrony of the response. This information enhances our general understanding of the biological significance of how acyl-homoserine lactone quorum-sensing circuits are arranged.

Identification of Quorum Sensing Signal Molecule of Lactobacillus delbrueckii subsp. bulgaricus

Many bacteria in nature use quorum sensing (QS) to regulate gene expression. The quorum sensing system plays critical roles in the adaptation of bacteria to the surrounding environment. Previous studies have shown that during high-density fermentation, the autolysis of lactic acid bacteria was regulated by the QS system, and the two-component system (TCS, LBUL_RS00115/LBUL_RS00110) is involved in the autolysis of Lactobacillus delbrueckii subsp. bulgaricus. However, the QS signal molecule, which regulates this pathway, has not been identified. In this study, we compared the genome of Lactobacillus bulgaricus ATCC BAA-365 with the locus of seven lactobacillus QS systems; the position of the QS signal molecule of Lactobacillus bulgaricus ATCC BAA-365 was predicted by bioinformatics tool. Its function was identified by in vitro experiments. Construction of TCS mutant by gene knockout of LBUL_RS00115 confirmed that the signal molecule regulates the density of the flora by the TCS (LBUL_RS00115/LBUL_RS00110). This study indicated that quorum quenching and inhibition based on the signal molecule might serve as an approach to reduce the rate of autolysis of LAB and increase the number of live bacteria in fermentation.

Effects of receptor correlations on molecular information transmission

Cells measure concentrations of external ligands by capturing ligand molecules with cell surface receptors. The numbers of molecules captured by different receptors co-vary because they depend on the same extrinsic ligand fluctuations. However, these numbers also counter-vary due to the intrinsic stochasticity of chemical processes because a single molecule randomly captured by a receptor cannot be captured by another. Such structure of receptor correlations is generally believed to lead to an increase in information about the external signal compared to the case of independent receptors. We analyze a solvable model of two molecular receptors and show that, contrary to this widespread expectation, the correlations have a small and negative effect on the information about the ligand concentration. Further, we show that measurements that average over multiple receptors are almost as informative as those that track the states of every individual one.

Cell-cell communication enhances the capacity of cell ensembles to sense shallow gradients during morphogenesis

Collective cell responses to exogenous cues depend on cell-cell interactions. In principle, these can result in enhanced sensitivity to weak and noisy stimuli. However, this has not yet been shown experimentally, and little is known about how multicellular signal processing modulates single-cell sensitivity to extracellular signaling inputs, including those guiding complex changes in the tissue form and function. Here we explored whether cell-cell communication can enhance the ability of cell ensembles to sense and respond to weak gradients of chemotactic cues. Using a combination of experiments with mammary epithelial cells and mathematical modeling, we find that multicellular sensing enables detection of and response to shallow epidermal growth factor (EGF) gradients that are undetectable by single cells. However, the advantage of this type of gradient sensing is limited by the noisiness of the signaling relay, necessary to integrate spatially distributed ligand concentration information. We calculate the fundamental sensory limits imposed by this communication noise and combine them with the experimental data to estimate the effective size of multicellular sensory groups involved in gradient sensing. Functional experiments strongly implicated intercellular communication through gap junctions and calcium release from intracellular stores as mediators of collective gradient sensing. The resulting integrative analysis provides a framework for understanding the advantages and limitations of sensory information processing by relays of chemically coupled cells.

Optimizing information flow in small genetic networks. IV. Spatial coupling

We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the input) by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively different regulatory strategy emerges where individual cells respond to the input in a nearly steplike fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models.