Spatial heterogeneity of autoinducer regulation systems

Cooperation in bioluminescence: understanding the role of autoinducers by a stochastic random resistor model

Quorum sensing is a communication mechanism adopted by different bacterial strains for the regulation of gene transcription. It takes place through the exchange of molecules called autoinducers. Bioluminescence is an emergent threshold phenomenon shown by some bacteria strains. Its precise relationship to quorum sensing is a debated topic, particularly regarding the role of the different autoinducers used by bacteria. In this paper, assuming a direct relationship between bioluminescence and quorum sensing, we investigate the role of multiple autoinducers in the bioluminescence response of Vibrio harveyi, considered as a model bioluminescent strain, due to its quorum sensing circuitry involving an array of three different autoinducers. Experiments on mutants of this bacterium, obtained by suppression of one or more autoinducers, reveal their relative non-trivial relevance and cooperative interaction patterns. The proposed analysis is implemented on a regular lattice, whose nodes represent microbial entities equipped with charges, which represent the ability to up/down regulate the gene expression. Quorum sensing results from a Coulomb-type field, produced by the charges. In analogy with random resistor network models, the lattice is permeated by an effective current which accounts for the amount and distribution of the charges. We propose that the presence of different autoinducers correspond to a different up/down regulation of gene expression, i.e., to a different way to account for the charges. Then, by introducing a modulation of the charge dependence into the current flowing within the network, we show that it is able to describe the bioluminescence exhibited by V. harveyi mutants. Furthermore, modulation of the charge dependence allows the interactions between the different autoinducers to be taken into account, providing a prediction regarding the data obtainable under specific growth conditions.

Disturbing the Spatial Organization of Biofilm Communities Affects Expression of agr-Regulated Virulence Factors in Staphylococcus aureus

Staphylococcus aureus uses quorum sensing and nutrient availability to control the expression of agr-regulated virulence factors. Quorum sensing is mediated by autoinducing peptide (AIP), which at a high concentration reduces expression of surface attachment proteins (coa, fnbpA) and increases expression of exotoxins (lukS) and proteases (splA). Nutrient availability can be sensed through the saeS/saeR system. Low nutrients increase expression of saeR, which augments expression of coa and fnbpA, distinct from the activity of AIP. The formation of spatial structure, such as biofilms, can alter quorum sensing and nutrient acquisition. In natural environments, biofilms encounter forces that may alter their spatial structure. These forces may impact quorum sensing and/or nutrient acquisition and thus affect the expression of agr-regulated virulence factors. However, this has not been studied. We show that periodically disturbing biofilms composed of S. aureus using a physical force affected the expression of agr-regulated virulence factors. In nutrient-poor environments, disturbance increased the expression of coa, fnbpA, lukS, and splA. Disturbance in a nutrient-rich environment at low or high disturbance amplitudes moderately reduced expression of coa and fnbpA but increased expression of lukS and splA. Interestingly, at an intermediate amplitude, the overall expression of agr-regulated virulence factors was the lowest; expression of lukS and splA remained unchanged relative to an undisturbed biofilm, while expression of coa and fnbpA significantly decreased. We hypothesize that these changes are a result of disturbance-driven changes in access to AIP and nutrients. Our results may allow the identification of environments where virulence is enhanced, or reduced, owing to a disturbance. IMPORTANCE Bacteria, such as Staphylococcus aureus, integrate signals from the environment to regulate genes encoding virulence factors. These signals include those produced by quorum-sensing systems and nutrient availability. We show that disturbing the spatial organization of S. aureus populations can lead to changes in the expression of virulence factors, likely by altering the ways in which S. aureus detects these signals. Our work may allow us to identify environments that increase or reduce the expression of virulence factors in S. aureus.

A biophysical threshold for biofilm formation

Bacteria are ubiquitous in our daily lives, either as motile planktonic cells or as immobilized surface-attached biofilms. These different phenotypic states play key roles in agriculture, environment, industry, and medicine; hence, it is critically important to be able to predict the conditions under which bacteria transition from one state to the other. Unfortunately, these transitions depend on a dizzyingly complex array of factors that are determined by the intrinsic properties of the individual cells as well as those of their surrounding environments, and are thus challenging to describe. To address this issue, here, we develop a generally-applicable biophysical model of the interplay between motility-mediated dispersal and biofilm formation under positive quorum sensing control. Using this model, we establish a universal rule predicting how the onset and extent of biofilm formation depend collectively on cell concentration and motility, nutrient diffusion and consumption, chemotactic sensing, and autoinducer production. Our work thus provides a key step toward quantitatively predicting and controlling biofilm formation in diverse and complex settings.

Frequency modulation of a bacterial quorum sensing response

In quorum sensing, bacteria secrete or release small molecules into the environment that, once they reach a certain threshold, trigger a behavioural change in the population. As the concentration of these so-called autoinducers is supposed to reflect population density, they were originally assumed to be continuously produced by all cells in a population. However, here we show that in the α-proteobacterium Sinorhizobium meliloti expression of the autoinducer synthase gene is realized in asynchronous stochastic pulses that result from scarcity and, presumably, low binding affinity of the key activator. Physiological cues modulate pulse frequency, and pulse frequency in turn modulates the velocity with which autoinducer levels in the environment reach the threshold to trigger the quorum sensing response. We therefore propose that frequency-modulated pulsing in S. meliloti represents the molecular mechanism for a collective decision-making process in which each cell's physiological state and need for behavioural adaptation is encoded in the pulse frequency with which it expresses the autoinducer synthase gene; the pulse frequencies of all members of the population are then integrated in the common pool of autoinducers, and only once this vote crosses the threshold, the response behaviour is initiated.

Deciphering bacterial social traits via diffusible signal factor (DSF) -mediated public goods in an anammox community

Both the benefits of bacterial quorum sensing (QS) and cross-feeding for bio-reactor performance in wastewater treatment have been recently reported. As the social traits of microbial communities, how bacterial QS regulating bacterial trade-off by cross-feeding remains unclear. Here, we find diffusion signal factor (DSF), a kind of QS molecules, can bridge bacterial interactions through regulating public goods (extracellular polymeric substances (EPS), amino acids) for metabolic cross-feedings. It showed that exogenous DSF-addition leads to change of public goods level and community structure dynamics in the anammox consortia. Approaches involving meta-omics clarified that anammox and a Lautropia-affiliated species in the phylum Proteobacteria can supply costly public goods for DSF-Secretor species via secondary messenger c-di-GMP regulator (Clp) after sensing DSF. Meanwhile, DSF-Secretor species help anammox bacteria scavenge extracellular detritus, which creates a more suitable environment for the anammox species, enhances the anammox activity, and improves the nitrogen removal rate of anammox reactor. The trade-off induces discrepant metabolic loads of different microbial clusters, which were responsible for the community succession. It illustrated the potential to artificially alleviate metabolic loads for certain bacteria. Deciphering microbial interactions via QS not only provides insights for understanding the social behavior of microbial community, but also creates new thought for enhancing treatment performance through regulating bacterial social traits via quorum sensing-mediated public goods.

Spatially propagating activation of quorum sensing in Vibrio fischeri and the transition to low population density

Bacteria communicate by secreting and detecting diffusible small molecule signals or pheromones. Using the local concentrations of these signals to regulate gene expression, individual cells can synchronize changes in phenotype population-wide, a behavior known as quorum sensing (QS). In unstirred media, the interplay between diffusion of signals, bacterial growth, and regulatory feedback can generate complex spatial and temporal patterns of expression of QS-controlled genes. Here we identify the parameters that allow a local signal to trigger a self-sustaining, traveling activation of QS behavior. Using the natural bioluminescence of wild-type Vibrio fischeri as a readout of its lux QS system, we measure the induction of a spreading QS response by a localized triggering stimulus in unstirred media. Our data show that a QS response propagates outward, sustained by positive feedback in synthesis of the diffusible signal, and that this response occurs only if the triggering stimulus exceeds a critical threshold. We also test how the autonomous or untriggered activation of the V. fischeri QS pathway changes at very low initial population densities. At the lowest population densities, clusters of cells do not transition to a self-sensing behavior, but rather remain in communication via signal diffusion until they reach sufficiently large size that their own growth slows. Our data, which are reproduced by simple growth and diffusion simulations, indicate that in part owing to bacterial growth behavior, natural QS systems can be characterized by long distance communication through signal diffusion even in very heterogeneous and spatially dispersed populations.

Data-driven statistical modeling of the emergent behavior of biohybrid microrobots

Multi-agent biohybrid microrobotic systems, owing to their small size and distributed nature, offer powerful solutions to challenges in biomedicine, bioremediation, and biosensing. Synthetic biology enables programmed emergent behaviors in the biotic component of biohybrid machines, expounding vast potential benefits for building biohybrid swarms with sophisticated control schemes. The design of synthetic genetic circuits tailored toward specific performance characteristics is an iterative process that relies on experimental characterization of spatially homogeneous engineered cell suspensions. However, biohybrid systems often distribute heterogeneously in complex environments, which will alter circuit performance. Thus, there is a critically unmet need for simple predictive models that describe emergent behaviors of biohybrid systems to inform synthetic gene circuit design. Here, we report a data-driven statistical model for computationally efficient recapitulation of the motility dynamics of two types of Escherichia coli bacteria-based biohybrid swarms-NanoBEADS and BacteriaBots. The statistical model was coupled with a computational model of cooperative gene expression, known as quorum sensing (QS). We determined differences in timescales for programmed emergent behavior in BacteriaBots and NanoBEADS swarms, using bacteria as a comparative baseline. We show that agent localization and genetic circuit sensitivity strongly influence the timeframe and the robustness of the emergent behavior in both systems. Finally, we use our model to design a QS-based decentralized control scheme wherein agents make independent decisions based on their interaction with other agents and the local environment. We show that synergistic integration of synthetic biology and predictive modeling is requisite for the efficient development of biohybrid systems with robust emergent behaviors.

Burst statistics in an early biofilm quorum sensing model: the role of spatial colony-growth heterogeneity

Quorum-sensing bacteria in a growing colony of cells send out signalling molecules (so-called “autoinducers”) and themselves sense the autoinducer concentration in their vicinity. Once—due to increased local cell density inside a “cluster” of the growing colony—the concentration of autoinducers exceeds a threshold value, cells in this clusters get “induced” into a communal, multi-cell biofilm-forming mode in a cluster-wide burst event. We analyse quantitatively the influence of spatial disorder, the local heterogeneity of the spatial distribution of cells in the colony, and additional physical parameters such as the autoinducer signal range on the induction dynamics of the cell colony. Spatial inhomogeneity with higher local cell concentrations in clusters leads to earlier but more localised induction events, while homogeneous distributions lead to comparatively delayed but more concerted induction of the cell colony, and, thus, a behaviour close to the mean-field dynamics. We quantify the induction dynamics with quantifiers such as the time series of induction events and burst sizes, the grouping into induction families, and the mean autoinducer concentration levels. Consequences for different scenarios of biofilm growth are discussed, providing possible cues for biofilm control in both health care and biotechnology.

Phenotypic Heterogeneity in Bacterial Quorum Sensing Systems

Quorum sensing is usually thought of as a collective behavior in which all members of a population partake. However, over the last decade, several reports of phenotypic heterogeneity in quorum sensing-related gene expression have been put forward, thus challenging this view. In the respective systems, cells of isogenic populations did not contribute equally to autoinducer production or target gene activation, and in some cases, the fraction of contributing cells was modulated by environmental factors. Here, we look into potential origins of these incidences and into how initial cell-to-cell variations might be amplified to establish distinct phenotypic heterogeneity. We furthermore discuss potential functions heterogeneity in bacterial quorum sensing systems could serve: as a preparation for environmental fluctuations (bet hedging), as a more cost-effective way of producing public goods (division of labor), as a loophole for genotypic cooperators when faced with non-contributing mutants (cheat protection), or simply as a means to fine-tune the output of the population as a whole (output modulation). We illustrate certain aspects of these recent developments with the model organisms Sinorhizobium meliloti, Sinorhizobium fredii and Bacillus subtilis, which possess quorum sensing systems of different complexity, but all show phenotypic heterogeneity therein.

Could Positive Feedback Enable Bacterial Pheromone Signaling To Coordinate Behaviors in Response to Heterogeneous Environmental Cues?

Pheromone signaling (PS) underlies many important bacterial behaviors, yet its ecological functions remain unresolved. Because pheromone-mediated behaviors require high cell density, the term "quorum sensing" is widely used to describe and make sense of PS. However, while this term has unified and popularized the field, bacterial PS clearly has roles beyond census taking, and the complexities of PS circuits indicate broader functional capacities. Two common features of bacterial PS are its regulation in response to environmental conditions and positive-feedback loops. Combined, these could enable PS to coordinate quorum-dependent group behaviors in response to heterogeneous environmental cues. Particularly in PS systems where positive feedback is strong, cells that are relatively far from a stimulatory environment could be recruited to a group response. Testing this model will benefit from in situ examination of relevant environmental cues and PS outputs in cells across populations, with and without positive feedback, in heterogeneous environments.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

ComX-Induced Exoproteases Degrade ComX in Bacillus subtilis PS-216

Gram-positive bacteria use peptides as auto-inducing (AI) signals to regulate the production of extracellular enzymes (e.g., proteases). ComX is an AI peptide, mostly known for its role in the regulation of bacterial competence and surfactant production in Bacillus subtilis. These two traits are regulated accordingly to the bacterial population size, thus classifying ComX as a quorum sensing signal. ComX also indirectly regulates exoprotease production through the intermediate transcriptional regulator DegQ. We here use this peptide-based AI system (the ComQXPA system) as a model to address exoprotease regulation by ComX in biofilms. We also investigate the potential of ComX regulated proteases to degrade the ComX AI peptide. Results indicate that ComX indeed induces the expression of aprE, the gene for the major serine protease subtilisin, and stimulates overall exoprotease production in biofilms of B. subtilis PS-216 and several other B. subtilis soil isolates. We also provide evidence that these exoproteases can degrade ComX. The ComX biological activity decay is reduced in the spent media of floating biofilms with low proteolytic activity found in the comP and degQ mutants. ComX biological activity decay can be restored by the addition of subtilisin to such media. In contrast, inhibition of metalloproteases by EDTA reduces ComX biological activity decay. This suggests that both serine and metalloproteases, which are induced by ComX, are ultimately capable of degrading this signaling peptide. This work brings novel information on regulation of exoproteases in B. subtilis floating biofilms and reveals that these proteolytic enzymes degrade the AI signaling peptide ComX, which is also a major determinant of their expression in biofilms.

Differential Equations Models to Study Quorum Sensing

Mathematical models to study quorum sensing (QS) have become an important tool to explore all aspects of this type of bacterial communication. A wide spectrum of mathematical tools and methods such as dynamical systems, stochastics, and spatial models can be employed. In this chapter, we focus on giving an overview of models consisting of differential equations (DE), which can be used to describe changing quantities, for example, the dynamics of one or more signaling molecule in time and space, often in conjunction with bacterial growth dynamics. The chapter is divided into two sections: ordinary differential equations (ODE) and partial differential equations (PDE) models of QS. Rates of change are represented mathematically by derivatives, i.e., in terms of DE. ODE models allow describing changes in one independent variable, for example, time. PDE models can be used to follow changes in more than one independent variable, for example, time and space. Both types of models often consist of systems (i.e., more than one equation) of equations, such as equations for bacterial growth and autoinducer concentration dynamics. Almost from the onset, mathematical modeling of QS using differential equations has been an interdisciplinary endeavor and many of the works we revised here will be placed into their biological context.

Cell differentiation defines acute and chronic infection cell types in Staphylococcus aureus

A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus, which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureusteichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types.

While in hospital, patients can be unwittingly exposed to bacteria that can cause disease. These hospital-associated bacteria can lead to potentially life-threatening infections that may also complicate the treatment of the patients’ existing medical conditions. Staphylococcus aureus is one such bacterium, and it can cause several types of infection including pneumonia, blood infections and long-term infections of prosthetic devices.

It is thought that S. aureus is able to cause so many different types of infection because it is capable of colonizing distinct tissues and organs in various parts of the body. Understanding the biological processes that drive the different infections is crucial to improving how these infections are treated.

S. aureus lives either as an independent, free-swimming cell or as part of a community known as a biofilm. These different lifestyles dictate the type of infection the bacterium can cause, with free-swimming cells producing toxins that contribute to intense, usually short-lived, infections and biofilms promoting longer-term infections that are difficult to eradicate. However, it is not clear how a population of S. aureus cells chooses to adopt a particular lifestyle and whether there are any environmental signals that influence this decision.

Here, Garcia-Betancur et al. found that S. aureus populations contain small groups of cells that have already specialized into a particular lifestyle. These groups of cells collectively influence the choice made by other cells in the population. While both lifestyles will be represented in the population, environmental factors influence the numbers of cells that initially adopt each type of lifestyle, which ultimately affects the choice made by the rest of the population. For example, if the bacteria colonize a tissue or organ that contains high levels of magnesium ions, the population is more likely to form biofilms.

In the future, the findings of Garcia-Betancur et al. may help us to predict how an infection may develop in a particular patient, which may help to diagnose the infection more quickly and allow it to be treated more effectively.

Cooperation and competition shape ecological resistance during periodic spatial disturbance of engineered bacteria

Cooperation is fundamental to the survival of many bacterial species. Previous studies have shown that spatial structure can both promote and suppress cooperation. Most environments where bacteria are found are periodically disturbed, which can affect the spatial structure of the population. Despite the important role that spatial disturbances play in maintaining ecological relationships, it remains unclear as to how periodic spatial disturbances affect bacteria dependent on cooperation for survival. Here, we use bacteria engineered with a strong Allee effect to investigate how the frequency of periodic spatial disturbances affects cooperation. We show that at intermediate frequencies of spatial disturbance, the ability of the bacterial population to cooperate is perturbed. A mathematical model demonstrates that periodic spatial disturbance leads to a tradeoff between accessing an autoinducer and accessing nutrients, which determines the ability of the bacteria to cooperate. Based on this relationship, we alter the ability of the bacteria to access an autoinducer. We show that increased access to an autoinducer can enhance cooperation, but can also reduce ecological resistance, defined as the ability of a population to resist changes due to disturbance. Our results may have implications in maintaining stability of microbial communities and in the treatment of infectious diseases.

An age-dependent model to analyse the evolutionary stability of bacterial quorum sensing

Bacterial communication is enabled through the collective release and sensing of signalling molecules in a process called quorum sensing. Cooperative processes can easily be destabilized by the appearance of cheaters, who contribute little or nothing at all to the production of common goods. This especially applies for planktonic cultures. In this study, we analyse the dynamics of bacterial quorum sensing and its evolutionary stability under two levels of cooperation, namely signal and enzyme production. The model accounts for mutation rates and switches between planktonic and biofilm state of growth. We present a mathematical approach to model these dynamics using age-dependent colony models. We explore the conditions under which cooperation is stable and find that spatial structuring can lead to long-term scenarios such as coexistence or bistability, depending on the non-linear combination of different parameters like death rates and production costs.

Mathematical Modelling of Bacterial Quorum Sensing: A Review

Bacterial quorum sensing (QS) refers to the process of cell-to-cell bacterial communication enabled through the production and sensing of the local concentration of small molecules called autoinducers to regulate the production of gene products (e.g. enzymes or virulence factors). Through autoinducers, bacteria interact with individuals of the same species, other bacterial species, and with their host. Among QS-regulated processes mediated through autoinducers are aggregation, biofilm formation, bioluminescence, and sporulation. Autoinducers are therefore "master" regulators of bacterial lifestyles. For over 10 years, mathematical modelling of QS has sought, in parallel to experimental discoveries, to elucidate the mechanisms regulating this process. In this review, we present the progress in mathematical modelling of QS, highlighting the various theoretical approaches that have been used and discussing some of the insights that have emerged. Modelling of QS has benefited almost from the onset of the involvement of experimentalists, with many of the papers which we review, published in non-mathematical journals. This review therefore attempts to give a broad overview of the topic to the mathematical biology community, as well as the current modelling efforts and future challenges.

Single Cell Analysis of a Bacterial Sender-Receiver System

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.

Chemical communication between bacteria and cell-free gene expression systems within linear chains of emulsion droplets

Position-dependent gene expression in gradients of morphogens is one of the key processes involved in cellular differentiation during development. Here, we study a simple artificial differentiation process, which is based on the diffusion of genetic inducers within one-dimensional arrangements of 50 μm large water-in-oil droplets. The droplets are filled with either bacteria or cell-free gene expression systems, both equipped with genetic constructs that produce inducers or respond to them via expression of a fluorescent protein. We quantitatively study the coupled diffusion-gene expression process and demonstrate that gene expression can be made position-dependent both within bacteria-containing and cell-free droplets. By generating diffusing quorum sensing signals in situ, we also establish communication between artificial cell-free sender cells and bacterial receivers, and vice versa.

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Phenotypic heterogeneity describes the occurrence of "nonconformist" cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations.

A Mathematical Model of Quorum Sensing Induced Biofilm Detachment

BACKGROUND

Cell dispersal (or detachment) is part of the developmental cycle of microbial biofilms. It can be externally or internally induced, and manifests itself in discrete sloughing events, whereby many cells disperse in an instance, or in continuous slower dispersal of single cells. One suggested trigger of cell dispersal is quorum sensing, a cell-cell communication mechanism used to coordinate gene expression and behavior in groups based on population densities.

METHOD

To better understand the interplay of colony growth and cell dispersal, we develop a dynamic, spatially extended mathematical model that includes biofilm growth, production of quorum sensing molecules, cell dispersal triggered by quorum sensing molecules, and re-attachment of cells. This is a highly nonlinear system of diffusion-reaction equations that we study in computer simulations.

RESULTS

Our results show that quorum sensing induced cell dispersal can be an efficient mechanism for bacteria to control the size of a biofilm colony, and at the same time enhance its downstream colonization potential. In fact we find that over the lifetime of a biofilm colony the majority of cells produced are lost into the aqueous phase, supporting the notion of biofilms as cell nurseries. We find that a single quorum sensing based mechanism can explain both, discrete dispersal events and continuous shedding of cells from a colony. Moreover, quorum sensing induced cell dispersal affects the structure and architecture of the biofilm, for example it might lead to the formation of hollow inner regions in a biofilm colony.

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Phenotypic heterogeneity describes the occurrence of "nonconformist" cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations.

Core principles of bacterial autoinducer systems

SUMMARY

Autoinduction (AI), the response to self-produced chemical signals, is widespread in the bacterial world. This process controls vastly different target functions, such as luminescence, nutrient acquisition, and biofilm formation, in different ways and integrates additional environmental and physiological cues. This diversity raises questions about unifying principles that underlie all AI systems. Here, we suggest that such core principles exist. We argue that the general purpose of AI systems is the homeostatic control of costly cooperative behaviors, including, but not limited to, secreted public goods. First, costly behaviors require preassessment of their efficiency by cheaper AI signals, which we encapsulate in a hybrid "push-pull" model. The "push" factors cell density, diffusion, and spatial clustering determine when a behavior becomes effective. The relative importance of each factor depends on each species' individual ecological context and life history. In turn, "pull" factors, often stress cues that reduce the activation threshold, determine the cellular demand for the target behavior. Second, control is homeostatic because AI systems, either themselves or through accessory mechanisms, not only initiate but also maintain the efficiency of target behaviors. Third, AI-controlled behaviors, even seemingly noncooperative ones, are generally cooperative in nature, when interpreted in the appropriate ecological context. The escape of individual cells from biofilms, for example, may be viewed as an altruistic behavior that increases the fitness of the resident population by reducing starvation stress. The framework proposed here helps appropriately categorize AI-controlled behaviors and allows for a deeper understanding of their ecological and evolutionary functions.

Communication and computation by bacteria compartmentalized within microemulsion droplets

Amphiphilic inducer molecules such as N-acyl-L-homoserine lactones (AHLs) or isopropyl-β-D-thio-galactopyranoside (IPTG) can be utilized for the implementation of an artificial communication system between groups of E. coli bacteria encapsulated within water-in-oil microemulsion droplets. Using spatially extended arrays of microdroplets, we study the diffusion of both AHL and IPTG from inducer-filled reservoirs into bacteria-containing droplets, and also from droplets with AHL producing sender bacteria into neighboring droplets containing receiver cells. Computational modeling of gene expression dynamics within the droplets suggests a strongly reduced effective diffusion coefficient of the inducers, which markedly affects the spatial communication pattern in the neighborhood of the senders. Engineered bacteria that integrate AHL and IPTG signals with a synthetic AND gate gene circuit are shown to respond only in the presence of both types of sender droplets, which demonstrates the potential of the system for genetically programmed pattern formation and distributed computing.

Homoserine lactones influence the reaction of plants to rhizobia

Bacterial quorum sensing molecules not only grant the communication within bacterial communities, but also influence eukaryotic hosts. N-acyl-homoserine lactones (AHLs) produced by pathogenic or beneficial bacteria were shown to induce diverse reactions in animals and plants. In plants, the reaction to AHLs depends on the length of the lipid side chain. Here we investigated the impact of two bacteria on Arabidopsis thaliana, which usually enter a close symbiosis with plants from the Fabaceae (legumes) family and produce a long-chain AHL (Sinorhizobium meliloti) or a short-chain AHL (Rhizobium etli). We demonstrate that, similarly to the reaction to pure AHL molecules, the impact, which the inoculation with rhizosphere bacteria has on plants, depends on the type of the produced AHL. The inoculation with oxo-C14-HSL-producing S. meliloti strains enhanced plant resistance towards pathogenic bacteria, whereas the inoculation with an AttM lactonase-expressing S. meliloti strain did not. Inoculation with the oxo-C8-HSL-producing R. etli had no impact on the resistance, which is in agreement with our previous hypothesis. In addition, plants seem to influence the availability of AHLs in the rhizosphere. Taken together, this report provides new insights in the role of N-acyl-homoserine lactones in the inter-kingdom communication at the root surface.