Interplay of two quorum sensing regulation systems of Vibrio fischeri

Quorum sensing and antibiotic resistance in polymicrobial infections

Quorum sensing (QS) is a critical bacterial communication system regulating behaviors like biofilm formation, virulence, and antibiotic resistance. This review highlights QS's role in polymicrobial infections, where bacterial species interactions enhance antibiotic resistance. We examine QS mechanisms, such as acyl-homoserine lactones (AHLs) in Gram-negative bacteria and autoinducing peptides (AIPs) in Gram-positive bacteria, and their impact on biofilm-associated antibiotic resistance. The challenges uniquely associated with polymicrobial infections, such as those found in cystic fibrosis lung infections, chronic wound infections, and medical device infections, are also summarized. Furthermore, we explore various laboratory models, including flow cells and dual-species culture models, used to study QS interactions in polymicrobial environments. The review also discusses promising quorum sensing inhibitors (QSIs), such as furanones and AHL analogs, which have demonstrated efficacy in reducing biofilm formation and virulence in laboratory and clinical studies. By addressing the interplay between QS and antibiotic resistance, this paper aims to advance therapeutic strategies that disrupt bacterial communication and improve antibiotic efficacy, ultimately mitigating the global challenge of antibiotic resistance in polymicrobial infections.

Hormesis in the Assessment of Toxicity Assessment by Luminescent Bacterial Methods

The threat posed by water pollutants to aquatic ecosystems and human health cannot be overlooked, and the assessment of the toxicity of these contaminants is paramount to understanding their risks and formulating effective control measures. Luminescent bacteria-based assays, as a vital tool in evaluating contaminant toxicity, encounter a challenge in ensuring accuracy due to the phenomenon of "Hormesis" exhibited by pollutants towards biological entities, which may skew toxicity assessments. This study elucidated the specific effects of pollutants on luminescent bacteria at different concentrations, used modeling to characterize the effects and predict their toxicity trends, and explored the applicable concentration ranges for different pollutants. Research revealed that six typical pollutants, namely PAHs, endocrine disruptors, antibiotics, pesticides, heavy metals, and phytosensory substances, could promote the luminescence intensity of luminescent bacteria at low concentrations, and the promotional effect increased and then decreased. However, when the concentration of the substances reached a certain threshold, the effect changed from promotional to inhibitory, and the rate of inhibition was directly proportional to the concentration. The EC50 values of six types of substances to luminescent bacteria is as follows: endocrine disruptors > pesticides > antibiotics > heavy metals > polycyclic aromatic hydrocarbons > chemosensory agents. The effect curves were further fitted using the model to analyze the maximum point of the promotion of luminescence intensity by different substances, the threshold concentration, and the tolerance of luminescent bacteria to different substances. The maximum promotion of bacterial luminescence intensity was 29% for Bisphenol A at 0.005 mg/L and the minimum threshold concentration of chromium was 0.004 mg/L, and the maximum bacterial tolerance to erythromycin is 6.74. In addition, most of the current environmental concentrations had a positive effect on luminescent bacteria and may still be in the range of concentrations that promote luminescence as the substances continue to accumulate. These findings will enhance the accuracy and comprehensiveness of toxicity assessments, thereby facilitating more informed and effective decision-making in the realms of environmental protection and pollution management.

Crosstalk enables mutual activation of coupled quorum sensing pathways through "jump-start" and "push-start" mechanisms

Many quorum sensing microbes produce more than one chemical signal and detect them using interconnected pathways that crosstalk with each other. While there are many hypotheses for the advantages of sensing multiple signals, the prevalence and functional significance of crosstalk between pathways are much less understood. We explore the effect of intracellular signal crosstalk using a simple model that captures key features of typical quorum sensing pathways: multiple pathways in a hierarchical configuration, operating with positive feedback, with crosstalk at the receptor and promoter levels. We find that crosstalk enables activation or inhibition of one output by the non-cognate signal, broadens the dynamic range of the outputs, and allows one pathway to modulate the feedback circuit of the other. Our findings show how crosstalk between quorum sensing pathways can be viewed not as a detriment to the processing of information, but as a mechanism that enhances the functional range of the full regulatory system. When positive feedback systems are coupled through crosstalk, several new modes of activation or deactivation become possible.

Parameters, architecture and emergent properties of the Pseudomonas aeruginosa LasI/LasR quorum-sensing circuit

Quorum sensing is a widespread process in bacteria that controls collective behaviours in response to cell density. Populations of cells coordinate gene expression through the perception of self-produced chemical signals. Although this process is well-characterized genetically and biochemically, quantitative information about network properties, including induction dynamics and steady-state behaviour, is scarce. Here we integrate experiments with mathematical modelling to quantitatively analyse the LasI/LasR quorum sensing pathway in the opportunistic pathogen Pseudomonas aeruginosa. We determine key kinetic parameters of the pathway and, using the parametrized model, show that quorum sensing behaves as a bistable hysteretic switch, with stable on and off states. We investigate the significance of feedback architecture and find that positive feedback on signal production is critical for induction dynamics and bistability, whereas positive feedback on receptor expression and negative feedback on signal production play a minor role. Taken together, our data-based modelling approach reveals fundamental and emergent properties of a bacterial quorum sensing circuit, and provides evidence that native quorum sensing can indeed function as the gene expression switch it is commonly perceived to be.

Hormetic mechanism of sulfonamides on Aliivibrio fischeri luminescence based on a bacterial cell-cell communication

Hormesis is a biphasic dose-response model with low-dose stimulation and high-dose inhibition. The mechanism for hormesis remains inconclusive, although it is becoming a central concept in toxicology. In this paper, the hormetic mechanism of sulfachloropyridazine (SCP) on Aliivibrio fischeri (A. fischeri) luminescence was explored by investigating into the interference of SCP with the bacterial quorum sensing (QS) communications. It was revealed that the SCP-induced hormesis on luminescence was due to its action on LitR - a key protein that connects lux and ain QS communications in A. fischeri. It was suggested SCP acted on LitR proteins to change its active forms, which subsequently induced hormetic effects on luxR (QS signal receptor) and thereby the luminescence. It is the first time that the hormetic mechanism based on bacterial QS was proposed, which provides a novel insight into the essence of the hormesis on A. fischeri luminescence.

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.

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.

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.

Modeling Analysis of Signal Sensitivity and Specificity by Vibrio fischeri LuxR Variants

The LuxR protein of the bacterium Vibrio fischeri belongs to a family of transcriptional activators that underlie pheromone-mediated signaling by responding to acyl-homoserine lactones (-HSLs) or related molecules. V. fischeri produces two acyl-HSLs, N-3-oxo-hexanoyl-HSL (3OC6-HSL) and N-octanoyl-HSL (C8-HSL), each of which interact with LuxR to facilitate its binding to a "lux box" DNA sequence, thereby enabling LuxR to activate transcription of the lux operon responsible for bioluminescence. We have investigated the HSL sensitivity of four different variants of V. fischeri LuxR: two derived from wild-type strains ES114 and MJ1, and two derivatives of LuxRMJ1 generated by directed evolution. For each LuxR variant, we measured the bioluminescence induced by combinations of C8-HSL and 3OC6-HSL. We fit these data to a model in which the two HSLs compete with each other to form multimeric LuxR complexes that directly interact with lux to activate bioluminescence. The model reproduces the observed effects of HSL combinations on the bioluminescence responses directed by LuxR variants, including competition and non-monotonic responses to C8-HSL and 3OC6-HSL. The analysis yields robust estimates for the underlying dissociation constants and cooperativities (Hill coefficients) of the LuxR-HSL complexes and their affinities for the lux box. It also reveals significant differences in the affinities of LuxRMJ1 and LuxRES114 for 3OC6-HSL. Further, LuxRMJ1 and LuxRES114 differed sharply from LuxRs retrieved by directed evolution in the cooperativity of LuxR-HSL complex formation and the affinity of these complexes for lux. These results show how computational modeling of in vivo experimental data can provide insight into the mechanistic consequences of directed evolution.

Dynamics of the quorum sensing switch: stochastic and non-stationary effects

Background

A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells. Upon reaching a threshold concentration, the signalling molecule activates the QS-controlled genes that promote phenotypic changes. This mechanism, for its simplicity, has become the model system for studying the emergence of a global response in prokaryotic cells. Yet, how cells precisely measure the signal concentration and act coordinately, despite the presence of fluctuations that unavoidably affects cell regulation and signalling, remains unclear.

Results

We propose a model for the QS signalling mechanism in Vibrio fischeri based on the synthetic strains lux01 and lux02. Our approach takes into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. By using both deterministic and stochastic models, we analyze the response and dynamics at the single-cell level and compare them to the global response at the population level. Our results show how fluctuations interfere with the synchronization of the cell activation and lead to a bimodal phenotypic distribution. In this context, we introduce the concept of precision in order to characterize the reliability of the QS communication process in the colony. We show that increasing the noise in the expression of LuxR helps cells to get activated at lower autoinducer concentrations but, at the same time, slows down the global response. The precision of the QS switch under non-stationary conditions decreases with noise, while at steady-state it is independent of the noise value.

Conclusions

Our in silico experiments show that the response of the LuxR/LuxI system depends on the interplay between non-stationary and stochastic effects and that the burst size of the transcription/translation noise at the level of LuxR controls the phenotypic variability of the population. These results, together with recent experimental evidences on LuxR regulation in wild-type species, suggest that bacteria have evolved mechanisms to regulate the intensity of those fluctuations.

Shedding light on bioluminescence regulation in Vibrio fischeri

The bioluminescence emitted by the marine bacterium Vibrio fischeri is a particularly striking result of individual microbial cells co-ordinating a group behaviour. The genes responsible for light production are principally regulated by the LuxR-LuxI quorum-sensing system. In addition to LuxR-LuxI, numerous other genetic elements and environmental conditions control bioluminescence production. Efforts to mathematically model the LuxR-LuxI system are providing insight into the dynamics of this autoinduction behaviour. The Hawaiian squid Euprymna scolopes forms a natural symbiosis with V. fischeri, and utilizes the symbiont-derived bioluminescence for certain nocturnal behaviours, such as counterillumination. Recent work suggests that the tissue with which V. fischeri associates not only can detect bioluminescence but may also use this light to monitor the V. fischeri population.

Quorum activation at a distance: spatiotemporal patterns of gene regulation from diffusion of an autoinducer signal

Quorum sensing (QS) bacteria regulate gene expression collectively by exchanging diffusible signal molecules known as autoinducers. Although QS is often studied in well-stirred laboratory cultures, QS bacteria colonize many physically and chemically heterogeneous environments where signal molecules are transported primarily by diffusion. This raises questions of the effective distance range of QS and the degree to which colony behavior can be synchronized over such distances. We have combined experiments and modeling to investigate the spatiotemporal patterns of gene expression that develop in response to a diffusing autoinducer signal. We embedded a QS strain in a narrow agar lane and introduced exogenous autoinducer at one terminus of the lane. We then measured the expression of a QS reporter as a function of space and time as the autoinducer diffused along the lane. The diffusing signal readily activates the reporter over distances of ~1 cm on time scales of ~10 h. However, the patterns of activation are qualitatively unlike the familiar spreading patterns of simple diffusion, as the kinetics of response are surprisingly insensitive to the distance the signal has traveled. We were able to reproduce these patterns with a mathematical model that combines simple diffusion of the signal with logistic growth of the bacteria and cooperative activation of the reporter. In a wild-type QS strain, we also observed the propagation of a unique spatiotemporal excitation. Our results show that a chemical signal transported only by diffusion can be remarkably effective in synchronizing gene expression over macroscopic distances.

Noise and crosstalk in two quorum-sensing inputs of Vibrio fischeri

Background

One of the puzzles in bacterial quorum sensing is understanding how an organism integrates the information gained from multiple input signals. The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism that receives input from three pheromone signals, including two acyl homoserine lactone (HSL) signals. While the role of the 3-oxo-C6 homoserine lactone (3OC6HSL) signal in activating the lux genes has been extensively studied and modeled, the role of the C8 homoserine lactone (C8HSL) is less obvious, as it can either activate luminescence or block its activation. It remains unclear how crosstalk between C8HSL and 3OC6HSL affects the information that the bacterium obtains through quorum sensing.

Results

We have used microfluidic methods to measure the response of individual V.fischeri cells to combinations of C8HSL and 3OC6HSL. By measuring the fluorescence of individual V.fischeri cells containing a chromosomal gfp-reporter for the lux genes, we study how combinations of exogenous HSLs affect both the population average and the cell-to-cell variability of lux activation levels. At the level of a population average, the crosstalk between the C8HSL and 3OC6HSL inputs is well-described by a competitive inhibition model. At the level of individual cells, the heterogeneity in the lux response depends only on the average degree of activation, so that the noise in the output is not reduced by the presence of the second HSL signal. Overall we find that the mutual information between the signal inputs and the lux output is less than one bit. A nonlinear correlation between fluorescence and bioluminescence outputs from lux leads to different noise properties for these reporters.

Conclusions

The lux genes in V.fischeri do not appear to distinguish between the two HSL inputs, and even with two signal inputs the regulation of lux is extremely noisy. Hence the role of crosstalk from the C8HSL input may not be to improve sensing precision, but rather to suppress the sensitivity of the switch for as long as possible during colony growth.

The antifouling potentiality of galactosamine characterized from Vibrio vulnificus exopolysaccharide

To gain a better insight into biofilm composition, the exopolysaccharide (EPS) of the Gram-negative bacterium Vibrio vulnificus was studied. Monosaccharide composition analysis of the wild-type and mutant V. vulnificus EPS carried out with Bio-liquid chromatography revealed the presence of D-glucosamine, D-galactose, D-glucose and D-xylose in both strains. D-galactosamine was found only in the mutant that formed less biofilm compared to its wild-type. The influence of galactosamine on biofilm formation was then studied by adding this substance gradually to six different Gram-negative/positive bacteria associated with various autoinducers. Four bacterial species known to use the autoinducer type-2 signaling system produced less biofilm in the presence of galactosamine. No significant inhibition of biofilm formation was observed in bacteria that produce autoinducer type-1 signal molecules. Galactosamine was also immobilized on polymeric nanofibers to determine its re-usability for the study of biofilm inhibition. The immobilized galactosamine retained >65% of its initial antifouling activity after 10 repeated uses. The results of this study suggest the antifouling role of galactosamine for bacteria that produce AI-2.

Heterogeneous response to a quorum-sensing signal in the luminescence of individual Vibrio fischeri

The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism: the bacterium releases diffusible small molecules (autoinducers) that accumulate in the environment as the population density increases. This accumulation of autoinducer (AI) eventually activates transcriptional regulators for bioluminescence as well as host colonization behaviors. Although V. fischeri quorum sensing has been extensively characterized in bulk populations, far less is known about how it performs at the level of the individual cell, where biochemical noise is likely to limit the precision of luminescence regulation. We have measured the time-dependence and AI-dependence of light production by individual V. fischeri cells that are immobilized in a perfusion chamber and supplied with a defined concentration of exogenous AI. We use low-light level microscopy to record and quantify the photon emission from the cells over periods of several hours as they respond to the introduction of AI. We observe an extremely heterogeneous response to the AI signal. Individual cells differ widely in the onset time for their luminescence and in their resulting brightness, even in the presence of high AI concentrations that saturate the light output from a bulk population. The observed heterogeneity shows that although a given concentration of quorum signal may determine the average light output from a population of cells, it provides far weaker control over the luminescence output of each individual cell.

Bright mutants of Vibrio fischeri ES114 reveal conditions and regulators that control bioluminescence and expression of the lux operon

Vibrio fischeri ES114, an isolate from the Euprymna scolopes light organ, produces little bioluminescence in culture but is ∼1,000-fold brighter when colonizing the host. Cell-density-dependent regulation alone cannot explain this phenomenon, because cells within colonies on solid medium are much dimmer than symbiotic cells despite their similar cell densities. To better understand this low luminescence in culture, we screened ∼20,000 mini-Tn5 mutants of ES114 for increased luminescence and identified 28 independent "luminescence-up" mutants with insertions in 14 loci. Mutations affecting the Pst phosphate uptake system led to the discovery that luminescence is upregulated under low-phosphate conditions by PhoB, and we also found that ainS, which encodes an autoinducer synthase, mediates repression of luminescence during growth on plates. Other novel luminescence-up mutants had insertions in acnB, topA, tfoY, phoQ, guaB, and two specific tRNA genes. Two loci, hns and lonA, were previously described as repressors of bioluminescence in transgenic Escherichia coli carrying the light-generating lux genes, and mutations in arcA and arcB were consistent with our report that Arc represses lux. Our results reveal a complex regulatory web governing luminescence and show how certain environmental conditions are integrated into regulation of the pheromone-dependent lux system.

Attenuation of Vibrio fischeri quorum sensing using rationally designed polymers

A first attempt to attenuate the quorum sensing (QS) of a marine heterotroph microorganism, Vibrio fischeri , using signal molecule-sequestering polymers (SSPs) is presented. A set of rationally designed polymers with affinity toward a signal molecule of V. fischeri , N-(beta-ketocaproyl)-l-homoserine lactone (3-oxo-C6-AHL) was produced. It is reported that computationally designed polymers could sequester a signal molecule of V. fischeri and prevent QS-controlled phenotypes (in this case, bioluminescence) from being up-regulated. It was proven that the attenuation of bioluminescence of V. fischeri was due to sequestration of the signal molecule by specific polymers and not due to the toxicity of polymer or nonspecific depletion of nutrients. The ability to disrupt the bacterial communication using easy to synthesize and chemically inert polymers could provide a new concept for the development of pharmaceuticals and susceptible device coatings such as catheters.

A mathematical model of the Gac/Rsm quorum sensing network in Pseudomonas fluorescens

I present a deterministic model of the dynamics of signal transduction and gene expression in the Gac/Rsm network of the soil-dwelling bacterium Pseudomonas fluorescens. The network is involved in quorum sensing and governs antifungal production in this important biocontrol agent. A central role is played by small untranslated RNAs, which sequester regulatory mRNA-binding proteins. The model provides a reasonable match to the available data, which consists primarily of time series from reporter gene fusions. I use the model to investigate the information-processing properties of the Gac/Rsm network, in part by comparing it to a simplified model capable of quorum sensing. The results suggest that the complexity and redundancy of the Gac/Rsm network have evolved to meet the conflicting requirements of high sensitivity to environmental conditions and a conservative, robust response to variability in parameter values. Similar systems exist in a wide variety of bacteria, where they control a diverse set of population-dependent behaviors. This makes them important subjects for mathematical models that can help link empirical understanding of network structure to theoretical insights into how these networks have evolved to function under natural conditions.

Systems biology of microbial communities

Microbes exist naturally in a wide range of environments in communities where their interactions are significant, spanning the extremes of high acidity and high temperature environments to soil and the ocean. We present a practical discussion of three different approaches for modeling microbial communities: rate equations, individual-based modeling, and population dynamics. We illustrate the approaches with detailed examples. Each approach is best fit to different levels of system representation, and they have different needs for detailed biological input. Thus, this set of approaches is able to address the operation and function of microbial communities on a wide range of organizational levels.