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The lux operon in V. fischeri and genomic organization of strains engineered for this study. Panel (A) illustrates the genetic structure of the lux locus in parental wild-type strain ES114 (top) as well as the strains used to assay LuxR activity, wherein the native luxRI is deleted and luxR alleles are placed in an engineered construct between ORF VFA0926 and luxC (hatched box). Panel (B) shows specific sequences of ES114 aligned with those of engineered strains. Red sequences are stop codons for luxR (reverse strand) and luxI. The green ATG represents the start codon for luxC. Further details (e.g. cloning strategy, sequence of the “consensus promoter”, etc.) are provided in Methods.
Source publication
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 fa...
Citations
... Because crosstalk mixes information received from separate signals, it would appear likely to degrade the performance of a quorum sensing pathway. It is however a highly evolvable property that can be reduced or even eliminated through (for example) receptor design 4,18,19 . Therefore, although there exist several hypotheses for why bacterial species use multiple autoinducer signals, there is still little understanding of why crosstalk is common in quorum sensing systems, and how it affects the output behaviors of these networks, beginning at the level of an individual organism. ...
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.
... Because crosstalk mixes information received from separate signals, it would appear likely to degrade the performance of a quorum sensing pathway. It is however a highly evolvable property that can be reduced or even eliminated through (for example) receptor design [18,19,4]. Therefore, although there exist several hypotheses for why bacterial species use multiple autoinducer signals, there is still little understanding of why crosstalk is common in quorum sensing systems, and how it affects the output behaviors of these networks, beginning at the level of an individual organism. ...
Many bacterial species are able to coordinate population-wide phenotypic responses through the exchange of diffusible chemical signals, a behavior known as quorum sensing. A quorum sensing bacterium may employ multiple types of chemical signals 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 the sensing pathways are much less understood. Here we explore the effect of intracellular signal crosstalk on a simple model of a quorum sensing circuit. The model captures key aspects of typical quorum sensing pathways, including detection of multiple signals that crosstalk at the receptor and promoter levels, positive feedback, and hierarchical positioning of sensing pathways. We find that a variety of behaviors can be tuned by modifying crosstalk and feedback strengths. These include activation or inhibition of one output by the non-cognate signal, broadening of dynamic range of the outputs, and the ability of either the upstream or downstream branch to modulate the feedback circuit of the other branch. Our findings show how crosstalk between quorum sensing pathways can be viewed not solely as a detriment to the flow of information but also 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.
... The concentration of AI in the solution was measured with a whole-cell lux biosensor E. coli MG1655 pVFR1 pSVRAF (with extra high sensitivity to AI due to the enhanced dosage of the regulatory luxR gene A. fischeri (Bazhenov et al. 2021a)) showing a dose-dependent increase in luminescence upon addition of AI at concentrations from 0.03 to 10 nM. Calibration was performed with use of N-(3-oxohexanoyl)-Lhomoserine lactone: the major AI produced by LuxI of bacteria of Aliivibrio genus (Colton et al. 2015;Hansen et al. 2015). ...
Bacterial expression systems play an indispensable role in the biosynthesis of recombinant proteins. Different proteins and the tasks associated with them may require different systems. The purpose of this work is to make an expression vector that allows switching on and off the expression of the target gene during cell incubation. Several expression vectors for use in Escherichia coli cells were developed using elements of the luxR/luxI type quorum sensing system of psychrophilic bacterium Aliivibrio logei. These vectors contain A. logei luxR2 and (optionally) luxI genes and LuxR2-regulated promoter, under the control of which a target gene is intended to be inserted. The synthesis of the target protein depends directly on the temperature: gene expression starts when the temperature drops to 22 °C and stops when it rises to 37 °C, which makes it possible to fix the desired amount of the target protein in the cell. At the same time, the expression of the target gene at a low temperature depends on the concentration of the autoinducer (L-homoserine N-(3-oxohexanoyl)-lactone, AI) in the culture medium in a wide range from 1 nM to 10 μM, which makes it possible to smoothly regulate the rate of target protein synthesis. Presence of luxI in the vector provides the possibility of autoinduction. Constructed expression vectors were tested with gfp, ardA, and ardB genes. At maximum, we obtained the target protein in an amount of up to 33% of the total cellular protein.
Key points
• A. logei quorum sensing system elements were applied in new expression vectors
• Expression of target gene is inducible at 22 °C and it is switched off at 37 °C
• Target gene expression at 22 °C is tunable by use different AI concentrations
Graphical Abstract
... The simulation also abstracts the light performance of the bacteria. Vibrio fischeri's signal sensitivity has been simulated [21], but does not allow for an understanding of the overall light performance. Capillary effect and surface tension have proved central in our investigations, but these physical phenomena, caused by forces on a molecular level, are too complex to simulate. ...
By hybridising the principles of the living with the methods of design, the emerging field of biodesign is exploring how to radically transform the ecological imprint of contemporary material culture while questioning the creative opportunities induced by the appropriation of metabolic processes. This new bio-based foundation challenges architects and designers to rethink the way in which architecture is imagined, represented and materialised. This paper presents developments in the speculative collaborative project Imprimer la lumière examining living bioluminescent bacterial substrates as an architectural building material. In order to appropriate the light performance of these living organisms, the paper asks how to characterise and control these within an architectural design context and reports on efforts to develop computational models for simulating the behaviour, growth rates and life span of living materials and interface these with architectural representational framework. Within nature, bioluminescence is predominantly produced by marine organisms. In this context, the emitted light is a chemical reaction, part of a metabolic system that needs to be sustained. Working with bioluminescence therefore implies taking into consideration the ecosystem in which the light-emitting metabolisms take place as much as their limited lifespan. As a consequence, time must be understood as a key dimension of the architectural design process and wet lab tools and critically implemented into the palette of architectural design instruments and protocols.This paper reports on the examination of how living materials and their environment can be represented, simulated and predicted as part of an eco-metabolistic model developing mechanisms of functionalising and steering a living architectural material.
... [14] pSVRAF pACYC184 with luxR of A. fischeri under the control of its own promoter inserted into the BamHI site, Cm r [15] Determination of AI Concentrations in the Samples of the A. logei Cell Culture Supernatant The concentration of AI in the solution was measured with a whole-cell lux biosensor E. coli MG1655 pVFR1 pSVRAF (with higher sensitivity to AI due to the enhanced content of the regulatory luxR gene from A. fischeri [16]) showing a dose-dependent increase in luminescence upon addition of AI at concentrations from 0.03 to 100 nM. Calibration was performed with use of 3OC6-HSL: the major AI of LuxR/LuxI-type QS in bacteria of the genus Aliivibrio [4,17]. ...
... Another mechanism occurs via the receptor LuxR, which can form the transcriptional activator for lux through binding of either C8HSL or 3OC6HSL. Different combinations of these autoinducers activate lux with different effectiveness 19 . A third mechanism arises through 3OC6HSL, which acts with LuxR to repress ainSR, apparently by binding upstream of its promoter, hence indirectly suppressing qrr 20,21 . ...
... Both strains lack the ability to synthesize C8HSL (due to ainS deletion) and 3OC6HSL (due to a frameshift in luxI). The two strains were derived (by addition of a transposon insertion in lonA) from the modified LuxR strains DC22 and DJ101, which express luxR from a constitutive promoter and luminesce strongly in response to C8HSL or 3OC6HSL respectively 19 . DC59 expresses luxR B , encoding a LuxR protein that more strongly activates ...
... Consistent with 20 , both C8HSL and C7HSL suppress mean qrr activity, with C8HSL effective at picomolar concentrations. The lux reporter is activated by 3OC6HSL and inhibited by C8HSL as expected 19 . Similarly 3OC6HSL and C7HSL have generally opposite effects on lux activity, with about 100 nM C7HSL sufficient to inhibit the lux response to 3OC6HSL. ...
Many pheromone sensing bacteria produce and detect more than one chemically distinct signal, or autoinducer. The pathways that detect these signals are typically noisy and interlocked through crosstalk and feedback. As a result, the sensing response of individual cells is described by statistical distributions that change under different combinations of signal inputs. Here we examine how signal crosstalk reshapes this response. We measure how combinations of two homoserine lactone (HSL) input signals alter the statistical distributions of individual cell responses in the AinS/R- and LuxI/R-controlled branches of the Vibrio fischeri bioluminescence pathway. We find that, while the distributions of pathway activation in individual cells vary in complex fashion with environmental conditions, these changes have a low-dimensional representation. For both the AinS/R and LuxI/R branches, the distribution of individual cell responses to mixtures of the two HSLs is effectively one-dimensional, so that a single tuning parameter can capture the full range of variability in the distributions. Combinations of crosstalking HSL signals extend the range of responses for each branch of the circuit, so that signals in combination allow population-wide distributions that are not available under a single HSL input. Dimension reduction also simplifies the problem of identifying the HSL conditions to which the pathways and their outputs are most sensitive. A comparison of the maximum sensitivity HSL conditions to actual HSL levels measured during culture growth indicates that the AinS/R and LuxI/R branches lack sensitivity to population density except during the very earliest and latest stages of growth respectively.
... LuxR was thus rationally engineered at position 46. Because of the tendency of LuxR-family transcription factors to aggregate in the absence of HSLs (Qin et al., 2000), no direct biochemical characterization of the binding affinity between LuxR and 3OC6-HSL has been reported, except for a roughly calculated dissociation constant retrieved from a model fitted to luminescence data (Colton et al., 2015). Here, we applied the rigid MBP technique, which has enabled the crystallization and structural determination of numerous proteins, to production of stable apo-LuxR. ...
LuxR, a bacterial quorum sensing-related transcription factor that responds to the signaling molecule 3-oxo-hexanoyl-homoserine lactone (3OC6-HSL). In this study, we employed molecular dynamics simulation and the Molecular Mechanics Generalized Born Surface Area (MM-GB/SA) method to rationally identify residues in Vibrio fischeri LuxR that are important for its interaction with 3OC6-HSL. Isoleucine-46 was selected for engineering as the key residue for interaction with 3OC6-HSL-LuxR-I46F would have the strongest binding energy to 3OC6-HSL and LuxR-I46R the weakest binding energy. Stable wild-type (WT) LuxR, I46F and I46R variants were produced in Escherichia coli (E. coli) in the absence of 3OC6-HSL by fusion with maltose-binding protein (MBP). Dissociation constants for 3OC6-HSL from MBP-fusions of WT-, I46F- and I46R-LuxR determined by surface plasmon resonance confirmed the binding affinity. We designed and constructed a novel whole-cell biosensor on the basis of LuxR-I46F in E. coli host cells with a reporting module that expressed green fluorescent protein. The biosensor had high sensitivity in response to the signaling molecule 3OC6-HSL produced by the target bacterial pathogen Yersinia pestis. Our work demonstrates a practical, generalizable framework for the rational design and adjustment of LuxR-family proteins for use in bioengineering and bioelectronics applications.
... The process of the AI-dependent activation of transcription by a LuxR-type protein can be described using dissociation equations as two sequential phenomena: the formation of the LuxR-AI complex, and its binding to the lux-box in the promoter region [19]. This model predicts an increase in sensitivity of the system to low concentrations of AI with a concentration increase in the LuxR protein in the cell. ...
Aliivibrio fischeri LuxR and Aliivibrio logei LuxR1 and LuxR2 regulatory proteins are quorum sensing transcriptional (QS) activators, inducing promoters of luxICDABEG genes in the presence of an autoinducer (3-oxo-hexanoyl-l-homoserine lactone). In the Aliivibrio cells, luxR genes are regulated by HNS, CRP, LitR, etc. Here we investigated the role of the luxR expression level in LuxI/R QS system functionality and improved the whole-cell biosensor for autoinducer detection. Escherichia coli-based bacterial lux-biosensors were used, in which Photorhabdus luminescensluxCDABE genes were controlled by LuxR-dependent promoters and luxR, luxR1, or luxR2 regulatory genes. We varied either the dosage of the regulatory gene in the cells using additional plasmids, or the level of the regulatory gene expression using the lactose operon promoter. It was shown that an increase in expression level, as well as dosage of the regulatory gene in biosensor cells, leads to an increase in sensitivity (the threshold concentration of AI is reduced by one order of magnitude) and to a two to threefold reduction in response time. The best parameters were obtained for a biosensor with an increased dosage of luxRA. fischeri (sensitivity to 3-oxo-hexanoyl-l-homoserine lactone reached 30–100 pM).
... So far, to our knowledge, TCSs have not been explicitly linked to quorum sensing by an endosymbiont, and ligand sensation by HKs is certainly not strictly required for quorum sensing (Colton et al. 2015;Urbanowski et al. 2004). However, TCSs should be expected to have a prominent role in intraspecies and interspecies communication by endosymbionts. ...
Bacteria inhabit diverse environments, including the inside of eukaryotic cells. While a bacterial invader may initially act as a parasite or pathogen, a subsequent mutualistic relationship can emerge in which the endosymbiotic bacteria and their host share metabolites. While the environment of the host cell provides improved stability when compared to an extracellular environment, the endosymbiont population must still cope with changing conditions, including variable nutrient concentrations, the host cell cycle, host developmental programs, and host genetic variation. Furthermore, the eukaryotic host can deploy mechanisms actively preventing a bacterial return to a pathogenic state. Many endosymbionts are likely to use two-component systems (TCSs) to sense their surroundings, and expanded genomic studies of endosymbionts should reveal how TCSs may promote bacterial integration with a host cell. We suggest that studying TCS maintenance or loss may be informative about the evolutionary pathway taken toward endosymbiosis, or even toward endosymbiont-to-organelle conversion.
... due to the removal of LuxR abundance assumption. Although a number of previous experimental works on the lux system showed a Hill coefficient around 1 or slightly lower in the tested conditions [20,33,37], in some works a higher number was reported [31,41]. While Hill coefficient values lower than 1 could be due to burden effects and/or violation of the LuxR abundance assumption, as described by the models illustrated in Sections 3.1.1 ...
... To our knowledge, this is the first study explicitly highlighting that a Hill coefficient greater than one could occur in absence of cooperative binding in the transcriptional activator. This effect was consistent with previously published experimental data from our group [31] and others [41], as well as novel preliminary experimental data explicitly measured in this work: the Hill coefficient of the output curve increased as a function of LuxR level. In our M1T model, an increase up to 2-fold was observed for the Hill coefficient compared to M1, which relied on a different assumption on HSL binding. ...
Accurate predictive mathematical models are urgently needed in synthetic biology to support the bottom-up design of complex biological systems, minimizing trial-and-error approaches. The majority of models used so far adopt empirical Hill functions to describe activation and repression in exogenously-controlled inducible promoter systems. However, such equations may be poorly predictive in practical situations that are typical in bottom-up design, including changes in promoter copy number, regulatory protein level, and cell load. In this work, we derived novel mechanistic steady-state models of the lux inducible system, used as case study, relying on different assumptions on regulatory protein (LuxR) and cognate promoter (Plux) concentrations, inducer-protein complex formation, and resource usage limitation. We demonstrated that a change in the considered model assumptions can significantly affect circuit output, and preliminary experimental data are in accordance with the simulated activation curves. We finally showed that the models are identifiable a priori (in the analytically tractable cases) and a posteriori, and we determined the specific experiments needed to parametrize them. Although a larger-scale experimental validation is required, in the future the reported models may support synthetic circuits output prediction in practical situations with unprecedented details.
