Toggle Switch Research Articles

Globally Monitoring Allosteric Coupling in the A2A Adenosine Receptor by NMR in Solution

In human G protein‐coupled receptors (GPCRs), drug binding near the extracellular region drives conformational changes over 30 Å away at the intracellular surface, leading to complex formation with partner proteins that initiate signaling. GPCR crystal structures have revealed the need for deeper understanding of conformational dynamics to describe mechanisms of allosteric coupling between the extracellular and intracellular surfaces.Using nuclear magnetic resonance (NMR) in solution, we provide a structural basis for allosteric coupling in the human A2A adenosine receptor (A2AAR), a validated drug target for Parkinson's disease and cancer co‐immunotherapies. Production of A2AAR in Pichia pastoris allowed stable‐isotope labeling with 2H,15N, and 13C, yielding reproducible high‐quality NMR correlation spectra. Assignment of endogenous tryptophans and glycines provided numerous probes distributed over the receptor intracelluar surface, extracellular surface, and transmembrane domain, enabling a global characterization of A2AAR responses to variable efficacy of bound drugs. The “toggle switch” Trp 2466.48 was especially sensitive to variable drug efficacy due to the changes in relative orientation of the nearby aromatic ring of Phe 2426.44 in the highly conserved Pro5.50‐Ile3.40‐Phe6.44 (P‐I‐F) activation motif, providing a highly responsive probe of changes in structure and dynamics upon agonist binding. The novel NMR probes also enabled us to observe ligand efficacy‐related local conformational polymorphisms near the intracellular surface.The distributed NMR probes were utilized to monitor the impact of a key mutation in the A2AAR allosteric center at Asp522.50. Amino acid replacement of Asp522.50 leads to immediate loss of intracellular signaling. In NMR studies, this mutation caused striking changes in conformational polymorphisms at the intracellular surface but did not alter response to drug efficacy at the extracellular surface. We correlated changes at the intracellular surface to structural rearrangements at Trp 2466.48 and the P‐I‐F motif, demonstrating an interplay between the allosteric center and Trp 2466.48, and providing novel insights into a signaling mechanism that may be applicable to a wide range of class A GPCRs.Support or Funding InformationAmerican Cancer Society (MTE)This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors.

SummaryAlthough the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors.

Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty

In applications, such as biomedicine and systems/synthetic biology, technical limitations in actuation complicate implementation of time-varying control signals. In order to alleviate some of these limitations, it may be desirable to derive simple control policies, such as step functions with fixed magnitude and length (or temporal pulses). In this technical note, we further develop a recently proposed pulse-based solution to the convergence problem, i.e., minimizing the convergence time to the target exponentially stable equilibrium, for monotone systems. In particular, we extend this solution to monotone systems with parametric uncertainty. Our solutions also provide worst case estimates on convergence times. Furthermore, we indicate how our tools can be used for a class of nonmonotone systems, and more importantly how these tools can be extended to other control problems. We illustrate our approach on switching under parametric uncertainty and regulation around a saddle point problems in a genetic toggle switch system.

Maximum Caliber Can Characterize Genetic Switches with Multiple Hidden Species.

Gene networks with feedback often involve interactions between multiple species of biomolecules, much more than experiments can actually monitor. Coupled with this is the challenge that experiments often measure gene expression in noisy fluorescence instead of protein numbers. How do we infer biophysical information and characterize the underlying circuits from this limited and convoluted data? We address this by building stochastic models using the principle of Maximum Caliber (MaxCal). MaxCal uses the basic information on synthesis, degradation, and feedback-without invoking any other auxiliary species and ad hoc reactions-to generate stochastic trajectories similar to those typically measured in experiments. MaxCal in conjunction with Maximum Likelihood (ML) can infer parameters of the model using fluctuating trajectories of protein expression over time. We demonstrate the success of the MaxCal + ML methodology using synthetic data generated from known circuits of different genetic switches: (i) a single-gene autoactivating circuit involving five species (including mRNA), (ii) a mutually repressing two-gene circuit (toggle switch) with seven species (including mRNA) considering stochastic time traces of two proteins, and (iii) the same toggle switch circuit considering stochastic time traces of only one of the two proteins. To further challenge the MaxCal + ML inference scheme, we repeat our analysis for the second and third scenario with traces expressed in noisy fluorescence instead of protein number to closely mimic typical experiments. We show that, for all of these models with increasing complexity and obfuscation, the minimal model of MaxCal is still able to capture the fluctuations of the trajectory and infer basic underlying rate parameters when benchmarked against the known values used to generate the synthetic data. Importantly, the model also yields an effective feedback parameter that can be used to quantify interactions within these circuits. These applications show the promise of MaxCal's ability to characterize circuits with limited data, and its utility to better understand evolution and advance design strategies for specific functions.

Effect of cell heterogeneity on isogenic populations with the synthetic genetic toggle switch network: Bifurcation analysis of two-dimensional cell population balance models

The dynamics of gene regulatory networks are often modeled with the assumption of cellular homogeneity. However, this assumption contradicts the plethora of experimental results in a variety of systems, which designates that cell populations are heterogeneous systems in the sense that properties such as size, shape, and DNA/RNA content are unevenly distributed amongst their individuals. In order to address the implications of heterogeneity, we utilize the so-called cell population balance (CPB) models. Here, we solve numerically multivariable CPB models to study the effect of heterogeneity on populations carrying the toggle switch network, which features nonlinear behavior at the single-cell level. In order to answer whether this nonlinear behavior is inherited to the heterogeneous population level, we perform bifurcation analysis on the steady-state solutions of the CPB model. We show that bistability is present at the population level with the pertinent bistability region shrinking when the impact of heterogeneity is enhanced.

Improving Medical Adherence using Smart Medicine Cabinet Monitoring System

<p>Patients at home may forget to take their medicines on time, miss doses or even take overdoses. This particularly applies to the elderly at home. Hence, this paper presents a monitoring system to improve the medical adherence which is based on Internet of Things (IoT) concept known as smart medicine cabinet monitoring system. The system is proposed to remind the elderly to take their medicines on time, to ensure that the elderly have taken their medicines and to notify the family member of the elderly about their medication intake. This paper presents a method of monitoring the medication intake of the elderly which is based on IoT concept to display the data on the web database. The system uses an Arduino microcontroller, a toggle switch, LCD Display, limit switch, alarm system and a Wi-Fi module. The developed system is seen to be another alternative that would help the elderly especially who are living alone for their medication adherence to home-based treatment.</p>

Adjusting Noise in the Genetic Toggle Switch through Stochastic Circuit Design

Bistable genetic circuits are important regulatory elements that can serve as biological switches. However, for a switch to function correctly, the noise inherent to the circuit needs to be taken into account, as it affects the robustness of the system. Using the example of a genetic toggle switch, we analyse the dependence of its intrinsic noise on the biochemical properties of the circuit. To that end, the circuit is described stochastically, and the variances of mRNA and protein fluctuations in each stable expression state are formulated as functions of relevant circuit parameters. This is done with the help of the linear noise approximation. As the obtained dependence is highly complex and difficult to interpret, simplified models with increasing complexity are analyzed successively. First, mRNA levels are eliminated assuming infinitely fast mRNA dynamics. Based on this model, influences of mutual inhibition dynamics and of the distribution of time-scales between the two gene expression systems are evaluated. By introducing translational bursts into the model, the interplay between mRNA and protein dynamics can be studied for quickly degrading mRNAs. Finally, special cases of the full stochastic model are discussed. Our results are verified by stochastic simulations and interpreted from a biological point of view. This enables to suggest genetic modifications for the targeted modulation of transition probabilities between distinct expression states.

Ligand-induced action of the W2866.48 rotamer toggle switch in the β2-adrenergic receptor.

Studies focused on GPCRs, particularly on the β2-adrenergic receptor (β2-AR), have demonstrated the relationship between ligand structure, receptor conformational changes and the corresponding pharmacological outcomes. Herein, we studied the molecular details of the rotameric flip of the W2866.48 sidechain, i.e. a presumed action switch that has not been reported in native β2-AR thus far. It is believed that although both the 'active' and 'inactive' conformers of β2-AR exhibit similar conformations of this switch, it may still play a substantial role in the ligand-induced activation of the receptor. By using both experimental methods (time-resolved fluorescence spectroscopy) and molecular modeling techniques (enhanced-sampling molecular dynamics), we characterized the conformational rearrangements of W2866.48 in relation to the type of ligand present in the binding cavity and to the conformation of the receptor ('active' vs. 'inactive' β2-AR). We found that the conformational behaviour of W2866.48 is correlated with the pharmacological character of the ligand present in the binding cavity but not with the instantaneous conformation of the receptor. Namely, agonists promote the W2866.48 conformations that facilitate the increase of the solvation within the inner receptor channel. In contrast, antagonists and inverse agonists act toward the decrease of the solvation in the inner channel. This creates an opportunity for using computational methodologies in determining the pharmacological properties of various ligands. The combination of the time-resolved fluorescence spectroscopy technique with the enhanced-sampling molecular dynamics simulations is shown to be a powerful tool for studying the ligand-induced conformational rearrangements in GPCRs.

Allosteric Coupling of Drug Binding and Intracellular Signaling in the A2A Adenosine Receptor

Signaling across cellular membranes, the 826 humanG protein-coupled receptors (GPCRs) govern a wide range of vital physiological processes, making GPCRs prominent drug targets. X-ray crystallography provided GPCR molecular architectures, which also revealed the need for additional structural dynamics data to support drug development. Here, nuclear magnetic resonance (NMR) spectroscopy with the wild-type-like A2A adenosine receptor (A2AAR) in solution provides a comprehensive characterization of signaling-related structural dynamics. All six tryptophan indole and eight glycine backbone 15N-1H NMR signals in A2AAR were individually assigned. These NMR probes provided insight into the role of Asp522.50 asan allosteric link between the orthosteric drug binding site and the intracellular signaling surface, revealing strong interactions with the toggle switch Trp 2466.48, and delineated the structural response to variable efficacy of bound drugs across A2AAR. The present data support GPCR signaling based on dynamic interactions between two semi-independent subdomains connected by an allosteric switch at Asp522.50.

Epigenetic control of pheromone MAPK signaling determines sexual fecundity in Candida albicans

Several pathogenic Candida species are capable of heritable and reversible switching between two epigenetic states, "white" and "opaque." In Candida albicans, white cells are essentially sterile, whereas opaque cells are mating-proficient. Here, we interrogate the mechanism by which the white-opaque switch regulates sexual fecundity and identify four genes in the pheromone MAPK pathway that are expressed at significantly higher levels in opaque cells than in white cells. These genes encode the β subunit of the G-protein complex (STE4), the pheromone MAPK scaffold (CST5), and the two terminal MAP kinases (CEK1/CEK2). To define the contribution of each factor to mating, C. albicans white cells were reverse-engineered to express elevated, opaque-like levels of these factors, either singly or in combination. We show that white cells co-overexpressing STE4, CST5, and CEK2 undergo mating four orders of magnitude more efficiently than control white cells and at a frequency approaching that of opaque cells. Moreover, engineered white cells recapitulate the transcriptional and morphological responses of opaque cells to pheromone. These results therefore reveal multiple bottlenecks in pheromone MAPK signaling in white cells and that alleviation of these bottlenecks enables efficient mating by these "sterile" cell types. Taken together, our findings establish that differential expression of several MAPK factors underlies the epigenetic control of mating in C. albicans We also discuss how fitness advantages could have driven the evolution of a toggle switch to regulate sexual reproduction in pathogenic Candida species.

Large Deviations for Gaussian Diffusions with Delay

Dynamical systems driven by nonlinear delay SDEs with small noise can exhibit important rare events on long timescales. When there is no delay, classical large deviations theory quantifies rare events such as escapes from metastable fixed points. Near such fixed points, one can approximate nonlinear delay SDEs by linear delay SDEs. Here, we develop a fully explicit large deviations framework for (necessarily Gaussian) processes $X_t$ driven by linear delay SDEs with small diffusion coefficients. Our approach enables fast numerical computation of the action functional controlling rare events for $X_t$ and of the most likely paths transiting from $X_0 = p$ to $X_T=q$. Via linear noise local approximations, we can then compute most likely routes of escape from metastable states for nonlinear delay SDEs. We apply our methodology to the detailed dynamics of a genetic regulatory circuit, namely the co-repressive toggle switch, which may be described by a nonlinear chemical Langevin SDE with delay.

Genetic toggle switch controlled by bacterial growth rate

BackgroundIn favorable conditions bacterial doubling time is less than 20 min, shorter than DNA replication time. In E. coli a single round of genome replication lasts about 40 min and it must be accomplished about 20 min before cell division. To achieve such fast growth rates bacteria perform multiple replication rounds simultaneously. As a result, when the division time is as short as 20 min E. coli has about 8 copies of origin of replication (ori) and the average copy number of the genes situated close to ori can be 4 times larger than those near the terminus of replication (ter). It implies that shortening of cell cycle may influence dynamics of regulatory pathways involving genes placed at distant loci.ResultsWe analyze this effect in a model of a genetic toggle switch, i.e. a system of two mutually repressing genes, one localized in the vicinity of ori and the other localized in the vicinity of ter. Using a stochastic model that accounts for cell growth and divisions we demonstrate that shortening of the cell cycle can induce switching of the toggle to the state in which expression of the gene placed near ter is suppressed. The toggle bistability causes that the ratio of expression of the competing genes changes more than two orders of magnitude for a two-fold change of the doubling time. The increasing stability of the two toggle states enhances system sensitivity but also its reaction time.ConclusionsBy fusing the competing genes with fluorescent tags this mechanism could be tested and employed to create an indicator of the doubling time. By manipulating copy numbers of the competing genes and locus of the gene situated near ter, one can obtain equal average expression of both genes for any doubling time T between 20 and 120 min. Such a toggle would accurately report departures of the doubling time from T.

Design of dynamic genetic memory.

In electronic systems, dynamic random access memory (DRAM) is one of the core modules in the modern silicon computer. As for a bio‐computer, one would need a mechanism for storage of bio‐information named ‘data’, which, in binary logic, has two levels, logical high and logical low, or in the normalised form, ‘1’ and ‘0’. This study proposes a possible genetic DRAM based on the modified electronic configuration, which uses the biological reaction to fulfil an equivalent RC circuit constituting a memory cell. The authors implement fundamental functions of the genetic DRAM by incorporating a genetic toggle switch for data hold. The results of simulation verify that the basic function can be used on a bio‐storage module for the future bio‐computer.

Balancing a genetic toggle switch by real-time feedback control and periodic forcing

Cybergenetics is a novel field of research aiming at remotely pilot cellular processes in real-time with to leverage the biotechnological potential of synthetic biology. Yet, the control of only a small number of genetic circuits has been tested so far. Here we investigate the control of multistable gene regulatory networks, which are ubiquitously found in nature and play critical roles in cell differentiation and decision-making. Using an in silico feedback control loop, we demonstrate that a bistable genetic toggle switch can be dynamically maintained near its unstable equilibrium position for extended periods of time. Importantly, we show that a direct method based on dual periodic forcing is sufficient to simultaneously maintain many cells in this undecided state. These findings pave the way for the control of more complex cell decision-making systems at both the single cell and the population levels, with vast fundamental and biotechnological applications.

Professor Thue W. Schwartz is the BCPT Nordic Prize Winner 2017 in Basic & Clinical Pharmacology & Toxicology.

Professor Thue W. Schwartz is the BCPT Nordic Prize Winner 2017 in Basic & Clinical Pharmacology & Toxicology.

An integrative circuit-host modelling framework for predicting synthetic gene network behaviours.

One fundamental challenge in synthetic biology is the lack of quantitative tools that accurately describe and predict the behaviours of engineered gene circuits. This challenge arises from multiple factors, among which the complex interdependence of circuits and their host is a leading cause. Here we present a gene circuit modelling framework that explicitly integrates circuit behaviours with host physiology through bidirectional circuit-host coupling. The framework consists of a coarse-grained but mechanistic description of host physiology that involves dynamic resource partitioning, multilayered circuit-host coupling including both generic and system-specific interactions, and a detailed kinetic module of exogenous circuits. We showed that, following training, the framework was able to capture and predict a large set of experimental data concerning the host and its foreign gene overexpression. To demonstrate its utility, we applied the framework to examine a growth-modulating feedback circuit whose dynamics is qualitatively altered by circuit-host interactions. Using an extended version of the framework, we further systematically revealed the behaviours of a toggle switch across scales from single-cell dynamics to population structure and to spatial ecology. This work advances our quantitative understanding of gene circuit behaviours and also benefits the rational design of synthetic gene networks.

Cell-cycle transitions: a common role for stoichiometric inhibitors.

The cell division cycle is the process by which eukaryotic cells replicate their chromosomes and partition them to two daughter cells. To maintain the integrity of the genome, proliferating cells must be able to block progression through the division cycle at key transition points (called "checkpoints") if there have been problems in the replication of the chromosomes or their biorientation on the mitotic spindle. These checkpoints are governed by protein-interaction networks, composed of phase-specific cell-cycle activators and inhibitors. Examples include Cdk1:Clb5 and its inhibitor Sic1 at the G1/S checkpoint in budding yeast, APC:Cdc20 and its inhibitor MCC at the mitotic checkpoint, and PP2A:B55 and its inhibitor, alpha-endosulfine, at the mitotic-exit checkpoint. Each of these inhibitors is a substrate as well as a stoichiometric inhibitor of the cell-cycle activator. Because the production of each inhibitor is promoted by a regulatory protein that is itself inhibited by the cell-cycle activator, their interaction network presents a regulatory motif characteristic of a "feedback-amplified domineering substrate" (FADS). We describe how the FADS motif responds to signals in the manner of a bistable toggle switch, and then we discuss how this toggle switch accounts for the abrupt and irreversible nature of three specific cell-cycle checkpoints.

Using Engineered Bacteria to Characterize Infection Dynamics and Antibiotic Effects In Vivo

Synthetic biology has focused on engineering microbes to synthesize useful products or to serve as living diagnostics and therapeutics. Here we utilize a host-derived Escherichia coli strain engineered with a genetic toggle switch as a research tool to examine invivo replicative states in a mouse model of chronic infection, and to compare invivo and invitro bacterial behavior. In contrast to the effect of antibiotics invitro, we find that the fraction of actively dividing bacteria remains relatively high throughout the course of a chronic infection invivo and increases in response to antibiotics. Moreover, the presence of non-dividing bacteria invivo does not necessarily lead to an antibiotic-tolerant infection, in contrast to expectations from invitro experiments. These results demonstrate the utility of engineered bacteria for querying pathogen behavior invivo, and the importance of validating invitro studies of antibiotic effects with invivo models.

A Tug-of-War Mechanism for Pattern Formation in a Genetic Network.

Synthesizing spatial patterns with genetic networks is an ongoing challenge in synthetic biology. A successful demonstration of pattern formation would imply a better understanding of systems in the natural world and advance applications in synthetic biology. In developmental systems, transient patterning may suffice in order to imprint instructions for long-term development. In this paper we show that transient but persistent patterns can emerge from a realizable synthetic gene network based on a toggle switch. We show that a bistable system incorporating diffusible molecules can generate patterns that resemble Turing patterns but are distinctly different in the underlying mechanism: diffusion of mutually inhibiting molecules creates a prolonged "tug-of-war" between patches of cells at opposing bistable states. The patterns are transient but longer wavelength patterns persist for extended periods of time. Analysis of a representative small scale model implies the eigenvalues of the persistent modes are just above the threshold of stability. The results are verified through simulation of biologically relevant models.

A study of comparative modelling, simulation and molecular dynamics of CXCR3 receptor with lipid bilayer

The G-coupled receptors seen on the cell surface are composites with a lipid bilayer. The chemokines are kind of G-coupled receptor which majorly involved in the activation and downstream signalling of the cell. In general, many G-coupled receptors lack their 3D structures which become a hurdle in the drug designing process. In this study, comparative modelling of the CXCR3 receptor was carried out, structure evaluation was done using various tools and softwares. Additionally, molecular dynamics and docking were performed to prove the structural quality and architecture. Interestingly, the studies like toggle switch mechanism, lipid dynamics, virtual screening were carried out to find the potent antagonist for the CXCR3 receptor. During virtual screening 14,303 similar molecules were retrieved among them only four compounds have an ability to interact with a crucial amino acid residue of an antagonist. Hence, these screened compounds can serve as a drug candidate for a CXCR3 receptor, but further in vitro and in vivo studies are ought to do to prove its same efficacy.