Pattern Formation and Bistability in a Synthetic Intercellular Genetic Toggle.

Differentiation within multicellular organisms is a complex process that helps to establish spatial patterning and tissue formation within the body. Often, the differentiation of cells is governed by morphogens and intercellular signaling molecules that guide the fate of each cell, frequently using toggle-like regulatory components. Synthetic biologists have long sought to recapitulate patterned differentiation with engineered cellular communities, and various methods for differentiating bacteria have been invented. Here, we couple a synthetic corepressive toggle switch with intercellular signaling pathways to create a "quorum-sensing toggle". We show that this circuit not only exhibits population-wide bistability in a well-mixed liquid environment but also generates patterns of differentiation in colonies grown on agar containing an externally supplied morphogen. If coupled to other metabolic processes, circuits such as the one described here would allow for the engineering of spatially patterned, differentiated bacteria for use in biomaterials and bioelectronics.

Fluorine-19 labeling of the tryptophan residues in the G protein-coupled receptor NK1R using the 5-fluoroindole precursor in Pichia pastoris expression.

In NMR spectroscopy of biomolecular systems, the use of fluorine-19 probes benefits from a clean background and high sensitivity. Therefore, 19F-labeling procedures are of wide-spread interest. Here, we use 5-fluoroindole as a precursor for cost-effective residue-specific introduction of 5-fluorotryptophan (5F-Trp) into G protein-coupled receptors (GPCRs) expressed in Pichia pastoris. The method was successfully implemented with the neurokinin 1 receptor (NK1R). The 19F-NMR spectra of 5F-Trp-labeled NK1R showed one well-separated high field-shifted resonance, which was assigned by mutational studies to the "toggle switch tryptophan". Residue-selective labeling thus enables site-specific investigations of this functionally important residue. The method described here is inexpensive, requires minimal genetic manipulation and can be expected to be applicable for yeast expression of GPCRs at large.

Snapshot of the cannabinoid receptor 1-arrestin complex unravels the biased signaling mechanism.

Cannabis activates the cannabinoid receptor 1 (CB1), which elicits analgesic and emotion regulation benefits, along with adverse effects, via Gi and ß-arrestin signaling pathways. However, the lack of understanding of the mechanism of ß-arrestin-1 (ßarr1) coupling and signaling bias has hindered drug development targeting CB1. Here, we present the high-resolution cryo-electron microscopy structure of CB1-ßarr1 complex bound to the synthetic cannabinoid MDMB-Fubinaca (FUB), revealing notable differences in the transducer pocket and ligand-binding site compared with the Gi protein complex. ßarr1 occupies a wider transducer pocket promoting substantial outward movement of the TM6 and distinctive twin toggle switch rearrangements, whereas FUB adopts a different pose, inserting more deeply than the Gi-coupled state, suggesting the allosteric correlation between the orthosteric binding pocket and the partner protein site. Taken together, our findings unravel the molecular mechanism of signaling bias toward CB1, facilitating the development of CB1 agonists.

Automated Design of Synthetic Gene Circuits in the Presence of Molecular Noise.

Microorganisms (mainly bacteria and yeast) are frequently used as hosts for genetic constructs in synthetic biology applications. Molecular noise might have a significant effect on the dynamics of gene regulation in microbial cells, mainly attributed to the low copy numbers of mRNA species involved. However, the inclusion of molecular noise in the automated design of biocircuits is not a common practice due to the computational burden linked to the chemical master equation describing the dynamics of stochastic gene regulatory circuits. Here, we address the automated design of synthetic gene circuits under the effect of molecular noise combining a mixed integer nonlinear global optimization method with a partial integro-differential equation model describing the evolution of stochastic gene regulatory systems that approximates very efficiently the chemical master equation. We demonstrate the performance of the proposed methodology through a number of examples of relevance in synthetic biology, including different bimodal stochastic gene switches, robust stochastic oscillators, and circuits capable of achieving biochemical adaptation under noise.

The EGFR phosphatase RPTPγ is a redox-regulated suppressor of promigratory signaling.

Spatially organized reaction dynamics between proto-oncogenic epidermal growth factor receptor (EGFR) and protein tyrosine phosphatases determine EGFR phosphorylation dynamics in response to growth factors and thereby cellular behavior within developing tissues. We show that the reaction dynamics of mutual inhibition between RPTPγ phosphatase and autocatalytic ligandless EGFR phosphorylation enable highly sensitive promigratory EGFR signaling responses to subnanomolar EGF levels, when < 5% receptors are occupied by EGF. EGF thereby triggers an autocatalytic phospho-EGFR reaction by the initial production of small amounts of phospho-EGFR through transient, asymmetric EGF-EGFR2 dimers. Single cell RPTPγ oxidation imaging revealed that phospho-EGFR induces activation of NADPH oxidase, which in turn inhibits RPTPγ-mediated dephosphorylation of EGFR, tilting the autocatalytic RPTPγ/EGFR toggle switch reaction towards ligandless phosphorylated EGFR. Reversibility of this reaction to EGF is maintained by the constitutive phosphatase activity of endoplasmic reticulum-associated TCPTP. This RPTPγ/EGFR reaction at the plasma membrane causes promigratory signaling that is separated from proliferative signaling induced by accumulated, liganded, phosphorylated EGF-EGFR in endosomes. Accordingly, loss of RPTPγ results in constitutive promigratory signaling from phosphorylated EGFR monomers. RPTPγ is thus a suppressor of promigratory oncogenic but not of proliferative EGFR signaling.

Genetic circuits in microbial biosensors for heavy metal detection in soil and water.

With the rapid population growth, the world is witnessing an ever-increasing demand for energy and natural resources. Consequently, soil, air, and water are polluted with diverse pollutants, including heavy metals (HM). The detection of heavy metals is necessary to remediate them, which is achieved with biosensors. Initially, these HM were detected using atomic absorption spectroscopy (AAS), emission spectroscopy, mass spectrometry, gas chromatography etc., but these were costly and time consuming which further paved a way for microbe-based biosensors. The development of genetic circuits for microbe-based biosensors has become more popular in recent years for heavy metal detection. In this review, we have especially discussed the various types of genetic circuits such as toggle switches, logic gates, and amplification modules used in these biosensors as they are used to enhance sensitivity and specificity. Genetic circuits also allow for rapid and multiple analyte detection at the same time. The use of microbial biosensors for the detection of HM in the soil as well as the water is also described below. Although with a higher success rate than classical biosensors, these microbial biosensors still have some drawbacks like bioavailability and size of the analyte which are needed to be addressed.

Understanding the Dynamics of the Structural States of Cannabinoid Receptors and the Role of Different Modulators.

The cannabinoid receptors CB1R and CB2R are members of the G protein-coupled receptor (GPCR) family. These receptors have recently come to light as possible therapeutic targets for conditions affecting the central nervous system. However, because CB1R is known to have psychoactive side effects, its potential as a drug target is constrained. Therefore, targeting CB2R has become the primary focus of recent research. Using various molecular modeling studies, we analyzed the active, inactive, and intermediate states of both CBRs in this study. We conducted in-depth research on the binding properties of various groups of cannabinoid modulators, including agonists, antagonists, and inverse agonists, with all of the different conformational states of the CBRs. The binding effects of these modulators were studied on various CB structural features, including the movement of the transmembrane helices, the volume of the binding cavity, the internal fluids, and the important GPCR properties. Then, using in vitro experiments and computational modeling, we investigated how vitamin E functions as a lipid modulator to influence THC binding. This comparative examination of modulator binding to CBRs provides significant insight into the mechanisms of structural alterations and ligand affinity, which can directly help in the rational design of selective modulators that target either CB1R or CB2R.

Functional Resilience of Mutually Repressing Motifs Embedded in Larger Networks.

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications for understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between 'master regulators' of cell fates can exhibit multistable dynamics enabling "single-positive" phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two motifs have been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these motifs in complex larger networks of varying sizes and connectivity to identify hallmarks under which these motifs maintain their canonical dynamical behavior. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors. We also show that this decay can be exacerbated by adding self-inhibition but not self-activation loops on the 'master regulators'. These observations offer insights into the design principles of biological networks containing these motifs and can help devise optimal strategies for the integration of these motifs into larger synthetic networks.

Elucidation of partial activation of cannabinoid receptor type 2 and identification of potential partial agonists: Molecular dynamics simulation and structure-based virtual screening.

Cannabinoid receptor type 2 (CB2R) is a member of the class A G protein-coupled receptor (GPCRs) family and a component of the endocannabinoid system that is modulated by the psychoactive chemical from Cannabis sativa, partial agonist Δ9-tetrahydrocannabinol (Δ9-THC). Selective activation of CB2R allows for the treatment of inflammatory and immune-related conditions without the psychotropic effects of CB1R. While CB2R-selective agonists are available, CB2R partial agonists are scarce. Hence, the pharmacological difference between CB2R full agonists and partial agonists remains to be deciphered, prompting the search for novel partial agonists. Here, using an induced-fit docking approach, we built a partial agonist Δ9-THC bound CB2R system from the inactive CB2R structure (PDB ID: 5ZTY) and performed microsecond molecular dynamics (MD) simulations. The simulations reveal an upward shift of the "toggle switch" W6.48(258) and minor outward movement of the transmembrane helix 6 (TM6). Dynamic network model identifies a possible communication path between the ligand and the toggle switch" W6.48(258). Furthermore, to identify potential CB2R partial agonists, we conducted structure-based virtual screening of ZINC15 "Druglike" library containing 17,900742 compounds against 3 conformations derived from MD simulation of CB2R complexed with partial agonist Δ9-THC using Glide virtual screening protocol comprising various filters with increasing accuracy. Nine diverse compounds predicted to have high MM-GBSA binding energy scores and good ADMET properties (including high gastrointestinal absorption and low toxicity) are proposed as potential CB2R partial agonists.

Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks.

Control-Based Continuation (CBC) is a general and systematic method to carry out the bifurcation analysis of physical experiments. CBC does not rely on a mathematical model and thus overcomes the uncertainty introduced when identifying bifurcation curves indirectly through modeling and parameter estimation. We demonstrate, in silico, CBC applicability to biochemical processes by tracking the equilibrium curve of a toggle switch, which includes additive process noise and exhibits bistability. We compare the results obtained when CBC uses a model-free and model-based control strategy and show that both can track stable and unstable solutions, revealing bistability. We then demonstrate CBC in conditions more representative of an in vivo experiment using an agent-based simulator describing cell growth and division, cell-to-cell variability, spatial distribution, and diffusion of chemicals. We further show how the identified curves can be used for parameter estimation and discuss how CBC can significantly accelerate the prototyping of synthetic gene regulatory networks.

Building an RNA-Based Toggle Switch Using Inhibitory RNA Aptamers.

Synthetic RNA systems offer unique advantages such as faster response, increased specificity, and programmability compared to conventional protein-based networks. Here, we demonstrate an in vitro RNA-based toggle switch using RNA aptamers capable of inhibiting the transcriptional activity of T7 or SP6 RNA polymerases. The activities of both polymerases are monitored simultaneously by using Broccoli and malachite green light-up aptamer systems. In our toggle switch, a T7 promoter drives the expression of SP6 inhibitory aptamers, and an SP6 promoter expresses T7 inhibitory aptamers. We show that the two distinct states originating from the mutual inhibition of aptamers can be toggled by adding DNA sequences to sequester the RNA inhibitory aptamers. Finally, we assessed our RNA-based toggle switch in degrading conditions by introducing controlled degradation of RNAs using a mix of RNases. Our results demonstrate that the RNA-based toggle switch could be used as a control element for nucleic acid networks in synthetic biology applications.

Monostability and bistability of biological switches.

Cell-fate transition can be modeled by ordinary differential equations (ODEs) which describe the behavior of several molecules in interaction, and for which each stable equilibrium corresponds to a possible phenotype (or 'biological trait'). In this paper, we focus on simple ODE systems modeling two molecules which each negatively (or positively) regulate the other. It is well-known that such models may lead to monostability or multistability, depending on the selected parameters. However, extensive numerical simulations have led systems biologists to conjecture that in the vast majority of cases, there cannot be more than two stable points. Our main result is a proof of this conjecture. More specifically, we provide a criterion ensuring at most bistability, which is indeed satisfied by most commonly used functions. This includes Hill functions, but also a wide family of convex and sigmoid functions. We also determine which parameters lead to monostability, and which lead to bistability, by developing a more general framework encompassing all our results.

Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources.

While the vision of synthetic biology is to create complex genetic systems in a rational fashion, system-level behaviors are often perplexing due to the context-dependent dynamics of modules. One major source of context-dependence emerges due to the limited availability of shared resources, coupling the behavior of disconnected components. Motivated by the ubiquitous role of toggle switches in genetic circuits ranging from controlling cell fate differentiation to optimizing cellular performance, here we reveal how their fundamental dynamic properties are affected by competition for scarce resources. Combining a mechanistic model with nullcline-based stability analysis and potential landscape-based robustness analysis, we uncover not only the detrimental impacts of resource competition, but also how the unbalancedness of the switch further exacerbates them. While in general both of these factors undermine the performance of the switch (by pushing the dynamics toward monostability and increased sensitivity to noise), we also demonstrate that some of the unwanted effects can be alleviated by strategically optimized resource competition. Our results provide explicit guidelines for the context-aware rational design of toggle switches to mitigate our reliance on lengthy and expensive trial-and-error processes, and can be seamlessly integrated into the computer-aided synthesis of complex genetic systems.

Operating principles of circular toggle polygons.

Decoding the dynamics of cellular decision-making and cell differentiation is a central question in cell and developmental biology. A common network motif involved in many cell-fate decisions is a mutually inhibitory feedback loop between two self-activating 'master regulators' A and B, also called as toggle switch. Typically, it can allow for three stable states-(high A, low B), (low A, high B) and (medium A, medium B). A toggle triad-three mutually repressing regulators A, B and C, i.e. three toggle switches arranged circularly (between A and B, between B and C, and between A and C)-can allow for six stable states: three 'single positive' and three 'double positive' ones. However, the operating principles of larger toggle polygons, i.e. toggle switches arranged circularly to form a polygon, remain unclear. Here, we simulate using both discrete and continuous methods the dynamics of different sized toggle polygons. We observed a pattern in their steady state frequency depending on whether the polygon was an even or odd numbered one. The even-numbered toggle polygons result in two dominant states with consecutive components of the network expressing alternating high and low levels. The odd-numbered toggle polygons, on the other hand, enable more number of states, usually twice the number of components with the states that follow 'circular permutation' patterns in their composition. Incorporating self-activations preserved these trends while increasing the frequency of multistability in the corresponding network. Our results offer insights into design principles of circular arrangement of regulatory units involved in cell-fate decision making, and can offer design strategies for synthesizing genetic circuits.

Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer.

Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.

Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae.

Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

Multi-stability in cellular differentiation enabled by a network of three mutually repressing master regulators.

Identifying the design principles of complex regulatory networks driving cellular decision-making remains essential to decode embryonic development as well as enhance cellular reprogramming. A well-studied network motif involved in cellular decision-making is a toggle switch-a set of two opposing transcription factors A and B, each of which is a master regulator of a specific cell fate and can inhibit the activity of the other. A toggle switch can lead to two possible states-(high A, low B) and (low A, high B)-and drives the 'either-or' choice between these two cell fates for a common progenitor cell. However, the principles of coupled toggle switches remain unclear. Here, we investigate the dynamics of three master regulators A, B and C inhibiting each other, thus forming three-coupled toggle switches to form a toggle triad. Our simulations show that this toggle triad can lead to co-existence of cells into three differentiated 'single positive' phenotypes-(high A, low B, low C), (low A, high B, low C) and (low A, low B, high C). Moreover, the hybrid or 'double positive' phenotypes-(high A, high B, low C), (low A, high B, high C) and (high A, low B, high C)-can coexist together with 'single positive' phenotypes. Including self-activation loops on A, B and C can increase the frequency of 'double positive' states. Finally, we apply our results to understand cellular decision-making in terms of differentiation of naive CD4+ T cells into Th1, Th2 and Th17 states, where hybrid Th1/Th2 and hybrid Th1/Th17 cells have been reported in addition to the Th1, Th2 and Th17 ones. Our results offer novel insights into the design principles of a multi-stable network topology and provide a framework for synthetic biology to design tristable systems.

Inducible Expression Systems Based on Xenogeneic Silencing and Counter-Silencing and Design of a Metabolic Toggle Switch.

Inducible expression systems represent key modules in regulatory circuit design and metabolic engineering approaches. However, established systems are often limited in terms of applications due to high background expression levels and inducer toxicity. In bacteria, xenogeneic silencing (XS) proteins are involved in the tight control of horizontally acquired, AT-rich DNA. The action of XS proteins may be opposed by interference with a specific transcription factor, resulting in the phenomenon of counter-silencing, thereby activating gene expression. In this study, we harnessed this principle for the construction of a synthetic promoter library consisting of phage promoters targeted by the Lsr2-like XS protein CgpS of Corynebacterium glutamicum. Counter-silencing was achieved by inserting the operator sequence of the gluconate-responsive transcription factor GntR. The GntR-dependent promoter library is comprised of 28 activated and 16 repressed regulatory elements featuring effector-dependent tunability. For selected candidates, background expression levels were confirmed to be significantly reduced in comparison to established heterologous expression systems. Finally, a GntR-dependent metabolic toggle switch was implemented in a C. glutamicum l-valine production strain allowing the dynamic redirection of carbon flux between biomass and product formation.

Dosage Sensing, Threshold Responses, and Epigenetic Memory: A Systems Biology Perspective on Random X-Chromosome Inactivation.

X-chromosome inactivation ensures dosage compensation between the sexes in mammals by randomly choosing one out of the two X chromosomes in females for inactivation. This process imposes a plethora of questions: How do cells count their X chromosome number and ensure that exactly one stays active? How do they randomly choose one of two identical X chromosomes for inactivation? And how do they stably maintain this state of monoallelic expression? Here, different regulatory concepts and their plausibility are evaluated in the context of theoretical studies that have investigated threshold behavior, ultrasensitivity, and bistability through mathematical modeling. It is discussed how a twofold difference between a single and a double dose of X-linked genes might be converted to an all-or-nothing response and how mutually exclusive expression can be initiated and maintained. Finally, candidate factors that might mediate the proposed regulatory principles are reviewed.

Facts and conjectures on calmodulin and its cousin proteins, parvalbumin and troponin C.

This review aims at giving a rational frame to understand the diversity of EF hand containing calcium binding proteins and their roles, with special focus on three members of this huge protein family, namely calmodulin, troponin C and parvalbumin. We propose that these proteins are members of structured macromolecular complexes, termed calcisomes, which constitute building devices allowing treatment of information within eukaryotic cells and namely calcium signals encoding and decoding, as well as control of cytosolic calcium levels in resting cells. Calmodulin is ubiquitous, present in all eukaryotic cells, and pleiotropic. This may be explained by its prominent role in regulating calcium movement in and out of the cell, thus maintaining calcium homeostasis which is fundamental for cell survival. The protein is further involved in decoding transient calcium signals associated with calcium movements after cell stimulation. We will show that the specificity of calmodulin's actions may be more easily explained if one considers its role in the light of calcisomes. Parvalbumin should not be considered as a simple intracellular calcium buffer. It is also a key factor for regulating calcium homeostasis in specific cells that need a rapid retrocontrol of calcium transients, such as fast muscle fibers. Finally, we propose that troponin C, with its four calcium binding domains distributed between two lobes presenting different calcium binding kinetics, exhibits all the characteristics needed to trigger and then post modulate muscle contraction and thus appears as a typical Feed Forward Loop system. If the present conjectures prove accurate, the way will be paved for a new pharmacology targeting the cell calcium signaling machinery. This article is part of a Special Issue entitled: ECS Meeting edited by Claus Heizmann, Joachim Krebs and Jacques Haiech.