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2022 ◽  
Author(s):  
Pradyumna Harlapur ◽  
Atchuta Srinivas Duddu ◽  
Kishore Hari ◽  
Mohit Kumar Jolly

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications in understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between 'master regulators' of cell-fates can exhibit multistable dynamics, thus enabling multiple '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 network motifs has 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 network motifs in complex larger networks of varying sizes and connectivity and identify conditions under which these motifs maintain their canonical dynamical behavior, thus identifying hallmarks of their functional resilience. We show that the in-degree of a motif - defined as the number of incoming edges onto a motif - determines its functional properties. For a smaller in-degree, the functional traits for both these motifs (bimodality, pairwise correlation coefficient(s), and the frequency of 'single-positive' phenotypes) are largely conserved, but increasing the in-degree can lead to a divergence from their stand-alone behaviors. These observations offer insights into design principles of biological networks containing these network motifs, as well as help devise optimal strategies for integration of these motifs into larger synthetic networks.


2021 ◽  
Author(s):  
Irene de Cesare ◽  
Davide Salzano ◽  
Mario di Bernardo ◽  
Ludovic Renson ◽  
Lucia Marucci

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 modelling 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 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 a real experiment using an agent-based simulator describing cells 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.


2021 ◽  
Author(s):  
Kishore Hari ◽  
Varun Ullanat ◽  
Archana Balasubramanian ◽  
Aditi Gopalan ◽  
Mohit Kumar Jolly

Elucidating the principles of cellular decision-making is of fundamental importance. These decisions are often orchestrated by underlying regulatory networks. While we understand the dynamics of simple network motifs, how do large networks lead to a limited number of phenotypes, despite their complexity, remains largely elusive. Here, we investigate five different networks governing epithelial-mesenchymal plasticity and identified a latent design principles in their topology that limits their phenotypic repertoire - the presence of two 'teams' of nodes engaging in a mutually inhibitory feedback loop, forming a toggle switch. These teams are specific to these networks and directly shape the phenotypic landscape and consequently the frequency and stability of terminal phenotypes vs. the intermediary ones. Our analysis reveals that network topology alone can contain information about phenotypic distributions it can lead to, thus obviating the need to simulate them. We unravel topological signatures that can drive canalization of cell-fates during diverse decision-making processes.


Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3133
Author(s):  
Jamiree Harrison ◽  
Enoch Yeung

The genetic toggle switch is a well known model in synthetic biology that represents the dynamic interactions between two genes that repress each other. The mathematical models for the genetic toggle switch that currently exist have been useful in describing circuit dynamics in rapidly dividing cells, assuming fixed or time-invariant kinetic rates. There is a growing interest in being able to model and extend synthetic biological function for growth conditions such as stationary phase or during nutrient starvation. As cells transition from one growth phase to another, kinetic rates become time-varying parameters. In this paper, we propose a novel class of parameter varying nonlinear models that can be used to describe the dynamics of genetic circuits, including the toggle switch, as they transition from different phases of growth. We show that there exists unique solutions for this class of systems, as well as for a class of systems that incorporates the microbial phenomena of quorum sensing. Further, we show that the domain of these systems, which is the positive orthant, is positively invariant. We also showcase a theoretical control strategy for these systems that would grant asymptotic monostability of a desired fixed point. We then take the general form of these systems and analyze their stability properties through the framework of time-varying Koopman operator theory. A necessary condition for asymptotic stability is also provided as well as a sufficient condition for instability. A Koopman control strategy for the system is also proposed, as well as an analogous discrete time-varying Koopman framework for applications with regularly sampled measurements.


2021 ◽  
Author(s):  
Stuart Sevier ◽  
Sahand Hormoz

All biological processes ultimately come from physical interactions. The mechanical properties of DNA play a critical role in transcription. RNA polymerase can over or under twist DNA (referred to as DNA supercoiling) when it moves along a gene resulting in mechanical stresses in DNA that impact its own motion and that of other polymerases. For example, when enough supercoiling accumulates, an isolated polymerase halts and transcription stops. DNA supercoiling can also mediate non-local interactions between polymerases that shape gene expression fluctuations. Here, we construct a comprehensive model of transcription that captures how RNA polymerase motion changes the degree of DNA supercoiling which in turn feeds back into the rate at which polymerases are recruited and move along the DNA. Surprisingly, our model predicts that a group of three or more polymerases move together at a constant velocity and sustain their motion (forming what we call a polymeton) whereas one or two polymerases would have halted. We further show that accounting for the impact of DNA supercoiling on both RNA polymerase recruitment and velocity recapitulates empirical observations of gene expression fluctuations. Finally, we propose a mechanical toggle switch whereby interactions between genes are mediated by DNA twisting as opposed to proteins. Understanding the mechanical regulation of gene expression provides new insights into how endogenous genes can interact and informs the design of new forms of engineered interactions.


2021 ◽  
Vol 12 ◽  
Author(s):  
Ingrid Langer ◽  
Dorota Latek

Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP) are two neuropeptides that contribute to the regulation of intestinal motility and secretion, exocrine and endocrine secretions, and homeostasis of the immune system. Their biological effects are mediated by three receptors named VPAC1, VPAC2 and PAC1 that belong to class B GPCRs. VIP and PACAP receptors have been identified as potential therapeutic targets for the treatment of chronic inflammation, neurodegenerative diseases and cancer. However, pharmacological use of endogenous ligands for these receptors is limited by their lack of specificity (PACAP binds with high affinity to VPAC1, VPAC2 and PAC1 receptors while VIP recognizes both VPAC1 and VPAC2 receptors), their poor oral bioavailability (VIP and PACAP are 27- to 38-amino acid peptides) and their short half-life. Therefore, the development of non-peptidic small molecules or specific stabilized peptidic ligands is of high interest. Structural similarities between VIP and PACAP receptors are major causes of difficulties in the design of efficient and selective compounds that could be used as therapeutics. In this study we performed structure-based virtual screening against the subset of the ZINC15 drug library. This drug repositioning screen provided new applications for a known drug: ticagrelor, a P2Y12 purinergic receptor antagonist. Ticagrelor inhibits both VPAC1 and VPAC2 receptors which was confirmed in VIP-binding and calcium mobilization assays. A following analysis of detailed ticagrelor binding modes to all three VIP and PACAP receptors with molecular dynamics revealed its allosteric mechanism of action. Using a validated homology model of inactive VPAC1 and a recently released cryo-EM structure of active VPAC1 we described how ticagrelor could block conformational changes in the region of ‘tyrosine toggle switch’ required for the receptor activation. We also discuss possible modifications of ticagrelor comparing other P2Y12 antagonist – cangrelor, closely related to ticagrelor but not active for VPAC1/VPAC2. This comparison with inactive cangrelor could lead to further improvement of the ticagrelor activity and selectivity for VIP and PACAP receptor sub-types.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sangho Ji ◽  
Wonjin Yang ◽  
Wookyung Yu

AbstractThe cannabinoid receptor 1 (CB1) is a class A G-protein coupled receptor (GPCR) that can exert various effects on the human body through the endocannabinoid system. Understanding CB1 activation has many benefits for the medical use of cannabinoids. A previous study reported that CB1 has two notable residues referred to as the toggle switch, F3.36 and W6.48, which are important for its activation mechanism. We performed a molecular dynamics simulation with a mutation in the toggle switch to examine its role in active and inactive states. We also examined structural changes, the residue–residue interaction network, and the interaction network among helices and loops of wildtype and mutant CB1 for both activation states. As a result, we found that the energetic changes in the hydrogen-bond network of the Na+ pocket, extracellular N-terminus–TM2–ECL1–TM3 interface including D2.63–K3.28 salt-bridge, and extracellular ECL2–TM5–ECL3–TM6 interface directly linked to the toggle switch contribute to the stability of CB1 by the broken aromatic interaction of the toggle switch. It makes the conformation of inactive CB1 receptor to be unstable. Our study explained the role of the toggle switch regarding the energetic interactions related to the Na+ pocket and extracellular loop interfaces, which could contribute to a better understanding of the activation mechanism of CB1.


2021 ◽  
Author(s):  
Alicia Climent Catala ◽  
Thomas E Ouldridge ◽  
Guy-Bart V Stan ◽  
Wooli Bae

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 ca- pable 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 in- hibitory 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 cell-like con- ditions 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 ele- ment for nucleic acid networks in synthetic biology applications.


2021 ◽  
Vol 2096 (1) ◽  
pp. 012072
Author(s):  
N V Kim ◽  
V N Zhidkov ◽  
V V Polyansky

Abstract Algorithms for the organization of standalone operation of a robotic manipulator have been considered in this Article. The controls on the control panel of a man-made equipment piece have been the manipulated object. A robotic manipulator fitted with a control system, and a machine vision system, have been the subsystems under study. The robotic manipulator interacts with the objects to switch on and off a toggle switch, turn a rotary switch, press on a pushbutton, etc. Manipulating the objects in question involves assessing of their positions and orientations, which is achieved through the machine vision system. Coordinated operation of the subsystems is required to plan and to implement control of the manipulator, while taking into account positions of the objects relative to each other. A configuration of interactions between the manipulator and the control panel, a method for organizing coordinated functioning of the machine vision system when manipulating controls, which includes assessing positions of the object of interest relative to the robotic manipulator, and an algorithm for planning control based on artificial neural network technology have been presented in this Article.


2021 ◽  
Author(s):  
Davide Salzano ◽  
Davide Fiore ◽  
Mario di Bernardo

We address the problem of regulating and keeping at a desired balance the relative numbers between cells exhibiting a different phenotype within a monostrain microbial consortium. We propose a strategy based on the use of external control inputs, assuming each cell in the community is endowed with a reversible, bistable memory mechanism. Specifically, we provide a general analytical framework to guide the design of external feedback control strategies aimed at balancing the ratio between cells whose memory is stabilized at either one of two equilibria associated to different cell phenotypes. We demonstrate the stability and robustness properties of the control laws proposed and validate them in silico implementing the memory element via a genetic toggle-switch. The proposed control framework may be used to allow long term coexistence of different populations, with both industrial and biotechnological applications. Examples include consortia where each population produces a compound of interest or where one population supports the growth of the other which has the role of producing a desired molecule. As a representative example we consider the realistic agent-based implementation of our control strategy to enable cooperative bioproduction in microbial consortia.


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