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

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 271
Author(s):  
Chentao Yong ◽  
Andras Gyorgy
Keyword(s):  
Cell Fate ◽  
Rational Design ◽  
Resource Competition ◽  
Dynamic Properties ◽  
Mechanistic Model ◽  
Robustness Analysis ◽  
System Level ◽  
Genetic Circuits ◽  
Scarce Resources ◽  
Genetic Systems

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.

scholarly journals Closed-Form Solution of Road Roughness-Induced Vehicle Energy Dissipation

2018 ◽  
Vol 86 (1) ◽  
Author(s):  
A. Louhghalam ◽  
M. Tootkaboni ◽  
T. Igusa ◽  
F. J. Ulm
Keyword(s):  
Energy Dissipation ◽  
Asymptotic Analysis ◽  
Closed Form ◽  
Dynamic Properties ◽  
Mechanistic Model ◽  
Closed Form Solution ◽  
Interaction Model ◽  
Form Solution ◽  
Dissipated Energy ◽  
Road Roughness

A major contributor to rolling resistance is road roughness-induced energy dissipation in vehicle suspension systems. We identify the parameters driving this dissipation via a combination of dimensional analysis and asymptotic analysis. We begin with a mechanistic model and basic random vibration theory to relate the statistics of road roughness profile and the dynamic properties of the vehicle to dissipated energy. Asymptotic analysis is then used to unravel the dependence of the dissipation on key vehicle and road characteristics. Finally, closed form expressions and scaling relations are developed that permit a straightforward application of the proposed road-vehicle interaction model for evaluating network-level environmental footprint associated with roughness-induced energy dissipation.

scholarly journals Resource Competition Shapes the Response of Genetic Circuits

2017 ◽  
Vol 6 (7) ◽  
pp. 1263-1272 ◽  
Author(s):  
Yili Qian ◽  
Hsin-Ho Huang ◽  
José I. Jiménez ◽  
Domitilla Del Vecchio
Keyword(s):  
Resource Competition ◽  
Genetic Circuits

scholarly journals Modelling co-translational dimerisation for programmable nonlinearity in synthetic biology

2020 ◽  
Author(s):  
Ruud Stoof ◽  
Ángel Goñi-Moreno
Keyword(s):  
Nonlinear Dynamics ◽  
Biological Networks ◽  
Rational Design ◽  
Fine Tuning ◽  
Genetic Circuits ◽  
On Demand ◽  
Regulatory Circuits ◽  
Protein Dimers ◽  
The Impact

AbstractNonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basics of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization—a well-known source of nonlinear dynamics. Specifically, our approach focusses on modelling co-translational dimerization: the formation of protein dimers during—and not after—translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e., post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in-vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.

Mutual Monitoring of Resources in an Enterprise Systems Program

2017 ◽  
Vol 48 (1) ◽  
pp. 100-115 ◽  
Author(s):  
Jamie Y. T. Chang
Keyword(s):  
Program Implementation ◽  
Resource Competition ◽  
Project Managers ◽  
Team Cognition ◽  
Resource Monitoring ◽  
Scarce Resources ◽  
Goal Interdependence ◽  
Positive Goal ◽  
Implementation Program ◽  
Individual Project

During the implementation of IT programs, competition among project managers for the scarce resources required for the completion of individual projects is a common phenomenon. To avoid such self-interested resource competition among individual project managers, according to agency theory, resource monitoring among project managers can serve as an effective management mechanism for effective resource conflict resolution within a program. Furthermore, team cognition theory suggests that an understanding of goals for each project among project managers can also serve as a solid foundation for effective resource monitoring. Social interdependence theory also suggests that positive goal interdependence among projects within a program can motivate project managers to engage in cooperative interactions, allowing them to accomplish individual project goals as well as the overall program's goals. Based on a survey of 146 enterprise system implementation programs, the results of this study confirm that mutual resource monitoring among project managers is positively associated with final program implementation efficiency. Goal understanding among project managers, as well as goal interdependence, is positively associated with the effectiveness of resource monitoring among project managers within the implementation program.

scholarly journals Winner-Takes-All Resource Competition Redirects Cascading Cell Fate Transitions

2020 ◽  
Author(s):  
Rong Zhang ◽  
Hanah Goetz ◽  
Juan Melendez-Alvarez ◽  
Jiao Li ◽  
Tian Ding ◽  
...  
Keyword(s):  
Cell Fate ◽  
Resource Competition ◽  
Synthetic Gene ◽  
Transition Path ◽  
Gene Circuits ◽  
Single Strain ◽  
Significant Challenge ◽  
Synthetic Gene Circuits ◽  
Winner Takes All

AbstractFailure of modularity remains a significant challenge for synthetic gene circuits assembled with tested modules as they often do not function as expected. Competition over shared limited gene expression resources is a crucial underlying reason. Here, we first built a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve two successive cell fate transitions. Interestingly, we found that the in vivo transition path was redirected as the activation of one switch always prevailed against the other instead of the theoretically expected coactivation. This qualitatively different type of resource competition between the two modules follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the modules. To decouple the resource competition, we constructed a two-strain circuit, which achieved successive activation and stable coactivation of the two switches. We unveiled a nonlinear resource competition within synthetic gene circuits and provided a division of labor strategy to minimize unfavorable effects.

scholarly journals Genome Architecture Leads a Bifurcation in Cell Identity

2017 ◽  
Author(s):  
Sijia Liu ◽  
Haiming Chen ◽  
Scott Ronquist ◽  
Laura Seaman ◽  
Nicholas Ceglia ◽  
...  
Keyword(s):  
Cell Fate ◽  
Human Fibroblasts ◽  
Biological Rhythms ◽  
System Level ◽  
Genome Architecture ◽  
Cell Identity ◽  
Cell Therapies ◽  
A Cell ◽  
Fate Decision ◽  
Myogenic Program

SUMMARYGenome architecture is important in transcriptional regulation and study of its features is a critical part of fully understanding cell identity. Altering cell identity is possible through overexpression of transcription factors (TFs); for example, fibroblasts can be reprogrammed into muscle cells by introducing MYOD1. How TFs dynamically orchestrate genome architecture and transcription as a cell adopts a new identity during reprogramming is not well understood. Here we show that MYOD1-mediated reprogramming of human fibroblasts into the myogenic lineage undergoes a critical transition, which we refer to as a bifurcation point, where cell identity definitively changes. By integrating knowledge of genome-wide dynamical architecture and transcription, we found significant chromatin reorganization prior to transcriptional changes that marked activation of the myogenic program. We also found that the local architectural and transcriptional dynamics of endogenous MYOD1 and MYOG reflected the global genomic bifurcation event. These TFs additionally participate in entrainment of biological rhythms. Understanding the system-level genome dynamics underlying a cell fate decision is a step toward devising more sophisticated reprogramming strategies that could be used in cell therapies.

scholarly journals The Effects of Ribosome Autocatalysis and Negative Feedback in Resource Competition

2016 ◽  
Author(s):  
Fiona Chandra ◽  
Domitilla Del Vecchio
Keyword(s):  
Steady State ◽  
Negative Feedback ◽  
Resource Competition ◽  
Mrna Level ◽  
Transient Behavior ◽  
Rrna Synthesis ◽  
Qualitative Behavior ◽  
Genetic Circuits ◽  
Synthetic Genes ◽  
State Models

Resource competition, and primarily competition for ribosomes, can lead to unexpected behavior of genetic circuits and has recently gained renewed attention with both experimental and theoretical studies. Current models studying the effects of resource competition assume a constant production of ribosomes and these models describe the experimental results well. However, ribosomes are also autocatalytic since they are partially made of protein and autocatalysis has been shown to have detrimental effects on a system's stability and robustness. Additionally, there are known feedback regulations on ribosome synthesis such as inhibition of rRNA synthesis via ppGpp. Here, we develop two-state models of ribosome and protein synthesis incorporating autocatalysis and feedback to investigate conditions under which these regulatory actions have a significant effect in situations of increased ribosome demand. Our modeling results indicate that for sufficiently low demand, defined by the mRNA level of synthetic genes, autocatalysis has little or no effect. However, beyond a certain demand level, the system goes through a transcritical bifurcation at which the only non-negative steady state is at zero ribosome concentration. The presence of negative feedback, in turn, can shift this point to higher demand values, thus restoring the qualitative behavior observed in a model with a constant ribosome production at low demand. However, autocatalysis affects the dynamics of the system and can lead to an overshoot in the temporal response of the synthetic genes to changes in induction level. Our results show that ribosome autocatalysis has a significant effect on the system robustness to increases in ribosome demand, however the existing negative feedback on ribosome production compensates for the effects of the necessary autocatalytic loop and restores the behavior seen in the system with constant ribosome production. These findings explain why previous models with constant ribosome production reproduce the steady state behavior well, however incorporating autocatalysis and feedback is needed to capture the transient behavior.

scholarly journals Novel tunable spatio-temporal patterns from a simple genetic oscillator circuit

2020 ◽  
Author(s):  
Guillermo Yáñez Feliú ◽  
Gonzalo Vidal ◽  
Macarena Muñoz Silva ◽  
Timothy J. Rudge
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Protein Degradation ◽  
Rational Design ◽  
Single Cells ◽  
Temporal Patterns ◽  
Ring Oscillator ◽  
Genetic Circuits ◽  
Growing Cell ◽  
Spatio Temporal

AbstractMulticellularity, the coordinated collective behaviour of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviours at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates travelling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the travelling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.

scholarly journals Rational Design of RNA Structures that Predictably Tune Eukaryotic Gene Expression

2017 ◽  
Author(s):  
Tim Weenink ◽  
Robert M. McKiernan ◽  
Tom Ellis
Keyword(s):  
Gene Expression ◽  
Rational Design ◽  
Rna Structures ◽  
Genetic Circuits ◽  
Protein Coding ◽  
Eukaryotic Gene Expression ◽  
Eukaryotic Gene ◽  
Engineering Projects ◽  
Fine Tune ◽  
Different Levels

AbstractPredictable tuning of gene expression is essential for engineering genetic circuits and for optimising enzyme levels in metabolic engineering projects. In bacteria, gene expression can be tuned at the stage of transcription, by exchanging the promoter, or at stage of translation by altering the ribosome binding site sequence. In eukaryotes, however, only promoter exchange is regularly used, as the tools to modulate translation are lacking. Working in S. cerevisiae yeast, we here describe how hairpin RNA structures inserted into the 5’ untranslated region (5’UTR) of mRNAs can be used to tune expression levels by altering the efficiency of translation initiation. We demonstrate a direct link between the calculated free energy of folding in the 5’UTR and protein abundance, and show that this enables rational design of hairpin libraries that give predicted expression outputs. Our approach is modular, working with different promoters and protein coding sequences, and it outperforms promoter mutation as a way to predictably generate a library where a protein is induced to express at a range of different levels. With this tool, computational RNA sequence design can be used to predictably fine-tune protein production, providing a new way to modulate gene expression in eukaryotes.

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