ArticlePLoS computational biology2014
Loads bias genetic and signaling switches in synthetic and natural systems.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- MaxCal can infer models from coupled stochastic trajectories of gene expression and cell division.Biophysical journal · 2023Article
- Article
- Context-aware synthetic biology by controller design: Engineering the mammalian cell.Cell systems · 2021Review
- Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources.Life (Basel, Switzerland) · 2021Article
- Critical Comparison of MaxCal and Other Stochastic Modeling Approaches in Analysis of Gene Networks.Entropy (Basel, Switzerland) · 2021Article
- Trajectory-based energy landscapes of gene regulatory networks.Biophysical journal · 2021Article
- A Practical Step-by-Step Guide for Quantifying Retroactivity in Gene Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Exploring the intrinsic behaviour of multisite phosphorylation systems as part of signalling pathways.Journal of the Royal Society, Interface · 2018Article
- Building Predictive Models of Genetic Circuits Using the Principle of Maximum Caliber.Biophysical journal · 2017Article
- Hierarchical control of enzymatic actuators using DNA-based switchable memories.Nature communications · 2017Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms.
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