Dynamics robustness of cascading systems.

A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robust...

Full description

Bibliographic Details
Main Authors: Jonathan T Young, Tetsuhiro S Hatakeyama, Kunihiko Kaneko
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-03-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC5367838?pdf=render
id doaj-318d3e8c6a874bf38c6020ec9720e2c8
record_format Article
spelling doaj-318d3e8c6a874bf38c6020ec9720e2c82020-11-25T02:43:14ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582017-03-01133e100543410.1371/journal.pcbi.1005434Dynamics robustness of cascading systems.Jonathan T YoungTetsuhiro S HatakeyamaKunihiko KanekoA most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.http://europepmc.org/articles/PMC5367838?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Jonathan T Young
Tetsuhiro S Hatakeyama
Kunihiko Kaneko
spellingShingle Jonathan T Young
Tetsuhiro S Hatakeyama
Kunihiko Kaneko
Dynamics robustness of cascading systems.
PLoS Computational Biology
author_facet Jonathan T Young
Tetsuhiro S Hatakeyama
Kunihiko Kaneko
author_sort Jonathan T Young
title Dynamics robustness of cascading systems.
title_short Dynamics robustness of cascading systems.
title_full Dynamics robustness of cascading systems.
title_fullStr Dynamics robustness of cascading systems.
title_full_unstemmed Dynamics robustness of cascading systems.
title_sort dynamics robustness of cascading systems.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2017-03-01
description A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.
url http://europepmc.org/articles/PMC5367838?pdf=render
work_keys_str_mv AT jonathantyoung dynamicsrobustnessofcascadingsystems
AT tetsuhiroshatakeyama dynamicsrobustnessofcascadingsystems
AT kunihikokaneko dynamicsrobustnessofcascadingsystems
_version_ 1724770593961672704