A modular approach for modeling the cell cycle based on functional response curves

PLoS Comput Biol. 2021 Aug 11;17(8):e1009008. doi: 10.1371/journal.pcbi.1009008. eCollection 2021 Aug.

Abstract

Modeling biochemical reactions by means of differential equations often results in systems with a large number of variables and parameters. As this might complicate the interpretation and generalization of the obtained results, it is often desirable to reduce the complexity of the model. One way to accomplish this is by replacing the detailed reaction mechanisms of certain modules in the model by a mathematical expression that qualitatively describes the dynamical behavior of these modules. Such an approach has been widely adopted for ultrasensitive responses, for which underlying reaction mechanisms are often replaced by a single Hill function. Also time delays are usually accounted for by using an explicit delay in delay differential equations. In contrast, however, S-shaped response curves, which by definition have multiple output values for certain input values and are often encountered in bistable systems, are not easily modeled in such an explicit way. Here, we extend the classical Hill function into a mathematical expression that can be used to describe both ultrasensitive and S-shaped responses. We show how three ubiquitous modules (ultrasensitive responses, S-shaped responses and time delays) can be combined in different configurations and explore the dynamics of these systems. As an example, we apply our strategy to set up a model of the cell cycle consisting of multiple bistable switches, which can incorporate events such as DNA damage and coupling to the circadian clock in a phenomenological way.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Cycle / genetics
  • Cell Cycle / physiology*
  • Cell Cycle Checkpoints / genetics
  • Cell Cycle Checkpoints / physiology
  • Cell Cycle Proteins / genetics
  • Cell Cycle Proteins / physiology
  • Computational Biology
  • Computer Simulation
  • DNA Damage
  • Humans
  • Kinetics
  • Models, Biological*
  • Systems Biology

Substances

  • Cell Cycle Proteins

Grants and funding

This work was supported by the Research Foundation Flanders (FWO, www.fwo.be) with individual support to J.D.B. (1189120N) and J.R. (11D0920N) and project support to L.G. (Grant GOA5317N) and the KU Leuven Research Fund (No. C14/18/084) to L.G. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.