Frequency-preference response in covalent modification cycles under substrate sequestration conditions

Juliana Reves Szemere, Horacio G. Rotstein, Alejandra C. Ventura

Research output: Contribution to journalArticlepeer-review

Abstract

Covalent modification cycles (CMCs) are basic units of signaling systems and their properties are well understood. However, their behavior has been mostly characterized in situations where the substrate is in excess over the modifying enzymes. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations, leading to substrate sequestration by the enzymes. In this enzyme-in-excess regime, CMCs have been shown to exhibit signal termination, the ability of the product to return to a stationary value lower than its peak in response to constant stimulation, while this stimulation is still active, with possible implications for the ability of systems to adapt to environmental inputs. We characterize the conditions leading to signal termination in CMCs in the enzyme-in-excess regime. We also demonstrate that this behavior leads to a preferred frequency response (band-pass filters) when the cycle is subjected to periodic stimulation, whereas the literature reports that CMCs investigated so far behave as low-pass filters. We characterize the relationship between signal termination and the preferred frequency response to periodic inputs and we explore the dynamic mechanism underlying these phenomena. Finally, we describe how the behavior of CMCs is reflected in similar types of responses in the cascades of which they are part. Evidence of protein abundance in vivo shows that enzymes and substrates are present in comparable concentrations, thus suggesting that signal termination and frequency-preference response to periodic inputs are also important dynamic features of cell signaling systems, which have been overlooked.

Original languageEnglish (US)
Article number32
Journalnpj Systems Biology and Applications
Volume7
Issue number1
DOIs
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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