Interpreting Frequency Responses to Dose-Conserved Pulsatile Input Signals in Simple Cell Signaling Motifs

Abstract

Many hormones are released in pulsatile patterns. This pattern can be modified, for instance by changing pulse frequency, to encode relevant physiological information. Often other properties of the pulse pattern will also change with frequency. How do signaling pathways of cells targeted by these hormones respond to different input patterns? In this study, we examine how a given dose of hormone can induce different outputs from the target system, depending on how this dose is distributed in time. We use simple mathematical models of feedforward signaling motifs to understand how the properties of the target system give rise to preferences in input pulse pattern. We frame these problems in terms of frequency responses to pulsatile inputs, where the amplitude or duration of the pulses is varied along with frequency to conserve input dose. We find that the form of the nonlinearity in the steady state input-output function of the system predicts the optimal input pattern. It does so by selecting an optimal input signal amplitude. Our results predict the behavior of common signaling motifs such as receptor binding with dimerization, and protein phosphorylation. The findings have implications for experiments aimed at studying the frequency response to pulsatile inputs, as well as for understanding how pulsatile patterns drive biological responses via feedforward signaling pathways.

Multiscale mathematical modeling of the hypothalamo-pituitary-gonadal axis

“…We just point here that, to our knowledge, none of the biochemically-designed models can distinguish the effect of an increase in the cumulative dose of GnRH from that of a genuine frequency increase ("pure frequency effect" obtained by compensating the frequency for duration and/or amplitude of GnRH pulses). This ascertainment motivated us to study, in a very simplified setup (feedforward signaling motifs), how a given dose of hormone can induce different outputs from the target system, depending on how this dose is distributed in time [22] and we found that nonlinearity in the steady state input-output function of the system predicts the optimal input pattern. Understanding how such input-output functions can be an emergent property of realistic signaling networks remains a totally Beyond their purpose for basic research and mechanistic knowledge, dynamical models can also be used in the context of the HPG axis from the more practical viewpoint of data analysis, and especially for model-based analysis of time series.…”

Computational model of the dual action of PTH — Application to a rat model of osteoporosis

“…sen such that the AUC computed with the PK model, by means of Eq. 27, was preserved (Fletcher et al, 2014). As for intermittent administration, the frequency of the step function amounts to 24 hours, which is split up into a period τ on during which the concentration is fixed at C max PTH,ser , and a period τ off during which the concentration is fixed at C back PTH,ser , with τ on + τ off = 24 h. For defining the actual value of τ on , the requirement was considered that the exact function of C PTH,ser (t) and the corresponding step function must exhibit the same AUC.…”

Models in neuroendocrinology

“…The pulsatile patterning of GnRH is important not only for the secretion of LH and FSH but also for gene transcription. The effects of GnRH on transcription of LH and FSH display a bell-shaped frequency-response relationship, and a recent model suggests that this frequency decoding arises from the interplay of two transcription factors that interact co-operatively, -a phenomenon that may commonly arise as an emergent feature of signalling networks , 60, [99,100].…”