Basal leakage in oscillation: Coupled transcriptional and translational control using feed-forward loops

Abstract

The circadian clock is a complex system that plays many important roles in most organisms. Previously, many mathematical models have been used to sharpen our understanding of the Arabidopsis clock, which brought to light the roles of each transcriptional and post-translational regulations. However, the presence of both regulations, instead of either transcription or post-translation, raised curiosity of whether the combination of these two regulations is important for the clock’s system. In this study, we built a series of simplified oscillators with different regulations to study the importance of post-translational regulation (specifically, 26S proteasome degradation) in the clock system. We found that a simple transcriptional-based oscillator can already generate sustained oscillation, but the oscillation can be easily destroyed in the presence of transcriptional leakage. Coupling post-translational control with transcriptional-based oscillator in a feed-forward loop will greatly improve the robustness of the oscillator in the presence of basal leakage. Using these general models, we were able to replicate the increased variability observed in the E3 ligase mutant for both plant and mammalian clocks. With this insight, we also predict a plausible regulator of several E3 ligase genes in the plant’s clock. Thus, our results provide insights into and the plausible importance in coupling transcription and post-translation controls in the clock system.

Noise response in monomolecular closed systems

“…For a given topology, when the exact direction of change is not specified by the theory, Monte Carlo (MC) methods can be used to sample the parameter space and to estimate the distribution of response patterns leading to the most probable outcome. This can be done by sampling random parameters for a given total number of species, calculating steady-state composition, calculating S in Equation ( 12), and applying the rules in Equations ( 15) and (16). Values of p i and p k can also be calculated and considered for better response estimates.…”

“…Presently, efforts are being made to associate noise in biological systems with diseases, to develop theories and software, and to explain biological phenomena. [ 9–20 ]…”

“…Presently, efforts are being made to associate noise in biological systems with diseases, to develop theories and software, and to explain biological phenomena. [9][10][11][12][13][14][15][16][17][18][19][20] Responses of biological networks to various stimulants and perturbations can be calculated, given network structure, parameters, and initial conditions. [21][22][23][24][25] However, parameter sets are rarely available.…”

Localization of Noise in Biochemical Networks

“…By so doing, conclusions can be deduced based on the most probable and consistent outcome, assuming that the generally robust nature of biological systems implies considerable independence in system behavior. 47 − 50 This approach is time-consuming and does not necessarily generate correct results. With many possible parameter sets, sensitivity is often studied with statistical quantities only.…”

“…The study of biological noise using numerical approaches, like all dynamic simulations, requires data for initial conditions and rate constants, which can sometimes be estimated by fitting. − However, available data are usually insufficient to constrain parameters. − In this case, one possible approach is to randomly draw parameters from a physically meaningful range and to perform simulations for all combinations of those parameters. By so doing, conclusions can be deduced based on the most probable and consistent outcome, assuming that the generally robust nature of biological systems implies considerable independence in system behavior. − This approach is time-consuming and does not necessarily generate correct results. With many possible parameter sets, sensitivity is often studied with statistical quantities only. − In any case, it is highly desirable to obtain properties of a system without knowing the actual parameters.…”