Homeostasis of mRNA concentrations through coupling transcription, export, and degradation

Summary Many experiments showed that eukaryotic cells maintain a constant mRNA concentration upon various perturbations by actively regulating mRNA production and degradation rates, known as mRNA buffering. However, the underlying mechanism is still unknown. In this work, we unveil a mechanistic model of mRNA buffering: the releasing-shuttling (RS) model. The model incorporates two crucial proteins, X and Y, which play several roles, including transcription, decay, and export factors, in the different stages of mRNA metabolism. The RS model predicts the constant mRNA concentration under genome-wide genetic perturbations and cell volume changes, the slowed-down mRNA degradation after Pol II depletion, and the temporal transcription dynamics after exonuclease depletion, in agreement with multiple experiments. Finally, we present a list of X and Y candidates and propose an experimental method to identify X. Our work uncovers potentially universal pathways coupling transcription, export, and degradation that help cells maintain mRNA homeostasis.

We simulate the modified model in which two kinds of different k n (Eq.16 and 17) are introduced.At time 0, we deplete either 95% Xt or 99% Yt, and monitor the temporal changes of the total mRNA levels.The fold changes represent the relative values of the perturbed cells compared to those before the perturbation.

Figure S1 :
Figure S1: Models based on mRNA feedback cannot achieve mRNA buffering, related to Figure 1.(a) Schematic of the positive feedback model.mRNA is produced with rate k n , and then gets degraded.The solid arrow represents the positive regulation.The equation below illustrates a specific form of positive regulation, which is used in the simulations of (b) and (c).(b) In the positive feedback model, a positive correlation exists between the mRNA production rate and mRNA concentration when the mRNA production rate k n fluctuates.(c) In the positive feedback model, the mRNA production rate is uncorrelated with the mRNA concentration when the mRNA degradation rate β m c 2 m fluctuates by perturbing β m .(d) Schematic of the negative feedback model.The solid arrow represents the negative regulation.The equation below illustrates a specific form of negative regulation, which is used in the simulations of (e) and (f).(e) In the negative feedback model, a positive correlation exists between the mRNA production rate and mRNA concentration when the mRNA production rate k n = a/(c m + b) fluctuates by perturbing the parameter a. (f) In the negative feedback model, a negative correlation exists between the mRNA production rate and mRNA concentration when the mRNA degradation rate β m c 2 m fluctuates by perturbing β m .In all scenarios, the mRNA concentration is not strictly buffered.

Figure S2 :
FigureS2: Breakdown of mRNA buffering in the modified model where X is not necessary for transcription, related to Figure1.We simulate the modified model in which two kinds of different k n (Eq.16 and 17) are introduced.At time 0, we deplete either 95% Xt or 99% Yt, and monitor the temporal changes of the total mRNA levels.The fold changes represent the relative values of the perturbed cells compared to those before the perturbation.

Figure S3 :Figure S5 :
Figure S3: mRNA buffering is still valid in the modified model where Y also shuttles, related to Figure 1.(a) Schematic of the modified model.(b)The temporal change of mRNA concentration after the total number of X or Y is reduced.We simulated the modified model in which the dynamics of Y follows Eq. 26-28.At time 0, we depleted either 90% Xt or 90% Yt, and monitored the temporal changes of the total mRNA levels.The fold changes represent the relative values of the perturbed cells compared to those before the perturbation.

Figure S6 :Figure S7 :Figure S8 :
Figure S6: Relationship between Xp and mRNA production rate in the simulation, related to Figure 4. Xp initially decreases with a nearly constant rate until it hits the Michaelis-Menten constant K x , which triggers a significant decrease in the mRNA production rate.

Table S1 :
Candidates of X and Y in S. cerevisiae, related to Figure5.name Functions as Gene name Functions as Gene name Functions as Gene name Functions as