Fig 1.
Transcript Expression Profile of TGFBR1 and TGFBR2 in 1055 Cell Lines.
The transcript data for TGFBR1 and TGFBR2 were obtained from the Human Protein Atlas database version 22.0. The expression levels are represented in normalized transcripts per million (nTPM). (A) Histogram depicting the distribution of TGF-β receptors expression across various cell lines. (B) Imbalanced expression of TGFBR1 and TGFBR2 was observed in numerous cancer cell lines. Each dot in the plot represents the expression levels of TGFBR1 and TGFBR2 in one of the 1055 cell lines. Specific cell lines of interest are labeled as representatives.
Fig 2.
A minimal mathematical model predicts that TGF-β signaling activity is dictated by the type of TGF-β receptor in lower abundance.
(A) A minimal model of the TGF-β pathway with two reactions including the TGF-β ligand (L), which interact with type I receptor (R1) and type II receptor (R2) with a binding affinity (K1). The active ligand-receptor complex (LRC) phosphorylates the SMAD protein with an equilibrium coefficient (K2). TGF-β signaling activity (Sa) at the steady state can be analytically calculated with equations (refer to S1 File for model details and equation derivation). (B) The response profile of TGF-β signaling activity (Sa) at the steady state is shown in relation to a 2-dimensional matrix of TGFBR1 and TGFBR2 expression numbers spanning five orders of magnitude. K1 = 1000, K2 = 10. TGF-β ligand concentration is set to be 0.1 nM.
Fig 3.
Computational modeling of heterogeneous signaling responses in the variation space of TGF-β receptors and SMAD2 expression.
(A) Scheme of the extended TGF-β signaling model. The development of the extended model is described in the S1 File. (B) Heterogeneous expression of TGF-β receptors and SMAD2 is illustrated as points in 3 multi-dimensional spaces. The two magnified circles exemplify two possible expression profiles of TGFBR1, TGFBR2 and SMAD2. (C) Model predictions for normalized P-SMAD2 responses in the expression space of TGFBR1, TGFBR2 and SMAD2. Each scatter point indicates a random set of protein expression levels in the space. The point colors indicate the normalized P-SMAD2 responses (P-SMAD2/SMAD2). (D) Contour landscape of the normalized P-SMAD2 responses to the combinations of TGFBR1 and TGFBR2. The dashed line indicates relationship between the relative P-SMAD2 level and the receptors when equal amounts of each receptor are present. The abundances of TGFBR1 and TGFBR2 in HaCaT, RH-30 and HepG2 cell lines are mapped according to the relative expression data shown in Fig 3E and the measured HaCaT TGF-β receptor number shown in Fig B in S1 File. The dashed arrows indicate the directions of receptor changes. (E) TGF-β receptor expression profiles for HaCaT, RH-30 and HepG2 cell lines. Bars indicate expression levels of each receptor (normalized transcripts per million, nTPM). The data is based on the Human Protein Atlas database version 22.0.
Fig 4.
Different types of cells show distinct sensitivities to the knockdown of TGF-β receptors.
Each type of TGF-β receptors was knocked down to different levels using various concentrations of siRNA. The relative P-SMAD2 responses and TGF-β receptor expression levels at 1 h after 100 pM TGF-β stimulation were measured and normalized to the non-targeting control (ntc) siRNA sample in the same experiment. Each plot contains the quantified data from three biological replicates. Immunoblotting results from one representative experiment are shown below each plot. The expression levels of relative TGFBR1 and TGFBR2 are plotted as a function of siRNA concentration in Fig I in S1 File. The black curve represents the fitted Hill curve and the dashed lines indicate the mean fold change of TGF-β receptor leads to the half of the P-SMAD2 response in the ntc sample (EC50). A statistical analysis of the fitted EC50s from 3 experiments is shown in Fig J in S1 File.
Fig 5.
Model predictions for the correlation between the SMAD2 signaling responses and the expressions of TGF-β signaling proteins in single cells.
(A) Illustration of model simulations for the SMAD2 signaling response to the variations of protein expressions in single cells. (B) Model simulations for the correlation between SMAD2 N2C fold change response at 1 h after 100 pM TGF-β stimulation and the expression of TGFBR1, TGFBR2, SMAD2 at 0 h and negative feedback regulation (NFR) strength. (C) Model simulations for the correlation between SMAD2 N2C fold change response at 8 h after 100 pM TGF-β stimulation and the expression of TGFBR1, TGFBR2, SMAD2 at 0h and negative feedback regulation (NFR) strength. The correlations (R-values and p-values) in the plots were calculated with Pearson correlation coefficients.
Fig 6.
Model predictions for SMAD2 signaling responses with imbalanced expression of TGFBR1 and TGFBR2 in single cells.
(A) Model predicts that SMAD2 N2C fold change is correlated with TGFBR2 when TGFBR1 is expressed at a higher level than TGFBR2 in single cells (in this example, the average TGFBR1 to TGFBR2 expression ratio was set to 5). (B) Model predicts that SMAD2 N2C fold change is correlated with TGFBR1 when TGFBR1 is expressed at a lower level than TGFBR2 in single cells (in this example, the average TGFBR2 to TGFBR1 expression ratio was set to 5). The correlations (R-values and p-values) in the plots were quantified with Pearson correlation coefficients.
Fig 7.
SMAD2 signaling responses are highly correlated with the amount of TGF-β receptors in single cells when TGFBR1 and TGFBR2 are expressed at a similar level.
(A) Model prediction for the correlation between SMAD2 N2C fold change response at 1 h and the number of TGF-β receptors when TGFBR1 and TGFBR2 are expressed at a similar level in single cells. The protein abundance values for TGFBR1 and TGFBR2 were set to be the same in single cell simulations (TGFBR1 to TGFBR2 expression ratio is 1). (B) Schematic representation of the optoTGFBRs optogenetic system. The development of the optoTGFBRs system was described in a previous publication [42]. (C) Illustration for the co-expression of optoTGFBR1 and optoTGFBR2-tdTomato with a 2A peptide element (P2A). (D) Time course profiles of iRFP-SMAD2 N2C fold change responses in individual optoTGFBRs-HeLa cells (n = 102) upon one pulse of blue light stimulation. (E) Representative live-cell images of SMAD2 responses to one pulse of blue light stimulation in single cells. The red, green and blue arrows indicate cells that express optoTGFBR2-tdTomato receptor at a high, intermediate and low level, respectively. (F) The plot of iRFP-SMAD2 N2C fold change responses at 20 min versus the expression of optoTGFBR2-tdTomato before blue light stimulation (0 h) in optoTGFBRs-HeLa cells.(G) The plot of iRFP-SMAD2 N2C fold change responses at 1 h versus the expression of optoTGFBR2-tdTomato before blue light stimulation (0 h) in optoTGFBRs-HeLa cells. The correlations (R-values and p-values) in the plots were calculated with Pearson correlation coefficients.
Fig 8.
Relationship between SMAD2 signaling responses and optoTGFBR2 expression level in optoTGFBRs-HeLa cells with imbalanced expression of optoTGFBR1 and optoTGFBR2.
The plot shows the fold change response of iRFP-SMAD2 N2C at 1 h versus the expression of optoTGFBR2-tdTomato before blue light stimulation (0 h) in optoTGFBRs-HeLa cells with overexpression of optoTGFBR1 (A) or optoTGFBR2-tdTomato (B), respectively. Representative live-cell images of SMAD2 responses to one pulse of blue light stimulation are provided on the right for each condition. The correlations (R-values and p-values) in the plots were calculated with Pearson correlation coefficients.