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Spatio-temporal modeling of signaling protein recruitment to EGFR.

Hsieh MY, Yang S, Raymond-Stinz MA, Edwards JS, Wilson BS - BMC Syst Biol (2010)

Bottom Line: The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.

ABSTRACT

Background: A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results: The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCgamma1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions: Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

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Analysis and simulation of the reaction kinetics between the four adaptors and EGFR. (A-B) Membrane sheets were prepared from serum-starved, batimastat-treated A431 cells without (A) or with EGF stimulation (B). Sheets were labeled with 5 nm gold reagents recognizing Shc. Circles in (A, B) highlight Shc label on these membranes. Bars, 0.1 μm. (C-F) Quantitative values of Shc, Stat5, PLCγ1, and Grb2 immunogold labeling on 3 μm2 area of membrane, reported as an average of at least 10 membranes. Blots in C-F show results of fractionation experiments, where crude cytosol and membrane fractions were prepared, proteins separated by SDS-PAGE and membranes blotted for Shc, Stat5, PLCγ1 and Grb2. In (G-I), blots report co-precipitation of Shc, Stat5 and PLCγ1 with EGFR over a time course of EGF stimulation. Bands were quantified by densitometry and plotted as density of the bands. In (J-M), simulations of reaction kinetics between the four adaptors and EGFR using experiment-fitted values produce results (black solid line) similar to experimental data (grey dashed line).
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Figure 3: Analysis and simulation of the reaction kinetics between the four adaptors and EGFR. (A-B) Membrane sheets were prepared from serum-starved, batimastat-treated A431 cells without (A) or with EGF stimulation (B). Sheets were labeled with 5 nm gold reagents recognizing Shc. Circles in (A, B) highlight Shc label on these membranes. Bars, 0.1 μm. (C-F) Quantitative values of Shc, Stat5, PLCγ1, and Grb2 immunogold labeling on 3 μm2 area of membrane, reported as an average of at least 10 membranes. Blots in C-F show results of fractionation experiments, where crude cytosol and membrane fractions were prepared, proteins separated by SDS-PAGE and membranes blotted for Shc, Stat5, PLCγ1 and Grb2. In (G-I), blots report co-precipitation of Shc, Stat5 and PLCγ1 with EGFR over a time course of EGF stimulation. Bands were quantified by densitometry and plotted as density of the bands. In (J-M), simulations of reaction kinetics between the four adaptors and EGFR using experiment-fitted values produce results (black solid line) similar to experimental data (grey dashed line).

Mentions: In Figure 3, we report results of three complementary techniques to evaluate the time course and extent of recruitment of these four proteins to activated EGFR. Figure 3A-B demonstrate the use of membrane "rip-flips" and immunoelectron microscopy to document the recruitment of Shc to plasma membranes of EGF-treated A431 cells. In this assay, fixed membranes are incubated with saturating amounts of anti-Shc primary antibodies, followed by labeling with secondary antibodies conjugated to electron-dense 5 nm gold particles. Results of Shc recruitment over a time course of EGF stimulation are reported in the plot in Figure 3C (top), providing the average number of Shc in a 3 μm2 area of membrane before correction for an estimated labeling efficiency of 70%. With an approximate surface area of 1256 sq microns for the whole cell, this translates to about 69,000 Shc molecules associated with A431 membranes at 2 min of EGF treatment after accounting for underlabelling. The kinetics of Shc recruitment to the membrane compare favorably with the increase in Shc that coprecipitated with EGFR over the same time course (Figure 3G). Finally, we used cell fractionation methods to estimate the fraction of Shc molecules in both membrane and cytoplasmic pools (Figure 3C, bottom). Extrapolating from the value of 69,000 Shc on A431 cell membranes at 2 min of EGF, with another 50% in the cytosol, we arrive at an estimate of 138,000 total Shc in A431 cells. This process was repeated for the other 3 proteins (Figures 3D-I), generating estimated values of 141,000 Grb2, 148,000 Stat5 and 387,000 PLCγ1 per cell.


Spatio-temporal modeling of signaling protein recruitment to EGFR.

Hsieh MY, Yang S, Raymond-Stinz MA, Edwards JS, Wilson BS - BMC Syst Biol (2010)

Analysis and simulation of the reaction kinetics between the four adaptors and EGFR. (A-B) Membrane sheets were prepared from serum-starved, batimastat-treated A431 cells without (A) or with EGF stimulation (B). Sheets were labeled with 5 nm gold reagents recognizing Shc. Circles in (A, B) highlight Shc label on these membranes. Bars, 0.1 μm. (C-F) Quantitative values of Shc, Stat5, PLCγ1, and Grb2 immunogold labeling on 3 μm2 area of membrane, reported as an average of at least 10 membranes. Blots in C-F show results of fractionation experiments, where crude cytosol and membrane fractions were prepared, proteins separated by SDS-PAGE and membranes blotted for Shc, Stat5, PLCγ1 and Grb2. In (G-I), blots report co-precipitation of Shc, Stat5 and PLCγ1 with EGFR over a time course of EGF stimulation. Bands were quantified by densitometry and plotted as density of the bands. In (J-M), simulations of reaction kinetics between the four adaptors and EGFR using experiment-fitted values produce results (black solid line) similar to experimental data (grey dashed line).
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Figure 3: Analysis and simulation of the reaction kinetics between the four adaptors and EGFR. (A-B) Membrane sheets were prepared from serum-starved, batimastat-treated A431 cells without (A) or with EGF stimulation (B). Sheets were labeled with 5 nm gold reagents recognizing Shc. Circles in (A, B) highlight Shc label on these membranes. Bars, 0.1 μm. (C-F) Quantitative values of Shc, Stat5, PLCγ1, and Grb2 immunogold labeling on 3 μm2 area of membrane, reported as an average of at least 10 membranes. Blots in C-F show results of fractionation experiments, where crude cytosol and membrane fractions were prepared, proteins separated by SDS-PAGE and membranes blotted for Shc, Stat5, PLCγ1 and Grb2. In (G-I), blots report co-precipitation of Shc, Stat5 and PLCγ1 with EGFR over a time course of EGF stimulation. Bands were quantified by densitometry and plotted as density of the bands. In (J-M), simulations of reaction kinetics between the four adaptors and EGFR using experiment-fitted values produce results (black solid line) similar to experimental data (grey dashed line).
Mentions: In Figure 3, we report results of three complementary techniques to evaluate the time course and extent of recruitment of these four proteins to activated EGFR. Figure 3A-B demonstrate the use of membrane "rip-flips" and immunoelectron microscopy to document the recruitment of Shc to plasma membranes of EGF-treated A431 cells. In this assay, fixed membranes are incubated with saturating amounts of anti-Shc primary antibodies, followed by labeling with secondary antibodies conjugated to electron-dense 5 nm gold particles. Results of Shc recruitment over a time course of EGF stimulation are reported in the plot in Figure 3C (top), providing the average number of Shc in a 3 μm2 area of membrane before correction for an estimated labeling efficiency of 70%. With an approximate surface area of 1256 sq microns for the whole cell, this translates to about 69,000 Shc molecules associated with A431 membranes at 2 min of EGF treatment after accounting for underlabelling. The kinetics of Shc recruitment to the membrane compare favorably with the increase in Shc that coprecipitated with EGFR over the same time course (Figure 3G). Finally, we used cell fractionation methods to estimate the fraction of Shc molecules in both membrane and cytoplasmic pools (Figure 3C, bottom). Extrapolating from the value of 69,000 Shc on A431 cell membranes at 2 min of EGF, with another 50% in the cytosol, we arrive at an estimate of 138,000 total Shc in A431 cells. This process was repeated for the other 3 proteins (Figures 3D-I), generating estimated values of 141,000 Grb2, 148,000 Stat5 and 387,000 PLCγ1 per cell.

Bottom Line: The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.

ABSTRACT

Background: A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results: The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCgamma1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions: Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

Show MeSH
Related in: MedlinePlus