title: Modeling Cellular Noise Underlying Heterogeneous Cell Responses in the Epidermal Growth Factor Signaling Pathway.
abstract: Cellular heterogeneity, which plays an essential role in biological phenomena, such as drug resistance and migration, is considered to arise from intrinsic (i.e., reaction kinetics) and extrinsic (i.e., protein variability) noise in the cell. However, the mechanistic effects of these types of noise to determine the heterogeneity of signal responses have not been elucidated. Here, we report that the output of epidermal growth factor (EGF) signaling activity is modulated by cellular noise, particularly by extrinsic noise of particular signaling components in the pathway. We developed a mathematical model of the EGF signaling pathway incorporating regulation between extracellular signal-regulated kinase (ERK) and nuclear pore complex (NPC), which is necessary for switch-like activation of the nuclear ERK response. As the threshold of switch-like behavior is more sensitive to perturbations than the graded response, the effect of biological noise is potentially critical for cell fate decision. Our simulation analysis indicated that extrinsic noise, but not intrinsic noise, contributes to cell-to-cell heterogeneity of nuclear ERK. In addition, we accurately estimated variations in abundance of the signal proteins between individual cells by direct comparison of experimental data with simulation results using Apparent Measurement Error (AME). AME was constant regardless of whether the protein levels varied in a correlated manner, while covariation among proteins influenced cell-to-cell heterogeneity of nuclear ERK, suppressing the variation. Simulations using the estimated protein abundances showed that each protein species has different effects on cell-to-cell variation in the nuclear ERK response. In particular, variability of EGF receptor, Ras, Raf, and MEK strongly influenced cellular heterogeneity, while others did not. Overall, our results indicated that cellular heterogeneity in response to EGF is strongly driven by extrinsic noise, and that such heterogeneity results from variability of particular protein species that function as sensitive nodes, which may contribute to the pathogenesis of human diseases.
authors.affiliation: Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Suita, Osaka, Japan.
authors.forename: Kazunari
authors.initials: K
authors.lastname: Iwamoto
authors.affiliation: Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Suita, Osaka, Japan.
authors.forename: Yuki
authors.initials: Y
authors.lastname: Shindo
authors.affiliation: Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Suita, Osaka, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
authors.forename: Koichi
authors.initials: K
authors.lastname: Takahashi
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004815:Epidermal Growth Factor / Q000378:metabolism*; D048049:Extracellular Signal-Regulated MAP Kinases / Q000378:metabolism*; D005786:Gene Expression Regulation / Q000502:physiology; D006801:Humans; D020935:MAP Kinase Signaling System / Q000502:physiology*; D008954:Models, Biological; D015233:Models, Statistical; D022022:Nuclear Pore / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology
chemical_list: D004815:Epidermal Growth Factor; D048049:Extracellular Signal-Regulated MAP Kinases