Title | Expression variation and covariation impair analog and enable binary signaling control. |
Publication Type | Journal Article |
Year of Publication | 2018 |
Authors | Kovary KM, Taylor B, Zhao ML, Teruel MN |
Journal | Mol Syst Biol |
Volume | 14 |
Issue | 5 |
Pagination | e7997 |
Date Published | 2018 05 14 |
ISSN | 1744-4292 |
Keywords | Animals, Cell Differentiation, Cells, Cultured, Computer Simulation, Evaluation Studies as Topic, Extracellular Signal-Regulated MAP Kinases, Female, Gene Expression Regulation, Genetic Variation, Humans, Image Processing, Computer-Assisted, Models, Molecular, Ovum, Proteomics, Signal Transduction, Xenopus laevis |
Abstract | Due to noise in the synthesis and degradation of proteins, the concentrations of individual vertebrate signaling proteins were estimated to vary with a coefficient of variation (CV) of approximately 25% between cells. Such high variation is beneficial for population-level regulation of cell functions but abolishes accurate single-cell signal transmission. Here, we measure cell-to-cell variability of relative protein abundance using quantitative proteomics of individual eggs and cultured human cells and show that variation is typically much lower, in the range of 5-15%, compatible with accurate single-cell transmission. Focusing on bimodal ERK signaling, we show that variation and covariation in MEK and ERK expression improves controllability of the percentage of activated cells, demonstrating how variation and covariation in expression enables population-level control of binary cell-fate decisions. Together, our study argues for a control principle whereby low expression variation enables accurate control of analog single-cell signaling, while increased variation, covariation, and numbers of pathway components are required to widen the stimulus range over which external inputs regulate binary cell activation to enable precise control of the fraction of activated cells in a population. |
DOI | 10.15252/msb.20177997 |
Custom 1 | |
Alternate Journal | Mol. Syst. Biol. |
PubMed ID | 29759982 |
PubMed Central ID | PMC5951153 |
Grant List | P50 GM107615 / GM / NIGMS NIH HHS / United States R01 DK106241 / DK / NIDDK NIH HHS / United States S10 OD018073 / OD / NIH HHS / United States T32 HG000044 / HG / NHGRI NIH HHS / United States P30 DK116074 / DK / NIDDK NIH HHS / United States R01 DK101743 / DK / NIDDK NIH HHS / United States F32 DK114981 / DK / NIDDK NIH HHS / United States |