Abstract
Population averaging due to paracrine communication can arbitrarily reduce cellular response variability. Yet, variability is ubiquitously observed, suggesting limits to paracrine averaging. It remains unclear whether and how biological systems may be affected by such limits of paracrine signaling. To address this question, we quantify the signal and noise of Ca(2+) and ERK spatial gradients in response to an in vitro wound within a novel microfluidics-based device. We find that while paracrine communication reduces gradient noise, it also reduces the gradient magnitude. Accordingly we predict the existence of a maximum gradient signal to noise ratio. Direct in vitro measurement of paracrine communication verifies these predictions and reveals that cells utilize optimal levels of paracrine signaling to maximize the accuracy of gradient-based positional information. Our results demonstrate the limits of population averaging and show the inherent tradeoff in utilizing paracrine communication to regulate cellular response fidelity.
Highlights
Cellular variability is likely a biological trait with significant phenotypic consequences
We show that paracrine communication increases extracellular signal-regulated kinase (ERK) response fidelity using live single-cell quantitative fluorescent imaging of primary Ca2+ and secondary ERK responses downstream of P2YR and EGFR, respectively
Inhibiting EGFR with tryphostin AG1478 prevents ERK activation upon ATP addition showing that ERK activation depends on secreted epidermal growth factor (EGF) binding to EGFR (Wetzker and Bohmer, 2003)
Summary
Cellular variability is likely a biological trait with significant phenotypic consequences. Single-cell quantification of protein concentration variability between cells shows that the concentration of many signaling molecules can vary by ~25% (coefficient of variation) (Sigal et al, 2006; Bar-Even et al, 2006; Spencer et al, 2009). A large and rapidly growing body of single-cell transcriptomics experiments further demonstrates that cells homogeneous in ’type’ have substantially heterogeneous gene expression patterns (Junker and Van Oudenaarden, 2014). The origin of this cellular variability has been traced to fundamental properties of gene expression. Single-molecule kinetics regulates gene expression and, as a result, is an inherently stochastic process (Sanchez and Golding, 2013)
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