Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise
- Equal contributors
1 Dept. of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, New York, NY, 10029, USA
2 Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland
3 Dept. of Anatomy, Pathology, and Cell Biology, Thomas Jefferson University, Philadelphia, PA, 19107, USA
4 Dept. of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, 19716, USA
Citation and License
BMC Systems Biology 2012, 6:109 doi:10.1186/1752-0509-6-109Published: 24 August 2012
Cell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses.
We observe bimodal distributions of extracellular signal-regulated kinase (ERK) responses to epidermal growth factor (EGF) stimulation, which are generally thought to indicate bistable or ultrasensitive signaling behavior in single cells. Surprisingly, we find that a simple MAPK/ERK-cascade model with negative feedback that displays graded, analog ERK responses at a single cell level can explain the experimentally observed bimodality at the cell population level. Model analysis suggests that a conversion of graded input–output responses in single cells to digital responses at the population level is caused by a broad distribution of ERK pathway activation thresholds brought about by cell-to-cell variability in protein expression.
Our results show that bimodal signaling response distributions do not necessarily imply digital (ultrasensitive or bistable) single cell signaling, and the interplay between protein expression noise and network topologies can bring about digital population responses from analog single cell dose responses. Thus, cells can retain the benefits of robustness arising from negative feedback, while simultaneously generating population-level on/off responses that are thought to be critical for regulating cell fate decisions.