Digital signaling decouples activation probability and population heterogeneity

• Published in: eLife Vol. 4; p. e08931
• Main Authors: Kellogg, Ryan A, Tian, Chengzhe, Lipniacki, Tomasz, Quake, Stephen R, Tay, Savaş
• Format: Journal Article
• Language: English
• Published: England eLife Sciences Publications, Ltd 21.10.2015; eLife Sciences Publications Ltd
• Subjects: Animals; Cell Line; cell-to-cell heterogeneity; Computational and Systems Biology; digital signaling; Fibroblasts - physiology; Gene Expression Regulation; Immunology; innate immunity; Mice; Microfluidics; Models, Theoretical; NF-kappa B - metabolism; Signal Transduction; signaling dynamics; Single-Cell Analysis; systems biology; Time Factors; computational biology; systems biology; mouse; digital signaling; innate immunity; signaling dynamics; cell-to-cell heterogeneity; immunology; single-cell analysis
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/elife.08931

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.