(94c) Robustness of Cellular Signaling with Respect to Dosage
AIChE Annual Meeting
2019
2019 AIChE Annual Meeting
Regenerative Engineering Society
Regenerative Engineering: Substrate-Derived Control of Cellular Behavior
Monday, November 11, 2019 - 8:50am to 9:10am
Results: We measured gene expression of two Dl target genes: sna, which is on the ventral-most 20% of the embryo, and sog, which resides in a broad lateral region, in embryos carrying 1, 2, or 4 copies of dl. The gene expression boundaries have small, but detectable differences depending on dl dosage. However, naïve models of Dl distribution, which assume that Dl concentration globally scales with dl gene dosage, predict high sensitivity gene expression boundaries. This implies there must be mechanisms that alter the shape of the Dl gradient when dl dosage is perturbed. Previous work2,3 has suggested three such mechanisms: facilitated diffusion of Dl by Cact, saturation of active Toll receptors, and the presence of Dl/Cact complex in the nucleus. We perform a parameter screen using a mechanistic model of the Dl/Cact system to show that these mechanisms are together necessary for robustness of gene expression boundary with respect to dl dosage.
Conclusions: In the Dl gradient system, gene expression is robust due to the action of three mechanisms: facilitated diffusion, Toll receptor saturation, and the action of Dl/Cact complex in the nucleus. Morphogen gradients must be able to determine cell fates in a concentration-dependent fashion, while at the same time maintain robustness with respect to morphogen dose. The Dl/Cact system shows an example of this engineering principle. Ultimately, we may be able to use our engineering knowledge gained from the basic study of tissue patterning to benefit the field of regenerative medicine.
This research was supported by NSF CBET-1254344 and NIH R21HD092830.
References:
- Reeves, GT & Stathopoulos, A. Cold Spring Harb Perspect Biol (2009) 1: a000836.
- Carrell, SN et al. Development (2017) 144: 4450-4461.
- OâConnell, MD & Reeves GT. PLoS Comput. Biol. (2015) 11: e1004159.