The Switch to Mate
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| Two haploid yeast cells of opposite mating types secrete pheromones, grow projections and mate. (Wikipedia) |
Many vital eukaryotic cellular functions require cells to respond to a directional gradient of a signaling molecule. The first two steps in any eukaryotic chemotactic/chemotropic pathway are gradient detection and cell polarization. Like many processes, such chemotactic and chemotropic decisions are made using a relatively small number of molecules and are thus susceptible to internal and external fluctuations during signal transduction. Large cell-to-cell variations in the magnitude and direction of a response are therefore possible and do, in fact, occur in natural systems. One very interesting and complex example to this kind of cellular response in a noisy environment is the mating of two yeast cells (Saccharomyces cerevisiae).
In their recent work, Drs. Rati Sharma and Elijah Roberts from the Johns Hopkins Biophysics Department use 3D probabilistic modeling of a simple gradient sensing pathway to study the capacity for individual cells to accurately determine the direction of an external gradient, despite fluctuations/noise. By including a stochastic external gradient in the simulations using a novel gradient boundary condition (see the diagram below), they compare and contrast three different variants of the gradient sensing pathway, one monostable and two bistable.
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| Diagram of the simulated system. |
The results show that an architecture combining bistability with spatial positive feedback permits the cell to both accurately detect and internally amplify an external gradient. The researchers observe strong polarization in all individual cells, but in a distribution of directions centered on the gradient. Polarization accuracy in the study was strongly dependent upon a spatial positive feedback term that allows the pathway to trade accuracy for polarization strength. Finally, it is shown that additional feedback links providing information about the gradient to multiple levels in the pathway can help the cell to refine initial inaccuracy in the polarization direction.
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Rati Sharma is a postdoctoral researcher who is interested in understanding stochasticity or noise in systems at the microscopic level. As a member of the Roberts Lab at Johns Hopkins University, she is studying noise and its effects on gene networks. In particular, she is studying the ways noise can effect and aid the cellular decision making process in gene networks, specifically, the pheromone response pathway of mating yeast cells.
During her PhD in Indian Institute of Science, she looked at noise and its effects on polymers and polymeric systems such as melts, semiflexible and Rouse polymers. In addition, she studied work and force fluctuation theorems on the application of flow and mechanical forces to polymers. The phenomenon of subdiffusion was a recurring theme in her study of stochasticity within these systems.
She has published 7 first author papers and co-authored 1 paper in peer reviewed international journals.
