New models question old assumptions about how many molecules it takes to control cel...( Blacksburg Va. -- A single cell whe...)

Blacksburg, Va. -- A single cell whether a yeast cell or one of your cells is exquisitely sensitive to its surroundings. It receives input signals, processes the information, makes decisions, and issues commands for making the proper response. As with any control system, noise errors, slip-ups, mis-reads can get in the way of correct decision making. Virginia Tech biologists and engineers have created a mathematical model to explore the roles of noise in controlling the basic events of the cell cycle DNA replication and cell division.

Their work will appear the week of February 23 in the Online Early Edition of the Proceedings of the National Academy of Sciences (PNAS) and later in the print version of the special feature issue on complex systems. The article, "Exploring the Roles of Noise in the Eukaryotic Cell Cycle," is by postdoctoral associate Sandip Kar; William Baumann, professor of electrical and computer engineering; Mark Paul, professor of mechanical engineering; and John Tyson, University Distinguished Professor of biological sciences.

Their efforts to accurately calculate the effects of noise in a yeast cell revealed flaws in two accepted notions about information processing in single cells: about the numbers of messenger RNA (mRNA) molecules in a cell, and about how long they live.

A fundamental challenge of systems biology is trying to understand the molecular basis of decision making in a single cell. "Information processing is done by a molecular network consisting of interacting genes and proteins," Tyson said. "You could compare it to a computer that is based on integrated circuits or to a mechanical control system based on sensors, wires and servomotors -- except that information processing in cells is unique in two ways. First, the cell is a sloppy, liquid environment, with molecules bouncing around and reacting with one another. Second, cells are extremely tiny; therefore sensitive to random fluctuati
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