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Breaking it down:  detecting how cells come about change

Student’s research into what drives cell-fate decisions wins HHMI fellowship

By Shawn Hutchins

Jatin NarulaBioengineering graduate student Jatin Narula combines systems and synthetic biology methods to identify and understand how gene regulatory networks guide change within a cell or a group of cells.

Through the research, which is supported by a newly awarded International Student Research Fellowship by the Howard Hughes Medical Institute (HHMI), Narula hopes to discover how cells detect changes in their environment and how they, in turn, use this information to make decisions for either adaptation or phenotypic change.

“For example when Bacillus subtilis, a common soil bacterium,sense nutritional deprivation, some cells stop their growth and initiate a multistage differentiation process of sporulation. The stress response produces a tough non-growing structure in which bacteria can pack its DNA,” explained Narula, who is a fourth-year Ph.D. student in Oleg Igoshin’s Cellular System Dynamics Group. “Then if conditions become favorable, the organism has the genetic information it needs to grow and propagate.”

Narula says the HHMI grant will address questions into what gene regulatory networks control this ‘bet-hedging’ strategy. He then he expects to break it down even further to find out how the decision to sporulate came about.

Narula said a combination of experimental and mathematical modeling approaches will be used to explain cell sporulation processes. “Fortunately gene regulatory networks are highly modular and can be dissected into subunits that play specific roles in processing environmental signals. So we can study the subunits separately to understand their contribution to the decision making process,” Narula added.

Due to the probabilistic nature of biochemical reactions, the dynamics of bacterial gene regulatory networks contain irregular fluctuations or 'intrinsic noise'. These fluctuations can interfere with or obscure environmental signals and significantly affect the ability of regulatory networks to make reliable decisions.

In a related project, Narula has designed a synthetic genetic circuit that can be used to tune the level of noise in gene expression in the bacteria Escherichiacoli. The application of this 'Tunable Noise Generator' should prove to be very useful in investigating how the strength of gene expression fluctuations affects cell growth and bacterial resistance to antibiotics.