Scientists have long known that animals and plants are governed by a circadian rhythm—a roughly 24-hour cycle guiding biological processes that is linked to alternating periods of light and dark. We know, for instance, that our bodies are entrained, or synchronized, by sunlight. Our cells would drift out of phase if exposed to continuous darkness. However, it has been difficult to understand entrainment because of the difficulty of making precise measurements that reveal the genetic underpinnings of the cycle.
To remedy the problem, UC San Diego biology professor Jeff Hasty led a team of researchers to develop a model biological system that is simpler than that of an organism. The scientists created a simple circadian system using a model consisting of glowing, blinking E. coli bacteria. Drawing on their knowledge of synthetic biology, microfluidic technology, and computational modelling, the researchers built a microfluidic chip containing chambers with E. coli.
As the press release explains:
Within each bacterium, the genetic machinery responsible for the biological clock oscillations was tied to green fluorescent protein, which caused the bacteria to periodically fluoresce.
To simulate day and night cycles, the researchers modified the bacteria to glow and blink whenever arabinose—a chemical that triggered the oscillatory clock mechanisms of the bacteria—was flushed through the microfluidic chip. In this way, the scientists were able to simulate periodic day-night cycles over a period of only minutes instead of days to better understand how a population of cells synchronizes its biological clocks.
Hasty said a similar microfluidic system in principal could be constructed with mammalian cells to study how human cells synchronize with light and darkness.
In the future, genetic models such as this one could be important because circadian-rhythm problems are linked with a number of medical issues ranging from jet lag, various sleep disorders to diabetes.
Abstract in Science magazine: Entrainment of a Population of Synthetic Genetic Oscillators