Microfluidic devices for measuring gene network dynamics in single cells

Key Points This Review examines the ways in which microfluidic devices have helped to reveal the dynamics of gene regulation and intracellular signalling. Gene regulatory networks often operate through highly dynamic processes that cannot be studied by stationary measurements. Microfluidic devices can trap cells for long periods of time, which allows time-lapse imaging of single cells. When these devices are combined with fluorescent reporters, the time-dependent activity of a network can be measured. New designs for microfludic devices allow the growth environments of cellular populations to be perturbed in non-trivial ways, such as through the creation of spatial gradients or temporal waves of chemical concentrations. Mathematical models that have been created from data obtained through time-lapse fluorescence microscopy have revealed novel functions of gene networks and new regulatory pathways. Multicellular and multispecies studies have also been conducted using microfluidic devices that have been designed for research in intercellular signalling. It is hoped that these new technologies will eventually help to identify techniques that can more accurately model genetic regulatory networks. Microfluidic 'lab-on-a-chip' devices can be used to study the dynamics of gene networks in single cells. This Review discusses the various designs of these devices and the insights into modelling the complex dynamics of gene regulation that these new technologies have provided. The dynamics governing gene regulation have an important role in determining the phenotype of a cell or organism. From processing extracellular signals to generating internal rhythms, gene networks are central to many time-dependent cellular processes. Recent technological advances now make it possible to track the dynamics of gene networks in single cells under various environmental conditions using microfluidic 'lab-on-a-chip' devices, and researchers are using these new techniques to analyse cellular dynamics and discover regulatory mechanisms. These technologies are expected to yield novel insights and allow the construction of mathematical models that more accurately describe the complex dynamics of gene regulation.