Research activities: Physics of cellular regulation
Real-time measurements of signaling dynamics by in vivo FRET
To understand the design of intracellular signaling networks, it is crucial to characterize their dynamic response to input stimuli. The pathway used by the bacterium Escherichia coli to sense chemical gradients is an excellent example of a simple signaling circuit (Figure 1a) that performs a well-defined function. Because the cell is too small to reliably measure the gradient across its length, it must make temporal comparisons of experienced concentrations as it uses flagellar propulsion to explore space over larger length scales. The impulse response – the output of the system to a very brief stimulus – reveals a biphasic shape characteristic of a derivative-taking kernel (Figure 1b).
- Figure 1: Dynamical modeling and measurements of the E. coli chemotaxis pathway (a) Structure of the E. coli chemotaxis pathway. Input (â„“) at the receptor-kinase complex (A) to output at the flagellar motor (M) is mediated by the phosphorylation of the response regulator CheY (Y-P), counteracted by the phosphatase CheZ (Z). The adaptation enzymes CheR (R) and CheB (B) provide negative feedback. (b) Signal-processing kernel of E. coli chemotaxis. Cyan points are impulse response data from motor response experiments of ref 1, and the black curve below is the averaged output of of stochastic simulations2 for an analogous stimulus. The smooth red curve is an analytical fit to experimental data of the form R(t) = a t exp(-b t)+c t exp(-d t) with its integral constrained to zero. (c) Dynamic input-output measurements using FRET. Temporal gradients of chemical stimuli are programmed (orange curves) and reproduced (black points of upper panel; measurement of optical density of a dye, bromophenol blue). Lower panel shows FRET response (magenta) of a mutant strain (VS149) deficient in adaptation to oscillatory stimuli (orange).
FRET
We use fluorescence resonance energy transfer (FRET) to study the dynamic input-output relations of signaling in living cells. Time-varying stimuli are generated by mixing fluids in a controlled fashion, and we have begun preliminary FRET experiments with the E. coli chemotaxis system (Figure 1c) to determine its response to temporal ramps and oscillatory stimuli. Such measurements will allow us to deduce the filtering properties of this signaling system over the entire range of physiologically relevant stimulus frequencies. Combining these results with mechanistic modeling of the pathway will reveal how such functionality is implemented at the molecular level3.
The techniques developed here should be applicable to the study of many signaling systems that can be stimulated with gradients of small molecules.
Behavior of microbes in microfabricated environments
One of the major difficulties in understanding intracellular networks stems from uncertainties about the environments in which cells function. We are using microfluidics technology to develop controlled microenvironments in which one can study the behavior of cells in a physically well-defined setting. Soft lithography techniques are used to obtain transparent silicone-rubber chips with micron-scale indentations that serve as fluid channels when mated with an opposing surface. Such devices are well suited for precise control of the cells' fluidic environment, since turbulent flows are non-existent at these small scales.
References
1. Segall, J. E., Block, S. M. & Berg, H. C. Temporal comparisons in bacterial chemotaxis. Proc Natl Acad Sci U S A 83, 8987-91 (1986).
2. Shimizu, T. S., Aksenov, S. V. & Bray, D. A spatially extended stochastic model of the bacterial chemotaxis signalling pathway. J Mol Biol 329, 291-309 (2003).
3. Tu, Y., Shimizu, T. S. & Berg, H. C. Modeling the chemotactic response of Escherichia coli to time-varying stimuli. Proc Natl Acad Sci U S A 105, 14855-60 (2008).