Title: Listening to the Noise: Random Fluctuations Reveal Biological Mechanisms

Abstract:  The cellular environment is abuzz with noise originating from the 
inherent random motion of reacting molecules in the living cell.  In this 
noisy environment, clonal cell populations exhibit cell-to-cell variability 
that can manifest significant phenotypic differences. Noise induced stochastic 
fluctuations in cellular constituents can be measured and their statistics 
quantified using flow cytometry, fluorescence in situ hybridization, time 
lapse fluorescence microscopy and other single cell and single molecule 
measurement techniques. We show that these random fluctuations carry within 
them valuable information about the underlying genetic network. Far from 
being a nuisance, the ever-present cellular noise acts as a rich source of 
excitation that, when processed through a gene network, carries its 
distinctive fingerprint that encodes a wealth of information about that 
network. We demonstrate that in some cases the analysis of these random 
fluctuations enables the full identification of network parameters, including 
those that may otherwise be difficult to measure. We use theoretical 
investigations to establish experimental guidelines for the identification 
of gene regulatory networks, and we apply these guideline to experimentally 
identify predictive models for different regulatory mechanisms in bacteria 
and yeast.