Colored extrinsic noise and stochastic gene expression
Vahid Shahrezaei, McGill, Centre for Nonlinear Dynamics

Stochasticity is both exploited and controlled by cells. Although the  
intrinsic stochasticity inherent in biochemistry is relatively well  
understood, cellular variation is predominantly generated by  
interactions of the system of interest with other stochastic systems  
in the cell or its environment. Such extrinsic fluctuations are non- 
specific, affecting many system components, and have a substantial  
lifetime comparable to the cell cycle (they are `colored'). Here we  
extend the standard stochastic simulation algorithm to include  
extrinsic fluctuations. We show that these fluctuations affect mean  
protein numbers and intrinsic noise, can speed up typical response  
times in simple networks, and can help explain trends in high- 
throughput measurements of variation in single cells. If extrinsic  
fluctuations in two components of the network are correlated, they  
may combine constructively (amplifying each other) or destructively  
(attenuating each other). Consequently, we predict that incoherent  
feedforward loops attenuate stochasticity, while coherent  
feedforwards amplify it. Our results demonstrate that both the  
timescales of extrinsic fluctuations and their non-specificity can  
substantially affect the function and performance of biochemical  
networks.