Gene network shaping of inherent noise spectra


Recent work demonstrates that stochastic fluctuations in molecular populations have consequences for gene regulation1,2,3,4,5,6,7,8,9,10. Previous experiments focused on noise sources or noise propagation through gene networks by measuring noise magnitudes. However, in theoretical analysis, we showed that noise frequency content is determined by the underlying gene circuits, leading to a mapping between gene circuit structure and the noise frequency range11,12. An intriguing prediction from our previous studies was that negative autoregulation shifts noise to higher frequencies where it is more easily filtered out by gene networks11—a property that may contribute to the prevalence of autoregulation motifs (for example, found in the regulation of 40% of Escherichia coli genes). Here we measure noise frequency content in growing cultures of E. coli, and verify the link between gene circuit structure and noise spectra by demonstrating the negative autoregulation-mediated spectral shift. We further demonstrate that noise spectral measurements provide mechanistic insights into gene regulation, as perturbations of gene circuit parameters are discernible in the measured noise frequency ranges. These results suggest that noise spectral measurements could facilitate the discovery of novel regulatory relationships.

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Figure 1: Measurement of noise frequency ranges using fluorescence time-lapse microscopy.
Figure 2: Effects of cell doubling time and protein half-life on noise frequency range.
Figure 3: Effect of negative autoregulation on noise frequency range.
Figure 4: Regulation strength modulation of noise frequency range.


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We thank I. Golding and J. Dunlap for advice on sample preparation and imaging, and M. Elowitz, J. Collins and T. Gardner for the gift of plasmids. This work was supported by the National Academies Keck Futures Initiative, the DARPA Bio-Computation Program, the NSF, the DOE Office of Advanced Scientific Computing Research, and was a user project of the Oak Ridge National Laboratory (ORNL) Center for Nanophase Materials Sciences (CNMS). D.W.A. acknowledges support from an ORNL CNMS Research Scholar Fellowship. R.D.D. acknowledges support from the DOE Science Undergraduate Laboratory Internship program. Author Contributions D.W.A., M.S.A., J.M.M., C.D.C. and M.L.S. planned the experimental, analytical and computational work. D.W.A., R.D.D., and J.R.W. performed the time-lapse microscopy measurements. M.S.A., J.R.W. and G.S.S. were responsible for the synthetic biology. D.W.A., R.D.D., C.D.C., J.M.M. and M.L.S. analysed the experimental data. J.M.M., N.F.S. and C.D.C. were responsible for simulations. C.D.C. and M.L.S. developed the frequency domain analytical approach. M.L.S. was responsible for integration of experimental, analytical and computational components.

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Correspondence to M. L. Simpson.

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Supplementary information

Supplementary Video

This movie shows fluorescence time-lapsed microscopy of one experiment using the pGFPasv gene circuit. The time lapse covers 8 hours with frames separated by 5 minutes. The yellow outline around one cell follows a single trajectory through six generations of cell division. The cell doubling time was approximately 90 minutes. (MOV 973 kb)

Supplementary Methods

Detailed methods are described here for the genetic constructs and cell strains; the extraction of noise frequency composition from fluorescence time-lapsed microscopy; and the analytical and computational modeling of the gene circuit noise properties. (DOC 2113 kb)

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Austin, D., Allen, M., McCollum, J. et al. Gene network shaping of inherent noise spectra. Nature 439, 608–611 (2006).

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