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Signal Processing in Single Cells

Signal Processing in Single Cells. Tony 03/30/2005. The Question. How signals are transmitted through gene cascades in noisy cellular environments?. Work by Rosenfeld et al. Gene Regulation Function (GRF)

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Signal Processing in Single Cells

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  1. Signal Processing in Single Cells Tony 03/30/2005

  2. The Question How signals are transmitted through gene cascades in noisy cellular environments?

  3. Work by Rosenfeld et al • Gene Regulation Function (GRF) • The relation between the concentration of active transcription factors in a cell and the rate at which their downstream gene products are produced through transcription and translation. • Three fundamental aspects of GRF to study: • Mean shape • Typical deviation from this mean • Time scale over which such fluctuations persist

  4. Gene cascade

  5. Experimental tricks • Regulator dilution method • Relative fluorescence intensity of individual protein molecules  apparent number of molecules per cell. • Hill function

  6. Mean shape

  7. Fluctuations • After normalizing production rates to the average cell-cycle phase, substantial variation still remains in the production rates, and their standard deviation is ~40% of the mean GRF. • Intrinsic noise • Results from stochasticity in the biochemical reactions at an individual gene and would cause identical copies of the same gene to express at different levels. • ~20% of the total noise • Extrinsic noise • Originates from fluctuations in cellular components such as metabolites, ribosomes, and polymerases. • Contributes a variation in protein production rates of ~35%.

  8. Time scales of the fluctuations

  9. Conclusions • Slow fluctuations give the genetic circuits memory, or individuality, lasting roughly one cell cycle. They present difficulty for modeling genetic circuits. • There is thus a fundamental tradeoff between accuracy and speed in purely transcriptional responses. Accurate cellular responses on faster time scales are likely to require feedback from their output.

  10. Work by Pedraza & Oudenaarden • Expression correlations between genes in single cells were measured. • A model was developed that explains the complex behavior exhibited by the correlations and reveals the dominant noise sources.

  11. Gene cascade

  12. Experimental results

  13. Model

  14. Model • Langevin approach • Noise terms: • Intrinsic noise at specific gene • Transmitted intrinsic noise from the upstream genes • The Intrinsic noise for upstream gene • The effect of temporal averaging • The susceptibility of downstream gene to upstream gene (logarithmic gain) • Global noise modulated by the network • The direct effect on the gene • The transmitted effect from upstream genes • The effect of the correlated transmission

  15. Results Even in a network where all components have low intrinsic noise, fluctuations can be substantial and the distributions of expression levels depend on the interactions between genes.

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