Signal Processing in Single Cells Tony 03/30/2005
Feb 02, 2016
Signal Processing in Single Cells
Tony
03/30/2005
How signals are transmitted through gene cascades in noisy cellular environments?
The Question
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
Gene cascade
Experimental tricks
• Regulator dilution method
• Relative fluorescence intensity of individual protein molecules apparent number of molecules per cell.
• Hill function
Mean shape
Fluctuations• After normalizing production rates to the average cell-cyc
le 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 indi
vidual 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 meta
bolites, ribosomes, and polymerases.– Contributes a variation in protein production rates of ~35%.
Time scales of the fluctuations
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.
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.
Gene cascade
Experimental results
Model
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 (log
arithmic 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
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.