Finite Number Effect
Translational Bursting
Promoter Kinetics
Stochasticity in a Eukaryotic Background
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Manifestations of stochasticity in cellular protein production are observable in processes both intrinsic and extrinsic to the gene in question. Intrinsic stochasiticy is characterized as that which is inherent in the processes of transcription and translation (e.g. Gillsepe Model); extrinsic stochasticity is characterized as that which arises from other sources (e.g. Presence of RNAP/ribosomes/mRNA degredation machinery, stage in cell cycle, or plasmid copy number.) While stochasticity in protein production comes from a variety sources, many labs have sought to distinguish dominant causes from neglible ones. Different experimental parameters and independent variables aside, there are underlying motifs in the characterization of stochasticity between studies.
A Prokaryotic vs. a Eukaryotic background is an example of an important distinction to make when characterizing stochasticity. Differences in transcriptional and translational processes lead to differences in dominant manifestations of non-genetic identity. In prokaryotes Ozbudak et. al. characterized a modular model of expression noise in prokaryotic Bacilus Subtillis. In his model stochastic variables representing transcriptional and translational processes represented the manifestation of stochasticity in the system. JJ Collins et. al. suggested that promoter kinetics, and not simply protein abundance, was a factor depending on if the chasis was prokaryotic or eukaryotic. The abundance of characterizations of noise in different backgrounds poses an obstacle for comparision and suggests that the significance of stochastic events truly depends on the nature of the system. This is not to say however that that stochastic events cannot be predicted and taken into account. Check out the In Depth section of this page to find out about the underlying motifs in stochastic processes across different backgrounds.
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