Difference between revisions of "Team:William and Mary/Description"

The transcription of a gene is an example of such a process-- in prokaryotes, both the time between and the amount of mRNAs produced in each of the bursts of transcription are, though they are constrained by natural laws and limits, nonetheless random values. This inability to predict with complete accuracy and precision, regardless of the amount of information that an observer has about the cell and its environment, confers a level of irreducible variability on transcription.

This variability, also commonly referred to as stochasticity or noise, in gene expression can be split into two components: extrinsic and intrinsic noise. Extrinsic factors, like differing RNA polymerase concentrations and nucleotide availability, affect transcription equally within the cell, regardless of what cis-regulatory elements drive transcription of the genes in question. Intrinsic properties, like DNA-protein binding kinetics, are promoter-specific contributions to noise.

For a synthetic biologist designing a genetic network, it is critical to understand the level of noise present in the network’s components. On one hand, a high level of noise in a component could make the network more unstable, and hence less effective or even unsafe. On the other hand, noise in the network could be harnessed to occasionally cross otherwise energetically unfavorable thresholds and hence open up new possibilities for network functionality and applications. Either way, as the frontier of synthetic biology moves towards ever more complex and intricate networks, it is clearly not sustainable to remain ignorant of the level of noise intrinsic to each component part of a synthesized construct.

Despite the extensive characterization of the average strength of the promoters available on the Biobrick registry, very few have information pertaining to the variability in their expression. Our project aims to tease apart the extrinsic and intrinsic components of gene expression noise, and characterize the noise inherent to commonly used promoters in synthetic biology.

Original work done by Michael Elowitz investigated stochasticity in gene expression at the single cell level using a dual-reporter fluorescent system [1]. In this method two constructs are created that both drive expression of a fluorescent protein using the same promoter, RBS, and terminator. One of these reporter constructs uses YFP and the other CFP. This dual reporter system is what allows the investigator to differentiate between the extrinsic factors of noise, which should affect both constructs equally, and the intrinsic factors, which will result in a difference in the ratio of CFP: YFP fluorescence. These constructs are then integrated into specific sites on the genome and the fluorescence output measured using fluorescent imaging.