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                                                 <p>Our submission for Best Composite Part is the <b>galK Integrator</b>.
 
                                                 <p>Our submission for Best Composite Part is the <b>galK Integrator</b>.
 
                                                 </p>
 
                                                 </p>
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Revision as of 00:51, 19 September 2015

NOISE - W&M iGEM

Composite Part

Our submission for Best Composite Part is the galK Integrator.

Driven by our insights about the increase in transcriptional noise strength from plasmid copy fluctuations, we decided to provide future teams with a simple way to better manage the noise in the expression of a key protein in their genetic networks by restricting the gene copy fluctuations to within 1 and 2 copies. The galK Integrator is a part which allows easy integration of any sequence onto the galK locus of the E. coli chromosome, which was the locus used by Elowitz et al. to successfully integrate a functional cyan fluorescent protein with an antibiotic resistance cassette [1]. For our method of genome integration the input is linear DNA, generated by PCR, containing what you would like to integrate onto the genome and an antibiotic resistance cassette to allow for selection. The galK Integrator allows digestion with the standard BioBrick enzymes and 3A assembly of your part of interest to create the integration construct (see below). This product can then be amplified using primers (details found here) and then used in the integration protocol. We have successfully used this part to integrate a 2.1kb segment attached to a 1.1kb antibiotic resistance cassette.

(RIGHT) The galK Integrator will serve to promote the reproducibility of our noise measurements, encourage other teams to measure the noise in other promoters of their own choosing, and allow greater flexibility for future teams in the design and implementation of their genetic networks. We hope that the introduction of this part into the Registry will mark the beginning of a greater appreciation of the value of accounting for stochastic effects on gene expression.


References:

1: Elowitz, Michael B., et al. "Stochastic gene expression in a single cell." Science 297.5584 (2002): 1183-1186.