Difference between revisions of "Part:BBa K516210:Experience"

UNIPV-Pavia iGEM 2011

NB: unless differently specified, all tests were performed in E. coli MGZ1 in M9 supplemented medium at 37°C in low copy plasmid pSB4C5.

Characterized with:

• BBa_K516211 pTet-RBS31-LuxI
• BBa_K516212 pTet-RBS32-LuxI
• BBa_K516214 pTet-RBS34-LuxI

LuxI has been characterized in terms of enzymatic activity under the regulation of p_Tet promoter.

K_M,LuxI and V_max parameters representing its activity have been estimated and the promoter strength (represented by a synthetic parameter α_pTet for every pTet-RBS combination) at full induction (100 ng/ml) has been estimated too with a simultaneous fitting of the available data.

LuxI has been characterized through the Biosensor BBa_T9002 (see BBa_T9002 experience page).
The HSL synthesis rate has been evaluated according to the model equations, properly adjusted. In particular, the ODE system describing the behavior of this measurement circuit is reported here:

Since the measurement systems are only assayed in the exponential growth phase, in the equation (3) N < N_max is assumed. The parameters N_max, μ and γ_HSL (see the Results section for more details) are known and summarized in the table below:

The parameters V_max, k_M,LuxI and α_RBSx were estimated with a simultaneous fitting of the data collected as described in measurement section for the four measurement parts pTet-RBSx-LuxI-TT assayed through BBa_T9002 biosensor - experience page.

The collected data have been used to identify the parameters of our model. Despite the data-poor context, the model predictions fit the experimental data, thus demonstrating that the equation that models the HSL synthesis by LuxI is a good approximation of real processes.

The provided parameters k_M and V_max represent the enzymatic activity of LuxI, described by our model. They must not be confused with the operative parameters of the Michaelis-Menten relation. These synthetic parameters have a great importance, since they can be used in more complicated models in order to predict the behavior of complex circuits.