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

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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >The failure of getting a significant difference between groups may be due to a small sample size and limitation of place reader measurement. Since Device 1 and Device 4 accounts for most of the variation, and both of which are under the same promoter, another possible explanation would be the context dependent performance of J23101, and an insulator part may be needed to further investigate property of this RBS if the same problem occurs across different teams [4]. We thank the iGEM Measurement Committee again for providing us an excellent opportunity to be part of this study and look forward to see the study results when data from all participating teams are put together.</div>
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Revision as of 02:29, 2 November 2017




Introduction
Inter-laboratory studies have great implications in both academia research and industry. Comparison of results can not only help determine the characteristics of certain products, but can also validate the test method and determine the source of uncertainty. Synthetic biology aims to achieve predicable gene expression outcomes [1], but challenges for this goal still exist on every level from parts design, circuity complexity to measurement methods. iGEM InterLab study is exactly designed to unravel the source of unpredictability and to quantify the degree of variability [2], the logical of which William and Mary iGEM team shares deeply. We have been an active participator of the InterLab Study since 2015 (the second year William and Mary joined the iGEM family) and we are very honored to be able to continue to contribute this study.
This year, the objective of InterLab is to test the precision of gene expression over different RBS devices with a GFP reporter. Teams from around the world are using the standard biological parts, same laboratory bacterium and standardized measurement procedure provided in a detailed protocol. Our team was excited about this year’s project and the improvements that InterLab has made such as the dried down DNA and extra reagents. We started our study on August, 8th.
Methods
Transformation
We transformed the plasmids (listed below) resuspended from the Distribution Kit into E. coli DH5-alpha cells. Colonies were given 16 hours to grow.
Calibration
Before we started plate reader measurement, we obtained the OD600 reference point and the fluorescein fluorescence curve in the microplate reader to standardize the absorbance reading and cell-based fluorescence reading. Our model was a Synergy H1 Hybrid Multi-Mode Microplate Reader. Ludox-S40 silica nanoparticles were used to calculate the correction factor of OD600. Black 96-well plates with clear bottoms were used. For the plate reader our excitation and emission setting were 485 nm and 528 nm respectively (Same setting was used for all experiments below).
The dilution curve of fluorescein was performed by carrying out a 11-step, 2-fold serial dilution of green fluorescein. Final scaling level was determined from medium-high points in the dilution that is likely to be less impacted by saturation or pipetting error. The μM Fluorescein/a.u.is defined as mean of mid-high level fluorescein concentration divided by the obtained plate reader reading.
Cell Measurement
2 colonies of each device was inoculated over night into 5 ml Luria- Bertani medium with 25 μg/mL Chloramphenicol in a 37°C, 220 rpm shaking incubator. Cell cultures were diluted to a target OD600 of 0.02 into same LB medium in 50 mL falcon tube covered with foil before use Diluted cultures were further grown at 37°C and 220 rpm. At 0, 2, 4, and 6 hours of incubation, 500 μL aliquot was taken from each two colonies of the 8 devices and were placed immediately on ice to prevent further growth. At the end of sampling point, 4 replicates 100 μl of each sample was pipetted into a 96-well microplate with the arrangement as below. Data was imported into the Excel Sheet for submission.
Results and Discussion
Below is the Fluorescein Standard Curve we obtained, from which we can still see the problem of saturation. We also converted the calibrated data of the time-measurement into a uM Fluorescence a.u./ OD600 versus time graph. Besides Device 1 and Device 4, all the others constructs show consistency of standardized fluorescence level in the two colonies over time.
From our experiment, we conclude that that BBa_J364100 is a stronger RBS, with an increase of 32.0%, 74.2% and 16.2% expression under J23101, J23106 and J23117 respectively compared to BBa_B0034.
The Standardized RBS tested in this experiment, BCD (bicistronic design) 2 is a synthetic cistron leader peptide region that contains two Shine Dalgano sequences that is reported to have increased precise and reliable translation initiation [3]. Device1 and 4, 2 and 5 and Device 3 and 6 features the same strong (J23101), medium (J23106) and weak (J23117) promoters from the well-characterized Anderson promotor family in iGEM registry. Device 1-3 are under standard RBS BBa_B0034, (which William_and_Mary iGEM 2016 has proudly characterized), while Device 4-6 incorporate the test subject BBa_J364100 (BCD2).
Since all of the devices are under constitutive promoters, we assumed that fluorescence expression to be consistent over time in an optimal growth condition (37°C in LB medium). we compiled a total of 48 data of all 4 time points and 2 colonies of the same RBS and did an anova test for BBa_B0034 and BBa_J364100 and obtained a p-value of .085.
The failure to get a significant difference between groups may be due to a small sample size or limitation of plate reader measurement. Since Device 1 and Device 4 account for most of the variation, and both are under the same promoter, another possible explanation would be the context dependent performance of J23101, and an insulator part may be needed to further investigate property of this RBS if the same problem occurs across different teams [4]. We thank the iGEM Measurement Committee again for providing us an excellent opportunity to be part of this study and look forward to see the study results when data from all participating teams are put together.
References
[1] Kwok, R. (2010). Five hard truths for synthetic biology. Nature, 463(7279), 288-290. doi:10.1038/463288a
[2] Beal, J., Haddock-Angelli, T., Gershater, M., Mora, K. D., Lizarazo, M., Hollenhorst, J., & Rettberg, R. (2016). Reproducibility of Fluorescent Expression from Engineered Biological Constructs in E. coli. Plos One, 11(3). doi:10.1371/journal.pone.0150182
[3] Mutalik, V. K., Guimaraes, J. C., Cambray, G., Lam, C., Christoffersen, M. J., Mai, Q., . . . Endy, D. (2013). Precise and reliable gene expression via standard transcription and translation initiation elements. Nature Methods, 10(4), 354-360. doi:10.1038/nmeth.2404
[4] Davis, J. H., Rubin, A. J., & Sauer, R. T. (2011). Design, construction and characterization of a set of insulated bacterial promoters. Nucleic Acids Research, 39(3), 1131–1141. http://doi.org/10.1093/nar/gkq810