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Team:Utah State/Results
From 2013.igem.org
All AMPs were first cloned in front of a 10x His Tag (BBa_K844000).
Text descriptions go here.
To demonstrate that the N-terminal 10x His Tag (BBa_K1162009) functions correctly, it was cloned in front of Green Florescent Protein (GFP)with the lac promoter+rbs system (BBa_K208010)to give the complete construct BBa_K1162013. This construct was expressed in E. coli grown in 50mL LB media with the addition of chloramphenicol and induced with IPTG. After allowing to grow overnight the cells were spun down and protein was purified with a nickel spin column (see protein purification protocol on protocols page). Fractions from this nickel spin column procedure were saved and run on an SDS-PAGE gel (see below). Since this was a GFP purification procedure, the different fractions were dotted on parafilm and place on a UV gel box to visualize the protein (see below).
From the SDS-PAGE gel it can be seen that there is pure GFP (~26.9 kDa) in the elution fraction number 2 and 3. The wash fractions do not appear to have any GFP which indicates that the N terminal 10x His Tag is strongly bound to the Nickel Column during washing steps. Coupled with the GFP dot image it is clear that this method of purification works as desired and adds another purification system to the registry.
After demonstration that the N-terminal purification system functioned as desired, other constructs were built to purify protein using this method.
To demonstrate that antimicrobial spider silk could be manufactured in E. coli, the AMP LL-37 (BBa_K1162006) was fused to 8 repeats of spider silk (BBa_K844004. A lac inducible promoter system (BBa_K208010), 10x His Tag (BBa_K844000), and double terminator (BBa_B0015) were added to create the first antimicrobial spider silk generator with BioBricks.
To visually monitor the structures of AMPs, amino acid sequences were entered into the Protein Homology/analogY Recognition Engine (PHYRE2,Protein structure prediction on the web: a case study using the Phyre server Kelley LA and Sternberg MJE. Nature Protocols 4, 363 - 371 (2009),http://www.sbg.bio.ic.ac.uk/~phyre2/html/page.cgi?id=index). Output for each of the AMPs used by Utah State iGEM 2013 team is given below. Note: Grammistin (BBa_K1162003) was too small to model with this program. Interestingly when amino acid sequence for each AMP was entered into the program fused with 10x Histag, no change was seen the in the protein structure.
EcAMP-1 (BBa_K1162001) Spheniscin (BBa_K1162002) Cg-Defh1 (BBa_K1162004)
Scygonadin (BBa_K1162005) LL37(BBa_K1162006)
WAM1(BBa_K1162007)structure
OHCATH (BBa_K1162008)
The E. coli JO1366 reconstruction (or E. coli 1366 reconstruction) was used in this study. Reactions for target production of Grammistin, LL37, and WAM1 were added to the reconstruction by using the amino acid composition of each protein and then adding the appropriate number of ATP for protein synthesis (4.3 ATP/ amino acid). Demand reactions were also added for modelling purposes to allow for end metabolites (in this case final AMP proteins) to accumulate. Since these amino acid sequences were so small it was decided to only model three of the AMPs.
Flux balance analysis (FBA) was performed to optimize the production of these three targets(Grammistin, LL37, and WAM). To have some initial results to compare later results to, initial theoretical analysis was performed by setting the lower bound of the biomass reaction to -0.1 mmol/gDW-hr, and optimizing for the target reaction (Grammistin, LL37, and WAM1). This procedure is based off of the work of Feist, et. al, 2010.
The carbon source that was modeled was glucose as this is the most commonly use carbon substrate. Since E. coli was chosen as the chassis for this project, aerobic conditions were also selected in the model. Target production for all three AMPs was maximized as this would be the main objective in a real world situation. In addition to setting the carbon substrate as glucose, media supplements were also modeled (in the form of 38 exchange reactions) to see the affect that additional metabolites would have on the final yield. In order to accomplish this, the lower bounds of the exchange reaction was set to -10 mmol/DW-hr.
The fluxes were converted into product yield (Y) by dividing by the substrate (S) consumption rate, the product yield from the additional supplement analysis was compared to the initial analysis product yield. In many cases, the product yield increased with the addition of these metabolites. Below is a table demonstrating the increase in yield of specific AMPs with the addition of metabolites. From the table it is seen that the addition of D-Fructose increasing the yield of Grammistin from 4.30% to 5.39%. The addition of L-Arginine would increase the yields of LL37 and WAM from 1.75% and 1.78% to 2.16% and 2.19% respectively. The addition of L-Arginine to produce more LL37 and WAM is understandable as it is contained in both AMPs.
OptKnock, a program that optimizes the flux through an objective reaction by systematically searching for reactions to “knock out” (by setting the upper and lower bounds of those reactions to zero) was performed for Grammistin(BBa_K1162003), LL37 (BBa_K1162006), and WAM1(BBa_K1162007).
Production envelope for Grammistin containing 3 knockouts
From carrying out OptKnock it was found that it was not able to find an optimal/maximal production rate for Grammistin(maximum production rate= 2.83 E-10 or zero). The other AMPs analyzed (LL37 and WAM) yielded similar results to Grammistin and hence additional AMPs were not modeled using OptKnock as each AMP took many hours to analyze. From the OptKnock data, knocking out genes may not be a good solution to optimization of AMPs in E. coli. One possible explanation for the OptKnock program not giving optimized production rate from knockouts is, that the AMPs are so small that their production may not have any affect on the overall metabolic system of E. coli.
Feist, A. M.; Zielinski, D. C.; Orth, J. D.; Schellenberger, J.; Herrgard, M. J.; Palsson, B. Ø., Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli. Metabolic Engineering 2010, 12 (3), 173-186.
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