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Revision as of 22:53, 10 October 2023
FRET-based system for the detection of erythromycin
FRET-based sensor system for the detection of erythromycin that consists of erythromycin C-12 hydroxylase (BBa_K4447001),an enzyme that catalyzes the oxidation of erythromycin, flanked by two fluorescent proteins: ECFP (BBa_K1159302)as an energy donor and Venus (BBa_K1907000)as an energy acceptor.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21INCOMPATIBLE WITH RFC[21]Illegal XhoI site found at 1913
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000INCOMPATIBLE WITH RFC[1000]Illegal BsaI.rc site found at 2562
Contents
Usage and Biology
With the rise of synthetic biology, biosensors have gained popularity over the years. Among all of the biosensors available, Förster resonance energy transfer (FRET) biosensors are a powerful approach for dynamically tracking the presence of a particular substrate.
In this composite part, we propose an enzymatic system based on how the Förster resonance energy transfer (FRET) operates: one enzyme capable of recognizing and degrading erythromycin will be flanked by two fluorescent proteins. This part incorporates NcoI and XhoI restriction sites in 5' and 3' ends for protein overexpression in pBAD/Myc-His plasmids, a gly-gly-ser spacer, and a polyhistidine tag before stop codon at the end of Venus for protein purification. Any linker does not separate each protein; for instance, stop codons for ECFP and erythromycin C-12 hydroxylase were removed. Figure 1 displays the three-dimensional structure of this protein system.
TecMonterreyGDL 2023further characterized the FRET-based system. See more details in Results.
Selecting Fluorescent Proteins
Fluorescent proteins are most commonly used as donor and acceptor fluorophores in FRET biosensors, especially since these proteins are genetically encodable and live-cell compatible. For this section, we relied on the articles from Bajar et al. (2016) and Agrawal et al. (2021), where different fluorescent proteins are compared according to the requirements of a particular system. The particularity of fluorescent proteins depends on three main advantages: fluorescent proteins-based biosensors are easily constructed via genetic engineering, they confer high cellular specificity by using specific promoters, and these systems are stable in cells for a long time due to high intracellular stability.
From the pairs suggested by Bajar et al. (2016), enhanced cyan fluorescent protein (ECFP) and mVENUS (YFP) are widely recommended because of a higher quantum yield and better folding at 37 °C. This fact is also confirmed by Agrawal et al. (2021), who successfully developed a functional FRET-based sensor to monitor silver ions using this pair of fluorescent proteins. Agrawal et al. (2021) mention that the emission spectrum was recorded after excitation of the sensor protein at 420 nm, and recording the emission in the range of 450 to 600 nm, reaching a peak in 530 nm.
Sequences from both fluorescent proteins were obtained from the BioBricks catalog provided by iGEM. Finally, we selected these fluorescent proteins:
•BBa_K1159302: Enhanced Cyan Fluorescent Protein (ECFP). This Biobrick is an improved version of BBa_E0022, allowing protein fusion that was not initially possible by assembly criteria.
•BBa_K1907000: Venus. This part is a variant of yellow fluorescent protein, making it more stable and improving efficiency maturation.
Characterization
Restriction Enzyme Digestion and Ligation
We performed a restriction enzyme digestion with the synthesized part and the vector defined. Our digestion involved using NcoI and EcoRI restriction enzymes. For both vector and insert, DNA concentration was stated as 4000 nanograms. Table 1 displays the protocol followed for a 50 µL reaction.
Reactive | Quantity |
---|---|
Nuclease-free water | add to 50 µL |
rCutSmart Buffer | 5 µL |
Template DNA (up to 4000 ng) | X µL |
NcoI restriction enzyme | 1 µL |
XhoI restriction enzyme | 1 µL |
With the DNA fragments purified from an agarose gel, we performed ligation at a molar ratio of 1:5 for vector and insert, as shown in Figure 3. The total vector concentration was 100 nanograms, whereas the reaction volume was 20 µL. Next, Table 2 displays the protocol followed for the reaction.
Reactive | Quantity |
---|---|
T4 DNA Ligase Buffer (10X) | 2 µL |
Vector DNA | 100 ng |
Insert DNA | 773.5 ng |
Nuclease-free water | up to 20 µL |
T4 DNA Ligase | 1.5 µL |
Further characterization through protein dynamics simulation
Characterized by TecMonterreyGDL 2023.
A predicted structure was obtained through ColabFold (Mirdita et al., 2022) using existing crystallographic structures for each constituent protein (Figure 4). To lend more confidence to the predicted structure, molecular dynamics (MD) simulations of the obtained model were performed. This helped assess if the predicted structure was maintained after the system was exposed to biophysical potentials.
A preliminary simulation was run with GROMACS to assess if the structure eventually converges over the course of the 10 ns simulation when including biophysical potentials. The system was solvated in water, the charges were neutralized with Na+ ions, and the system was energy minimized to avoid problems from disagreement between ColabFold’s predicted structure and the energy minimum of our system according to the AMBER99SB-ILDN forcefield (Lindorff-Larsen et al., 2010).
The most dynamic regions of our system (Figure 5) correspond to the regions that display the greatest conformational change when comparing X-ray structures of the open and closed conformations of EryK.
Ligation with pET28(+) plasmid
Characterized by TecMonterreyGDL 2023.
The gene sequence for the protein construct was transformed into the pET28b(+) vector. This was done using T4 DNA Ligase Buffer (New England Biolabs) and T4 DNA Ligase (New England Biolabs). Table 3 shows the components used for the ligation reaction at a 1:5 molar ratio. 11 μL of insert and 6 μL of vector were used leaving no need for nuclease-free water.
Insert Table 3 here
The ligation was then transformed into E. coli BL21 by adding 5 μL of the ligation reaction to 50 μL of competent cells. After incubation colonies were observed indicating successful transformation (Figure 6).
Expression in E. coli BL21
Characterized by TecMonterreyGDL 2023.
Overexpression trials were performed by induction with 1M isopropyl β-d-1-thiogalactopyranoside (IPTG) to stimulate protein overexpression (Studier, F. W., 2014). After running an SDS-PAGE to confirm overexpression, very little protein was obtained and further purification indicated no protein was attained (Figure 7).
To test the efficiency of the protein construct, plates with different non-lethal concentrations of erythromycin were made (Figure 8). It’s important to note that the final iteration of the biosensor will use only the purified protein to avoid unwanted mutations and unnecessary environmental risk. While no visible difference was observed in fluorescence levels between the plates, it wasn’t proven whether fluorescence was directly related to erythromycin or if it was basal.
References
[1]. Agrawal, N., Soleja, N., Bano, R., Nazir, R., Siddiqi, T. O., & Mohsin, M. (2021). FRET-Based Genetically Encoded Sensor to Monitor Silver Ions. ACS omega, 6(22), 14164–14173. https://doi.org/10.1021/acsomega.1c00741
[2]. Bajar, B., Lam, A., Badiee, R. et al. (2016). Fluorescent indicators for simultaneous reporting of all four cell cycle phases. Nat Methods 13, 993–996. https://doi.org/10.1038/nmeth.4045
[3]. Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2022). ColabFold: making protein folding accessible to all. Nature methods, 19(6), 679–682. https://doi.org/10.1038/s41592-022-01488-1
[4]. Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., & Shaw, D. E. (2010). Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins, 78(8), 1950–1958. https://doi.org/10.1002/prot.22711
[5]. Studier F. W. (2014). Stable expression clones and auto-induction for protein production in E. coli. Methods in molecular biology (Clifton, N.J.), 1091, 17–32. https://doi.org/10.1007/978-1-62703-691-7_2