"From Concept to Reality: Our Experimental Journey"
Our experimental objective is to produce the designed fusion protein using Escherichia coli BL21(DE3) and characterize the function of the deliver. We successfully constructed a plasmid with the fusion protein gene and attempted to induce the extraction of the fusion protein.
We constructed pET-28a(+)-TRACER-IL24 recombinant plasmids and pUC19-TRACER-IL24 recombinant plasmids as shown in Fig.1a. and Fig.2a.. The nucleic acid electrophoresis bands after double enzyme digestion were consistent with expectations, confirming that the insertion was correct.
As shown in Fig.1b., Lane 1 is Marker III; Lane 2 is a complete pET-28a(+) with a theoretical length of 5369bp; Lanes 3-4 show the double-digested pET-28a(+) vector, with a theoretical length of 5350 bp; Lanes 5-6 display the PCR-amplified target fragment, with a theoretical length of 697 bp. All results match the expected lengths.
Fig 1. Illustration of the recombinant plasmid. A. pET-28a(+)-TRACER-IL24 recombinant plasmid map. B. Nucleic acid electrophoresis is used to verify the enzymatic digestion results.
Fig 2. Illustration of the recombinant plasmid. A. Map of the recombinant plasmid pUC19-TRACER-IL24. B. Nucleic acid electrophoresis was used to verify the enzymatic digestion results.
We attempted to extract and purify the target protein from the bacterial culture, but the initial protein concentration was low, and no distinct bands were observed in the SDS-PAGE analysis, rendering it unsuitable for subsequent experimental requirements.
The standard curve determined and plotted using the BCA method is shown in Fig 3. In SDS-PAGE, no distinct bands were observed except for the protein marker (Fig 4).
The results of the BCA method and SDS-PAGE experiments indicated that the extracted protein concentration was relatively low, and no obvious bands could appear on the SDS-PAGE, suggesting that the protein concentration we extracted could not meet the requirements of subsequent experiments.
Fig 3. Results of protein concentration determination by BCA method
Fig 4. SDS-PAGE characterization results of protein molecular weight
Firstly, increasing the induced concentration of IPTG and using three concentration methods (water bath concentration, ammonium sulfate precipitation concentration, and freeze-drying concentration) did not achieve the expected results.
The standard curve determined and plotted using the BCA method is shown in Fig 5. Calculate the corresponding concentrations using the assay data. Among the results obtained from the three protein extraction methods, freeze-dried concentration yielded the best concentration results. However, the protein obtained using this method still failed to meet our requirements.
The results calculated based on the BCA method indicated that even after enhanced induction and the application of three concentration methods respectively, the protein concentration did not show a significant increase.
Fig 5. Results of protein concentration determination by BCA method - Enhanced induction
Fig 6. TRACER protein solubility analysis
Subsequently, we attempted to extract the fusion protein from the ultrasonication-treated pellet, but the concentration remained insufficient for subsequent experiments (Table 1).
Based on the modeling group results (Fig 6), the information indicates that the fusion protein has low solubility and may be present in the precipitate. So we decided to extract the proteins from the supernatant and the precipitate respectively after ultrasonic disruption.
We determined the protein concentration by the BCA method and plotted the standard curves (Fig 7a and 7b). Analysis of the measurement data indicates that although the protein concentration of the purified sample has significantly increased, the final value still falls short of the level required for subsequent experiments. This clearly indicates that our current protein extraction and concentration processes have bottlenecks and need to be optimized.
Fig 7. Results of protein concentration determination by BCA method. A. Results of the first experiment. B. Results of the second experiment.
| Purification Process | Maximum concentration of purified samples | Note |
|---|---|---|
| Direct Purification | 179.4 μg/ml | - |
| Enhance the intensity of induced expression and perform concentration | 114.7 μg/ml | Excessive freeze-thaw cycles during the concentration process led to reduced protein concentration, resulting in ineffective concentration. |
| Extraction of fusion protein from supernatant and precipitate | 247.6 μg/ml | Neither the supernatant nor the precipitate exhibited elevated protein concentrations, and the highest concentration of purified sample was found in the supernatant. |
In this system, engineered bacteria are delivered directly into the body. The core mechanism lies in: the sustainable expression of fusion proteins under the control of the constitutive promoter Pj23100; When bacteria target colorectal cancer tissues, they activate specific lysis programs, thereby releasing therapeutic proteins locally at the lesion site and achieving precise drug delivery.
Fig 8. The redesigned genetic circuit
Additionally, we employed NetLogo to conduct organizational-level simulations, analyzing the relationship between inoculation levels and lysis cycles, and obtained corresponding spatiotemporal distribution visualization data.
As shown in Fig 9, different initial inoculation amounts have a significant impact on biomass accumulation and pyrolysis cycle: with the increase of inoculation amount, the pyrolysis cycle is significantly shortened, and the population synchrony is enhanced. Simulation results indicate that the initial inoculum size regulates the lysis cycle of the entire population by determining the accumulation rate of the quorum-sensing signal.
Fig 9. Effects of different initial inoculum sizes on lysis cycle
The spatiotemporal visualization results from the NetLogo simulation (Fig 10) reveal that higher inoculation doses lead to a more concentrated spatiotemporal distribution of lysis events and exhibit a more stable periodic pattern.
Fig 10. Spatiotemporal visualization results of NetLogo simulation