Proof of concept
Modec3 is an efficient and real-time monitoring tool based on the Mi3-protein cage. This new detection tool can operate at low biomarker concentrations, is cost-effective, easy to use, modular, and scalable. It can be developed into simple and practical detection tools for various biomarkers, making it highly promising in terms of applications and market potential.
The Mi3-protein cage is the most critical component in our project's detection module. This module is based on the 2-keto-3-deoxy-6-phosphogluconate (KDPG) aldolase from the hyperthermophilic bacterium Thermotoga maritima, part of the Entner-Doudoroff pathway. To investigate whether this module can function effectively within the entire system and potentially serve as a detection module for test strips in the future, we initially conducted stability studies using dry experiments.
We first performed 50ns molecular dynamics simulations at 298.15K,323.15K and 348.15K for the subunit of Mi3. Using the Charmm36 force field, TIP3P was selected for the water model.
Fig.1. Simulation data for Mi3 subunit at 298.15K,323.15K,348.15K for 50 ns.
The RMSD analysis revealed minimal structural alterations in the Mi3 subunit during simulations at 298.15K and 323.15K over a duration of 50ns. However, at 348.15K, there was a slight fluctuation observed in the Mi3 subunit. Furthermore, RMSF analysis indicated that residues 131 to 141 exhibited higher flexibility, providing insights into the protein's dynamic behavior. In terms of radius of gyration (Rg), the data at 298.15K and 323.15K exhibited comparable values, suggesting similar compactness in the protein structure under these conditions. Conversely, at 348.15K, the Mi3 subunit displayed significant fluctuations initially, ultimately stabilizing at a lower level.The solvent-accessible surface areas of all three temperatures were found to be quite similar.
For more detailed simulations of dry experiments related to the Mi3-protein cage, please refer to our dry experiment section.
From this perspective, the Mi3-protein cage exhibits high stability and advantages in terms of having multiple modifiable sites, making it an ideal functional carrier. Building on this, we aim to modify the Mi3-protein cage for application in the rapid detection of various disease biomarkers and inflammatory factors. Initially, we selected eGFP, which has strong fluorescence intensity, as our marker for amplifying fluorescence signals. However, the choice of the biological coupling system, the selection of the "adaptor" molecule for achieving a "plug-and-play" project positioning, and the regulation of the assembly ratio between eGFP and the "adaptor" protein have become pressing issues to address.
Therefore, we conducted relevant experiments to select the appropriate biological coupling system, identified the use of the SpyCatcher-SpyTag biological coupling system, and determined the assembly ratio between Mi3-protein cage and eGFP through grayscale analysis to achieve higher assembly efficiency. For more specific data, please refer to the "Engineering Success" section.
Fig.2 Lanes 2, 3, 4, 5 represent samples assembled with Mi3 and eGFP in the ratios of 1:1, 6:5, 3:2, 2:1, 3:1, and 6:1, respectively.Lane 8 serves as the control group with known concentrations of SpyCatcher-Mi3.
Continuing with our approach, in order to attach antibodies for detection onto the protein cage, we considered two strategies. These strategies were evaluated through dry experiments simulated in Figures 3, 4, and 5, as well as wet experiments presented in Figure 7. Ultimately, we chose to utilize "streptavidin" to connect antibodies to the cage through interaction with biotin. For more specific experimental data, please refer to the "Dry Experiments" and "Engineering Success" sections.
Fig.3 The RMSD of the detection component within 50ns.
Fig.4. The RMSF of the detection component within 50ns.
Fig.5. The Rg of the detection component.
Figure 6 (a) SpyCatcher-Mi3:SpyTag-Streptavidin=1:1 Ratio Fluorescence Characterization (b) SpyCatcher-Mi3 Control Group
Continuing further, in order to achieve better fluorescence performance and enhance the sensitivity of our detection, we optimized the assembly ratios of Mi3, eGFP, and streptavidin. This optimization was carried out through fluorescence characterization, electrophoresis characterization, and nanoflow cytometry using techniques such as gel electrophoresis and nanoflow cytometry. Ultimately, we determined that the assembly ratio of SpyCatcher-Mi3 subunits to SpyTag-eGFP to SpyTag-Streptavidin as 60:50:10 yielded the highest fluorescence intensity with relatively uniform intensity. For specific experimental data and charts, please refer to the "Engineering Success" section.
Finally, to validate our constructed monitoring system, we needed to measure the efficiency of capturing antibodies loaded on the protein cage with the target antigen. However, the sample concentrations we collected were low, and the relevant parameters for protein sample determination had stringent requirements for the detection environment. Therefore, we chose microscale thermophoresis (MST) technology to assess this parameter. The MST curve characterizing the fluorescence of the assembled samples is shown in Figure 7, and the affinity constant curve of IgG and BSA on the assembled protein cage is depicted in Figure 8.
Fig.7 MST curves of the assembled sample fluorescence.
Fig.8 Affinity Constant Curves of IgG and BSA on the Assembled Protein Cage
Through a combination of dry and wet experiments, we successfully validated the stability of Mi3, selected the biological coupling system and labels, and optimized the protein assembly ratios to achieve better detection performance. Finally, we characterized our constructed monitoring system and assessed its affinity using MST. The results indicate that the system we have built shows excellent potential for applications. Furthermore, the efficient and real-time monitoring tool we have developed also holds significant commercialization potential, as detailed in our " Entrepreneurship" section.
