In this project, we not only focused on validating the functionality of antimicrobial peptides (AMPs), but also systematically distilled the engineering experience gained through the processes of design, construction, optimization, and application development. These outcomes go beyond experimental results alone, offering reusable resources and insights for future iGEM teams working on AMPs and for the broader synthetic biology community. Our contributions can be summarized in the following six areas:
We contributed to the iGEM Registry by providing additional characterization data for the widely used constitutive promoter J23100 (BBa_J23100). By replacing the T7 promoter in the pET32a-RGG vector with J23100 and using sfGFP as a reporter, we confirmed that J23100 enables strong expression in E. coli BL21(DE3) without the need for inducers. Quantitative measurements showed excitation and emission peaks at 419 nm and 509 nm, respectively, with fluorescence intensities of 577.79, 887.23, and 1120.00 RFU at OD600 values of 0.8, 1.0, and 1.2. These results not only reinforce J23100’s strong promoter properties but also add detailed quantitative data to the Registry, enabling future teams to make more informed design choices.
Small antimicrobial peptides often suffer from low yield, instability, and host toxicity when expressed in E. coli. We first expressed Ulink-AMP using the pET-28a-SUMO fusion vector, confirming that the SUMO tag improved solubility and reduced host toxicity. We then introduced the anionic peptide EELDNALN, which significantly enhanced both stability and yield via charge neutralization. Compared with conventional fusion strategies, this “cationic AMP + anionic peptide” approach provides a generalizable optimization method that future teams can readily adopt when facing similar challenges.
Guided by molecular docking and structural modeling, we designed three site-directed mutants (AMP-TB1, AMP-TB2, and AMP-TB3). MIC assays and agar diffusion tests allowed systematic comparison of their antimicrobial activity, ultimately identifying AMP-TB2 as the best-performing candidate in both yield and functionality. This established a closed-loop workflow from in silico prediction → targeted mutagenesis → experimental validation → candidate selection, demonstrating the effectiveness of semi-rational design for AMP optimization. This workflow can be directly applied to other peptide engineering projects.
To comprehensively evaluate AMP function under biosafety constraints, we developed a tiered validation framework:
By integrating experimental assays with computational docking, this framework addresses the limitations of relying on a single validation method and provides a reproducible approach for future teams operating under resource or biosafety restrictions.
Stability is a critical bottleneck for translating AMPs into practical applications. We systematically evaluated AMP–TB2 at different storage temperatures (4°C, 20°C, 37°C) and time intervals (7 and 14 days). Results showed that TB2 retained high activity against Gram–positive bacteria but lost activity more rapidly against Gram–negative bacteria.
This example of feeding back experimental bottlenecks into design iterations demonstrates a practical pathway for bridging “molecule” to “application.”
To ensure long–term stability and improve usability, we carried out two hardware iterations:
These hardware innovations not only enhanced the feasibility of an AMP spray but also demonstrated how synthetic biology projects can be translated from laboratory concepts into user–friendly products, serving as a reference for future teams exploring productization.
In summary, our contributions encompass both systematic engineering of AMPs— including expression optimization, semi–rational design, multi–layer validation, stability testing, and hardware innovation—and community–level enrichment of the Registry through supplemental promoter characterization. The former provides reusable methodologies and practical insights for AMP research and application, while the latter strengthens foundational data for future design. Together, these outcomes form a meaningful legacy for the iGEM community, supporting future teams in advancing their projects with greater efficiency and confidence.