Our team’ s contribution to the iGEM competition builds upon the work of our predecessors, aiming to leave a meaningful legacy for future participants. We strive to provide resources across multiple domains: software tools developed during our project, a "real-world" science education framework featuring science outreach tailored for preschool-aged children, and substantive contributions to wet lab research. By integrating these elements, we hope to inspire future iGEM teams to build upon our work and continue advancing ethical reflection, inclusivity, and innovation in the field of synthetic biology.
We are thrilled that our project holds the potential to offer a novel approach to immunotherapy for hepatocellular carcinoma (HCC). Centered on the synthetic Notch (SynNotch) system, our project has developed an engineered macrophage platform—SYNERGY (also referred to as Syn-M)—that can be specifically activated within the liver microenvironment. Through this strategy, we aim to effectively address two major challenges in HCC immunotherapy: tumor antigen heterogeneity and the immunosuppressive tumor microenvironment, thereby enabling precise and potent killing of liver cancer cells. Looking ahead, we also envision adapting this platform for the precision treatment of other diseases by swapping downstream effector genes and functional modules, offering a new therapeutic paradigm and innovative perspective for managing other liver-related conditions, including hepatitis and liver fibrosis.
(I) Experimental Methods
Our team (AFMU-China 2025) employed a variety of experimental methods throughout the project and actively explored technology translation and innovative approaches. In terms of system-level innovation, our project achieved, for the first time, liver-specific activation of engineered macrophages (Syn-M). Additionally, by using a bicistronic expression system to simultaneously overexpress P65 and knock down SIRPα, we synergistically enhanced the anti-tumor efficacy of Syn-M. Regarding experimental protocols, we have meticulously documented detailed procedures and critical considerations on our Protocol page, including stable cell line generation via lentiviral transduction, macrophage phagocytosis assays, flow cytometry analysis, immunofluorescence experiments, and more. These resources provide a reproducible experimental framework and valuable practical references for future research.
(Ⅱ) Parts
We are delighted to contribute the biological parts we constructed to the iGEM Registry, enabling future researchers or iGEM teams to build upon our project for further exploration. This year, we went through multiple rounds of the engineering cycle—designing, building, and testing—and ultimately developed 8 new basic parts and 4 new composite parts. For more details, please visit our Parts page .
(Ⅲ) Software
During the project implementation, we realized that we needed to further screen candidate proteins from nearly a thousand liver-highly expressed proteins to identify those meeting three key criteria: high or exclusive expression in the liver, being a hepatocyte marker protein, and membrane localization. Manually performing this screening would involve an exceptionally heavy workload; therefore, we developed the ProteinFilter Pro software. ProteinFilter Pro directly connects to international authoritative protein databases such as UniProt via API interfaces, building a dedicated dynamic knowledge base for proteins. Users can flexibly set screening criteria based on key attributes—including membrane localization, tissue-specific expression levels, and transmembrane domains—and the platform enables millisecond-level preliminary searches, significantly enhancing the efficiency of target discovery. More importantly, we have innovatively integrated machine learning algorithms into the protein engineering design workflow. For selected candidate proteins, ProteinFilter Pro can not only predict their 3D structures from amino acid sequences but also rationally optimize protein binding interfaces based on these predicted structures. This means we are no longer limited to passively “screening” natural targets; instead, we can actively design or optimize them. ProteinFilter Pro is now freely available to all interested iGEMers.
In our human practice engagements with hepatocellular carcinoma (HCC) patients, we identified a critical bottleneck in clinical diagnosis: traditional CT image analysis heavily relies on physicians' subjective judgment, leading to diagnostic variability that can impact early detection rates and treatment planning. This is particularly challenging for sub-centimeter lesions (5mm) or atypical nodules, where manual interpretation is prone to oversight due to fatigue or limited experience. To address this, we developed an intelligent CT image analysis platform that integrates deep learning with 3D reconstruction, providing an "intelligent eye" for precise liver cancer diagnosis. We believe intelligent medical tools are crucial bridges connecting synthetic biology to clinical application. While currently optimized for liver cancer, our platform's modular architecture can be extended to other organs, potentially serving as a versatile, open-source medical imaging solution for the iGEM community and beyond.
Macrophages in the surrounding liver cancer through the participatory learning, narration situation, multi-sensory integration, iterative improvement, ethical, safety practice and assessment framework such as the core concept of education, we have designed for different scientific literacy population (such as high scientific literacy research and clinical workers, biotechnology research and development personnel, and medium scientific literacy of the undergraduates, Diversified education strategies were designed for middle school students, primary school students and kindergarten children with limited scientific literacy, as well as special populations such as patients and their families, the elderly, the deaf and the vulnerable groups.
We cooperate with Fudan university of picture books microbes of my friends is specially designed for young children (such as the pupil and the kindergarten group) design tools, scientific enlightenment through vivid story narration will abstract scientific knowledge into children can sense, can participate in experience. With the theme of "My microbial friends", the core characters of the picture book include common microorganisms such as yeast, Escherichia coli and hepatitis virus, and tell their "daily interaction" with human beings through anthropic methods. This "story + interaction + metaphor" design allows young children to naturally develop their interest in biological science in the process of listening to stories and playing with crafts. At the same time, it lays an emotional and cognitive foundation for learning more complex scientific concepts (such as the function of the immune system), which is the key contact point for young children in the education path of the project "from curiosity to habit".
The results of the project directly benefited the families of liver cancer patients and the public, which improved the inclusiveness and influence of science communication. At the same time, this project provided the iGEM team with a practical paradigm of "starting from social issues and promoting the transformation of scientific research with education", which verified the technical value through education, collected feedback to optimize the design, and formed a positive cycle of "scientific research-education-social needs". More importantly, we open source the modular toolkit, standardized 30-day implementation plan and training process, which reduces the implementation threshold of science education, and provides a reproducible "real science education" template for other iGEM teams or popular science teams around the world, helping more teams to deeply integrate frontier research and social responsibility. To truly realize the long-term goal of "science changes daily choices". Click here and see more.