Contribution
Our team developed an innovative biosensor to address the limitations of traditional methods of pesticide detection, which are often costly and inconvenient. The biosensor uses genetically engineered E. coli (strain BL21) containing plasmids with specific aptamers. These aptamers, formed by transcribed mRNA folding into a three-dimensional structure, bind to pesticides and block the ribosome binding site, preventing translation of the reporter gene. This interaction leads to a decrease in fluorescence. By measuring the fluorescence intensity, users can quickly and easily determine the pesticide concentration in food samples.
Using our biosensor, consumers can easily assess pesticide levels in their food, ensuring greater transparency and confidence in food quality. As the detection process is timely without the need for costly or complex laboratory equipment, consumers can identify unsafe foods with harmful pesticide levels, and thus support better decision-making on food choices, helping to prevent exposure to toxic substances and safeguard health.
To facilitate our users' experience in using the biosensor, we developed a software for our users to analyse the pesticide level in the food samples. Users can upload photos of their test results onto the software, which will help to measure the pesticide concentration of the samples by correlating it with the fluorescence intensity. Additionally, the software enables users to track their past records, providing a comprehensive history of their test results, helping them to monitor trends over time and identify potential sources of toxic substances, thus ensuring ongoing food safety. Other iGEM teams and researchers will probably investigate this topic as well. To encourage these efforts, we have shared all the detailed information about our project to help promote further research and collaboration in this field.
Our team has made a significant contribution to the iGEM Registry through the design, construction, and characterization of a comprehensive suite of biosensor devices for detecting specific pesticides. Our contribution reflects a complete engineering cycle, from initial proof-of-concept to optimized, application-ready parts, providing a valuable toolkit for future teams working on aptamer-based detection systems.
Our foundational work began with the development of glyphosate-sensing devices. The initial construct, [BBa_2561FDBM], established the core mechanism but exhibited constitutive activity, demonstrating the critical need for proper genetic insulation. Its successor, [BBa_25EK3998], incorporated a spacer to resolve this leakiness, but revealed a new challenge with excessive expression under the strong T7 promoter, leading to signal saturation. This learning directly informed our key breakthrough: the adoption of the moderate-strength PlacUV5-MB7 promoter. The resulting flagship part, [BBa_253OHGFW], represents a fully optimized glyphosate biosensor, providing a reliable, quantifiable fluorescent response with a high R-squared value in the critical 0-1 mg/L range.
Building on this success, we systematically applied our optimized design to create a portfolio of specific biosensors, contributing devices for acephate [BBa_257CXA8C], malathion [BBa_256J01OB], chlorpyrifos [BBa_25UJOQTV], and acetamiprid [BBa_252FWFC5]. This collection demonstrates the modularity and scalability of our design principle, enabling the detection of multiple agricultural contaminants using a shared genetic framework.
Looking towards future applications requiring GMO-free detection, we also contributed [BBa_251ONSGX], a cell-free protein synthesis variant of our glyphosate sensor. This part allows for portable, safe testing outside of a cellular chassis, showcasing a direct pathway to real-world implementation.
Collectively, these parts provide the synthetic biology community with well-documented, experimentally validated building blocks. They tell a complete story of iterative design and troubleshooting, offering not just functional devices but also a clear roadmap of the engineering principles required to develop effective, whole-cell biosensors.
To ensure our PestiGuard biosensor functions as intended, for the modelling part, we employed a comprehensive three-part computational study of the aptamer-ligand interaction. This virtual approach, which included structure generation, molecular docking, and molecular dynamics (MD) simulations, was crucial for validating the biosensor's core premise before moving to resource-intensive wet-lab work. Our modeling successfully addressed three critical design challenges: Aptamer Selection, by systematically evaluating and ranking numerous candidate sequences based on their predicted binding affinity to the pesticide; Structural and Conformational Validation, by using MD simulations to confirm that the RNA aptamer would correctly fold into a functional, stable structure despite being transcribed from a DNA template; and Mechanistic Validation, by visually and quantitatively observing the dynamic conformational change the RNA molecule undergoes immediately upon binding, which is the necessary event to silence the GFP reporter. In essence, our computational strategy accelerated the design process, maximized our chances of success, and provided essential insights, allowing us to develop a viable diagnostic tool despite limited resources.
Our education program is designed to actively engage stakeholders across various age groups, backgrounds, and educational levels in synthetic biology, ensuring inclusivity and personalised learning experiences. We implemented a diverse range of methods, including publications, games, workshops, booths, school assemblies, broadcasts, and social media campaigns to reach and inspire a broad audience effectively. Through this comprehensive, progressive approach, participants are guided from beginner to advanced levels along a meaningful learning journey in synthetic biology.
Our team developed educational booklets tailored for primary and secondary school students. These booklets introduce the basic structure of DNA, the technique of using micropipettes, and the concepts related to recombinant DNA technology. These publications also provide insights into our unique plasmid and hardware design. Our goal is to spark interest in synthetic biology among students of all ages by presenting complex concepts in an accessible way. With clear content and engaging designs, these materials have effectively helped students gain a deeper understanding of synthetic biology and our project.
Additionally, we produced storybooks and leaflets for kindergarten students, highlighting the consequences of consuming unwashed food with pesticides. Both storybooks and leaflets aim to convey the importance of food safety and raise awareness of potential health risks associated with pesticide use, delivering the message in an engaging and age-appropriate way. By doing so, students can understand the importance of food safety from an early age.
Our team designed and published a variety of engaging games centered on synthetic biology, including the card game PestiGuard - Hunting Pesticides, the DNA Adventure book, the DNA Base Pairing game, and the Synthetic Biology MC Quiz, e.t.c. We simplified complex information into interactive key concepts, enabling players to develop a deeper understanding of synthetic biology and share their experiences with peers. To maximize accessibility, the card game is available for download on our team’s Instagram, making it easy for the public to enjoy.
These interactive resources not only make learning enjoyable but also enhance the exploration of synthetic biology concepts. By integrating play with education, we aim to inspire curiosity and foster interest in this field among students of all ages.
Our educational activities include a diverse range of workshops, designed to engage students at various education levels in the exciting world of synthetic biology.
For the secondary school level, we organized interactive workshops such as DNA extraction from fruits at Munsang College (MSC) and S.K.H. Holy Trinity Church Secondary School (HTCSS), which many participants found fun and engaging. In another workshop, participants utilised skills in using micropipettes to create sensory bottles, making the learning experience hands-on and memorable. These sessions covered topics such as pesticides and synthetic biology, along with activities like DNA model folding and microscopic observation. To further boost engagement, we incorporated games like Kahoot and MC quizzes in the workshops. For young learners in kindergarten, we included activities such as storytelling sessions, an ATCG base pairing game, and paper folding of DNA models, helping them to understand the basic structure of DNA while inspiring their interest and curiosity in science. Feedback from our questionnaires indicates a positive impact on students’ understanding of synthetic biology.
To encourage further exploration of synthetic biology, we set up a DNA Bracelet Making booth at HTCSS, allowing students to demonstrate their understanding of DNA creatively. Educational game booths at MSC featured a memory card game and a synthetic biology quiz, promoting enjoyable learning experiences in synthetic biology for students. These activities are designed to spark curiosity about fundamental biology concepts.
For more capable learners, we also provided training in Benchling, wet lab techniques, and modeling. These advanced training sessions consolidated their prior knowledge of synthetic biology. The training also equipped the participants with practical skills in this field, thus they became more capable in tackling challenges in synthetic biology. We aim to create an interactive and supportive learning environment to inspire more future scientists and innovators in the field.
Our team actively promoted our project by hosting multiple assemblies at our member schools and broadcasts. These initiatives not only introduced iGEM and synthetic biology, but also highlighted our innovative project. Through these broadcasts and assemblies, we inspired our peers by presenting synthetic biology concepts and showcasing our activities, encouraging them to get involved and explore this fascinating field. We also hope to ignite a passion for scientific research among students, motivating them to consider careers in this area. By introducing iGEM, we believe we are laying the groundwork for the next generation of iGEMers.
Our team established an Instagram account to introduce our project and promote synthetic biology. Through this platform, we shared updates on our working progress and the workshops we organized. Additionally, we launched a YouTube account and created several engaging reels on both platforms that elucidate the core biotechnology concepts, wet lab techniques, and the roles of modeling and hardware design in our project, among other essential topics. Our goal is to raise public awareness about the potential hazards associated with pesticides and present our project’s vision for a more sustainable solution. We are dedicated to conveying these scientific concepts in an entertaining and accessible way, inspiring a deeper understanding of synthetic biology and its potential to tackle real-world challenges.
To empower students with knowledge in synthetic biology, we established a dedicated library corner at MSC featuring books on biotechnology and food safety. This initiative aims to promote the key concepts about biotechnology and laboratory practices, providing students with the opportunity to deepen their understanding of these topics by borrowing books and exploring a variety of resources.
In our commitment to making a meaningful contribution to society, we designed several synthetic biology-themed products for a charity sale, including keychains, tote bags, and folders. All proceeds from the sale were donated to Food Angel, a food rescue and assistance program founded in 2011 by the Bo Charity Foundation.
The Smartbox act as the main platform for integrating the biosensor components, including the optical system for fluorescence detection. Smartbox is equipped with a light source and a photodetector, which captures the fluorescence expressed by the eGFP reporter gene, thus allowing for measurement of gene expression to detect pesticide concentrations.
The Smartbox features a foldable design that enhances portability and ease of storage. When not in use, the box can be collapsed into a compact form, making it convenient for transportation to different laboratory settings or field locations. This design also facilitates easy assembly and disassembly, allowing for quick setup during experiments.
The use of filters ensures that only the relevant wavelengths are measured, minimizing the background noise and enhancing signal clarity.
The hardware includes mechanisms for easy sample handling, such as adaptors for different size of culture tubes. This therefore improves efficiency and reduces the risk of contamination during measurement.
The software is coded using React 19 and TypeScript and designed to analyze the data collected from the Smartbox. It processes images of biosensor kits, by pixel-level RGB brightness analysis within predefined Regions of Interest (ROIs). It then correlates these readings with pesticide concentrations standard curves using built-in algorithms. This measure provides an accessible and lab-free method for data collection of biosensor data.
The software features a powerful client-side frontend analysis engine that requires no server-side processing. It implements linear interpolation algorithm that accurately calculates pesticide concentrations from user-defined curves, or on-strip calibration standards. The results will be displayed through Material-UI user interface (UI), completing with tables and confidence-level indicators (High, Medium, Low) to ensure a rapid and reliable interpretation of data.
The platform is set to detect five key pesticides: Acephate, Glyphosate, Malathion, Chlorpyrifos, and Acetamiprid.
The data management system of this platform was implemented using Zustand state management store. The platform automatically saves every analysis of user, creating a comprehensive history database. Each record stores the source image, final calculated concentrations, confidence levels, and a precise timestamp.
This enables users to easily track results over time, compare different analyses visually, and monitor trends, which is crucial for longitudinal studies and ensuring reproducibility.
The software is engineered with a highly modular architecture that breaks down the core analysis logic from the configuration data. Pesticide parameters, calibration curves, and test kit coordinates are stored in separate, easily editable constant files. This design allows the platform to rapidly adapt new pesticide detection or different biosensor strip layouts just by modifying the configuration files, regardless the need to rewrite the image processing engine and ensure the platform's versatility for easier future research use and agricultural applications.