1.Starting with Chronic Disease Detection
Our project began with a focus on addressing the challenges of chronic disease management, particularly for conditions related to the "Four Highs"—hypertension, hyperlipidemia, hyperglycemia, and obesity. These chronic conditions are major contributors to coronary heart disease (CHD) and present a growing burden on global healthcare systems. Early detection and consistent monitoring of these risk factors are essential for managing these diseases effectively. In regions where healthcare access is hindered by long wait times, high costs, and concerns about hospital-acquired infections, there is a clear need for at-home solutions. This led us to explore the development of a home-based diagnostic tool for monitoring chronic diseases.
2.Initial Exploration of a Home-Based POCT System by Biomarker Detection
Our exploration centered around creating a Point-of-Care Testing (POCT) system for use at home, designed to detect key biomarkers like glucose and uric acid. These biomarkers are critical for the management of conditions such as diabetes and hyperuricemia. Using synthetic biology, we engineered plasmid-based biosensors that provide fluorescence signals to measure biomarker concentrations. This bioengineering approach, focused on cost-efficient biological components, offers improved accuracy compared to traditional home-use devices, reducing the need for frequent recalibration.
Biosensor detection pathway. Using uric acid detection as an example, a simulated detection system operates as follows: Transcription Unit 1 transports the target molecule into the cell while simultaneously triggering the expression of the HucR protein. The activity of the HucR protein is influenced by the concentration of uric acid, which in turn affects the function of HucO. This modulation impacts the expression level of the fluorescent protein in Transcription Unit 2, thereby enabling detection.
On the hardware side, our goal was to design a complementary system that supports the biosensor detection of biomarkers. This involved developing a hardware platform that integrates seamlessly with the biosensors.
3.Human Practices Shaping Design
Through comprehensive consultations with healthcare professionals, patients, and device manufacturers, etc., we identified key performance specifications that shaped both the bioengineering and hardware components of the system.
Key Performance Specification and Breakdown of strategy:
| Key Performance Specifications | Bioengineering Taskforce Strategy Assignments | Hardware Taskforce Strategy Assignments |
|---|---|---|
| Achieve moderate cost | 1 - Focus on cost efficiency in biological components | 1 - Replace tablet with mobile phone functionality 2 - Cost-effective Components selection |
| Ensure compact size | "1 - Reduce size by removing the tablet component 2 - Compatible industrial design" |
|
| Simplify operation | 1 - Design user-friendly software interface for ease of use | |
| Guarantee biosafety (no excessive biological risk) | 1 - Implement self-suicide safety system | 1 - Create one-time use testing box with non-replaceable reagents |
| Ensure accuracy & stability | 1 - Ensure data stability and comparability from a biological perspective | 1 - Address optical interference to improve accuracy |
| Enable easy data sharing | 1 - Connect to mobile phone (through bluetooth), extend internet compatibility by mobile phone 2 - Data illustration |
4.Hardware Design and POC Achievement
Our hardware taskforce worked closely with the bioengineering taskforce to ensure the system met the identified key performance specifications. The hardware design was broken down into six key components: Optical Sensing and Signal Processing, Microfluidic Chip, Temperature Monitoring and Control, Outer Shell, Software and User Interface, and Electronic Circuit Module. Each module was assigned specific Proof of Concept (POC) stage goals, and by the project's end, we successfully achieved the targeted POC milestones for all modules, ensuring seamless integration and functionality with the biosensor platform.
5.Evolution Toward Modularity and Adaptability
As the project evolved, we recognized the need to expand the system’s capabilities to detect multiple biomarkers simultaneously. This led to the incorporation of modularity into both the bioengineering and hardware designs. By standardizing the biosensor platform, we allowed for easy addition or replacement of biomarkers. For example, while we initially explored lactic acid detection, further development shifted our focus to tryptophan, demonstrating the flexibility of the system.
On the hardware side, the device was designed to accommodate the detection of up to three biomarkers simultaneously. This was achieved through modular, interchangeable components, enabling easy customization for future users. The combination of flexible biosensors and a modular hardware platform allows the system to evolve and adapt to broader applications beyond glucose and uric acid monitoring.
Conclusion
In summary, our project began with the goal of improving chronic disease management through the development of a home-based POCT system. By closely integrating human practices, we identified key performance specifications—such as affordability, ease of use, biosafety, and data transmission—and implemented these through both bioengineering and hardware development. As the project progressed, we enhanced the system’s flexibility through modularity and multi-biomarker detection capabilities, ensuring that it is adaptable for future innovations in personalized health diagnostics.
Reference
- Wang, W., Hu, M., Liu, H., Zhang, X., Li, H., Zhou, F., Liu, Y. M., Lei, F., Qin, J. J., Zhao, Y. C., Chen, Z., Liu, W., Song, X., Huang, X., Zhu, L., Ji, Y. X., Zhang, P., Zhang, X. J., She, Z. G., Yang, J., … Li, H. (2021). Global Burden of Disease Study 2019 suggests that metabolic risk factors are the leading drivers of the burden of ischemic heart disease. Cell metabolism, 33(10), 1943–1956.e2. https://doi.org/10.1016/j.cmet.2021.08.005
- Krouwer JS, Cembrowski GS. A Review of Standards and Statistics Used to Describe Blood Glucose Monitor Performance. Journal of Diabetes Science and Technology. 2010;4(1):75-83. doi:10.1177/193229681000400110
- https://2019.igem.org/Team:QHFZ-China
- https://2017.igem.org/Team:Hong_Kong_UCCKE
- Wilkinson, S. P., et al. (2004). HucR, a Novel Uric Acid-responsive Member of the MarR Family of Transcriptional Regulators from Deinococcus radiodurans. Journal of Biological Chemistry, 279(49), 51442-51450. https://doi.org/10.1074/jbc.M409360200
- Rho, S., Jung, W., Park, J. K., Choi, M. H., Kim, M., Kim, J., Byun, J., Park, T., Lee, B. I., Wilkinson, S. P., & Park, S. (2022). The structure of Deinococcus radiodurans transcriptional regulator HucR retold with the urate bound. Biochemical and Biophysical Research Communications, 615, 63-69. https://doi.org/10.1016/j.bbrc.2022.05.034
- King, F., Ahn, D., Hsiao, V., Porco, T., & Klonoff, D. C. (2018). A Review of Blood Glucose Monitor Accuracy. Diabetes Technology & Therapeutics. https://doi.org/10.1089/dia.2018.0232
- Guo, J., & Ma, X. (2017). Simultaneous monitoring of glucose and uric acid on a single test strip with dual channels. Biosensors and Bioelectronics, 94, 415-419. https://doi.org/10.1016/j.bios.2017.03.026