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Description

D E S C R I P T I O N

Background

The importance of diagnostics

From a macro perspective, with the experience and lessons learned from the COVID-19 pandemic and the landmarked publication of Model List of Essential In Vitro Diagnostics by the World Health Organization (WHO) in 2019, we have come to an era where diagnostics is as equally important as therapeutics. From a micro perspective, timely diagnosis of primary diseases may significantly increase the survival and recovery rate of patients. Taken lung cancer as an example, post-treatment 5-year survival rate range from 77-92% for stage I, but drop to just 10-36% for stage IIIA－IVA.[1] Both perspectives highlight the critical need to improve global health diagnostics to accelerate progress toward universal health coverage (UHC)[2].

Figure 1: Picture showing the equal importance of diagnostics and therapeutics.

According to recent statistic data, the new cases of lung cancer in China were approximately one million and lung cancer had the highest incidence rate among other cancers[3]. Therefore, in China, primary diagnosis of cancer has been high on the agenda. Early in 2016, the State Council issued an outline of the country’s 2030 health plan, emphasizing the importance of early diagnosis of cancer[4]. To answer the appeal lauched by our country, initially, we were determined to find a new way to improve the situation of primary diagnosis of lung cancer. However, as for which disease to detect, we changed our mind later in iGEM journey, and as for how to realize our goal, the following analysis guides our way.

The status quo of diagnostics and its current methodologies

Although the importance of diagnostics is stressed worldwide, however, the status quo of diagnostics is not optimistic. Most governments, health agencies, and financial donors in low-income and middle-income countries have traditionally prioritized medicines, with little investment in diagnostics[5]. Systemic lack of investment in testing means basic diagnostic capacity is available in only 1% of primary-care clinics in many low- and middle-income countries[6].

This lack of investment is partly due to limited awareness of the importance of diagnostics, but also reflects the limitations of existing diagnostic methodologies. Next-Generation Sequencing (NGS), real-time fluorescence quantification PCR (qPCR), Enzyme-Linked Immunosorbent Assay (ELISA) are commonly used methodologies in hospitals. They are invariably time-intensive, expensive, and need specialized technicians[7]. For instance, in clinical scenarios, the cost of NGS analysis in Non-Small Cell Lung cancer (NSCL) estimated by literature ranges from 471.36 CAD (Targeted DNA Panels) to 1287.87 CAD (Trusight Tumor 170 Kit)[8], with an average turnaround time of nearly 3 days (Trusight Tumor 170 Kit)[9]. Most important of all, these methodologies are case-specific, namely, for different diseases, different methods are applied.

Therefore, we urge to brainstorm a new method to change the status quo. To achieve this goal, we need to be aware of what biological theories we can utilize and what application scenarios we aim at. The former is comprehensively elucidated in the Project Decription with more details in Wet lab and Dry lab page, and the latter is further discussed as follows.

Figure 2: Pictures showing two methodologies applied in hospitals and one unknown but new methodology developed by our team. Pictures are from network.

Gold colloidal kit and disease diagnosis based on biomarker detection

Regarding the needs of common people in daily life, gold colloidal kit undoubtedly provides easy access to assess the health conditions of individuals, due to its shorter working time, lower cost, and user-friendliness. Additionally, the key factor in a colloidal gold-based test is antigen, which is termed a biomarker.

A biomarker, or biological marker, is a measurable indicator of some biological state or condition. [10] In recent years, biomarkers have become increasingly important in monitoring the development of a disease for its advantages including precision of measurement, economy, reliability, etc.[11] Moreover, the sampling process using biomarkers can avoid invasive procedure, which is further supported by the advent of the gold colloidal kit using sputum.

Thus, we envision a diagnostic method based on gold colloid and disease biomarkers.

Figure 3: Schematic diagram of gold colloidal kit (adapted from network).

Project Description

Here, team Peking has created a new methodology for disease diagnosis based on biomarker detection, namely, GPA (General disease detection with Protease and Aptamer) system. GPA combines AI and protease-based circuits to compensate for the shortages of previous methods, and accomplish the core value of synthetic biology—modularization—which is embodied in the design of our system. Our system is composed of three main components:

  1. The biomarker recognition part – variable, depending on the target biomarker.
  2. The signal amplification part - constant
  3. The signal output part - constant

The initial phase of our system focuses on aptamers, which are selected to recognize variable biomarkers. These flexible, single-stranded nucleotides process high affinity toward target molecules. Traditionally, aptamers are selected through the SELEX process, which is time-consuming and limits the scalability of aptamer-based products. To overcome this, we have developed an AI tool called MAGA, which streamlines the identification of aptamers with high binding affinity for specific biomarkers. With MAGA, two distinct aptamers can be easily obtained for simultaneous binding to a given biomarker.

Next, the protease-based circuit[12] comes into play for signal transformation and amplification. This circuit is based on split protease, which means half of an integrated protease. Each aptamer is linked to a split protease. This linkage is attributed to a click reaction through non-canonical amino acids and the non-covalent interactions between biotin and streptavidin. When both aptamers bind to the same biomarker, the split proteases dimerize to form an active protease, which then cleaves a downstream target. This cleavage triggers a cascade reaction, amplifying the signal generated by the aptamer recognition. It’s notable that due to time limitations, our wet lab work only focused on thrombin and its aptamers to validate the feasibility of the system.

Finally, our system incorporates a specially designed gold colloidal test, serving as the output and promoting the application of the system in daily life.

To provide a better understanding of our design, we applied biophysics analysis, which also enables us to fine-tune our design into a robust, reliable system and ultimately enhances its potential for real-world applications.

Figure 4: The overall design of our GPA system.

Figure 5: Pictures emphasizing the modularization of our system.

Future Prospects of Our System

Large-scale disease detection

Apart from gold colloidal kit, what else can our system achieve? Inspired by the communication with a biotechnology company, we discover that our system have potentials in large-scale disease detection. Experienced in antibody production, they told us that in the diagnosis of a common kind of disease, antibody still has its competitiveness for its mature production process and its stability for storage. However, if the quantity of biomarkers is large (much more than one), for example, biomarkers of a heterogeneous disease, our system has significant advantages over antibodies. This is because it is faster, easier, and cheaper to generate new aptamers tailored to different biomarkers.

Figure 6: Schematic diagram of large-scale disease detection, with Alzheimer Disease as an example (image sourced from the network).

R E F E R E N C E S

[1] Chinese Thoracic Society. [Chinese expert consensus on diagnosis of early lung cancer (2023 Edition)]. Zhonghua Jie He He Hu Xi Za Zhi. 2023 Jan 12;46(1):1-18. Chinese.

[2][6] Boehme C, Hannay E, Pai M. Promoting diagnostics as a global good. Nat Med. 2021 Mar;27(3):367-368.

[3] Zheng RS, Chen R, Han BF, Wang SM, Li L, Sun KX, Zeng HM, Wei WW, He J. [Cancer incidence and mortality in China, 2022]. Zhonghua Zhong Liu Za Zhi. 2024 Mar 23;46(3):221-231. Chinese.

[4] https://www.gov.cn/zhengce/2016-10/25/content_5124174.htm

[5] Pai M, Walia K, Boehme CC. Essential medicines and essential diagnostics: a package deal. Lancet Public Health. 2019 Oct;4(10):e492.

[6] Boehme C, Hannay E, Pai M. Promoting diagnostics as a global good. Nat Med. 2021 Mar;27(3):367-368.

[7] Ting Wang, Ziwei Wang, Linlin Bai, Xingcai Zhang, Jia Feng, Cheng Qian, Yongming Wang, Rui Wang, “Next-generation CRISPR-based diagnostic tools for human diseases”, TrAC Trends in Analytical Chemistry, Volume 168, 2023.

[8] Kumar S, Bennett A, Campbell PA, Palidwor G, Lo B, Perkins TJ, Nochaiwong S, Sekhon HS, Stewart DJ, Thavorn K. Costs of Next-Generation Sequencing Assays in Non-Small Cell Lung Cancer: A Micro-Costing Study. Curr Oncol. 2022 Jul 23;29(8):5238-5246.

[9] https://emea.illumina.com/products/by-type/clinical-research-products/trusight-tumor-170.html

[10] https://en.wikipedia.org/wiki/Biomarker

[11] Bodaghi A, Fattahi N, Ramazani A. Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases. Heliyon. 2023 Feb;9(2):e13323.

[12] Fink T, Lonzarić J, Praznik A, Plaper T, Merljak E, Leben K, Jerala N, Lebar T, Strmšek Ž, Lapenta F, Benčina M, Jerala R. “Design of fast proteolysis-based signaling and logic circuits in mammalian cells”, Nat Chem Biol, 2019 Feb;15(2):115-122.