Overview

Design-Build-Test-Learn is an iterative process used to systematically optimize and refine our biological systems for the detection of COPD.

Design: In this phase, we designed a biological system based on the desired function or performance. Build: After the design is completed, we used molecular biology techniques to construct the designed biological parts and systems.

Test: After the construction is completed, these biological systems would be tested under experimental conditions to determine whether their function and performance meet the design expectations. Learn: Based on the data obtained in the testing phase, we evaluated and modified the design to further improve in the next iteration.

This cyclical process is critical in our project because it allows us to quickly and systematically optimize biological systems until the desired function or performance is achieved.

Design

COPD (Chronic Obstructive Pulmonary Disease) is a lung disease that impacts around 212.3 million people around the globe, with the majority of cases occurring in developing countries such as China, where there is a significant lack of hospitals/clinics in its vast underdeveloped rural areas. In addition, conventional methods for the diagnosis of COPD have a multitude of problems. The most notable problem is that current diagnosis methods are not COPD-specific. Vital capacity, for example, is also used to diagnose pneumonia. Conventional methods are rough, non-specific, and heavily dependent on experiences of the diagnosing doctor. Therefore, what we are aiming for is an efficient, specific, and entirely objective method for COPD diagnosis.

Build

MicroRNA is central to our project. We found some specific miRNAs whose concentration is associated with the pathological progression of COPD. miRNA-1274a, for example, affects apoptosis and cellular senescence. That’s why the concentration of miRNA-1274a in lung tissues is correlated to COPD (Gon et al., 2019).

Test

We used RT-qPCR, a combination of RT-PCR and qPCR, for testing miR-1274a and miR-223 performances in an in vitro reaction under various concentrations. After analysis of our results, we excluded miR-1274a as our target of detection due to its poor performance with RT-qPCR, the ‘golden standard’ and conventional miRNA detection method. MiR-223 yielded significantly better results than miR-1274a and negative control U6 (Figure 1), therefore we selected it as our primary target of detection. RT-qPCR results would be compared to our MB-ERC2 system results in the future.

Learn and redesign

RT-qPCR, while being the ‘golden standard’ for miRNA detection, still has several short-comings, the most notable one being efficiency. The entire procedure of RT-qPCR is several hours in length, and involves multiple steps requiring different reaction conditions (i.e. temperature). Furthermore, human errors during transitions between the steps may lead to misdiagnosis. Therefore, we are aiming for a convenient (e.g. isothermal and one-step only) and efficient method for miRNA detection.

Build

Rolling circle amplification (RCA) is a method commonly used in exponential amplification of target sequences, while cas12a cleavage of fluorophore-quencher reporters could generate fluorescence signals that can be potentially quantified. Therefore, we decided to combine the two, drawing inspiration from He et al. (2023a). Before we attempted a one-step, isothermal reaction system, we first tried tandem combinations of ligation, RCA and Cas12a. Our first test trial was a three step assay (ligation-RCA-Cas12), lasting approximately 5-6 hours. After that, we attempted a two step method (with ligation and RCA jointly carried out instead of separately, as in the three step assay), which shortened the reaction time to 3-4 hours. Then, after both intermediary assays yielded satisfactory results, we began testing a one-step reaction (Figure 2).

Test

Our one-pot isothermal MB-ERC2 system yielded results comparable to those from RT-qPCR. Furthermore, reaction time ranges from 20 minutes minimum to 2 hours maximum, significantly shorter than both RT-qPCR and the intermediary assays.

More information: https://2023.igem.wiki/hs-china/results

Build

After we achieved initial success, we began a series of experiments intended to determine the optimal concentrations of reagents used in the MB-ERC2 system (Figure 3 as an example for Phi29 concentration optimization，more information: https://2023.igem.wiki/hs-china/results). Furthermore, we designed a series of padlocks to observe the effects of crRNA recognition zone location and miRNA binding zone mismatches on reaction kinetics. Through these experiments, we determined the optimal conditions for the MB-ERC2 system.

References

Gon, Y., Shimizu, T., Mizumura, K., Maruoka, S., & Hikichi, M. (2019). Molecular techniques for respiratory diseases: MicroRNA and extracellular vesicles. Respirology, 25(2), 149–160. https://doi.org/10.1111/resp.13756

He, Y., Wen, Y., Tian, Z., Hart, N. T., Han, S., Hughes, S. J., & Zeng, Y. (2023a). A one-pot isothermal Cas12-based assay for the sensitive detection of microRNAs. Nature Biomedical Engineering. https://doi.org/10.1038/s41551-023-01033-1