| Info. | Vol.13 - No.3 (2019.09.20) |
|---|---|
| Title | Microwell Array-based Digital PCR for Influenza Virus Detection |
| Authors | Christian D. Ahrberg1,†, Jong Min Lee1,† & Bong Geun Chung1,* |
| Institutions | 1Department of Mechanical Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Republic of Korea †These authors contrilbuted equally. *Correspondence and requests for materials should be addressed to B. G. Chung (bchung@sogang.ac.kr) |
| Abstract | Digital polymerase chain reaction (dPCR) enables the accurate determination of deoxyribonucleic acid (DNA) copy numbers. In contrast to real-time PCR (qPCR), dPCR can perform quantification without requiring previous standard curve experiments. Furthermore, dPCR is more sensitive for rare targets in genetic samples. Despite the significant advantages of dPCR over qPCR, dPCR is not widely applied yet due to the complicated requirements of instrumentations regarding creating sample subvolumes and the equipment cost associated with this. In this paper, we present a microwell array that can be used for dPCR. The microwell array can be operated with little microfluidic expertise, while it can be manufactured at a unit cost of less than 1$. The amplification results of the microwell array can be analyzed with a custom-written Python script. With this method, we have been able to amplify and quantify complementary deoxyribonucleic acid (cDNA) samples for the H7N9 influenza virus in a concentration range spanning three orders of magnitude (1,000-100,000 copies/μL). |
| Keyword | Digital PCR, Microwell array, Influenza virus detection, Python image recognition |
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