DOI QR코드

DOI QR Code

High-accuracy quantitative principle of a new compact digital PCR equipment: Lab On An Array

  • Lee, Haeun (Department of Bioconvergence Engineering, Dankook University) ;
  • Lee, Cherl-Joon (Department of Bioconvergence Engineering, Dankook University) ;
  • Kim, Dong Hee (Department of Anesthesiology and Pain Management, Dankook University Hospital) ;
  • Cho, Chun-Sung (Department of Neurosurgery, Dankook University College of Medicine) ;
  • Shin, Wonseok (NGS Clinical Laboratory, Dankook University Hospital) ;
  • Han, Kyudong (Department of Bioconvergence Engineering, Dankook University)
  • Received : 2021.07.06
  • Accepted : 2021.08.11
  • Published : 2021.09.30

Abstract

Digital PCR (dPCR) is the third-generation PCR that enables real-time absolute quantification without reference materials. Recently, global diagnosis companies have developed new dPCR equipment. In line with the development, the Lab On An Array (LOAA) dPCR analyzer (Optolane) was launched last year. The LOAA dPCR is a semiconductor chip-based separation PCR type equipment. The LOAA dPCR includes Micro Electro Mechanical System that can be injected by partitioning the target gene into 56 to 20,000 wells. The amount of target gene per wells is digitized to 0 or 1 as the number of well gradually increases to 20,000 wells because its principle follows Poisson distribution, which allows the LOAA dPCR to perform precise absolute quantification. LOAA determined region of interest first prior to dPCR operation. To exclude invalid wells for the quantification, the LOAA dPCR has applied various filtering methods using brightness, slope, baseline, and noise filters. As the coronavirus disease 2019 has now spread around the world, needs for diagnostic equipment of point of care testing (POCT) are increasing. The LOAA dPCR is expected to be suitable for POCT diagnosis due to its compact size and high accuracy. Here, we describe the quantitative principle of the LOAA dPCR and suggest that it can be applied to various fields.

Keywords

Acknowledgement

The Department of Microbiology was supported through the Research-Focused Department Promotion Project as a part of the University Innovation Support Program for Dankook University in 2021. The authors gratefully acknowledge the Center for Bio-Medical Engineering Core Facility at Dankook University for providing valuable reagents and research space. The authors have appreciatively acknowledged the Optolane for providing valuable data.

References

  1. Morley AA. Digital PCR: a brief history. Biomol Detect Quantif 2014;1:1-2. https://doi.org/10.1016/j.bdq.2014.06.001
  2. Baker M. Digital PCR hits its stride. Nat Methods 2012;9:541-544. https://doi.org/10.1038/nmeth.2027
  3. Khan MS, Tariq MO, Nawaz M, Ahmed J. MEMS sensors for diagnostics and treatment in the fight against COVID-19 and other pandemics. IEEE Access 2021;9:61123-61149. https://doi.org/10.1109/ACCESS.2021.3073958
  4. Gupta N, Augustine S, Narayan T, O'Riordan A, Das A, Kumar D, et al. Point-of-care PCR assays for COVID-19 detection. Biosensors (Basel) 2021;11:141.
  5. Keni R, Alexander A, Nayak PG, Mudgal J, Nandakumar K. COVID-19: emergence, spread, possible treatments, and global burden. Front Public Health 2020;8:216. https://doi.org/10.3389/fpubh.2020.00216
  6. Bonate PL. A brief introduction to Monte Carlo simulation. Clin Pharmacokinet 2001;40:15-22. https://doi.org/10.2165/00003088-200140010-00002
  7. Talab AM, Huang Z, Xi F, HaiMing L. Detection crack in image using Otsu method and multiple filtering in image processing techniques. Optik 2016;127:1030-1033. https://doi.org/10.1016/j.ijleo.2015.09.147
  8. Lee SS, Park JH, Bae YK. Comparison of two digital PCR methods for EGFR DNA and SARS-CoV-2 RNA quantification. Clin Chim Acta 2021;521:9-18. https://doi.org/10.1016/j.cca.2021.06.016
  9. Tong Y, Shen S, Jiang H, Chen Z. Application of digital PCR in detecting human diseases associated gene mutation. Cell Physiol Biochem 2017;43:1718-1730. https://doi.org/10.1159/000484035
  10. Pavsic J, Devonshire AS, Parkes H, Schimmel H, Foy CA, Karczmarczyk M, et al. Standardization of nucleic acid tests for clinical measurements of bacteria and viruses. J Clin Microbiol 2015;53:2008-2014. https://doi.org/10.1128/JCM.02136-14