OPTIMIZATION AND VALIDATION OF DIGITAL PCR (DPCR) IN DETECTING SARS-COV-2 SAMPLE AND ITS COMPARISON TO QUANTITATIVE PCR (QPCR)

• Main Author: Volincia Oinesti, Daeli
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/69037
• Institution: Institut Teknologi Bandung

COVID-19 is a global pandemic caused by SARS-CoV-2 viruses from the Coronaviridae family. Virus transmission can occur in three main ways. They are direct contact, fomite, and airborne. Recent research publications show that airborne transmission has become the dominant route of SARS-CoV-2 worldwide spread, especially in indoor areas. AirScan is a new innovative service by Nusantics (Indonesia) that provides air quality checking and SARS-CoV-2 airborne detection using three specific target genes, namely the Helicase, RdRp, and RPP30 (as human indicator genes). The conduction of air sampling used an air sampler with a gelatin filter. The results of gelatin filter extraction in the form of RNA will then be detected using quantitative PCR (qPCR). However, air sample detection is typically challenging due to the low concentration of viruses in aerosol, which inflicts the need for a more sensitive and accurate method. Digital PCR is a new generation of PCR technique capable of compartmentalization that increases sensitivity, precision, and tolerance to inhibitor presence. This study aimed to compare the results of the AirScan sample detected by quantitative PCR (AirScan standard protocol) with the results of digital PCR detection. To achieve the results, the researcher conducted several workflows to establish a procedure for using digital PCR. It includes a) comparing cDNA synthesis methods, b) optimizing digital PCR parameters, and c) validating the procedure. The comparison analyses of cDNA percentage results towards three different methods showed that a specific primer addition in the QuantiTect modification method could increase the cDNA percentage results by 117.65% on average. Furthermore, a dPCR optimization was performed on primer-probe concentration, exposure time value, and gain value. The optimization experiment showed that Helicase and RdRp target generated the optimal data results at a primer-probe concentration of 500 nM - 200 nM, 700 ms for exposure time, and 8 dB for gain value. Meanwhile, the RPP30 target showed the optimum data with primer-probe concentration at 400 nM - 150 nM, 500 ms for exposure time, and 7 dB for gain value. After that, this research used two types of samples to validate the optimization results. They were the DNA synthetic and cDNA from the inactivated virus. Validation results of DNA synthetic gave an optimum dynamic range at 10.000 - 60.000 copies/reactions (RSD < 10%), while results of cDNA from inactivated virus showed the dynamic range around 1000 copies/reaction (RSD < 10%). The quantification results of both samples showed good linearity, with R2 ? 0.98. After passing the optimization and validation stages, digital PCR was used to verify AirScan samples. The researcher conducted verification experiments on AirScan samples detected before (using qPCR) and new (fresh) AirScan samples. This study shows that digital PCR could detect more targets in samples with higher quantification than quantitative PCR results. Future studies can further develop this study as the basis of AirScan services and virus detection in general.