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Development of an IoT-integrated multiplexed digital PCR system for quantitative detection of infectious diseases.
Choi, Ji Wook; Seo, Won Ho; Lee, Young Suh; Kim, So Young; Kim, Bong Suk; Lee, Kyoung G; Lee, Seok Jae; Chung, Bong Geun.
  • Choi JW; Department of Mechanical Engineering, Sogang University, Seoul, Korea. bchung@sogang.ac.kr.
  • Seo WH; Department of Biomedical Engineering, Sogang University, Seoul, Korea.
  • Lee YS; Department of Mechanical Engineering, Sogang University, Seoul, Korea. bchung@sogang.ac.kr.
  • Kim SY; Biology, Graduate School of Natural Sciences, Soonchunhyang University, Asan, Korea.
  • Kim BS; Bio R&D Lab, BioTNS Co., Ltd., Daejeon, Korea.
  • Lee KG; Center for Nano Bio Development, National NanoFab Center (NNFC), Daejeon, Korea.
  • Lee SJ; Center for Nano Bio Development, National NanoFab Center (NNFC), Daejeon, Korea.
  • Chung BG; Department of Mechanical Engineering, Sogang University, Seoul, Korea. bchung@sogang.ac.kr.
Lab Chip ; 22(20): 3933-3941, 2022 10 11.
Article in English | MEDLINE | ID: covidwho-2028739
ABSTRACT
For rapid detection of the COVID-19 infection, the digital polymerase chain reaction (dPCR) with higher sensitivity and specificity has been presented as a promising method of point-of-care testing (POCT). Unlike the conventional real-time PCR (qPCR), the dPCR system allows absolute quantification of the target DNA without a calibration curve. Although a number of dPCR systems have previously been reported, most of these previous assays lack multiplexing capabilities. As different variants of COVID-19 have rapidly emerged, there is an urgent need for highly specific multiplexed detection systems. Additionally, the advances in the Internet of Things (IoT) technology have enabled the onsite detection of infectious diseases. Here, we present an IoT-integrated multiplexed dPCR (IM-dPCR) system involving sample compartmentalization, DNA amplification, fluorescence imaging, and quantitative analysis. This IM-dPCR system comprises three modules a plasmonic heating-based thermal cycler, a multi-color fluorescence imaging set-up, and a firmware control module. Combined with a custom-developed smartphone application built on an IoT platform, the IM-dPCR system enabled automatic processing, data collection, and cloud storage. Using a self-priming microfluidic chip, 9 RNA groups (e.g., H1N1, H3N2, IFZ B, DENV2, DENV3, DENV4, OC43, 229E, and NL63) associated with three infectious diseases (e.g., influenza, dengue, and human coronaviruses) were analyzed with higher linearity (>98%) and sensitivity (1 copy per µL). The IM-dPCR system exhibited comparable analytical accuracy to commercial qPCR platforms. Therefore, this IM-dPCR system plays a crucial role in the onsite detection of infectious diseases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Diseases / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Diagnostic study / Experimental Studies / Randomized controlled trials Topics: Variants Limits: Humans Language: English Journal: Lab Chip Journal subject: Biotechnology / Chemistry Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Diseases / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Diagnostic study / Experimental Studies / Randomized controlled trials Topics: Variants Limits: Humans Language: English Journal: Lab Chip Journal subject: Biotechnology / Chemistry Year: 2022 Document Type: Article