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Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis
[Display omitted] •A semi-nested, heptaplex RT-PCR assay for SARS-CoV-2 detection has been developed.•The complex melting spectrum was interpreted by an artificial intelligence algorithm.•The developed assay enables 96-sample pooled testing for increase of testing capacity.•About 8,000 pre-amplified...
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Published in: | Clinica chimica acta 2022-06, Vol.531, p.309-317 |
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creator | Thi Nguyen, Ngoc Anh Thi Bui, Hoai Thi-Huong Pham, Quynh Thi Thao Hoang, Ly Xuan Ta, Hung Heikkinen, Timo Van Le, Duyet Dinh Van, Trang Quoc Ngo, Nam Thi Hong Huynh, Phuong Thi Huyen Tran, Trang Quoc Phan, Hoan Van Hoang, Luong van Doorn, H.Rogier Thi Ngoc Nguyen, Diep Thi Nguyen, Tam Sy Vo, Nam Viet Vo, Cuong Khac Trinh, Sau The Pham, Tai Duc Le, Quang Van Le, Phan Thai Nguyen, Son Thi Tran, Loan Dinh Vu, Toan Vu Nguyen, Quynh Anh Thi Trieu, Nguyet Thi Le, Thuy Dinh Nguyen, Ung Steman, Jakob Huu Ho, Tho |
description | [Display omitted]
•A semi-nested, heptaplex RT-PCR assay for SARS-CoV-2 detection has been developed.•The complex melting spectrum was interpreted by an artificial intelligence algorithm.•The developed assay enables 96-sample pooled testing for increase of testing capacity.•About 8,000 pre-amplified samples could be screened in one realtime PCR run.
Asymptomatic transmission was found to be the Achilles’ heel of the symptom-based screening strategy, necessitating the implementation of mass testing to efficiently contain the transmission of COVID-19 pandemic. However, the global shortage of molecular reagents and the low throughput of available realtime PCR facilities were major limiting factors.
A novel semi-nested and heptaplex (7-plex) RT-PCR assay with melting analysis for detection of SARS-CoV-2 RNA has been established for either individual testing or 96-sample pooled testing. The complex melting spectrum collected from the heptaplex RT-PCR amplicons was interpreted with the support of an artificial intelligence algorithm for the detection of SARS-CoV-2 RNA. The analytical and clinical performance of the semi-nested RT-PCR assay was evaluated using RNAs synthesized in-vitro and those isolated from nasopharyngeal samples.
The LOD of the assay for individual testing was estimated to be 7.2 copies/reaction. Clinical performance evaluation indicated a sensitivity of 100% (95% CI: 97.83–100) and a specificity of 99.87% (95% CI: 99.55–99.98). More importantly, the assay supports a breakthrough sample pooling method, which makes possible parallel screening of up to 96 samples in one real-time PCR well without loss of sensitivity. As a result, up to 8,820 individual pre-amplified samples could be screened for SARS-CoV-2 within each 96-well plate of realtime PCR using the pooled testing procedure.
The novel semi-nested RT-PCR assay provides a solution for highly multiplex (7-plex) detection of SARS-CoV-2 and enables 96-sample pooled detection for increase of testing capacity.
. |
doi_str_mv | 10.1016/j.cca.2022.04.997 |
format | article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9052777</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0009898122011263</els_id><sourcerecordid>2659229078</sourcerecordid><originalsourceid>FETCH-LOGICAL-c381t-8279fe414d49f6960fbe9bb49a7c7ebb7f481bfdcdfa1971ccf799de30358ffe3</originalsourceid><addsrcrecordid>eNp9kV9rHCEUxaW0NNukH6AvZR774lSdPyqFQljaJhBo2E37Ko5ed1xmdDvOLOTbx7BpaF_yJNd7zlHOD6EPlJSU0PbzvjRGl4wwVpK6lJK_QisqeIWrWrLXaEUIkVhIQc_Qu5T2eaxJS9-is6ppCBGcr9B-C6PHAdIMttjc4dv1poCguwFSkSAkP_sjFDrYove7Hs_9FJddf1jmwsIMZvYxFNEV28vNFq_jb8yKTqccla9HGGYfdtmsh_vk0wV64_SQ4P3TeY5-ff92t77CNz9_XK8vb7CpBJ2xYFw6qGlta-la2RLXgey6WmpuOHQdd7WgnbPGOk0lp8Y4LqWFilSNcA6qc_T1lHtYuhGsgTBPelCHyY96uldRe_X_Jvhe7eJRSdIwznkO-PQUMMU_S65GjT4ZGAYdIC5JsbaRjEnCRZbSk9RMMaUJ3PMzlKhHRmqvMiP1yEiRWmVG2fPx3_89O_5CyYIvJwHklo4eJpWMh2DA-ilXrmz0L8Q_ANXbpDU</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2659229078</pqid></control><display><type>article</type><title>Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis</title><source>ScienceDirect Freedom Collection</source><creator>Thi Nguyen, Ngoc Anh ; Thi Bui, Hoai ; Thi-Huong Pham, Quynh ; Thi Thao Hoang, Ly ; Xuan Ta, Hung ; Heikkinen, Timo ; Van Le, Duyet ; Dinh Van, Trang ; Quoc Ngo, Nam ; Thi Hong Huynh, Phuong ; Thi Huyen Tran, Trang ; Quoc Phan, Hoan ; Van Hoang, Luong ; van Doorn, H.Rogier ; Thi Ngoc Nguyen, Diep ; Thi Nguyen, Tam ; Sy Vo, Nam ; Viet Vo, Cuong ; Khac Trinh, Sau ; The Pham, Tai ; Duc Le, Quang ; Van Le, Phan ; Thai Nguyen, Son ; Thi Tran, Loan ; Dinh Vu, Toan ; Vu Nguyen, Quynh Anh ; Thi Trieu, Nguyet ; Thi Le, Thuy ; Dinh Nguyen, Ung ; Steman, Jakob ; Huu Ho, Tho</creator><creatorcontrib>Thi Nguyen, Ngoc Anh ; Thi Bui, Hoai ; Thi-Huong Pham, Quynh ; Thi Thao Hoang, Ly ; Xuan Ta, Hung ; Heikkinen, Timo ; Van Le, Duyet ; Dinh Van, Trang ; Quoc Ngo, Nam ; Thi Hong Huynh, Phuong ; Thi Huyen Tran, Trang ; Quoc Phan, Hoan ; Van Hoang, Luong ; van Doorn, H.Rogier ; Thi Ngoc Nguyen, Diep ; Thi Nguyen, Tam ; Sy Vo, Nam ; Viet Vo, Cuong ; Khac Trinh, Sau ; The Pham, Tai ; Duc Le, Quang ; Van Le, Phan ; Thai Nguyen, Son ; Thi Tran, Loan ; Dinh Vu, Toan ; Vu Nguyen, Quynh Anh ; Thi Trieu, Nguyet ; Thi Le, Thuy ; Dinh Nguyen, Ung ; Steman, Jakob ; Huu Ho, Tho</creatorcontrib><description>[Display omitted]
•A semi-nested, heptaplex RT-PCR assay for SARS-CoV-2 detection has been developed.•The complex melting spectrum was interpreted by an artificial intelligence algorithm.•The developed assay enables 96-sample pooled testing for increase of testing capacity.•About 8,000 pre-amplified samples could be screened in one realtime PCR run.
Asymptomatic transmission was found to be the Achilles’ heel of the symptom-based screening strategy, necessitating the implementation of mass testing to efficiently contain the transmission of COVID-19 pandemic. However, the global shortage of molecular reagents and the low throughput of available realtime PCR facilities were major limiting factors.
A novel semi-nested and heptaplex (7-plex) RT-PCR assay with melting analysis for detection of SARS-CoV-2 RNA has been established for either individual testing or 96-sample pooled testing. The complex melting spectrum collected from the heptaplex RT-PCR amplicons was interpreted with the support of an artificial intelligence algorithm for the detection of SARS-CoV-2 RNA. The analytical and clinical performance of the semi-nested RT-PCR assay was evaluated using RNAs synthesized in-vitro and those isolated from nasopharyngeal samples.
The LOD of the assay for individual testing was estimated to be 7.2 copies/reaction. Clinical performance evaluation indicated a sensitivity of 100% (95% CI: 97.83–100) and a specificity of 99.87% (95% CI: 99.55–99.98). More importantly, the assay supports a breakthrough sample pooling method, which makes possible parallel screening of up to 96 samples in one real-time PCR well without loss of sensitivity. As a result, up to 8,820 individual pre-amplified samples could be screened for SARS-CoV-2 within each 96-well plate of realtime PCR using the pooled testing procedure.
The novel semi-nested RT-PCR assay provides a solution for highly multiplex (7-plex) detection of SARS-CoV-2 and enables 96-sample pooled detection for increase of testing capacity.
.</description><identifier>ISSN: 0009-8981</identifier><identifier>EISSN: 1873-3492</identifier><identifier>DOI: 10.1016/j.cca.2022.04.997</identifier><identifier>PMID: 35500877</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Artificial Intelligence ; Artificial intelligent ; COVID-19 ; COVID-19 - diagnosis ; High-throughput PCR ; Humans ; Melting analysis ; Pandemics ; Pooling ; Reverse Transcriptase Polymerase Chain Reaction ; RNA, Viral - genetics ; SARS-CoV-2 - genetics ; Semi-nested ; Sensitivity and Specificity</subject><ispartof>Clinica chimica acta, 2022-06, Vol.531, p.309-317</ispartof><rights>2022 Elsevier B.V.</rights><rights>Copyright © 2022 Elsevier B.V. All rights reserved.</rights><rights>2022 Elsevier B.V. All rights reserved. 2022 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c381t-8279fe414d49f6960fbe9bb49a7c7ebb7f481bfdcdfa1971ccf799de30358ffe3</citedby><cites>FETCH-LOGICAL-c381t-8279fe414d49f6960fbe9bb49a7c7ebb7f481bfdcdfa1971ccf799de30358ffe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35500877$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Thi Nguyen, Ngoc Anh</creatorcontrib><creatorcontrib>Thi Bui, Hoai</creatorcontrib><creatorcontrib>Thi-Huong Pham, Quynh</creatorcontrib><creatorcontrib>Thi Thao Hoang, Ly</creatorcontrib><creatorcontrib>Xuan Ta, Hung</creatorcontrib><creatorcontrib>Heikkinen, Timo</creatorcontrib><creatorcontrib>Van Le, Duyet</creatorcontrib><creatorcontrib>Dinh Van, Trang</creatorcontrib><creatorcontrib>Quoc Ngo, Nam</creatorcontrib><creatorcontrib>Thi Hong Huynh, Phuong</creatorcontrib><creatorcontrib>Thi Huyen Tran, Trang</creatorcontrib><creatorcontrib>Quoc Phan, Hoan</creatorcontrib><creatorcontrib>Van Hoang, Luong</creatorcontrib><creatorcontrib>van Doorn, H.Rogier</creatorcontrib><creatorcontrib>Thi Ngoc Nguyen, Diep</creatorcontrib><creatorcontrib>Thi Nguyen, Tam</creatorcontrib><creatorcontrib>Sy Vo, Nam</creatorcontrib><creatorcontrib>Viet Vo, Cuong</creatorcontrib><creatorcontrib>Khac Trinh, Sau</creatorcontrib><creatorcontrib>The Pham, Tai</creatorcontrib><creatorcontrib>Duc Le, Quang</creatorcontrib><creatorcontrib>Van Le, Phan</creatorcontrib><creatorcontrib>Thai Nguyen, Son</creatorcontrib><creatorcontrib>Thi Tran, Loan</creatorcontrib><creatorcontrib>Dinh Vu, Toan</creatorcontrib><creatorcontrib>Vu Nguyen, Quynh Anh</creatorcontrib><creatorcontrib>Thi Trieu, Nguyet</creatorcontrib><creatorcontrib>Thi Le, Thuy</creatorcontrib><creatorcontrib>Dinh Nguyen, Ung</creatorcontrib><creatorcontrib>Steman, Jakob</creatorcontrib><creatorcontrib>Huu Ho, Tho</creatorcontrib><title>Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis</title><title>Clinica chimica acta</title><addtitle>Clin Chim Acta</addtitle><description>[Display omitted]
•A semi-nested, heptaplex RT-PCR assay for SARS-CoV-2 detection has been developed.•The complex melting spectrum was interpreted by an artificial intelligence algorithm.•The developed assay enables 96-sample pooled testing for increase of testing capacity.•About 8,000 pre-amplified samples could be screened in one realtime PCR run.
Asymptomatic transmission was found to be the Achilles’ heel of the symptom-based screening strategy, necessitating the implementation of mass testing to efficiently contain the transmission of COVID-19 pandemic. However, the global shortage of molecular reagents and the low throughput of available realtime PCR facilities were major limiting factors.
A novel semi-nested and heptaplex (7-plex) RT-PCR assay with melting analysis for detection of SARS-CoV-2 RNA has been established for either individual testing or 96-sample pooled testing. The complex melting spectrum collected from the heptaplex RT-PCR amplicons was interpreted with the support of an artificial intelligence algorithm for the detection of SARS-CoV-2 RNA. The analytical and clinical performance of the semi-nested RT-PCR assay was evaluated using RNAs synthesized in-vitro and those isolated from nasopharyngeal samples.
The LOD of the assay for individual testing was estimated to be 7.2 copies/reaction. Clinical performance evaluation indicated a sensitivity of 100% (95% CI: 97.83–100) and a specificity of 99.87% (95% CI: 99.55–99.98). More importantly, the assay supports a breakthrough sample pooling method, which makes possible parallel screening of up to 96 samples in one real-time PCR well without loss of sensitivity. As a result, up to 8,820 individual pre-amplified samples could be screened for SARS-CoV-2 within each 96-well plate of realtime PCR using the pooled testing procedure.
The novel semi-nested RT-PCR assay provides a solution for highly multiplex (7-plex) detection of SARS-CoV-2 and enables 96-sample pooled detection for increase of testing capacity.
.</description><subject>Artificial Intelligence</subject><subject>Artificial intelligent</subject><subject>COVID-19</subject><subject>COVID-19 - diagnosis</subject><subject>High-throughput PCR</subject><subject>Humans</subject><subject>Melting analysis</subject><subject>Pandemics</subject><subject>Pooling</subject><subject>Reverse Transcriptase Polymerase Chain Reaction</subject><subject>RNA, Viral - genetics</subject><subject>SARS-CoV-2 - genetics</subject><subject>Semi-nested</subject><subject>Sensitivity and Specificity</subject><issn>0009-8981</issn><issn>1873-3492</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kV9rHCEUxaW0NNukH6AvZR774lSdPyqFQljaJhBo2E37Ko5ed1xmdDvOLOTbx7BpaF_yJNd7zlHOD6EPlJSU0PbzvjRGl4wwVpK6lJK_QisqeIWrWrLXaEUIkVhIQc_Qu5T2eaxJS9-is6ppCBGcr9B-C6PHAdIMttjc4dv1poCguwFSkSAkP_sjFDrYove7Hs_9FJddf1jmwsIMZvYxFNEV28vNFq_jb8yKTqccla9HGGYfdtmsh_vk0wV64_SQ4P3TeY5-ff92t77CNz9_XK8vb7CpBJ2xYFw6qGlta-la2RLXgey6WmpuOHQdd7WgnbPGOk0lp8Y4LqWFilSNcA6qc_T1lHtYuhGsgTBPelCHyY96uldRe_X_Jvhe7eJRSdIwznkO-PQUMMU_S65GjT4ZGAYdIC5JsbaRjEnCRZbSk9RMMaUJ3PMzlKhHRmqvMiP1yEiRWmVG2fPx3_89O_5CyYIvJwHklo4eJpWMh2DA-ilXrmz0L8Q_ANXbpDU</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Thi Nguyen, Ngoc Anh</creator><creator>Thi Bui, Hoai</creator><creator>Thi-Huong Pham, Quynh</creator><creator>Thi Thao Hoang, Ly</creator><creator>Xuan Ta, Hung</creator><creator>Heikkinen, Timo</creator><creator>Van Le, Duyet</creator><creator>Dinh Van, Trang</creator><creator>Quoc Ngo, Nam</creator><creator>Thi Hong Huynh, Phuong</creator><creator>Thi Huyen Tran, Trang</creator><creator>Quoc Phan, Hoan</creator><creator>Van Hoang, Luong</creator><creator>van Doorn, H.Rogier</creator><creator>Thi Ngoc Nguyen, Diep</creator><creator>Thi Nguyen, Tam</creator><creator>Sy Vo, Nam</creator><creator>Viet Vo, Cuong</creator><creator>Khac Trinh, Sau</creator><creator>The Pham, Tai</creator><creator>Duc Le, Quang</creator><creator>Van Le, Phan</creator><creator>Thai Nguyen, Son</creator><creator>Thi Tran, Loan</creator><creator>Dinh Vu, Toan</creator><creator>Vu Nguyen, Quynh Anh</creator><creator>Thi Trieu, Nguyet</creator><creator>Thi Le, Thuy</creator><creator>Dinh Nguyen, Ung</creator><creator>Steman, Jakob</creator><creator>Huu Ho, Tho</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20220601</creationdate><title>Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis</title><author>Thi Nguyen, Ngoc Anh ; Thi Bui, Hoai ; Thi-Huong Pham, Quynh ; Thi Thao Hoang, Ly ; Xuan Ta, Hung ; Heikkinen, Timo ; Van Le, Duyet ; Dinh Van, Trang ; Quoc Ngo, Nam ; Thi Hong Huynh, Phuong ; Thi Huyen Tran, Trang ; Quoc Phan, Hoan ; Van Hoang, Luong ; van Doorn, H.Rogier ; Thi Ngoc Nguyen, Diep ; Thi Nguyen, Tam ; Sy Vo, Nam ; Viet Vo, Cuong ; Khac Trinh, Sau ; The Pham, Tai ; Duc Le, Quang ; Van Le, Phan ; Thai Nguyen, Son ; Thi Tran, Loan ; Dinh Vu, Toan ; Vu Nguyen, Quynh Anh ; Thi Trieu, Nguyet ; Thi Le, Thuy ; Dinh Nguyen, Ung ; Steman, Jakob ; Huu Ho, Tho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-8279fe414d49f6960fbe9bb49a7c7ebb7f481bfdcdfa1971ccf799de30358ffe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial Intelligence</topic><topic>Artificial intelligent</topic><topic>COVID-19</topic><topic>COVID-19 - diagnosis</topic><topic>High-throughput PCR</topic><topic>Humans</topic><topic>Melting analysis</topic><topic>Pandemics</topic><topic>Pooling</topic><topic>Reverse Transcriptase Polymerase Chain Reaction</topic><topic>RNA, Viral - genetics</topic><topic>SARS-CoV-2 - genetics</topic><topic>Semi-nested</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Thi Nguyen, Ngoc Anh</creatorcontrib><creatorcontrib>Thi Bui, Hoai</creatorcontrib><creatorcontrib>Thi-Huong Pham, Quynh</creatorcontrib><creatorcontrib>Thi Thao Hoang, Ly</creatorcontrib><creatorcontrib>Xuan Ta, Hung</creatorcontrib><creatorcontrib>Heikkinen, Timo</creatorcontrib><creatorcontrib>Van Le, Duyet</creatorcontrib><creatorcontrib>Dinh Van, Trang</creatorcontrib><creatorcontrib>Quoc Ngo, Nam</creatorcontrib><creatorcontrib>Thi Hong Huynh, Phuong</creatorcontrib><creatorcontrib>Thi Huyen Tran, Trang</creatorcontrib><creatorcontrib>Quoc Phan, Hoan</creatorcontrib><creatorcontrib>Van Hoang, Luong</creatorcontrib><creatorcontrib>van Doorn, H.Rogier</creatorcontrib><creatorcontrib>Thi Ngoc Nguyen, Diep</creatorcontrib><creatorcontrib>Thi Nguyen, Tam</creatorcontrib><creatorcontrib>Sy Vo, Nam</creatorcontrib><creatorcontrib>Viet Vo, Cuong</creatorcontrib><creatorcontrib>Khac Trinh, Sau</creatorcontrib><creatorcontrib>The Pham, Tai</creatorcontrib><creatorcontrib>Duc Le, Quang</creatorcontrib><creatorcontrib>Van Le, Phan</creatorcontrib><creatorcontrib>Thai Nguyen, Son</creatorcontrib><creatorcontrib>Thi Tran, Loan</creatorcontrib><creatorcontrib>Dinh Vu, Toan</creatorcontrib><creatorcontrib>Vu Nguyen, Quynh Anh</creatorcontrib><creatorcontrib>Thi Trieu, Nguyet</creatorcontrib><creatorcontrib>Thi Le, Thuy</creatorcontrib><creatorcontrib>Dinh Nguyen, Ung</creatorcontrib><creatorcontrib>Steman, Jakob</creatorcontrib><creatorcontrib>Huu Ho, Tho</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Clinica chimica acta</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thi Nguyen, Ngoc Anh</au><au>Thi Bui, Hoai</au><au>Thi-Huong Pham, Quynh</au><au>Thi Thao Hoang, Ly</au><au>Xuan Ta, Hung</au><au>Heikkinen, Timo</au><au>Van Le, Duyet</au><au>Dinh Van, Trang</au><au>Quoc Ngo, Nam</au><au>Thi Hong Huynh, Phuong</au><au>Thi Huyen Tran, Trang</au><au>Quoc Phan, Hoan</au><au>Van Hoang, Luong</au><au>van Doorn, H.Rogier</au><au>Thi Ngoc Nguyen, Diep</au><au>Thi Nguyen, Tam</au><au>Sy Vo, Nam</au><au>Viet Vo, Cuong</au><au>Khac Trinh, Sau</au><au>The Pham, Tai</au><au>Duc Le, Quang</au><au>Van Le, Phan</au><au>Thai Nguyen, Son</au><au>Thi Tran, Loan</au><au>Dinh Vu, Toan</au><au>Vu Nguyen, Quynh Anh</au><au>Thi Trieu, Nguyet</au><au>Thi Le, Thuy</au><au>Dinh Nguyen, Ung</au><au>Steman, Jakob</au><au>Huu Ho, Tho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis</atitle><jtitle>Clinica chimica acta</jtitle><addtitle>Clin Chim Acta</addtitle><date>2022-06-01</date><risdate>2022</risdate><volume>531</volume><spage>309</spage><epage>317</epage><pages>309-317</pages><issn>0009-8981</issn><eissn>1873-3492</eissn><abstract>[Display omitted]
•A semi-nested, heptaplex RT-PCR assay for SARS-CoV-2 detection has been developed.•The complex melting spectrum was interpreted by an artificial intelligence algorithm.•The developed assay enables 96-sample pooled testing for increase of testing capacity.•About 8,000 pre-amplified samples could be screened in one realtime PCR run.
Asymptomatic transmission was found to be the Achilles’ heel of the symptom-based screening strategy, necessitating the implementation of mass testing to efficiently contain the transmission of COVID-19 pandemic. However, the global shortage of molecular reagents and the low throughput of available realtime PCR facilities were major limiting factors.
A novel semi-nested and heptaplex (7-plex) RT-PCR assay with melting analysis for detection of SARS-CoV-2 RNA has been established for either individual testing or 96-sample pooled testing. The complex melting spectrum collected from the heptaplex RT-PCR amplicons was interpreted with the support of an artificial intelligence algorithm for the detection of SARS-CoV-2 RNA. The analytical and clinical performance of the semi-nested RT-PCR assay was evaluated using RNAs synthesized in-vitro and those isolated from nasopharyngeal samples.
The LOD of the assay for individual testing was estimated to be 7.2 copies/reaction. Clinical performance evaluation indicated a sensitivity of 100% (95% CI: 97.83–100) and a specificity of 99.87% (95% CI: 99.55–99.98). More importantly, the assay supports a breakthrough sample pooling method, which makes possible parallel screening of up to 96 samples in one real-time PCR well without loss of sensitivity. As a result, up to 8,820 individual pre-amplified samples could be screened for SARS-CoV-2 within each 96-well plate of realtime PCR using the pooled testing procedure.
The novel semi-nested RT-PCR assay provides a solution for highly multiplex (7-plex) detection of SARS-CoV-2 and enables 96-sample pooled detection for increase of testing capacity.
.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>35500877</pmid><doi>10.1016/j.cca.2022.04.997</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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source | ScienceDirect Freedom Collection |
subjects | Artificial Intelligence Artificial intelligent COVID-19 COVID-19 - diagnosis High-throughput PCR Humans Melting analysis Pandemics Pooling Reverse Transcriptase Polymerase Chain Reaction RNA, Viral - genetics SARS-CoV-2 - genetics Semi-nested Sensitivity and Specificity |
title | Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis |
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