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One-step colorimetric isothermal detection of COVID-19 with AI-assisted automated result analysis: A platform model for future emerging point-of-care RNA/DNA disease diagnosis
Colorimetric loop-mediated DNA isothermal amplification-based assays have gained momentum in the diagnosis of COVID-19 owing to their unmatched feasibility in low-resource settings. However, the vast majority of them are restricted to proprietary pH-sensitive dyes that limit downstream assay optimiz...
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Published in: | Talanta (Oxford) 2022-11, Vol.249, p.123375-123375, Article 123375 |
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creator | Jaroenram, Wansadaj Chatnuntawech, Itthi Kampeera, Jantana Pengpanich, Sukanya Leaungwutiwong, Pornsawan Tondee, Benyatip Sirithammajak, Sarawut Suvannakad, Rapheephat Khumwan, Pakapreud Dangtip, Sirintip Arunrut, Narong Bantuchai, Sirasate Nguitragool, Wang Wongwaroran, Suchawit Khanchaitit, Paisan Sattabongkot, Jetsumon Teerapittayanon, Surat Kiatpathomchai, Wansika |
description | Colorimetric loop-mediated DNA isothermal amplification-based assays have gained momentum in the diagnosis of COVID-19 owing to their unmatched feasibility in low-resource settings. However, the vast majority of them are restricted to proprietary pH-sensitive dyes that limit downstream assay optimization or hinder efficient result interpretation. To address this problem, we developed a novel dual colorimetric RT-LAMP assay using in-house pH-dependent indicators to maximize the visual detection and assay simplicity, and further integrated it with the artificial intelligence (AI) operated tool (RT-LAMP-DETR) to enable a more precise and rapid result analysis in large scale testing. The dual assay leverages xylenol orange (XO) and a newly formulated lavender green (LG) dye for distinctive colorimetric readouts, which enhance the test accuracy when performed and analyzed simultaneously. Our RT-LAMP assay has a detection limit of 50 viral copies/reaction with the cycle threshold (Ct) value ≤ 39.7 ± 0.4 determined by the WHO-approved RT-qPCR assay. RT-LAMP-DETR exhibited a complete concordance with the results from naked-eye observation and RT-qPCR, achieving 100% sensitivity, specificity, and accuracy that altogether render it suitable for ultrasensitive point-of-care COVID-19 screening efforts. From the perspective of pandemic preparedness, our method offers a simpler, faster, and cheaper (∼$8/test) approach for COVID-19 testing and other emerging pathogens with respect to RT-qPCR.
[Display omitted]
•We developed a novel ultrasensitive and specific dual RT-LAMP assay.•It targets the Nsp9 segment of SARS-CoV-2 ORF1ab and human 18 S rRNA gene.•Results can be analyzed with the naked-eye and an AI-operated automated model.•The assay can be exploited for decentralized high-throughput COVID-19 screening. |
doi_str_mv | 10.1016/j.talanta.2022.123375 |
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[Display omitted]
•We developed a novel ultrasensitive and specific dual RT-LAMP assay.•It targets the Nsp9 segment of SARS-CoV-2 ORF1ab and human 18 S rRNA gene.•Results can be analyzed with the naked-eye and an AI-operated automated model.•The assay can be exploited for decentralized high-throughput COVID-19 screening.</description><identifier>ISSN: 0039-9140</identifier><identifier>EISSN: 1873-3573</identifier><identifier>DOI: 10.1016/j.talanta.2022.123375</identifier><identifier>PMID: 35738204</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Artificial Intelligence ; Colorimetric RT-LAMP ; Colorimetry - methods ; COVID-19 - diagnosis ; COVID-19 Testing ; DNA ; Humans ; LAMP-DETR ; Machine learning ; Nucleic Acid Amplification Techniques - methods ; Point-of-Care Systems ; RNA ; RNA, Viral - genetics ; SARS-CoV-2 ; SARS-CoV-2 - genetics ; Sensitivity and Specificity</subject><ispartof>Talanta (Oxford), 2022-11, Vol.249, p.123375-123375, Article 123375</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-c467t-4d6d085fd7916d8b2000319551516c239e0c507e06ef384aa3d6986ac6fcfb763</citedby><cites>FETCH-LOGICAL-c467t-4d6d085fd7916d8b2000319551516c239e0c507e06ef384aa3d6986ac6fcfb763</cites><orcidid>0000-0002-3570-3430 ; 0000-0002-9034-141X ; 0000-0003-3093-2485 ; 0000-0001-6487-3095 ; 0000-0002-3491-7410 ; 0000-0001-9687-3460 ; 0000-0001-6215-8290 ; 0000-0003-3582-5312</orcidid></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/35738204$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jaroenram, Wansadaj</creatorcontrib><creatorcontrib>Chatnuntawech, Itthi</creatorcontrib><creatorcontrib>Kampeera, Jantana</creatorcontrib><creatorcontrib>Pengpanich, Sukanya</creatorcontrib><creatorcontrib>Leaungwutiwong, Pornsawan</creatorcontrib><creatorcontrib>Tondee, Benyatip</creatorcontrib><creatorcontrib>Sirithammajak, Sarawut</creatorcontrib><creatorcontrib>Suvannakad, Rapheephat</creatorcontrib><creatorcontrib>Khumwan, Pakapreud</creatorcontrib><creatorcontrib>Dangtip, Sirintip</creatorcontrib><creatorcontrib>Arunrut, Narong</creatorcontrib><creatorcontrib>Bantuchai, Sirasate</creatorcontrib><creatorcontrib>Nguitragool, Wang</creatorcontrib><creatorcontrib>Wongwaroran, Suchawit</creatorcontrib><creatorcontrib>Khanchaitit, Paisan</creatorcontrib><creatorcontrib>Sattabongkot, Jetsumon</creatorcontrib><creatorcontrib>Teerapittayanon, Surat</creatorcontrib><creatorcontrib>Kiatpathomchai, Wansika</creatorcontrib><title>One-step colorimetric isothermal detection of COVID-19 with AI-assisted automated result analysis: A platform model for future emerging point-of-care RNA/DNA disease diagnosis</title><title>Talanta (Oxford)</title><addtitle>Talanta</addtitle><description>Colorimetric loop-mediated DNA isothermal amplification-based assays have gained momentum in the diagnosis of COVID-19 owing to their unmatched feasibility in low-resource settings. However, the vast majority of them are restricted to proprietary pH-sensitive dyes that limit downstream assay optimization or hinder efficient result interpretation. To address this problem, we developed a novel dual colorimetric RT-LAMP assay using in-house pH-dependent indicators to maximize the visual detection and assay simplicity, and further integrated it with the artificial intelligence (AI) operated tool (RT-LAMP-DETR) to enable a more precise and rapid result analysis in large scale testing. The dual assay leverages xylenol orange (XO) and a newly formulated lavender green (LG) dye for distinctive colorimetric readouts, which enhance the test accuracy when performed and analyzed simultaneously. Our RT-LAMP assay has a detection limit of 50 viral copies/reaction with the cycle threshold (Ct) value ≤ 39.7 ± 0.4 determined by the WHO-approved RT-qPCR assay. RT-LAMP-DETR exhibited a complete concordance with the results from naked-eye observation and RT-qPCR, achieving 100% sensitivity, specificity, and accuracy that altogether render it suitable for ultrasensitive point-of-care COVID-19 screening efforts. From the perspective of pandemic preparedness, our method offers a simpler, faster, and cheaper (∼$8/test) approach for COVID-19 testing and other emerging pathogens with respect to RT-qPCR.
[Display omitted]
•We developed a novel ultrasensitive and specific dual RT-LAMP assay.•It targets the Nsp9 segment of SARS-CoV-2 ORF1ab and human 18 S rRNA gene.•Results can be analyzed with the naked-eye and an AI-operated automated model.•The assay can be exploited for decentralized high-throughput COVID-19 screening.</description><subject>Artificial Intelligence</subject><subject>Colorimetric RT-LAMP</subject><subject>Colorimetry - methods</subject><subject>COVID-19 - diagnosis</subject><subject>COVID-19 Testing</subject><subject>DNA</subject><subject>Humans</subject><subject>LAMP-DETR</subject><subject>Machine learning</subject><subject>Nucleic Acid Amplification Techniques - methods</subject><subject>Point-of-Care Systems</subject><subject>RNA</subject><subject>RNA, Viral - genetics</subject><subject>SARS-CoV-2</subject><subject>SARS-CoV-2 - genetics</subject><subject>Sensitivity and Specificity</subject><issn>0039-9140</issn><issn>1873-3573</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqFkc-O0zAQxiMEYsvCI4B85OKuHceOwwEUdflTabWVEHC1XHvSukriYju72qfiFXHUsoITpxl5vvlmPL-ieE3JkhIqrg7LpHs9Jr0sSVkuaclYzZ8UCyprhhmv2dNiQQhrcEMrclG8iPFACCkZYc-Li7kuS1Itil-bEXBMcETG9z64AVJwBrno0x7CoHtkIYFJzo_Id2i1-bG-xrRB9y7tUbvGOkaX2y3SU_KDnrMAceoT0qPuH3LxHWrRsdep82FAg7fQo5yibkpTAAQDhJ0bd-jo3Ziw77DR-fnrbXt1fdsi6yLoCDnq3eiz28viWaf7CK_O8bL4_unjt9UXfLP5vF61N9hUok64ssISyTtbN1RYuS3z3xltOKecClOyBojhpAYioGOy0ppZ0UihjehMt60Fuyzen3yP03YAa2BMQffqmC-kw4Py2ql_K6Pbq52_U01FKs5lNnh7Ngj-5wQxqcFFA31mBn6KqhSSkkoKOUv5SWqCjzFA9ziGEjXDVgd1hq1m2OoEO_e9-XvHx64_dLPgw0kA-VJ3DoKKxsFowLqQmSrr3X9G_AZAjsDx</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Jaroenram, Wansadaj</creator><creator>Chatnuntawech, Itthi</creator><creator>Kampeera, Jantana</creator><creator>Pengpanich, Sukanya</creator><creator>Leaungwutiwong, Pornsawan</creator><creator>Tondee, Benyatip</creator><creator>Sirithammajak, Sarawut</creator><creator>Suvannakad, Rapheephat</creator><creator>Khumwan, Pakapreud</creator><creator>Dangtip, Sirintip</creator><creator>Arunrut, Narong</creator><creator>Bantuchai, Sirasate</creator><creator>Nguitragool, Wang</creator><creator>Wongwaroran, Suchawit</creator><creator>Khanchaitit, Paisan</creator><creator>Sattabongkot, Jetsumon</creator><creator>Teerapittayanon, Surat</creator><creator>Kiatpathomchai, Wansika</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><orcidid>https://orcid.org/0000-0002-3570-3430</orcidid><orcidid>https://orcid.org/0000-0002-9034-141X</orcidid><orcidid>https://orcid.org/0000-0003-3093-2485</orcidid><orcidid>https://orcid.org/0000-0001-6487-3095</orcidid><orcidid>https://orcid.org/0000-0002-3491-7410</orcidid><orcidid>https://orcid.org/0000-0001-9687-3460</orcidid><orcidid>https://orcid.org/0000-0001-6215-8290</orcidid><orcidid>https://orcid.org/0000-0003-3582-5312</orcidid></search><sort><creationdate>20221101</creationdate><title>One-step colorimetric isothermal detection of COVID-19 with AI-assisted automated result analysis: A platform model for future emerging point-of-care RNA/DNA disease diagnosis</title><author>Jaroenram, Wansadaj ; 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However, the vast majority of them are restricted to proprietary pH-sensitive dyes that limit downstream assay optimization or hinder efficient result interpretation. To address this problem, we developed a novel dual colorimetric RT-LAMP assay using in-house pH-dependent indicators to maximize the visual detection and assay simplicity, and further integrated it with the artificial intelligence (AI) operated tool (RT-LAMP-DETR) to enable a more precise and rapid result analysis in large scale testing. The dual assay leverages xylenol orange (XO) and a newly formulated lavender green (LG) dye for distinctive colorimetric readouts, which enhance the test accuracy when performed and analyzed simultaneously. Our RT-LAMP assay has a detection limit of 50 viral copies/reaction with the cycle threshold (Ct) value ≤ 39.7 ± 0.4 determined by the WHO-approved RT-qPCR assay. RT-LAMP-DETR exhibited a complete concordance with the results from naked-eye observation and RT-qPCR, achieving 100% sensitivity, specificity, and accuracy that altogether render it suitable for ultrasensitive point-of-care COVID-19 screening efforts. From the perspective of pandemic preparedness, our method offers a simpler, faster, and cheaper (∼$8/test) approach for COVID-19 testing and other emerging pathogens with respect to RT-qPCR.
[Display omitted]
•We developed a novel ultrasensitive and specific dual RT-LAMP assay.•It targets the Nsp9 segment of SARS-CoV-2 ORF1ab and human 18 S rRNA gene.•Results can be analyzed with the naked-eye and an AI-operated automated model.•The assay can be exploited for decentralized high-throughput COVID-19 screening.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>35738204</pmid><doi>10.1016/j.talanta.2022.123375</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-3570-3430</orcidid><orcidid>https://orcid.org/0000-0002-9034-141X</orcidid><orcidid>https://orcid.org/0000-0003-3093-2485</orcidid><orcidid>https://orcid.org/0000-0001-6487-3095</orcidid><orcidid>https://orcid.org/0000-0002-3491-7410</orcidid><orcidid>https://orcid.org/0000-0001-9687-3460</orcidid><orcidid>https://orcid.org/0000-0001-6215-8290</orcidid><orcidid>https://orcid.org/0000-0003-3582-5312</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Artificial Intelligence Colorimetric RT-LAMP Colorimetry - methods COVID-19 - diagnosis COVID-19 Testing DNA Humans LAMP-DETR Machine learning Nucleic Acid Amplification Techniques - methods Point-of-Care Systems RNA RNA, Viral - genetics SARS-CoV-2 SARS-CoV-2 - genetics Sensitivity and Specificity |
title | One-step colorimetric isothermal detection of COVID-19 with AI-assisted automated result analysis: A platform model for future emerging point-of-care RNA/DNA disease diagnosis |
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