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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404558/ https://www.ncbi.nlm.nih.gov/pubmed/35738204 http://dx.doi.org/10.1016/j.talanta.2022.123375 |
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author | 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 |
author_facet | 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 |
author_sort | Jaroenram, Wansadaj |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-9404558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94045582022-08-25 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 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 Talanta Article 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. Elsevier B.V. 2022-11-01 2022-03-10 /pmc/articles/PMC9404558/ /pubmed/35738204 http://dx.doi.org/10.1016/j.talanta.2022.123375 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article 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 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 | 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_full | 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_fullStr | 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_full_unstemmed | 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_short | 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_sort | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404558/ https://www.ncbi.nlm.nih.gov/pubmed/35738204 http://dx.doi.org/10.1016/j.talanta.2022.123375 |
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