An Open One-Step RT-qPCR for SARS-CoV-2 detection

Author:

Cerda Ariel,Rivera Maira,Armijo Grace,Ibarra-Henriquez Catalina,Reyes Javiera,Blázquez-Sánchez PaulaORCID,Avilés Javiera,Arce Aníbal,Seguel Aldo,Brown Alexander J.ORCID,Vásquez Yesseny,Cortez-San Martín Marcelo,Cubillos Francisco A.,García Patricia,Ferres Marcela,Ramírez-Sarmiento César A.ORCID,Federici Fernán,Gutiérrez Rodrigo A.ORCID

Abstract

The COVID-19 pandemic has resulted in millions of deaths globally, and while several diagnostic systems were proposed, real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard. However, diagnostic reagents, including enzymes used in RT-PCR, are subject to centralized production models and intellectual property restrictions, which present a challenge for less developed countries. With the aim of generating a standardized One-Step open RT-qPCR protocol to detect SARS-CoV-2 RNA in clinical samples, we purified and tested recombinant enzymes and a non-proprietary buffer. The protocol utilized M-MLV RT and Taq DNA pol enzymes to perform a Taqman probe-based assay. Synthetic RNA samples were used to validate the One-Step RT-qPCR components, demonstrating sensitivity comparable to a commercial kit routinely employed in clinical settings for patient diagnosis. Further evaluation on 40 clinical samples (20 positive and 20 negative) confirmed its comparable diagnostic accuracy. This study represents a proof of concept for an open approach to developing diagnostic kits for viral infections and diseases, which could provide a cost-effective and accessible solution for less developed countries.

Funder

ANID Millennium Science Initiative Program

Fondo de Desarrollo de Areas Prioritarias/Center for Genome Regulation

Fondo de Desarrollo Científico y Tecnológico

International Cooperation Program with Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica

National Institutes of Health NIAID - Training Program in Immunology

National Agency for Research and Development

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference78 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3