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      Development and implementation of a scalable and versatile test for COVID-19 diagnostics in rural communities

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          Abstract

          Rapid and widespread testing of severe acute respiratory coronavirus 2 (SARS-CoV-2) is essential for an effective public health response aimed at containing and mitigating the coronavirus disease 2019 (COVID-19) pandemic. Successful health policy implementation relies on early identification of infected individuals and extensive contact tracing. However, rural communities, where resources for testing are sparse or simply absent, face distinctive challenges to achieving this success. Accordingly, we report the development of an academic, public land grant University laboratory-based detection assay for the identification of SARS-CoV-2 in samples from various clinical specimens that can be readily deployed in areas where access to testing is limited. The test, which is a quantitative reverse transcription polymerase chain reaction (RT-qPCR)-based procedure, was validated on samples provided by the state laboratory and submitted for FDA Emergency Use Authorization. Our test exhibits comparable sensitivity and exceeds specificity and inclusivity values compared to other molecular assays. Additionally, this test can be re-configured to meet supply chain shortages, modified for scale up demands, and is amenable to several clinical specimens. Test development also involved 3D engineering critical supplies and formulating a stable collection media that allowed samples to be transported for hours over a dispersed rural region without the need for a cold-chain. These two elements that were critical when shortages impacted testing and when personnel needed to reach areas that were geographically isolated from the testing center. Overall, using a robust, easy-to-adapt methodology, we show that an academic laboratory can supplement COVID-19 testing needs and help local health departments assess and manage outbreaks. This additional testing capacity is particularly germane for smaller cities and rural regions that would otherwise be unable to meet the testing demand.

          Abstract

          Here, the authors report the development of a versatile academic, SARSCoV-2 RT-qPCR molecular diagnostic test that uses 3D printed technology for sample collection, is implemented in rural setting in the US state of Virginia and validated in its population.

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          Most cited references17

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            Tracking changes in SARS-CoV-2 Spike: evidence that D614G increases infectivity of the COVID-19 virus

            Summary A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic. Dynamic tracking of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographic levels: national, regional and municipal. The shift occurred even in local epidemics where the original D614 form was well established prior to the introduction of the G614 variant. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have a fitness advantage. We found that the G614 variant grows to higher titer as pseudotyped virions. In infected individuals G614 is associated with lower RT-PCR cycle thresholds, suggestive of higher upper respiratory tract viral loads, although not with increased disease severity. These findings illuminate changes important for a mechanistic understanding of the virus, and support continuing surveillance of Spike mutations to aid in the development of immunological interventions.
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              CRISPR-Cas12–based detection of SARS-CoV-2

              An outbreak of betacoronavirus SARS-CoV-2 began in Wuhan, China in December 2019. COVID-19, the disease associated with infection, rapidly spread to produce a global pandemic. We report development of a rapid (<40 min), easy-to-implement and accurate CRISPR-Cas12-based lateral flow assay for detection of SARS-CoV-2 from respiratory swab RNA extracts. We validated our method using contrived reference samples and clinical samples from US patients, including 36 patients with COVID-19 infection and 42 patients with other viral respiratory infections. Our CRISPR-based DETECTR assay provides a visual and faster alternative to the US CDC SARS-CoV-2 real-time RT-PCR assay, with 95% positive predictive agreement and 100% negative predictive agreement.. SARS-CoV-2 in patient samples is detected in under an hour using a CRISPR-based lateral flow assay.
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                Author and article information

                Contributors
                finkielc@vt.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 July 2021
                20 July 2021
                2021
                : 12
                : 4400
                Affiliations
                [1 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Molecular Diagnostics Laboratory, Fralin Biomedical Research Institute, , Virginia Tech, ; Roanoke, VA USA
                [2 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Center for Glial Biology in Health, Disease, and Cancer, , Fralin Biomedical Research Institute at VTC, ; Roanoke, VA USA
                [3 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Department of Statistics, , Virginia Tech, ; Blacksburg, VA USA
                [4 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Virginia Tech Carilion School of Medicine, ; Roanoke, VA USA
                [5 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Department of Geosciences, , Virginia Tech, ; Blacksburg, VA USA
                [6 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Translational Biology, Medicine, and Health Graduate Program, , Virginia Tech, ; Roanoke, VA USA
                [7 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Fralin Biomedical Research Institute at VTC, ; Roanoke, VA USA
                [8 ]GRID grid.14105.31, ISNI 0000000122478951, MRC London Institute of Medical Sciences, ; London, UK
                [9 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Institute of Clinical Sciences, , Imperial College London, ; London, UK
                [10 ]GRID grid.280313.b, ISNI 0000 0004 0387 7895, Division of Surveillance and Investigation, Office of Epidemiology, , Virginia Department of Health, ; Christiansburg, USA
                [11 ]GRID grid.280313.b, ISNI 0000 0004 0387 7895, New River Valley Health District, Virginia Department of Health, ; Christiansburg, USA
                [12 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Integrated Cellular Responses Laboratory, , Fralin Biomedical Research Institute at VTC, ; Roanoke, VA USA
                [13 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Department of Biological Sciences, , Virginia Tech, ; Blacksburg, VA USA
                Author information
                http://orcid.org/0000-0002-9212-5294
                http://orcid.org/0000-0002-2298-7753
                http://orcid.org/0000-0002-6514-8976
                http://orcid.org/0000-0002-1381-5351
                http://orcid.org/0000-0001-8803-5950
                http://orcid.org/0000-0002-3169-1508
                http://orcid.org/0000-0001-6976-3936
                http://orcid.org/0000-0001-8468-1357
                http://orcid.org/0000-0002-6526-4782
                http://orcid.org/0000-0002-5843-9871
                http://orcid.org/0000-0002-8417-4643
                Article
                24552
                10.1038/s41467-021-24552-4
                8292415
                34285229
                20508964-43f2-4b31-be18-c44cf96f8f16
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 February 2021
                : 24 June 2021
                Categories
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                Custom metadata
                © The Author(s) 2021

                Uncategorized
                genomic analysis,gene expression profiling
                Uncategorized
                genomic analysis, gene expression profiling

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