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Estrategia eficiente de diagnóstico de saliva por PCR con transcriptasa inversa cuantitativa del SARS-CoV-2 utilizando robots pipeteadores de código abierto
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1Center for Innovative Medical Devices and Sensors (REDDI Lab),Clemson University, 2Department of Bioengineering,Clemson University, 3Swann Medicine, 4Student Health Services,Clemson University, 5Department of Chemical & Biomolecular Engineering,Clemson University, 6Department of Chemical & Biomolecular Engineering,University of Delaware
Capitoli
- 00:04Introduction
- 00:56Sample Intake, Heat Treatment, and Sample Assignment
- 01:52Operating Sample Loading Robots
- 04:09Manual Sample Loading
- 04:52Addition of Controls to Testing Plates
- 05:54Performing RT-qPCR and Determining Plate Validity
- 07:00Interpreting Sample Results
- 08:08Results: RT-qPCR Detection of N1 (SARS-CoV-2) Synthetic RNA and P1 (Hs_RPP30) Synthetic DNA, Comparison Between Manual and Automated Saliva Transfer N1 Ct Values, and Evaluation of Heat Treatment Methods for Viscosity Reduction in Saliva
- 10:26Conclusion
El protocolo describe un método de diagnóstico de SARS-CoV-2 que utiliza la automatización de código abierto para realizar pruebas moleculares RT-qPCR de muestras de saliva. Este enfoque escalable se puede aplicar a la vigilancia clínica de la salud pública, así como para aumentar la capacidad de los laboratorios universitarios más pequeños.
Tags
Keywords Extracted From The Given Text:
SARS-CoV-2Quantitative Reverse Transcriptase PCRSaliva DiagnosticOpen-source Pipetting RobotsCOVID-19 DiagnosticsSaliva-based TestingAutomated Parallel WorkflowsSample DecontaminationHeat TreatmentSample LoadingSample Assignment3D Printed RacksMaster Mix PlatesPython Operating Protocol
