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Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots
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
Chapters
- 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
The protocol describes a SARS-CoV-2 diagnostic method that utilizes open-source automation to perform RT-qPCR molecular testing of saliva samples. This scalable approach can be applied to clinical public health surveillance as well as to increase the capacity of smaller university laboratories.
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
