Point-Of-Need One-Pot Multiplexed RT-LAMP Test For Detecting Three Common Respiratory Viruses In Saliva

Abstract

Respiratory viral infections pose a significant global public health challenge, partly due to the difficulty in rapidly and accurately distinguishing between viruses with similar symptoms at the point of care, hindering timely and appropriate treatment and limiting effective infection control and prevention efforts. Here, we developed a multiplexed, non- invasive saliva-based, reverse transcription loop-mediated isothermal amplification (RT- LAMP) test that enables the simultaneous detection of three of the most common respiratory infections, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Influenza (Flu), and respiratory syncytial virus (RSV), in a single reaction via specific probes and monitored in real-time by a machine-learning-enabled compact analyzer. Our results demonstrate that the multiplexed assay can effectively detect three target RNAs with high accuracy. Further, testing with spiked saliva samples showed strong agreement with reverse transcription polymerase chain reaction (RT-PCR) assay, with area under the curve (AUC) values of 0.82, 0.93, and 0.96 for RSV, Influenza, and SARS-CoV-2, respectively. By enabling the rapid detection of respiratory infections from easily collected saliva samples at the point of care, the device presented here offers a practical and efficient tool for improving outcomes and helping prevent the spread of contagious diseases. SignificanceThis research presents an innovative approach to respiratory infection diagnostics by combining a one-pot isothermal molecular test with machine learning-based analysis to simultaneously detect SARS-CoV-2, Influenza, and RSV in saliva samples. The battery- powered portable analyzer features novel machine-learning-assisted fluorescence detection for multiplexed reporter quantification, eliminating the need for traditional filter- based optical components and enabling adaptation to new targets without hardware changes. The test demonstrates high accuracy in detecting single and co-infections in spiked saliva samples, providing a rapid, cost-effective point-of-need solution. This tool can expand testing access, improve patient outcomes, and support more effective disease control, particularly in resource-limited or decentralized healthcare settings.