Project description:Reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a fast and convenient method to amplify and identify the transcripts of a targeted pathogen. We combined bioinformatic and experimental analyses to improve the RT-LAMP assay performance for COVID-19 diagnosis. First, we developed an improved algorithm to design LAMP primers targeting the nucleocapsid (N), membrane (M), and spike (S) genes of SARS-CoV-2. Next, we rigorously validated these new assays for their efficacy and specificity. Further, we demonstrated that multiplexed RT-LAMP assays could directly detect as low as a few copies of SARS-CoV-2 RNA in saliva, without the need of RNA isolation. Importantly, further testing using saliva samples from COVID-19 patients indicated that the new RT-LAMP assays were in total agreement in sensitivity and specificity with standard RT-qPCR. In summary, our new LAMP primer design algorithm along with the validated assays provide a fast and reliable method for the diagnosis of COVID-19 cases.
Project description:We combined RT-LAMP with deep sequencing to detect as few as 5–10 virions of SARS-CoV-2 in unprocessed human saliva. Based on a multi-dimensional barcoding strategy, COV-ID can be used to test thousands of samples overnight in a single sequencing run with limited labor and laboratory equipment. The sequencing-based readout allows COV-ID to detect multiple amplicons simultaneously, including key controls such as host transcripts and artificial spike-ins, as well as multiple pathogens. Here we demonstrate this flexibility by simultaneous detection of 4 amplicons in contrived saliva samples: SARS-CoV-2, influenza A, human STATHERIN, and an artificial SARS spike-in. The approach was validated on clinical saliva samples, where it showed 100% agreement with RT-qPCR. COV-ID can also be performed directly on saliva adsorbed on filter paper, simplifying collection logistics and sample handling.
Project description:Saliva is a convenient non-invasive source of liquid biopsy to monitor human health and diagnose diseases. In particular, extracellular vesicles (EVs) in saliva can potentially reveal clinically relevant information for systemic health. Recent studies have shown that RNA in saliva EVs could be exploited as biomarkers for disease diagnosis. However, there is no standardized protocol for profiling RNA in saliva EV nor clear guideline on selecting saliva fractions for biomarker analysis. To address these issues, we established a robust protocol for small RNA profiling from fractionated saliva. With this method, we performed comprehensive small RNA sequencing of four saliva fractions, including cell-free saliva (CFS), EV-depleted saliva (EV-D), exosome (EXO), and microvesicle (MV) from ten healthy volunteers. Methods: To address these issues, we established a robust protocol for small RNA profiling from fractionated saliva. With this method, we performed comprehensive small RNA sequencing of four saliva fractions, including cell-free saliva (CFS), EV-depleted saliva (EV-D), exosome (EXO), and microvesicle (MV) from ten healthy volunteers.
Project description:Exosomes were isolared from saliva od healthy individuals and head and neck cancer (HNSCC) patients.miRNA profiling of saliva-derived exosomes was perfomred using nCounter SPRINT system. Samples were grouped according to Healthy and Tumor based on their saliva-derived exosomal miRNA profile.