Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.

High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.

Development of an efficient one-step real-time reverse transcription polymerase chain reaction method for severe acute respiratory syndrome-coronavirus-2 detection.

The general methods to detect the RNA of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) in clinical diagnostic testing involve reverse transcriptases and thermostable DNA polymerases. In this study, we compared the detection of SARS-CoV-2 by a one-step real-time RT-PCR method using a heat-resistant reverse transcriptase variant MM4 from Moloney murine leukemia virus, two thermostable DNA polymerase variants with reverse transcriptase activity from Thermotoga petrophila K4 and Thermococcus kodakarensis KOD1, or a wild-type DNA polymerase from Thermus thermophilus M1. The highest performance was achieved by combining MM4 with the thermostable DNA polymerase from T. thermophilus M1. These enzymes efficiently amplified specific RNA using uracil-DNA glycosylase (UNG) to remove contamination and human RNase P RNA amplification as an internal control. The standard curve was obtained from 5 to 105 copies of synthetic RNA. The one-step real-time RT-PCR method's sensitivity and specificity were 99.44% and 100%, respectively (n = 213), compared to those of a commercially available diagnostic kit. Therefore, our method will be useful for the accurate detection and quantification of SARS-CoV-2.