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.

An integrated system of air sampling and simultaneous enrichment for rapid biosensing of airborne coronavirus and influenza virus.

Point-of-care risk assessment (PCRA) for airborne viruses requires a system that can enrich low-concentration airborne viruses dispersed in field environments into a small volume of liquid. In this study, airborne virus particles were collected to a degree above the limit of detection (LOD) for a real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). This study employed an electrostatic air sampler to capture aerosolized test viruses (human coronavirus 229E (HCoV-229E), influenza A virus subtype H1N1 (A/H1N1), and influenza A virus subtype H3N2 (A/H3N2)) in a continuously flowing liquid (aerosol-to-hydrosol (ATH) enrichment) and a concanavalin A (ConA)-coated magnetic particles (CMPs)-installed fluidic channel for simultaneous hydrosol-to-hydrosol (HTH) enrichment. The air sampler's ATH enrichment capacity (EC) was evaluated using the aerosol counting method. In contrast, the HTH EC for the ATH-collected sample was evaluated using transmission-electron-microscopy (TEM)-based image analysis and real-time qRT-PCR assay. For example, the ATH EC for HCoV-229E was up to 67,000, resulting in a viral concentration of 0.08 PFU/mL (in a liquid sample) for a viral epidemic scenario of 1.2 PFU/m3 (in air). The real-time qRT-PCR assay result for this liquid sample was "non-detectable" however, subsequent HTH enrichment for 10 min caused the "non-detectable" sample to become "detectable" (cycle threshold (CT) value of 33.8 ± 0.06).