Genotyping SARS-CoV-2 Variants Using Ratiometric Nucleic Acid Barcode Panels.

Designing diagnostic assays to genotype rapidly mutating viruses remains a challenge despite the overall improvements in nucleic acid detection technologies. RT-PCR and next-generation sequencing are unsuitable for genotyping during outbreaks or in point-of-care detection due to their infrastructure requirements and longer turnaround times. We developed a quantum dot barcode multiplexing system to genotype mutated viruses. We designed multiple quantum dot barcodes to target conserved, wildtype, and mutated regions of SARS-CoV-2. We calculated ratios of the signal output from different barcodes that enabled SARS-CoV-2 detection and identified SARS-CoV-2 variant strains from a sample. We detected different sequence types, including conserved genes, nucleotide deletions, and single nucleotide substitutions. Our system detected SARS-CoV-2 patient specimens with 98% sensitivity and 94% specificity across 91 patient samples. Further, we leveraged our barcoding and ratio system to track the emergence of the N501Y SARS-CoV-2 mutation from December 2020 to May 2021 and demonstrated that the more transmissible N501Y mutation started to dominate infections by April 2021. Our barcoding and signal ratio approach can genotype viruses and track the emergence of viral mutations in a single diagnostic test. This technology can be extended to tracking other viruses. Combined with smartphone detection technologies, this assay can be adapted for point-of-care tracking of viral mutations in real time.

Surface and Air Contamination With Severe Acute Respiratory Syndrome Coronavirus 2 From Hospitalized Coronavirus Disease 2019 Patients in Toronto, Canada, March-May 2020.

BACKGROUND: We determined the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in air and on surfaces in rooms of patients hospitalized with coronavirus disease 2019 (COVID-19) and investigated patient characteristics associated with SARS-CoV-2 environmental contamination. METHODS: Nasopharyngeal swabs, surface, and air samples were collected from the rooms of 78 inpatients with COVID-19 at 6 acute care hospitals in Toronto from March to May 2020. Samples were tested for SARS-CoV-2 ribonucleic acid (RNA), cultured to determine potential infectivity, and whole viral genomes were sequenced. Association between patient factors and detection of SARS-CoV-2 RNA in surface samples were investigated. RESULTS: Severe acute respiratory syndrome coronavirus 2 RNA was detected from surfaces (125 of 474 samples; 42 of 78 patients) and air (3 of 146 samples; 3 of 45 patients); 17% (6 of 36) of surface samples from 3 patients yielded viable virus. Viral sequences from nasopharyngeal and surface samples clustered by patient. Multivariable analysis indicated hypoxia at admission, polymerase chain reaction-positive nasopharyngeal swab (cycle threshold of ≤30) on or after surface sampling date, higher Charlson comorbidity score, and shorter time from onset of illness to sampling date were significantly associated with detection of SARS-CoV-2 RNA in surface samples. CONCLUSIONS: The infrequent recovery of infectious SARS-CoV-2 virus from the environment suggests that the risk to healthcare workers from air and near-patient surfaces in acute care hospital wards is likely limited.

A Colorimetric Test to Differentiate Patients Infected with Influenza from COVID-19.

Patients infected with SARS-CoV-2 and influenza display similar symptoms, but treatment requirements are different. Clinicians need to accurately distinguish SARS-CoV-2 from influenza to provide appropriate treatment. Here, the authors develope a color-based technique to differentiate between patients infected with SARS-CoV-2 and influenza A using a nucleic acid enzyme-gold nanoparticle (GNP) molecular test requiring minimal equipment. The MNAzyme and GNP probes are designed to be robust to viral mutations. Conserved regions of the viral genomes are targeted, and two MNAzymes are created for each virus. The ability of the system to distinguish between SARS-CoV-2 and influenza A using 79 patient samples is tested. When detecting SARS-CoV-2 positive patients, the clinical sensitivity is 90%, and the specificity is 100%. When detecting influenza A, the clinical sensitivity and specificity are 93% and 100%, respectively. The high clinical performance of the MNAzyme-GNP assay shows that it can be used to help clinicians choose effective treatments.