UCI-developed COVID-19 check detects, identifies particular variants with 100% accuracy | UCI Information
Irvine, Calif., Aug. 3, 2022 — College of California, Irvine researchers have developed a COVID-19 check that detects and identifies particular SARS-CoV-2 variants with 100% accuracy. In a research, the RNA-encoded viral nucleic acid analytic reporter accurately decided the alpha, gamma, delta, epsilon and omicron genetic mutations in nasopharyngeal medical samples. This means might allow healthcare suppliers to make customized therapy choices for improved affected person care.
Just lately revealed on-line within the Journal of the American Chemical Society, a paper on the analysis describes the design and validation of the Revealr SARS-CoV-2 genotyping system.
“The COVID-19 pandemic has created an pressing want for individualized diagnostic instruments that may acknowledge the presence of the virus in addition to the actual pressure. Figuring out and triaging sufferers contaminated with variants that improve viral transmissibility and scale back vaccine safety is essential to controlling unfold of the illness,” stated corresponding creator John Chaput, UCI professor of pharmaceutical sciences. “Revealr goes past easy COVID detection strategies, such because the generally used antigen equipment, to establish the exact SARS-CoV-2 pressure infecting a affected person.”
The workforce analyzed 34 medical samples collected in early, mid- and late 2021 on the UCI Medical Middle from sufferers experiencing COVID-19 signs. The RNA was remoted from the nasopharyngeal swabs, and the right SARS-CoV-2 variant was recognized in each case.
“Though Revealr was developed as a COVID detection assay, the following step is to develop to different respiratory tract infections that share signs with COVID-19, like influenza,” Chaput stated. “The flexibility to tell apart single-point mutation in a DNA or RNA genetic sequence makes it ideally fitted to any genotyping, together with most cancers. Past human well being, Revealr might discover use in forensic or agricultural functions that presently depend on DNA sequencing.”
The research workforce included Chaput lab member Kefan Yang, a graduate scholar in chemical and biomolecular engineering; Chaput lab member Daniel Schuder, a graduate scholar in molecular biology and biochemistry; and Arlene Ngor, who manages the Chaput lab.
The researchers have filed a patent software on Revealr genotyping.
The gathering of medical samples was supported by the Chao Household Complete Most cancers Middle Experimental Tissue Shared Useful resource below Nationwide Most cancers Institute award quantity P30CA062203.
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