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The Importance of Hybrid-capture Technology to Recognize and Characterize Viral Threats

C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Senior Director of BioPharma Product Strategy Twist Bioscience
    Biography

      Dr. Rebecca Nugent joined Twist Bioscience in 2015 after spending many years in the biofuels and green chemicals industry. Dr. Nugent has held many roles within Twist and is currently the Sr. Director of Biopharma Product Strategy. Previously she led R&D teams focused on the development of Synthetic Biology and Next-Generation Sequencing Target Enrichment (NGS TE) products. Dr. Rebecca Nugent received her Ph.D. in Molecular Biology from the University of Southern California, where she studied yeast genetics with an emphasis on genomic stability in Dr. Susan Forsburg's lab. During her postdoctoral fellowship she developed life science tools through characterizing and engineering novel Restriction Enzymes at New England Biolabs.


    Abstract

    As viral threats continue to emerge, viral detection assays are important not only for recognizing if a virus is present, but also for surveillance and variant characterization. Accurate detection and monitoring are especially important as the SARS-CoV-2 virus mutates, requiring robust tools capable of new variants. This has been made especially clear with the emergence of new SARS-CoV-2 variants that cannot be detected by conventional PCR tests. In this presentation we will review the different types of virus detection assays. We will focus on hybrid capture followed by Next Generation Sequencing (NGS) for viral detection. The technology behind hybrid capture will be discussed. We will then demonstrate how hybrid capture is capable of distinguishing viruses causing similar respiratory illness symptoms. We will also demonstrate how hybrid capture can be used for detecting and characterizing SARS-CoV-2.

    Learning Objectives:

    1. The differences in diagnostic viral detection assays

    2. The basics of hybrid capture and how it can be used for viral recognition and characterization.


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