An Automated Integrated Multiple Assay Platform utilizing CRISPR-based Transistors for CRISPR Quality Control Applications

Presented at: CRISPR 2020
C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Co-Founder and CSO, Cardea Bio
    Biography

      Kiana received her PhD in Biomedical Engineering at Rutgers University. She then continued her postdoctoral studies in bio-engineering at the UC Berkeley. She is a recipient of the National Institutes of Health postdoctoral training fellowship at the Buck Institute for Age Research and is a consultant for the Gates Foundation. Kiana runs the Cardea Innovation lab at the Keck Graduate Institute of Applied Life Sciences.


    Abstract

    The discovery of CRISPR technology has revolutionized the fields of transcriptional activation and repression, genome editing, gene-based therapeutics and diagnostics. The applications of this technology have been rapidly expanding as researchers continue to discover new Cas enzymes, engineer high fidelity Cas orthologs and modify and synthesize guide RNAs to efficiently direct these Cas enzymes to their targets. Despite these new discoveries and advancements in the CRISPR space, these developments can impact the Cas complex stability and efficiency and limit the efficient use of CRISPR technology. Therefore, quality control tools are needed to evaluate and understand the stability and functionality of these newly discovered or engineered Cas enzymes and synthetic gRNAs to better inform their design and applications in various environmental conditions. For example, the stability of various CRISPR-Cas complexes may vary at altered pH and temperatures making them less or more suitable for their intended applications. We have recently developed a CRISPR-based transistor technology, termed CRISPR-Chip™, that can monitor CRISPR’s efficiency in terms of Cas-gRNA binding, the stability of the Cas-gRNA complex, and the efficiency of DNA/RNA binding and cleavage under different environmental conditions. This talk will focus on the expansion of CRISPR-Chip technology being integrated into an automated platform that allows the user to perform multiple CRISPR quality control assays simultaneously. This technology is also paired with sophisticated software analysis and machine learning capabilities to further identify the relevant factors affecting CRISPR performance.

    Learning Objectives:

    1. Using an optics- and label-free approach to CRISPR research

    2. Explain current approaches to selecting the most robust gRNA for CRISPR assays

    3. The opportunities that come with automated CRISPR quality control straight at your lab bench


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