Gene-editing by a "click-of-a-button"

C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Assistant Professor, Concordia University
    Biography
      Steve completed his Ph.D in Biomedical Engineering specializing in microfluidic (or "lab-n-chip") technologies at the University of Toronto. He then spent 3 years at UC Berkeley and at the Joint BioEnergy Institute as a postdoctoral researcher where he learned pathway engineering and synthetic biology. As of 2016, he is an Assistant Professor at Concordia University in the Department of Electrical and Computer Engineering and also in the Department of Biology. His research focuses on developing microfluidic tools for health, energy, and synthetic biology applications. Recently, he has been awarded the Allan Kuchinsky Bio-Automation Award from Synthetic Biology Automation Society and elected as an Emerging Investigator from the Royal Society of Chemistry. More information on the Shih lab can be found at https://users.encs.concordia.ca/~sshih/.

    Abstract

    If you have ever worked in the field of gene-editing, then you must know the powerful gene-editing technology known as CRISPR.  It has the potential to alter science and biotechnology at an inconceivable rapid rate.  But what you may not know is the laborious and manual intensive work that is needed to edit cells.  Gene editing of course has incredible promise in fields like synthetic biology and medicine, but without automated technologies to expedite their process, these could just be figments of our imagination.  In my talk, I will describe how my lab has created an automated microfluidic benchtop platform that will edit cells on-demand using a user-activated sequence.  I will also describe the use of our system for rapid editing of mammalian cells and how we can carry out manipulations at the single cell level with near instant generation of clonal, isogenic cell lines (and comparing to gold-standard techniques).  Finally, I will describe our ongoing efforts to make this technology accessible to all users (in collaboration with our startup DropGenie).

    Learning Objectives:

    1. Define current paradigm of gene editing

    2. Identify bottlenecks in the process of gene editing

    3. Explain automation approaches to gene edit cells


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