MAY 14, 2020 10:00 AM CEST

Massively Parallel Genome Engineering followed by pooled growth selections for rapid target discovery in microbes

Sponsored by: Inscripta
Speaker
  • Scientific Liaison, EMEA, Inscripta
    Biography
      Laura Klitten has worked with scientific communication within medical genetics, non-coding RNAs, molecular biology and new technologies in a variety of industrial roles for the last 8 years. Dr. Klitten is the Scientific Liaison with Inscripta's EMEA team. Dr. Klitten is, among other tasks, responsible for correct and timely communication between internal and external partners and act as the "voice of customer" within Inscripta to ensure outstanding support and execution of projects demonstrating the many applications of the Onyx Digital Genome Engineering platform. Before joining Inscripta, Dr. Klitten had different commercial roles including Global Product Manager at QIAGEN and Exiqon. Dr. Klitten earned her M.Sc. and Ph.D degrees at the University of Copenhagen, Denmark.

    Abstract
    DATE:  May 14, 2020
    TIME:  10:00am CEST
     
    Massively parallel genome engineering enables rapid and simultaneous evaluation of genotype-phenotype relationships at a genomic scale. With the Inscripta Onyx™ Platform we replaced every promoter in the E. coli genome with one of five synthetic constitutive promoters across an expression ladder from low to high relative strength. Additionally, we generated two versions of a genome scale knockout library by inserting three premature stop codons in every gene at two different positions near the 5’ end. We then pooled these libraries for a total of 23,576 genomic edits, and under strong selective pressure quantified shifts in the edited populations to determine relative strain performance.
     
    From this experiment we readily identify thousands of genotype-phenotype interactions that confirm known mechanisms and reveal large sets of novel interactions in coordinated functional modules. These results demonstrate the power of high efficiency automated genome engineering and encourage a future in which any research group can readily engage in both new target discovery and obtain a global view of the relevant genotype-phenotype interactions in their system of study.
     
     
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