BME PhD Dissertation Defense - James DiCarlo

  • Starts: 11:00 am on Tuesday, June 9, 2015
Title: "Engineering Yeast Genomes and Populations" Committee: George M. Church, Ph.D. (Research Advisor) Robert Winthrop Professor of Genetics Harvard Medical School Ahmad S. Khalil, Ph.D. (BME Co-Advisor) Assistant Professor of Biomedical Engineering Associate Director, Center of Synthetic Biology Boston University James J. Collins, Ph.D. Termeer Professor of Bioengineering Massachusetts Institute of Technology James Galagan, Ph.D. Associate Professor, Biomedical Engineering and Microbiology Associate Director, Systems Biology, National Emerging Infectious Diseases Laboratory Associate Director, Microbial Genome Analysis, Broad Institute Boston University Wilson Wong, Ph.D.(Appointed Examination Chair) Associate Professor of Biomedical Engineering Boston University Abstract: The field of synthetic biology seeks to use design principles of life to create new genes, organisms and populations to both better understand biology as well as generate species with useful properties. Budding yeast, Saccharomyces cerevisiae, has been a workhorse for synthetic biology, as well as an important model organism in the broader fields of molecular biology and genetics. This thesis aimed to create genome engineering tools for the manipulation of genomes, with direct applications in yeast. I focused developing high-throughput and highly efficient methods for making genomic modifications in yeast to allow for the generation of large libraries of precisely modified yeast genomes. By manipulation of endogenous DNA recombinases and mismatch repair enzymes in yeast, we were able to develop an oligonucleotide only method for genome engineering to generate libraries with a frequency of modification as high as 1%, translating to a library size of as large as 10^5 individuals. Additionally, we validated the use of RNA-guided CRISPR/Cas9 endonucleases to make changes in yeast genomes, resulting in frequencies of genome modification >90% in transformed populations. We further optimized this method to generate larger libraries as high as 10^5 individuals and explored a proof of concept epistasis experiment involving thermotolerance. Lastly, the propagation of changes to successive generations is useful when engineering organisms on the population level. To this end we explored the use of RNA-guided gene drives to bias inheritance in S. cerevisiae. We show that inheritance of these selfish elements can be biased to over 99% and is reversible.
Location:
New Research Building Room 350 77 Avenue Louis Pasteur Boston, MA 02115