Scalable perturbation and measurement of biological function via molecular encoding
Author(s)
Feldman, David,Ph. D.Massachusetts Institute of Technology.
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Other Contributors
Massachusetts Institute of Technology. Department of Physics.
Advisor
Paul C. Blainey, Feng Zhang, and Ibrahim Cisse.
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Methods are presented for optical genetic screens and lineage tracking and recovery. Pooled optical screens use pooling and molecular encoding to conduct image-based genetic screens at large scales with reduced biological noise. These assays complement existing pooled screening approaches by measuring cellular processes over space and time. Pairing of perturbations with separate barcode sequences expands the range of genetic libraries that can be assayed, but can be challenging due to lentiviral recombination that swap barcodes within a library. Here, barcode swapping is carefully measured on a cell-by-cell basis, and a method is presented to mitigate the effects of barcode swapping in a pooled lentiviral library. Lineages within a complex cell population can be tracked via genomically integrated barcodes. Identifying and isolating lineages of interest from an ancestral population based on the characteristics of their progeny would enable probing underlying lineage-specific mechanisms, but is not possible with existing inert barcode libraries. A novel barcoding technique is shown that uses the high specificity of CRISPR/Cas9 nuclease activity to isolate viable cells from rare lineages within a population. Linking sequences to biological function is one of the defining challenges of the post-genomic era. Genetic screens are essential tools for defining genes underlying functions and enable rigorous testing of models linking sequence to function, but are limited by our ability to link sequence identity to observable cell phenotypes, such as growth, gene expression, and biochemical activity. Technological advances that integrate the fast-growing experimental genetic toolbox with high-throughput functional characterization have the potential to unlock new areas of biology for quantitative, systematic analysis.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 109-117).
Date issued
2019Department
Massachusetts Institute of Technology. Department of PhysicsPublisher
Massachusetts Institute of Technology
Keywords
Physics.