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Image-based pooled genetic screens for complex cellular phenotypes
Biological processes are organized in hierarchical interactions of molecules, cells, tissues, and organisms. Cells perform complex functions individually, which when misregulated can result in disease states affecting the entire organism. However, knowledge of the genetic and molecular basis for many cellular phenomena is incomplete, limiting the ability to reverse disease states and engineer biological function. Although recent technologies have enabled scalable functional genomics approaches such as pooled CRISPR screening, the cellular phenotypes that can be linked to gene function in a pooled screen have been restricted to measurement by sequencing, and are often a step removed from the biological process of interest. In contrast, microscopy provides a high-throughput and flexible means to measure a wide range of biologically-relevant phenotypes. Here, we apply an image-based pooled screening approach based on in situ sequencing to understand the contributions of protein-coding genes to a wide range of cellular processes. Specifically, we combine pooled CRISPR/Cas9 genomic perturbations of 5,072 fitness-conferring genes with microscopy-based visualization of DNA, DNA damage response, actin, and microtubules across more than 31 million human cells. By leveraging the complex phenotypes resulting from each perturbation, we identify co-functional genes across diverse cellular activities, revealing novel gene functions and associations. Additionally, we demonstrate pooled CRISPR screening combined with live-cell imaging of more than 400,000 cell division events to further identify unexpected contributions to chromosome segregation. Altogether, this work demonstrates image-based pooled genetic screening as a scalable approach to measure and understand genetic contributions to complex phenotypes and cellular functions.
Thesis Supervisor:
Paul C. Blainey, PhD
Associate Professor of Biological Engineering, MIT
Thesis Committee Chair:
Mark Bathe, PhD
Professor of Biological Engineering, MIT
Thesis Reader:
Iain M. Cheeseman, PhD
Professor of Biology, MIT
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