CloneSifter: enrichment of rare clones from heterogeneous cell populations
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12915_2020_Article_911.pdf
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Author(s)
Feldman, David
Tsai, FuNien
Garrity, Anthony J
O’Rourke, Ryan
Brenan, Lisa
Ho, Patricia
Gonzalez, Elizabeth
Konermann, Silvana
Johannessen, Cory M
Beroukhim, Rameen
Date Issued
November 24, 2020
Publisher
BioMed Central
Citation
BMC Biology. 2020 Nov 24;18(1):177
Version
Final published version
Abstract
Abstract
Background
Many biological processes, such as cancer metastasis, organismal development, and acquisition of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. While large-scale barcoding with NGS readout has facilitated cellular fitness assessment at the population level, this approach does not support characterization of clones prior to selection. Single-cell genomics methods provide high biological resolution, but are challenging to scale across large populations to probe rare clones and are destructive, limiting further functional analysis of important clones.
Results
Here, we develop CloneSifter, a methodology for tracking and enriching rare clones throughout their response to selection. CloneSifter utilizes a CRISPR sgRNA-barcode library that facilitates the isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrate that CloneSifter can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1883 in a heterogeneous cell population.
Conclusions
CloneSifter provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Department of Biological Engineering
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1186/s12915-020-00911-3
