bioRxivBioengineeringPreprint
High-throughput CRISPR live-cell imaging of low-frequency chromosomal events quantifies the latent efficiency of chromosome engineering
Xixun HuiD, Yuichiro IwamotoiD, Kyotaro YamazakiiD, Nanami Kishima, Natsuko OtakiiD, Hitomaru MiyamotoiD, Yuichiro MiyaokaiD, Yasuhiro KazukiiD, Sadao OtaiD
Abstract
Abstract/SummaryQuantifying low-frequency chromosomal alterations in living cell populations at early stages is essential in many fields including cancer studies and chromosome engineering, yet selection-based readouts impose delays and can lose fragile positives before readout, biasing frequency estimates; CRISPR imaging rarely reports detection limits at 10^-4. Here, we developed High-throughput CRISPR Imaging (Hi-CRI), integrating engineered dCas9-sgRNA ribonucleoprotein (RNP) labeling, suppression of nonspecific aggregates via metabolic modulation and protease treatment, high-speed volumetric imaging by oblique plane microscopy, GPU-accelerated image analysis, and an explicit error-controlled detection-limit framework. Using per-cell signal-to-noise ratio calling, Hi-CRI achieves a 0.01% detection limit for target-positive cell fractions. In microcell-mediated chromosome transfer of a mouse artificial chromosome (MAC) into HT1080 recipients, Hi-CRI measured 0.03% MAC-positive cells among 184,235 recipients at day 1 post-fusion, versus 0.0007% by antibiotic-selection-based clonogenic assay at day 8 post-fusion, consistent with substantial loss before readout (pre-readout attrition). Hi-CRI enables viability-preserving, selection-independent quantification of low-frequency chromosomal states. TeaserRare chromosome events can be counted in living cells by high-throughput CRISPR imaging before selection hides them.
- organism: mouse
- assay: fluorescence / live-cell microscopy
- research focus: chromatin & epigenetic regulation
- approach: deep learning
- approach: experimental assay
- Citations
- 0
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