High-throughput genome-wide phenotypic screening via immunomagnetic cell sorting

Abstract

Genome-scale functional genetic screens are used to identify key genetic regulators of a phenotype of interest. However, the identification of genetic modifications that lead to a phenotypic change requires sorting large numbers of cells, which increases operational times and costs and limits cell viability. Here, we introduce immunomagnetic cell sorting facilitated by a microfluidic chip as a rapid and scalable high-throughput method for loss-of-function phenotypic screening using CRISPR–Cas9. We used the method to process an entire genome-wide screen containing more than 108 cells in less than 1 h—considerably surpassing the throughput achieved by fluorescence-activated cell sorting, the gold-standard technique for phenotypic cell sorting—while maintaining high levels of cell viability. We identified modulators of the display of CD47, which is a negative regulator of phagocytosis and an important cell-surface target for immuno-oncology drugs. The top hit of the screen, the glutaminyl cyclase QPCTL, was validated and shown to modify the N-terminal glutamine of CD47. The method presented could bridge the gap between fluorescence-activated cell sorting and less flexible yet higher-throughput systems such as magnetic-activated cell sorting.

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Fig. 1: A microfluidic chip for high-throughput cell sorting.
Fig. 2: FACS-free MICS–CRISPR screen identifies QPCTL as a modifier of CD47.
Fig. 3: QPCTL regulates CD47pyro-Glu formation.
Fig. 4: Direct detection of CD47pyro-Glu by MS.

Data availability

The main data supporting the results in this study are available within the paper and the Supplementary Information. Supplementary Tables 24 contain raw read counts, normalized read counts and normalized Z scores for all of the screens. Unprocessed sequencing files are available from the corresponding authors on reasonable request.

Code availability

The ImageJ custom macro used for automated image segmentation is provided in the Supplementary Information.

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Acknowledgements

We thank members of the Kelley, Moffat, Angers and C. Boone and B. Andrews laboratories for helpful discussions; K. Chan for TKOv3 library virus preparation; M. Usaj for help with data analysis; P. Mero for administrative assistance; J. Tomic for help with tissue culture; E. Cohen, M. Soste and F. Soares for technical assistance; D. White and J. Warzyszynska for flow cytometry assistance; and staff at the Centre for Applied Genomics (TCAG) at the Hospital for Sick Children (SickKids) for sequencing. This work was supported by grants from the Canadian Institutes for Health Research (to J.M., S.O.K. and S.A.) and the University of Toronto’s Medicine by Design initiative, which receives funding from the Canada First Research Excellence Fund (to S.O.K., J.M. and S.A). J.M. is a Canada Research Chair in Functional Genomics.

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Authors

Contributions

B.M. and P.M.A. performed most of the experiments and analysed data with help from R.S.A., D.P., M.L. and S.N.M. M.Z. and R.S.A. developed the MS assay. A.H.Y.T. helped with screen sequencing and data analysis. B.M., P.M.A., R.S.A., J.M. and S.O.K. wrote the manuscript. B.M., P.M.A., E.H.S., S.A., J.M. and S.O.K. designed the study. S.A., J.M. and S.O.K. supervised the study.

Corresponding authors

Correspondence to Jason Moffat or Shana O. Kelley.

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Supplementary information

Supplementary Information

Supplementary figures, tables, protocols and codes.

Reporting Summary

Supplementary Dataset 1

Screen data for MACS.

Supplementary Dataset 2

Screen data for immunomagnetic cell sorting.

Supplementary Dataset 3

Screen data for FACS.

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Mair, B., Aldridge, P.M., Atwal, R.S. et al. High-throughput genome-wide phenotypic screening via immunomagnetic cell sorting. Nat Biomed Eng 3, 796–805 (2019). https://doi.org/10.1038/s41551-019-0454-8

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