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Published February 2024 | Published
Journal Article Open

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

  • 1. ROR icon California Institute of Technology

Abstract

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

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Acknowledgement

We thank A. Kahan of the V. Gradinaru Lab for the gift of mouse brain sections during initial validation; M. E. Bronner for reading a draft of the manuscript; and the following resources within the Beckman Institute at Caltech: Molecular Technologies for providing HCR reagents, G. Spigolon of the Biological Imaging Facility for assistance with imaging, and the Zebrafish Facility for providing zebrafish embryos. The Leica Stellaris 8 confocal microscope in the Biological Imaging Facility within the Beckman Institute at Caltech was purchased with support from Caltech and the following Caltech entities: the Beckman Institute, the Resnick Sustainability Institute, the Division of Biology & Biological Engineering, and the Merkin Institute for Translational Research.

Funding

This work was funded by the National Institute of Biomedical Imaging and Bioengineering (R01EB006192), a National Institute of General Medical Sciences training grant (GM008042 to S.J.S.) and the Beckman Institute, California Institute of Technology (PMTC). Open Access funding provided by California Institute of Technology. Deposited in PMC for immediate release.

Contributions

Conceptualization: N.A.P.; Methodology: S.J.S., M.E.F., N.A.P.; Software: M.E.F.; Validation: S.J.S., M.E.F., J.K.H.; Investigation: S.J.S., J.K.H., G.J.S.; Writing - original draft: S.J.S., N.A.P.; Writing - review & editing: S.J.S., M.E.F., J.K.H., G.J.S., N.A.P.; Visualization: S.J.S., M.E.F.; Supervision: N.A.P.; Project administration: N.A.P.; Funding acquisition: N.A.P.

Data Availability

All relevant data can be found within the article and its supplementary information.

Conflict of Interest

The authors declare competing financial interests in the form of patents, pending patent applications, and the startup company Molecular Instruments, Inc.

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Additional details

Created:
March 6, 2024
Modified:
March 18, 2024