Published August 2021 | Version Accepted Version + Supplemental Material
Journal Article Open

Ultrasensitive ultrasound imaging of gene expression with signal unmixing

Abstract

Acoustic reporter genes (ARGs) that encode air-filled gas vesicles enable ultrasound-based imaging of gene expression in genetically modified bacteria and mammalian cells, facilitating the study of cellular function in deep tissues. Despite the promise of this technology for biological research and potential clinical applications, the sensitivity with which ARG-expressing cells can be visualized is currently limited. Here we present burst ultrasound reconstructed with signal templates (BURST)—an ARG imaging paradigm that improves the cellular detection limit by more than 1,000-fold compared to conventional methods. BURST takes advantage of the unique temporal signal pattern produced by gas vesicles as they collapse under acoustic pressure above a threshold defined by the ARG. By extracting the unique pattern of this signal from total scattering, BURST boosts the sensitivity of ultrasound to image ARG-expressing cells, as demonstrated in vitro and in vivo in the mouse gastrointestinal tract and liver. Furthermore, in dilute cell suspensions, BURST imaging enables the detection of gene expression in individual bacteria and mammalian cells. The resulting abilities of BURST expand the potential use of ultrasound for non-invasive imaging of cellular functions.

Additional Information

© 2021 Nature Publishing Group. Received 29 June 2020; Accepted 30 June 2021; Published 05 August 2021. We thank P. Dutka for assistance with electron microscopy, M. Swift for assistance with animal protocols and B. Jin for the supine mouse illustration. D.P.S. is supported by the NSF graduate research fellowship (award number 1745301). A.B.-Z. is supported by the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 792866. A.F. was supported by the NSERC graduate fellowship. This research was funded by the National Institutes of Health (grant no. R01-EB018975 (to M.G.S.)). Related research in the Shapiro laboratory is also supported by the Chan-Zuckerberg Initiative, Heritage Medical Research Institute, Burroughs Wellcome Career Award at the Scientific Interface, the Pew Scholarship in the Biomedical Sciences and the Packard Fellowship for Science and Engineering. Data availability: Primary image data are available on GitHub (https://github.com/shapiro-lab/burst-imaging-public). Source data are provided with this paper. Code availability: MATLAB code is available on GitHub (https://github.com/shapiro-lab/burst-imaging-public). Author Contributions: D.P.S. and M.G.S. conceived and designed the study. D.P.S., A.F. and A.B.-Z. designed the BURST pulse sequence. D.P.S. designed the BURST+ pulse sequence and the signal unmixing algorithm. D.P.S. wrote the MATLAB scripts for ultrasound imaging and data processing. A.B.-Z. prepared genetic constructs in S. Typhimurium and E. coli Nissle 1917. A.F. and S.S. prepared genetic constructs in HEK293 cells. S.S. performed flow cytometry measurements. D.P.S. performed the in vitro ultrasound experiments. D.P.S., A.L.-G. and B.L. performed in vivo ultrasound experiments. D.P.S. and M.G.S. analyzed the data. D.P.S. and M.G.S. wrote the manuscript with input from all authors. M.G.S. supervised the research. Competing interests: The California Institute of Technology has filed a patent application (US 16/736,581) related to the imaging method described in this article. Peer review information: Nature Methods thanks Junjie Yao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Nina Vogt was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Attached Files

Accepted Version - nihms-1720572.pdf

Supplemental Material - 41592_2021_1229_Fig10_ESM.webp

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Additional details

Identifiers

PMCID
PMC8363212
Eprint ID
109325
DOI
10.1038/s41592-021-01229-w
Resolver ID
CaltechAUTHORS:20210601-112517625

Funding

NSF Graduate Research Fellowship
DGE-1745301
Marie Curie Fellowship
792866
Natural Sciences and Engineering Research Council of Canada (NSERC)
NIH
R01-EB018975
Chan-Zuckerberg Initiative
Heritage Medical Research Institute
Burroughs Wellcome Fund
Pew Charitable Trust
Alfred P. Sloan Foundation

Dates

Created
2021-06-01
Created from EPrint's datestamp field
Updated
2022-02-10
Created from EPrint's last_modified field

Caltech Custom Metadata

Caltech groups
Heritage Medical Research Institute, Tianqiao and Chrissy Chen Institute for Neuroscience