Genomically mined acoustic reporter genes for real-time in vivo monitoring of tumors and tumor-homing bacteria
Abstract
Ultrasound allows imaging at a much greater depth than optical methods, but existing genetically encoded acoustic reporters for in vivo cellular imaging have been limited by poor sensitivity, specificity and in vivo expression. Here we describe two acoustic reporter genes (ARGs)—one for use in bacteria and one for use in mammalian cells—identified through a phylogenetic screen of candidate gas vesicle gene clusters from diverse bacteria and archaea that provide stronger ultrasound contrast, produce non-linear signals distinguishable from background tissue and have stable long-term expression. Compared to their first-generation counterparts, these improved bacterial and mammalian ARGs produce 9-fold and 38-fold stronger non-linear contrast, respectively. Using these new ARGs, we non-invasively imaged in situ tumor colonization and gene expression in tumor-homing therapeutic bacteria, tracked the progression of tumor gene expression and growth in a mouse model of breast cancer, and performed gene-expression-guided needle biopsies of a genetically mosaic tumor, demonstrating non-invasive access to dynamic biological processes at centimeter depth.
Additional Information
The authors would like to thank D. Newman for a sample of Streptomyces coelicolor A3(2) and Y. Li, A. Bar-Zion and H. (R.) Li for help with tissue histology. Electron microscopy was performed in the Beckman Institute Resource Center for Transmission Electron Microscopy at the California Institute of Technology. Mammalian cell sorting was performed at the Analytical Cytometry Core at City of Hope in Duarte, California. Confocal microscopy was performed in the Beckman Institute Biological Imaging Center. This research was supported by the National Institutes of Health (R01-EB018975 to M.G.S.) and the Pew Charitable Trust. R.C.H. was supported by the Caltech Center for Environmental Microbial Interactions. M.T.B. was supported by a National Science Foundation Graduate Research Fellowship Program fellowship. Related research in the Shapiro laboratory is supported by the David and Lucille Packard Foundation, the Burroughs Wellcome Fund, the Heritage Medical Research Institute and the Chan Zuckerberg Initiative. M.G.S. is an investigator of the Howard Hughes Medical Institute. These authors contributed equally: Robert C. Hurt, Marjorie T. Buss, Mengtong Duan. Contributions. R.C.H., M.T.B., M.D., K.W., M.B.S., P.D., Z.J., M.Y.Y., A.F. and R.D. planned and performed experiments. R.C.H. conceived and performed the phylogenetic screening experiments. M.T.B. and M.D. performed all in vivo experiments, with help from M.B.S and P.B.-L. P.D. and M.D. performed TEM imaging. D.R.M. built the ultrasound plate-scanning setup, and D.R.M. and D.P.S. wrote the associated MATLAB scripts for controlling it. Z.J. and D.P.S. wrote the MATLAB scripts for ultrasound imaging of EcN in vitro and in vivo. Z.J. performed the calibration of the L22-14v transducer. M.H.A. provided the Axe-Txe stability cassette and advised on tumor colonization experiments. R.C.H., M.T.B., M.D., D.P.S., P.D. and Z.J. analyzed data. R.C.H., M.T.B., M.D. and M.G.S. wrote the manuscript, with input from all other authors. M.G.S. supervised the research. Data availability. Plasmids will be made available through Addgene upon publication (https://www.addgene.org/Mikhail_Shapiro). All other materials and data are available from the corresponding author upon reasonable request. Genomic sequence information was downloaded from the NCBI sequence database via Batch Entrez (https://www.ncbi.nlm.nih.gov/sites/batchentrez). Source data are provided with this paper. Code availability. Ultrasound data acquisition and analysis code is available on the Shapiro laboratory GitHub at https://github.com/shapiro-lab. Competing interests. R.C.H., M.T.B., M.D., K.W., A.F., M.Y.Y. and M.G.S. are co-inventors on two patent applications related to this work that were filed by and assigned to the California Institute of Technology. The other authors declare no competing interests.Additional details
Identifiers
- Eprint ID
- 120181
- Resolver ID
- CaltechAUTHORS:20230317-826078000.2
Funding
- NIH
- R01-EB018975
- Pew Charitable Trust
- Caltech Center for Environmental Microbial Interactions (CEMI)
- NSF Graduate Research Fellowship
- David and Lucile Packard Foundation
- Burroughs Wellcome Fund
- Heritage Medical Research Institute
- Chan Zuckerberg Initiative
- Howard Hughes Medical Institute (HHMI)
Dates
- Created
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2023-03-17Created from EPrint's datestamp field
- Updated
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2023-03-17Created from EPrint's last_modified field