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Acoustically triggered mechanotherapy using genetically encoded gas vesicles

Nature Nanotechnology volume 16, pages 1403–1412 (2021)Cite this article

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Abstract

Recent advances in molecular engineering and synthetic biology provide biomolecular and cell-based therapies with a high degree of molecular specificity, but limited spatiotemporal control. Here we show that biomolecules and cells can be engineered to deliver potent mechanical effects at specific locations inside the body through ultrasound-induced inertial cavitation. This capability is enabled by gas vesicles, a unique class of genetically encodable air-filled protein nanostructures. We show that low-frequency ultrasound can convert these biomolecules into micrometre-scale cavitating bubbles, unleashing strong local mechanical effects. This enables engineered gas vesicles to serve as remotely actuated cell-killing and tissue-disrupting agents, and allows genetically engineered cells to lyse, release molecular payloads and produce local mechanical damage on command. We demonstrate the capabilities of biomolecular inertial cavitation in vitro, in cellulo and in vivo, including in a mouse model of tumour-homing probiotic therapy.

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Fig. 1: Purified GVs act as seeds for stable and inertial cavitation.
Fig. 2: Ultrafast optical imaging and acoustic recording of GV-seeded bubble formation and cavitation.
Fig. 3: Molecularly targeted GVs serve as ultrasound-triggered disruptors of mammalian cells.
Fig. 4: GVs as genetically encoded seeds for cellular inertial cavitation and payload release.
Fig. 5: GV-seeded cavitation and tissue disruption in vivo.
Fig. 6: Tumour mechanotherapy seeded by tumour-homing probiotics.

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Data availability

Plasmids sequences are given in Supplementary Table 3, and will be made available through Addgene. All the raw data related to the plots and graphs are available at https://github.com/shapiro-lab/GV_cavitation.git. All the other materials and data are available from the corresponding author upon reasonable request.

Code availability

MATLAB codes are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors thank D. Piraner, A. Lakshmanan, A. Farhadi and P. Ramesh for helpful discussions. In addition, we thank A. Farhadi for his help with the GvpC-RGD variant and H. Davis for his inputs on the optical design of the high-speed set-up. We thank M. Harel (www.maayanillustration.com) for the illustrations in this paper. We also thank A. McDowall for help with electron microscopy and C. Rabut for help with the animal experiments. This project was supported by the David and Lucile Packard Fellowship for Science and Engineering (M.G.S.) and the Heritage Medical Research Institute (M.G.S.). In addition, this project received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement no. 792866 (A.B.-Z.). A.B.-Z. was also supported by the Lester Deutsch Fellowship. A.N. was supported by the Amgen scholars programme. S.S. is supported by the NSF Graduate Research Fellowship. M.H.A. is supported by the NSF Graduate Research Fellowship and the P.D. Soros Fellowship. M.T.B. is supported by the NSF Graduate Research Fellowship. D. Maresca is supported by the Human Frontiers Science Program Cross-Disciplinary Fellowship.

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Authors and Affiliations

  1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Avinoam Bar-Zion, Atousa Nourmahnad, Sangjin Yoo, Marjorie T. Buss, Dina Malounda, Audrey Lee-Gosselin, Margaret B. Swift, David Maresca & Mikhail G. Shapiro

  2. Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA

    David R. Mittelstein

  3. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Shirin Shivaei, Robert C. Hurt & Mohamad H. Abedi

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Contributions

A.B.-Z. and M.G.S. conceived the study. A.B.-Z., A.N., D. Maresca, D.R.M., S.Y. and S.S. designed, planned and conducted the in vitro experiments. A.B.-Z., A.N., M.T.B., R.C.H., A.L.-G. and M.B.S. designed, planned and conducted in vivo experiments. A.B.-Z. edited the gene circuits with the guidance of M.H.A. A.B.-Z., A.N., D.R.M., S.Y. and D. Maresca analysed the data. D. Malounda prepared the purified GVs. All the authors discussed the results. A.B.-Z., A.N. and M.G.S wrote the manuscript with input from all the authors. All the authors have given their approval for the final version of the manuscript. M.G.S. supervised the research.

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Correspondence to Mikhail G. Shapiro.

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The California Institute of Technology has filed a patent application related to this manuscript. The authors have no other competing interests.

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Peer review information Nature Nanotechnology thanks Mark Borden and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 GVs attenuate ultrasound at high concentrations.

(a) Illustration of the sample chamber and setup as seen in the images. (b) B-mode images of purified Ana GVs in different concentrations showing acoustic shadowing at high concentrations. Scale bar, 3 mm. (c) Average broadband emissions measured as a function of GV concentration. GVs were insonated with a single 30-cycle pulse with PNP = 1.0 MPa (n = 5).

Extended Data Fig. 2 GV-seeded cavitation at 3 MHz requires higher pressure levels.

(a) Broadband signals recorded from GVs (0.3 nM) and BSA (matched in mg/mL to GVs concentration) insonated at 3 MHz. Broadband signal increased with pressure and was significantly higher for GV samples at PNP≥0.5 MPa (p < 0.05 for PNP < 1.33 MPa, and p < 0.001 at higher pressure levels, n = 8 independent samples). (b) Comparison between broadband signals from GVs insonated with 670 kHz and 3 MHz pulses (n = 16 and n = 8 independent samples, respectively). Error bars, mean ± s.e.m (a-b).

Extended Data Fig. 3 High frame rate optical imaging of GV collapse and bubble cavitation.

High-speed camera frames (left to right then top to bottom) of GV collapse and cavitation (200 ns between each frame, 31×31 μm field of view), focusing on a single bubble. Initial black spots, which correspond to intact GVs, first disappear due to collapse, liberating gas that coalesces into a cavitating bubble in this region. GVs were insonated with a single 30-cycle pulse with PNP of 1.4 MPa and a central frequency of 670 kHz.

Extended Data Fig. 4 Simulation of free bubble dissolution.

The kinetics of gas bubble dissolution were calculated based on the modified-EP (Epstein and Plesset) equation, following the analysis in [25]: \(- \frac{{{{{\mathbf{dr}}}}}}{{{{{\mathbf{dt}}}}}} = \frac{{{{\mathbf{L}}}}}{{{{{\mathbf{r}}}}/{{{\mathbf{D}}}}_{{{\mathbf{w}}}}}}\left( {\frac{{1 + 2\sigma /{{{\mathbf{P}}}}_a{{{\mathbf{r}}}} - {{{\mathbf{f}}}}}}{{1 + 3\sigma /4{{{\mathbf{P}}}}_a{{{\mathbf{r}}}}}}} \right)\), where Pa = 101.3 kPa is the hydrostatic pressure outside the bubble and r is the bubble radius. Here, L = 0.02 is Ostwald’s coefficient, Dw = 2 × 10−5 cm2 s−1 is the gas diffusivity in water, σ = 72 mNm−1 is the surface tension, and f = 1 is the ratio between the gas concentration in the medium versus that at saturation. This model assumes a perfectly spherical geometry and neglects the potentially stabilizing effects of the nearby collapsed GV shell. However, it provides useful simulations that illustrate the time constants relevant to the process of GV cavitation. (a) Radius-time curves of free air-filled bubbles of different initial sizes. The gas liberated from a collapsed GV occupied the volume of a sphere with a radius of 89 nm under atmospheric conditions and no surface tension, and is expected to have an initial radius slightly larger than 20 nm when surface tension between air and water is assumed across its surface. The actual initial radius is expected to be somewhere between these two values, depending on the degree of stabilization by collapsed GV shells or other solution components. (b) Time before 50% volume reduction for free air-filled bubbles of different sizes. These time constants support the ability of nanobubble to survive the half-cycle between GV collapse (peak pressure) and peak rarefaction. In addition, they can guide the selection of the pulse repetition interval after the initial bubble growth.

Extended Data Fig. 5 High frame rate optical imaging of GVs attached to tumour cells.

(a) GVs attached to U87 cells (0.4 µs) are collapsed by the ultrasound wave (0.8 µs). (b) Differential map comparing pre- and post-collapse images (c) Only after the collapse of the GVs are cavitation events seen (3.4 µs and 9.2 µs). The samples were insonated with a single 30-cycle pulse with PNP = 1.4 MPa a central frequency of 670 kHz. The representative result in panels a-c belongs to one of the 8 repeats presented in Fig. 3g. Scale bars represent 20 µm (a-c).

Extended Data Fig. 6 Targeted and expressed GVs are frequently grouped in close proximity.

The close proximity between expressed or targeted GVs could play an important role in GV cavitation (a) SEM image of Ana GVs attached to U87 cell, forming large patches. (b) TEM image of GVs expressed in S. typhimurium showing a large cluster. Scale bar is 5 μm (a), 1 μm (b). SEM scans of GVs attached to cells and TEM scans of GV expressing S. typhimurium were repeated more than 10 times, all with similar results showing patches or clusters of GVs.

Extended Data Fig. 7 Ultrasound images comparing GV expression in bacteria and mammalian cells.

(a) Ultrasound images of agarose phantoms containing S. typhimurium cells expressing GVs . The initial frame shows the echo from collapsing GVs (left, Peak US,), and the second one presents the residual signal from the cells after bubble dissolution (middle, Collapsed). The GV-specific signal, calculated as the difference between these two images, reveals high GV content in bacteria (right, Difference). (b) Ultrasound images of agarose phantoms containing GV-expressing HEK293 cells. The bacteria and mammalian cell samples were loaded into agarose phantoms at the same concentration as used in cavitation experiments. The volume of each well was 25 µl and it contained either 2 × 105 trypsinized mARG-HEK cells or OD600 = 1 (about 2 × 106) GV-expressing S. typhimurium cells. The combined volume of the mARG-HEK cells greatly exceeds the combined volume of the bacterial cells. However, the partial volume occupied by GVs in mammalian cell is much lower than in bacteria, resulting in lower GV-specific signal.

Extended Data Fig. 8 Color deconvolution of H&E stains reveals effects of GV cavitation on surrounding tissue.

Histologic stains of liver samples were collected after systemic saline injection followed by FUS exposure (negative control, a-d) or GV injection followed by FUS exposure (e-h). Color deconvolution was applied to H&E stains of liver sections (a, e) to obtain separate images of red blood cells (b, f) and tissue (c, g). The residual unmixed images are presented in (d, h). Necrotic regions in the H&E images (e, zoom-in in i) were found around hemorrhagic foci (f, zoom-in in j) in the livers of mice injected with GVs following FUS exposure. Scale bar is 2 mm (d, h), 200 μm (j). The representative results in this figure belong to one of the 5 repeats presented in Fig. 5g, h.

Extended Data Fig. 9 Flow Cytometry Quantification.

Gating strategy for quantifying cell death in mArg-HEK cells, including the SSC-FSC gating of one sample from each population and its Zombie NIR fluorescence histogram. Cell death was quantified by gating the fraction of cells that emitted Zombie NIR fluorescence. The cutoff was the same for all samples.

Supplementary information

Supplementary Information

Supplementary Tables 1–3.

Reporting Summary

41565_2021_971_MOESM3_ESM.avi

Supplementary Video 1 Representative high frame rate movie of GV attached to a Mylar plate. A series of 256 images showing cavitation nucleated by GVs attached to a Mylar plate were collected over 51.2 µs at 5 million frames per second (fps) The movie is displayed at 5 fps, 1 million times slower than the real time.

41565_2021_971_MOESM4_ESM.avi

Supplementary Video 2 Representative high frame rate movie of GVs attached to tumour cells. A series of 256 images showing cavitation nucleated by GVs attached to U87 tumour cells were collected over 51.2 µs at 5 million frames per second (fps) The movie is displayed at 5 fps, 1 million times slower than the real time. The swaying background is a result of the movement of the Mylar membrane at the bottom of the dish during of the ultrasound pulse.

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Bar-Zion, A., Nourmahnad, A., Mittelstein, D.R. et al. Acoustically triggered mechanotherapy using genetically encoded gas vesicles. Nat. Nanotechnol. 16, 1403–1412 (2021). https://doi.org/10.1038/s41565-021-00971-8

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