Gas vesicles are a unique class of gas-filled protein nanostructures whose physical properties allow them to serve as highly sensitive imaging agents for ultrasound and magnetic resonance imaging (MRI), detectable at sub-nanomolar concentrations. Here we provide a protocol for isolating gas vesicles from native and heterologous host organisms, functionalizing these nanostructures with moieties for targeting and fluorescence, characterizing their biophysical properties and imaging them using ultrasound and magnetic resonance imaging. Gas vesicles can be isolated from natural cyanobacterial and haloarchaeal host organisms or from E. coli expressing a heterologous gas vesicle gene cluster, and purified using buoyancy-assisted techniques. They can then be modified by replacing surface-bound proteins with engineered, heterologously expressed variants, or through chemical conjugation, resulting in altered mechanical, surface and targeting properties. Pressurized absorbance spectroscopy is used to characterize their mechanical properties, while dynamic light scattering and transmission electron microscopy are used to determine nanoparticle size and morphology, respectively. Gas vesicles can then be imaged with ultrasound in vitro and in vivo using pulse sequences optimized for their detection versus background. They can also be imaged with hyperpolarized xenon MRI using chemical exchange saturation transfer between gas vesicle-bound and dissolved xenon – a technique currently implemented in vitro. Taking 3–8 days to prepare, these genetically encodable nanostructures enable multi-modal, noninvasive biological imaging with high sensitivity and potential for molecular targeting.

Labile complexation of cucurbit[6]uril with xenon becomes detectable through saturation transfer with highly efficient gas turnover for ultra-sensitive NMR applications.

The reversible binding of xenon to host molecules has found numerous applications in nuclear magnetic resonance studies. Quantitative characterization of the Xe exchange dynamics is important to understand and optimize the physico-chemical behavior of such Xe hosts, but is often challenging to achieve at low host concentrations. We have investigated a sensitive quantification technique based on chemical exchange saturation transfer with hyperpolarized nuclei, qHyper-CEST. Using simulated signals we demonstrated that qHyper-CEST yielded accurate and precise results and was robust in the presence of large amounts of noise (10%). This is of particular importance for samples with completely unknown exchange rates. Using these findings we experimentally determined the following exchange parameters for the Xe host cryptophane-A monoacid in dimethyl sulfoxide in one type of experiment: the ratio of bound and free Xe, the Xe exchange rate, the resonance frequencies of free and bound Xe, the Xe host occupancy, and the Xe binding constant. Taken together, qHyper-CEST facilitates sensitive quantification of the Xe exchange dynamics and binding to hydrophobic cavities and has the potential to analyze many different host systems or binding sites. This makes qHyper-CEST an indispensable tool for the efficient design of highly specific biosensors.

Caged xenon has great potential in overcoming sensitivity limitations for solution-state NMR detection of dilute molecules. However, no application of such a system as a magnetic resonance imaging (MRI) contrast agent has yet been performed with live cells. We demonstrate MRI localization of cells labeled with caged xenon in a packed-bed bioreactor working under perfusion with hyperpolarized-xenon-saturated medium. Xenon hosts enable NMR/MRI experiments with switchable contrast and selectivity for cell-associated versus unbound cages. We present MR images with 10(3) -fold sensitivity enhancement for cell-internalized, dual-mode (fluorescence/MRI) xenon hosts at low micromolar concentrations. Our results illustrate the capability of functionalized xenon to act as a highly sensitive cell tracer for MRI detection even without signal averaging. The method will bridge the challenging gap for translation to in vivo studies for the optimization of targeted biosensors and their multiplexing applications.