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Published November 27, 2018 | Supplemental Material
Journal Article Open

Protein Nanostructures Produce Self-Adjusting Hyperpolarized Magnetic Resonance Imaging Contrast through Physical Gas Partitioning

Abstract

Signal amplification strategies are critical for overcoming the intrinsically poor sensitivity of nuclear magnetic resonance (NMR) reporters in noninvasive molecular detection. A mechanism widely used for signal enhancement is chemical exchange saturation transfer (CEST) of nuclei between a dilute sensing pool and an abundant detection pool. However, the dependence of CEST amplification on the relative size of these spin pools confounds quantitative molecular detection with a larger detection pool typically making saturation transfer less efficient. Here we show that a recently discovered class of genetically encoded nanoscale reporters for ^(129)Xe magnetic resonance overcomes this fundamental limitation through an elastic binding capacity for NMR-active nuclei. This approach pairs high signal amplification from hyperpolarized spins with ideal, self-adjusting saturation transfer behavior as the overall spin ensemble changes in size. These reporters are based on gas vesicles, i.e., microbe-derived, gas-filled protein nanostructures. We show that the xenon fraction that partitions into gas vesicles follows the ideal gas law, allowing the signal transfer under hyperpolarized xenon chemical exchange saturation transfer (Hyper-CEST) imaging to scale linearly with the total xenon ensemble. This conceptually distinct elastic response allows the production of quantitative signal contrast that is robust to variability in the concentration of xenon, enabling virtually unlimited improvement in absolute contrast with increased xenon delivery, and establishing a unique principle of operation for contrast agent development in emerging biochemical and in vivo applications of hyperpolarized NMR and magnetic resonance imaging.

Additional Information

© 2018 American Chemical Society. Received: June 4, 2018; Accepted: September 11, 2018; Published: September 11, 2018. Support by the Human Frontiers Science Program (HFSP Program Grant RGP0050/2016 to M.S. and L.S.) and by the German Research Foundation (Koselleck Grant SCHR 995/5-1 to L.S.) is gratefully acknowledged. The authors declare no competing financial interest.

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