Gas vesicles are gas-filled nanocompartments that allow a diverse group of bacteria and archaea to control their buoyancy. The molecular basis of their properties and assembly remains unclear. Here, we report the 3.2 Å cryo-EM structure of the gas vesicle shell made from the structural protein GvpA that self-assembles into hollow helical cylinders closed off by cone-shaped tips. Two helical half shells connect through a characteristic arrangement of GvpA monomers, suggesting a mechanism of gas vesicle biogenesis. The fold of GvpA features a corrugated wall structure typical for force-bearing thin-walled cylinders. Small pores enable gas molecules to diffuse across the shell, while the exceptionally hydrophobic interior surface effectively repels water. Comparative structural analysis confirms the evolutionary conservation of gas vesicle assemblies and demonstrates molecular features of shell reinforcement by GvpC. Our findings will further research into gas vesicle biology and facilitate molecular engineering of gas vesicles for ultrasound imaging.

Ultrasound imaging is one of the most widely used modalities in clinical practice, revealing human prenatal development but also arterial function in the adult brain. Ultrasound waves travel deep within soft biological tissues and provide information about the motion and mechanical properties of internal organs. A drawback of ultrasound imaging is its limited ability to detect molecular targets due to a lack of cell-type specific acoustic contrast. To date, this limitation has been addressed by targeting synthetic ultrasound contrast agents to molecular targets. This molecular ultrasound imaging approach has proved to be successful but is restricted to the vascular space. Here, we introduce the nascent field of biomolecular ultrasound imaging, a molecular imaging approach that relies on genetically encoded acoustic biomolecules to interface ultrasound waves with cellular processes. We review ultrasound imaging applications bridging wave physics and chemical engineering with potential for deep brain imaging.