From bacteria to biosensors: Engineering gas vesicles for biomolecular ultrasound imaging

Ultrasound imaging is a cornerstone of medical diagnostics, offering high-resolution, real-time visualization of anatomical structures. However, its application to molecular and cellular imaging has been limited by the lack of nanoscale contrast agents. Gas vesicles (GVs), air-filled protein nanostructures evolved for buoyancy in microorganisms, offer transformative potential in this domain. This thesis explores the engineering and application of GVs as biomolecular ultrasound contrast agents, emphasizing their use as biosensors for molecular imaging. It builds on their unique genetic encodability, tunable acoustic properties, and nanoscale dimensions to address key limitations in ultrasound imaging.

In chapter 1 and chapter 2 we introduce the potential of GVs as genetically encoded ultrasound contrast agents, highlighting their advantages over traditional agents like microbubbles. These chapters provide an overview of ultrasound imaging’s evolution, focusing on the emerging field of biomolecular ultrasound imaging, which leverages GVs to bridge the gap between molecular processes and ultrasound modalities. Applications such as neuroscience imaging and functional imaging of dynamic biological processes are discussed, emphasizing GVs’ nanoscale properties and unique acoustic behavior.

The contents of chapter 3 focus on the cryo-electron microscopy (cryo-EM) structural analysis of GVs. This study provides an atomic-level model of the GV shell, particularly in the absence of the reinforcement protein GvpC. By combining structural insights with a sequence analysis of GvpC, the chapter proposes a hypothetical binding mechanism that informs mutagenesis experiments in later work. This structural foundation is critical for the subsequent engineering of GVs for biosensor applications.

In chapter 4 we present the development and validation of pHonon, the first GV-based pH biosensor. By engineering pH-sensitive histidine residues into GvpC, the biosensor’s acoustic properties were tuned to detect pH variations. Validation experiments, conducted both in vitro and in vivo, demonstrated pHonon’s efficacy for real-time, non-invasive pH imaging. This work highlights the versatility of GVs as platforms for biosensor engineering and their potential for applications in both basic research and clinical diagnostics.

Then, chapter 5 explores alternative approaches to enhancing GV functionality through aggregation. By inducing GV clustering via methods like biotin-streptavidin interactions and depletion interactions, significant improvements in ultrasound contrast were achieved. This chapter shows that aggregation enhances both linear and non-linear acoustic responses, providing a complementary strategy to genetic engineering for optimizing GV performance. These findings open new avenues for improving the signal strength and utility of GVs in various imaging applications.

The thesis concludes by summarizing the key findings and their implications for the field of biomolecular ultrasound imaging. It emphasizes the breakthroughs achieved, such as the high-resolution GV structural model, the development of pHonon, and the exploration of aggregation-based contrast enhancement. These contributions advance the field significantly, offering innovative solutions to challenges in molecular imaging. This thesis lays the basis for future research on broadening the array of biomarkers identifiable by GVs, improving genetic engineering methods, and investigating additional imaging techniques to enhance the effectiveness of biomolecular ultrasound imaging.