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Engineering Acoustic Protein Nanostructures for Non-Invasive Molecular Imaging using Ultrasound


Lakshmanan, Anupama (2019) Engineering Acoustic Protein Nanostructures for Non-Invasive Molecular Imaging using Ultrasound. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/ASX5-KB62.


Visualizing biomolecular and cellular processes in real time within deep tissues is fundamental to our understanding of the normal and pathological activity underlying health and disease. Ultrasound provides the ability to non-invasively image deep inside biological tissues with high spatial and temporal resolution. However, this technology has limited capacity to monitor molecular and cellular processes, due to the lack of appropriate intra-cellular and endogenously producible nanoscale contrast agents, which can directly couple sound waves to the activity or concentration of physiologically relevant molecules. This problem could in principle be solved by developing genetically encodable ultrasound sensors – biomolecules that can get illuminated in ultrasound imaging in response to specific cellular or molecular activity. This thesis describes the engineering and characterization of acoustic protein nanostructures called 'gas vesicles', or 'GVs', to accomplish this task.

GVs are protein-shelled gas-filled nanostructures produced by buoyant microbes, and were recently shown to be capable of scattering sound waves to produce ultrasound contrast. Owing to this property, they were initially conceptualized as a new class of ultrasound contrast agents. However, little was known about their tunability to enable molecular ultrasound imaging for a wide range of applications. In this thesis, we leveraged the genetic encodability of GVs to modify them at the level of their DNA sequence and constituent proteins, and thereby tune their mechanical, acoustic, surface and targeting properties. We accomplished this by establishing a facile and modular molecular engineering platform, to produce GVs that provide enhanced nonlinear signals for sensitive and specific detection in deep tissues, target specific cell types such as cancer and immune cells, and also provide distinct acoustic collapse spectra for multiplexed imaging. We then extended this platform to build GV-based biosensors that modulate their nonlinear ultrasound signals in response to changes in the activity or concentration of specific molecules in their environment. Specifically, we engineered acoustic sensors for three different types of enzymes and for calcium – whose activity or flux underlie a wide range of important cellular processes. Furthermore, we succeeded in transferring the genetic code of gas vesicles from their species of origin into a variety of other microbes that do not naturally produce them, in order to unlock their potential as ultrasound reporter genes. Our results establish GVs as reliable acoustic biomolecules, and thereby extend the capabilities of ultrasound for molecular and cellular imaging in a manner analogous to green fluorescent protein (GFP) and its derivatives in optical microscopy. When combined with the advantages of ultrasound for non-invasive imaging, this work facilitates novel technology to significantly enhance our understanding of molecular and cellular processes in basic biology, as well as enable improved diagnosis, monitoring and treatment of diseases.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Acoustic Biomolecules, Ultrasound, Gas Vesicles, Protein Engineering, Acoustic Reporter Genes, Molecular Imaging, Non-Invasive, Genetic Engineering, Protein Nanostructures
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Awards:Milton and Francis Clauser Doctoral Prize, 2019. Demetriades-Tsafka-Kokkalis Prize in Biotechnology or Related Fields, 2019. Everhart Distinguished Graduate Student Lecturer Award, 2018
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Shapiro, Mikhail G.
Thesis Committee:
  • Tirrell, David A. (chair)
  • Gradinaru, Viviana
  • Yang, Changhuei
  • Shapiro, Mikhail G.
Defense Date:31 May 2019
Funding AgencyGrant Number
National Science Foundation Graduate Research Fellowship1144469
NIH Training Grant5T32GM112592-03
NIH Training Grant5T32GM112592-04
Record Number:CaltechTHESIS:06062019-165907194
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for Ch. 1 adapted for Ch. 2 adapted for Ch. 3 adapted for Ch. 4
Lakshmanan, Anupama0000-0002-6702-837X
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11698
Deposited By: Anupama Lakshmanan
Deposited On:10 Jun 2019 22:20
Last Modified:26 May 2023 22:14

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