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ACS Nano
Article
Data sources: UnpayWall
ACS Nano
Article . 2016 . Peer-reviewed
Data sources: Crossref
ACS Nano
Article . 2018
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Molecular Engineering of Acoustic Protein Nanostructures

Authors: Lakshmanan, Anupama; Farhadi, Arash; Nety, Suchita P.; Lee-Gosselin, Audrey; Bourdeau, Raymond W.; Maresca, David; Shapiro, Mikhail G.;

Molecular Engineering of Acoustic Protein Nanostructures

Abstract

Ultrasound is among the most widely used biomedical imaging modalities, but has limited ability to image specific molecular targets due to the lack of suitable nanoscale contrast agents. Gas vesicles-genetically encoded protein nanostructures isolated from buoyant photosynthetic microbes-have recently been identified as nanoscale reporters for ultrasound. Their unique physical properties give gas vesicles significant advantages over conventional microbubble contrast agents, including nanoscale dimensions and inherent physical stability. Furthermore, as a genetically encoded material, gas vesicles present the possibility that the nanoscale mechanical, acoustic, and targeting properties of an imaging agent can be engineered at the level of its constituent proteins. Here, we demonstrate that genetic engineering of gas vesicles results in nanostructures with new mechanical, acoustic, surface, and functional properties to enable harmonic, multiplexed, and multimodal ultrasound imaging as well as cell-specific molecular targeting. These results establish a biomolecular platform for the engineering of acoustic nanomaterials.

Country
United States
Related Organizations
Keywords

genetic engineering, Microbubbles, ultrasound, Contrast Media, Proteins, protein engineering, Acoustics, molecular imaging, 530, macrophages, Nanostructures, acoustic nanostructures, cancer, contrast agents, gas vesicles, Ultrasonography

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    140
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
140
Top 1%
Top 10%
Top 1%
Green
bronze
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