Dataset Information

Encapsulins-Bacterial Protein Nanocompartments: Structure, Properties, and Application.

ABSTRACT: Recently, a new class of prokaryotic compartments, collectively called encapsulins or protein nanocompartments, has been discovered. The shell proteins of these structures self-organize to form icosahedral compartments with a diameter of 25-42 nm, while one or more cargo proteins with various functions can be encapsulated in the nanocompartment. Non-native cargo proteins can be loaded into nanocompartments and the surface of the shells can be further functionalized, which allows for developing targeted drug delivery systems or using encapsulins as contrast agents for magnetic resonance imaging. Since the genes encoding encapsulins can be integrated into the cell genome, encapsulins are attractive for investigation in various scientific fields, including biomedicine and nanotechnology.

SUBMITTER: Gabashvili AN

PROVIDER: S-EPMC7355545 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Encapsulins-Bacterial Protein Nanocompartments: Structure, Properties, and Application.

Gabashvili Anna N AN Chmelyuk Nelly S NS Efremova Maria V MV Malinovskaya Julia A JA Semkina Alevtina S AS Abakumov Maxim A MA

Biomolecules 20200626 6

Recently, a new class of prokaryotic compartments, collectively called encapsulins or protein nanocompartments, has been discovered. The shell proteins of these structures self-organize to form icosahedral compartments with a diameter of 25-42 nm, while one or more cargo proteins with various functions can be encapsulated in the nanocompartment. Non-native cargo proteins can be loaded into nanocompartments and the surface of the shells can be further functionalized, which allows for developing t ...[more]

PMID: 32604934

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Project description:The development of Drug Delivery Systems (DDS) has led to increasingly efficient therapies for the treatment and detection of various diseases. DDS use a range of nanoscale delivery platforms produced from polymeric of inorganic materials, such as micelles, and metal and polymeric nanoparticles, but their variant chemical composition make alterations to their size, shape, or structures inherently complex. Genetically encoded protein nanocages are highly promising DDS candidates because of their modular composition, ease of recombinant production in a range of hosts, control over assembly and loading of cargo molecules and biodegradability. One example of naturally occurring nanocompartments are encapsulins, recently discovered bacterial organelles that have been shown to be reprogrammable as nanobioreactors and vaccine candidates. Here we report the design and application of a targeted DDS platform based on the Thermotoga maritima encapsulin reprogrammed to display an antibody mimic protein called Designed Ankyrin repeat protein (DARPin) on the outer surface and to encapsulate a cytotoxic payload. The DARPin9.29 chosen in this study specifically binds to human epidermal growth factor receptor 2 (HER2) on breast cancer cells, as demonstrated in an in vitro cell culture model. The encapsulin-based DDS is assembled in one step in vivo by co-expressing the encapsulin-DARPin9.29 fusion protein with an engineered flavin-binding protein mini-singlet oxygen generator (MiniSOG), from a single plasmid in Escherichia coli. Purified encapsulin-DARPin_miniSOG nanocompartments bind specifically to HER2 positive breast cancer cells and trigger apoptosis, indicating that the system is functional and specific. The DDS is modular and has the potential to form the basis of a multi-receptor targeted system by utilising the DARPin screening libraries, allowing use of new DARPins of known specificities, and through the proven flexibility of the encapsulin cargo loading mechanism, allowing selection of cargo proteins of choice.

Dataset Information

Encapsulins-Bacterial Protein Nanocompartments: Structure, Properties, and Application.

Publications

Encapsulins-Bacterial Protein Nanocompartments: Structure, Properties, and Application.

Similar Datasets

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