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Systematic engineering of virus-like particles to identify self-assembly rules for shifting particle size.

ABSTRACT: Virus-like particles (VLPs) are promising scaffolds for biomaterials as well as diagnostic and therapeutic applications. However, there are some key challenges to be solved, such as the ability to engineer alternate sizes for varied use cases. To this end, we created a library of MS2 VLP variants at two key residues in the coat protein which have been implicated as important to controlling VLP size and geometry. By adapting a method for systematic mutagenesis coupled with size-based selections and high-throughput sequencing as a readout, we developed a quantitative assessment of two residues in MS2 coat protein that govern the size shift in MS2 VLPs. We then applied the strategy to the equivalent residues in Qβ VLPs, an MS2 homolog, and demonstrate that the analogous pair of residues are also able to impact Qβ VLP size and shape. These results underscore the power of fitness landscapes in identifying critical features for assembly.

SUBMITTER: Ikwuagwu B

PROVIDER: S-EPMC10776172 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Systematic engineering of virus-like particles to identify self-assembly rules for shifting particle size.

Ikwuagwu Bon B Hartman Emily E Mills Carolyn E CE Tullman-Ercek Danielle D

Virology 20230105

Virus-like particles (VLPs) are promising scaffolds for biomaterials as well as diagnostic and therapeutic applications. However, there are some key challenges to be solved, such as the ability to engineer alternate sizes for varied use cases. To this end, we created a library of MS2 VLP variants at two key residues in the coat protein which have been implicated as important to controlling VLP size and geometry. By adapting a method for systematic mutagenesis coupled with size-based selections a ...[more]

PMID: 36669330

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Project description:A range of amphiphilic statistical copolymers is synthesized where the hydrophilic component is either methacrylic acid (MAA) or 2-(dimethylamino)ethyl methacrylate (DMAEMA) and the hydrophobic component comprises methyl, ethyl, butyl, hexyl, or 2-ethylhexyl methacrylate, which provide a broad range of partition coefficients (log P). Small-angle X-ray scattering studies confirm that these amphiphilic copolymers self-assemble to form well-defined spherical nanoparticles in an aqueous solution, with more hydrophobic copolymers forming larger nanoparticles. Varying the nature of the alkyl substituent also influenced self-assembly with more hydrophobic comonomers producing larger nanoparticles at a given copolymer composition. A model based on particle surface charge density (PSC model) is used to describe the relationship between copolymer composition and nanoparticle size. This model assumes that the hydrophilic monomer is preferentially located at the particle surface and provides a good fit to all of the experimental data. More specifically, a linear relationship is observed between the surface area fraction covered by the hydrophilic comonomer required to achieve stabilization and the log P value for the hydrophobic comonomer. Contrast variation small-angle neutron scattering is used to study the internal structure of these nanoparticles. This technique indicates partial phase separation within the nanoparticles, with about half of the available hydrophilic comonomer repeat units being located at the surface and hydrophobic comonomer-rich cores. This information enables a refined PSC model to be developed, which indicates the same relationship between the surface area fraction of the hydrophilic comonomer and the log P of the hydrophobic comonomer repeat units for the anionic (MAA) and cationic (DMAEMA) comonomer systems. This study demonstrates how nanoparticle size can be readily controlled and predicted using relatively ill-defined statistical copolymers, making such systems a viable attractive alternative to diblock copolymer nanoparticles for a range of industrial applications.

Dataset Information

Systematic engineering of virus-like particles to identify self-assembly rules for shifting particle size.

Publications

Systematic engineering of virus-like particles to identify self-assembly rules for shifting particle size.

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