Search PubMedSearch

Biomedical subjects

Aditya Raguram

Publications and source records attributed to Aditya Raguram.

2 recordsLinked to original sources

Directed evolution of engineered virus-like particles with improved production and transduction efficiencies.

Engineered virus-like particles (eVLPs) are promising vehicles for transient delivery of proteins and RNAs, including gene editing agents. We report a system for the laboratory evolution of eVLPs that enables the discovery of eVLP variants with improved properties. The system uses barcoded guide RNAs loaded within DNA-free eVLP-packaged cargos to uniquely label each eVLP variant in a library, enabling the identification of desired variants following selections for desired properties. We applied this system to mutate and select eVLP capsids with improved eVLP production properties or transduction efficiencies in human cells. By combining beneficial capsid mutations, we developed fifth-generation (v5) eVLPs, which exhibit a 2-4-fold increase in cultured mammalian cell delivery potency compared to previous-best v4 eVLPs. Analyses of v5 eVLPs suggest that these capsid mutations optimize packaging and delivery of desired ribonucleoprotein cargos rather than native viral genomes and substantially alter eVLP capsid structure. These findings suggest the potential of barcoded eVLP evolution to support the development of improved eVLPs.

Humans

Therapeutic in vivo delivery of gene editing agents.

In vivo gene editing therapies offer the potential to treat the root causes of many genetic diseases. Realizing the promise of therapeutic in vivo gene editing requires the ability to safely and efficiently deliver gene editing agents to relevant organs and tissues in vivo. Here, we review current delivery technologies that have been used to enable therapeutic in vivo gene editing, including viral vectors, lipid nanoparticles, and virus-like particles. Since no single delivery modality is likely to be appropriate for every possible application, we compare the benefits and drawbacks of each method and highlight opportunities for future improvements.

CRISPR-Cas Systems