Undergraduate Research & Scholarships

Junyi Xu Rose Hills

Exploring Effects of Size Reduced MS2 and Spray-Dried Storage Methods

Protein-based nanoparticles have emerged as a promising field of study for drug delivery. These nanoparticles, known as virus-like particles (VLPs), have great potential due to their versatility in transporting therapeutic agents to specific sites in the body. However, effectively delivering VLPs into mammalian cells has proven to be a challenge. My project aims to optimize the internalization efficiency of MS2 VLPs by reducing their size through a single amino acid mutation known as S37P. This mutation allows us to maintain their ability to be chemically modified and to load therapeutic agents while achieving uniform particle size reduction. For my project, I have created nine reduced MS2 variants (miniMS2) based from double mutants of regular sized MS2 variants that was identified to improve internalization efficiency by 67-fold in comparison to wild-type in previous studies. I will evaluate this variant for drug delivery by assessing its size, surface charge, and thermostability. In addition, I will also aim to develop a more accessible storage method for these particles that will preserve their stability for longer periods, even at room temperature. My ultimate goal is to enhance drug delivery efficiency through genetic engineering and develop a more accessible storage method, advancing the field of nanomedicine.

Message To Sponsor

Thank you so much for your generous support of my research project. Your contribution has allowed me to pursue my passion for advancing drug delivery and exploring new approaches to storage. With your funding, students like me are enabled to experience research and academia while conducting experiments and generating valuable data that will contribute to our field of study. I am honored to have your support and am excited to proceed through my project. Thank you for your generosity and for believing in the potential of my research!
Major: Chemical Biology, Data Science
Mentor: Paige Pistono
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