SMU Lyle nanorobotics professor awarded prestigious research grant to make gene therapy safer
SMU nanotechnology expert MinJun Kim and his team have been awarded a $1.8 million, R01 grant from the National Institutes of Health (NIH) for research related to gene therapy – a technique that modifies a person’s genes to treat or cure disease. NIH R01 (Research Program) grants are extremely competitive, with fewer than 10 percent of applicants receiving one.
DALLAS (SMU) – SMU nanotechnology expert MinJun Kim and his team have been awarded a $1.8 million, R01 grant from the National Institutes of Health (NIH) for research related to gene therapy – a technique that modifies a person’s genes to treat or cure disease.
NIH R01 (Research Program) grants are extremely competitive, with fewer than 10 percent of applicants receiving one.
The four-year grant will allow Kim, the Robert C. Womack Chair in the Lyle School of Engineering at SMU (Southern Methodist University) and principal investigator of the BAST Lab, to develop a simpler, more effective way to accurately determine whether viruses intended for gene therapy contain their full genetic cargo.
Nanoparticles are too small to be visible to the naked eye – ranging in size from 1 to 100 nanometers (one billionth of a meter) in size. Nanomaterials can occur naturally and can also be engineered to perform specific functions, such as the delivery of drugs to various forms of cancer. Viruses are soft nanoparticles.
The protein coat surrounding the nucleic acid of a virus is called a capsid. It protects the genetic material that the virus is carrying. Not being able to determine the integrity of the capsid and the amount of genetic material it may be protecting can lead to overdosing or underdosing. That threat is a key barrier to using harmless viruses as a way to deliver within the human body a healthy copy of a gene to replace or modify a disease-causing one – a process known as viral gene therapy.
“We anticipate that the groundwork laid by this project will undeniably transform the way nanoscale species, such as viruses and virus-like nanoparticles, are analyzed for cargo content,” Kim said.
George Alexandrakis at the University of Texas at Arlington, Steven Gray at the University of Texas Southwestern Medical Center, and Prashanta Dutta at Washington State University are working with lead investigator Kim on the research.
Addressing critical problems in viral gene therapy
The team will be testing how accurately a device they created measures the genetic content for adeno-associated virus (AAV), a virus encapsulated with single-stranded or double-stranded DNA that has not been found to cause any diseases in people. Pharmaceutical companies consider AAV to be a great potential vessel for gene therapy. For instance, Luxturna, the first FDA-approved gene therapy (2017), is an AAV that carries genetic materials to treat hereditary blindness.
The device and analytical tools being developed – which Kim called “next-generation technology for all-in-one virus characterization” – is known as a bimodal optical-electric plasmonic nanopore sensor.
The sensor will determine the size, effective charge and deformability of individual AAVs. Voltage-induced deformability matters, because the shape of virus capsids change based on how much cargo content is present inside them.
Kim and his team will be applying machine-learning, computer systems that draw inferences and “learn” from patterns in data, to the massive quantity of optical-electrical signals the nanopore sensor receives, giving better classifications of whether drug-delivering viruses are carrying their intended disease-fighting genetic materials.
“Current analytical methods require using large amounts of the virus preparation for quality control, which is costly and wasteful,” Kim said. “Our proposed sensor requires only minute virus amounts. This project will enable my team to conduct cutting-edge research, acquiring knowledge in state-of-the-art nanotechnology, including biomechanics and mechanobiology, nanophotonics, nanofabrication, machine learning, physical virology, and gene delivery systems.”
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