A novel computing platform developed by researchers at the University of Pittsburgh School of Medicine identifies powerful viral vectors that could deliver gene therapies to the retina with maximum efficiency and precision.
The technology, described in an article published today in eLife magazine, is streamlining the development of gene therapy approaches to treating genetic blindness diseases. The approach saves valuable time and resources by speeding up the identification of suitable genetic candidates capable of treating an affected part of the retina with astonishing accuracy.
Loss of vision has a major impact on the quality of life. It has long been one of the greatest fears of people, alongside cancer and Alzheimer’s. But visual field restoration has entered a new era in which many patients received effective treatment for the first time. Therefore, the potential of our new platform is enormous – it will allow us to translate new therapies that are already working for some patients into the clinic much faster. “
Leah Byrne, Ph.D., Senior Writer, Assistant Professor of Ophthalmology, University of Pittsburgh
Although blinded genetic disorders that affect the retina are considered rare, around 1 in 3,000 people worldwide carry one or more copies of defective genes that lead to retinal degeneration and vision loss. For centuries, many people with inherited blindness were virtually guaranteed to spend part of their lives in darkness.
Now that several gene therapies are already on the market in Europe and the US, and dozens more are entering clinical trials, hope is within reach for people with hereditary blindness, but one major obstacle remains: ensuring that vectors, or inactivated viruses, are targeting the The therapeutic genetics carry enter the exact cells that the scientists are targeting. The retina is made up of hundreds of millions of cells arranged in a series of layers, so aiming the vector precisely at a specific location within this universe is no trivial task.
To approach the problem, researchers developed a computer platform called scAAVengr, which uses single-cell RNA sequencing to quickly and quantitatively assess – among dozens of options – which adeno-associated virus vector, or AAV, is best for the task , a gene therapy on a specific part of the retina.
The traditional approach to evaluating AAVs is painstakingly slow, requiring several years and many laboratory animals. It is also not very accurate, as it does not directly measure whether AAVs have not only entered the cells but have also given off their gene therapy cargo.
In contrast, scAAVengr uses single cell RNA sequencing, which detects whether the cargo is safely arriving at its destination. And with scAAVengr, this process takes months, not years.
The platform’s uses aren’t just limited to the retina – the researchers showed that it also works in identifying AAVs that target other tissues such as the brain, heart, and liver.
“A rising tide is lifting all boats, and we hope this technology advances gene therapy treatments for other uses as well as vision restoration,” said Byrne. “The rapidly evolving areas of gene editing and optogenetics all rely on efficient gene delivery, so being able to quickly and strategically select transport vectors would be an exciting step forward.
Öztürk, BE, et al. (2021) scAAVengr, a transcriptome-based pipeline for the quantitative ranking of genetically modified AAVs with single cell dissolution. eLife. doi.org/10.7554/eLife.64175.