Resolve Biosciences’ Molecular Cartography platform detects specific gene expression patterns in SARS-CoV-2 not seen with existing single-cell RNA-seq technologies

Resolve Biosciences, the pioneer in Molecular Cartography™, today announced initial results from several prominent early access collaborations with leading laboratories across Europe. Teams of scientists are currently using the groundbreaking subcellular spatial analysis technology to help resolve daunting challenges in COVID-19 pathology, neurology, and developmental biology research.

Under development since 2016, Resolve’s Molecular Cartography platform features the company’s proprietary, highly multiplexed, single-molecule detection technology to provide the highest-resolution view of subcellular transcriptomic activity. Unlike other spatial analysis techniques, the Resolve platform provides the required sensitivity, specificity, and workflow convenience to elucidate the cell’s complex transcriptional landscape. The technology generates deep contextual data sets that illuminate molecular interactions at subcellular resolution while preserving the sample tissue for future analysis.

The Resolve Molecular Cartography platform has been available through an oversubscribed early access program during the past year. Initial findings from several of the high-profile projects include:

SARS-CoV-2 transcripts of the nucleocapsid protein (shown in yellow) are predominantly found close to the cell nucleus. Interestingly, some cells show a polar localization of SARS-CoV-2 transcripts. Transcripts of 80 other genes (marked in different colors) are distributed throughout the cell. The Resolve Biosciences Molecular Cartography™ technology enabled scientists to compare infected and non-infected cells to understand subcellular gene regulation and how the infection affects neighboring cells over time. Image courtesy of Medical University of Graz, Austria.

Ryan MacDonald, PhD, Biotechnology and Biological Sciences Research Council David Phillips Fellow and Lecturer at the Institute of Ophthalmology, and his colleagues are using Molecular Cartography technology to better understand how a healthy retina develops and changes with advancing age. Scientists were able to visualize the spatial expression of 48 genes simultaneously in the same zebrafish sample to observe the development of different cell types using specific marker genes in the retina. Then by visualizing gene expression changes over the entire lifespan, specifically within the support cells called glia, they were able to identify candidate genes that are dysregulated in the aging retina and potentially underlie progressive neuronal degeneration and vision loss.

“Thanks to its exquisite resolution, the technology from Resolve Biosciences allows us to detect specific gene expression patterns in SARS-CoV-2 that we could not see with existing RNA sequencing or single-cell RNA-seq technologies,” said Prof. Zatloukal. “Since the Resolve workflow provides spatial information at subcellular resolution and still preserves the tissue integrity, we see clear clinical opportunities with this approach moving forward.”

“Over the past year, Resolve Biosciences has had the privilege of working with many of the true visionaries of single-cell and spatial biology,” said Jason T. Gammack, Co-founder and CEO of Resolve Biosciences. “We are grateful for their engagement and feedback, and proud that they were able to gain new insights that were not possible with alternative approaches. We look forward to empowering more scientists around the world with this same ability to rapidly advance the understanding of complex biology with our novel Molecular Cartography platform.”

Resolve Biosciences is now expanding its early access program globally. Scientists interested in learning more about how to access and apply the power of its innovative Molecular Cartography technology can contact the company.

Source – BusinessWire

Leave a Reply

Your email address will not be published. Required fields are marked *

*

Time limit is exhausted. Please reload CAPTCHA.