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Resolve Biosciences and Zeiss today announced a collaboration to improve spatial biology applications. The partnership will help enable digital twins of cells to combine information about the shape, size, gene activations, and protein interactions of cells. This promises to accelerate the market for spatial biology tools that help scientists and doctors peer into the inner workings of cells.
The new collaboration will focus on improving the integration between Zeiss’ advanced microscopy and 3D imaging solutions for subcellular spatial analysis and Resolve’s genetic analysis technology. The companies hope to streamline the workflows by developing novel optical systems and computational approaches.
“Spatial biology is the next frontier in life science and diagnostic applications,” Resolve CEO Jason Gammack told VentureBeat. “We refer to this transition as Genomics 3.0.” Gammack believes it will usher in a new era of molecular biology that mirrors previous genomic, proteomics, and metabolomics developments.
Zeiss is one of the world’s largest producers of high-powered microscopes. Resolve is a startup focused on developing tools for watching genes and proteins interact in a cell. The company received $24 million in funding last December.
Resolve’s Molecular Cartography platform has been in development since 2016 and is currently available through a commercial service offering to researchers in Europe and North America. The company’s existing platform offers users the ability to watch transcription activity — how genes are activated — and correlate this with a 3D microscopic view of what is happening in the elements of a cell called organelles. Future upgrades to the technology will improve the ability to track DNA sequences and add more comprehensive information about protein and metabolomic interactions.
The partnership could help Resolve keep pace with a bevy of new competitors in the spatial biology market. Recent entrants include 10x Genomics, Spatial Genomics, BGI Research, and nanoString. Acquisitions and mergers in the space include 10x Genomics’ recent acquisitions of Spatial Transcriptomics, ReadCoor, and Cartana.
Dawn of the spatial biology market
The field of spatial biology began to take hold in 2016 with the discovery of new techniques to watch gene expression at the level of individual cells in a process called spatial transcriptomics. Nature Methods declared spatially resolved transcriptomics the method of the year.
Companies like Resolve are developing new techniques for watching proteins called spatial proteomics. Resolve calls their specific flavor of technology Molecular Cartography.
JP Morgan predicts spatial biology could grow into a $2 billion market. But more significantly, it could lead to much more sophisticated and comprehensive maps of humans and microbes.
Scientists will have a much better window into how cells trigger proteins and respond to microbes and exactly how drugs work inside the cell. Spatial biology could also help scientists improve microbial engineering for industrial applications such as breaking down waste, growing drugs, and mass-producing vaccines. Current molecular cartography applications include studying the progression of COVID-19 between cells, mapping neural development, and understanding how eye retinas develop and age.
Spatial biology provides new context of genomic info
The real power of digital twins lies in finding better ways to co-register information from across different sensors. In larger digital twins, this might include lidar, enterprise applications, and building information models. The innovation lies in finding better ways to align high-resolution microscopic images with data about gene transcription and protein activation at this smaller scale.
Spatial biology provides an entirely new context of genomic information. It allows scientists to understand the temporal-spatial relationship of biological activity within cells and tissues for the first time.
The future of spatial biology will also require new data analytics pipelines to find novel ways of combining different kinds of data for further research and diagnostics. Future advances will benefit from improvements in the workflows enabled by this new partnership and integration with other tools and services.
“We are also actively engaging with the rich community of open source developers to ensure our datasets can be analyzed with their next-generation tools,” Gammack said.
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