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Researchers from the lab of Stein Aerts at VIB-KU Leuven have developed a new spatial transcriptomics technique, Nova-ST, which promises to make gene expression profiling in tissue samples more accessible and affordable. This innovative technique offers significant advantages over existing methods by providing high-resolution spatial tissue analysis. The research has been published in Cell Reports Methods.
Advances in Spatial Transcriptomics
Transcriptomics, the study of gene expression, traditionally lacks spatial information about where genes are active within tissues. This limitation has hindered understanding of complex biological processes dependent on specific gene activity patterns. Spatial transcriptomics has emerged as a solution, enabling scientists to map gene expression across tissue sections with spatial context. However, current techniques often face challenges related to high costs, limited resolution, and compatibility issues.
Nova-ST, developed by Aerts' lab in collaboration with the Single-cell Microfluidics and Bioinformatics expertise units at VIB.AI and the VIB-KU Leuven Center for Brain & Disease Research, addresses these challenges. The technique offers greater affordability, impressive resolution, and versatility, making it a valuable tool for researchers.
The Technology Behind Nova-ST
Nova-ST utilizes Illumina NovaSeq 6000 S4 or the new generation NovaSeq X sequencing flow cells, which are commonly used for large-scale DNA sequencing. These flow cells have a dense nano-patterned surface with tiny, randomly barcoded nanowells arranged in a hexagonal lattice. Each well captures mRNA molecules from specific locations within the tissue sample, allowing for high spatial resolution, potentially at the single-cell level.
“We use these capture sites to snag mRNA molecules while preserving their spatial coordinates,” explained Suresh Poovathingal, the researcher who led the development and optimization of this process. “Sequencing these captured mRNA molecules reveals the gene expression profile for each capture site. By piecing together this information, we can reconstruct a detailed map of gene activity across the entire tissue section.”
Key Advantages of Nova-ST
Nova-ST provides several notable benefits. It is cost-effective by utilizing Illumina flow cells and a novel chip-cutting technique, producing multiple Nova-ST chips from a single flow cell, and thereby reducing expenses. The dense nano-patterned surface allows for high spatial resolution, potentially at the single-cell level. Additionally, Nova-ST is compatible with various tissue types, enhancing its versatility. The technique also benefits from advancements in next-generation Illumina flow cells.
“Importantly, Nova-ST’s open-source nature makes the protocol accessible to a wider range of researchers and allows for further customization,” stated Kristofer Davie, who directed the data analysis. "Our workflow is designed to be user-friendly and adaptable, ensuring that researchers can tailor the technique to their specific needs."
Practical Applications and Impact
Nova-ST is part of broader efforts within the spatial transcriptomics community to democratize advanced platforms. Other examples include Seq-Scope from the University of Michigan and Open-ST from the Max Delbrück Center in Germany.
Aerts' lab is already utilizing Nova-ST in research on neurodegeneration and cancer biology. For instance, they examined muscle samples for Sandrine Da Cruz's lab at VIB-KU Leuven to study neurodegenerative disease effects on neuromuscular junctions. They are also collaborating with Diether Lambrechts' lab at VIB-KU Leuven to expand Nova-ST for simultaneous spatial analysis of immune cell receptors and gene expression, enabling studies of immune cell distribution in tumors undergoing immunotherapy.
“Nova-ST is a game-changer for research across multiple fields, from cancer biology to plant biology,” noted Aerts. “By making this platform open source, we aim to empower scientists worldwide to explore and innovate.”
Original Publication
Poovathingal, S., Davie, K., Borm, L. E., Vandepoel, R., Poulvellarie, N., Verfaillie, A., Corthout, N., & Aerts, S. (2024). Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics. Cell Reports Methods, 100831. https://doi.org/10.1016/j.crmeth.2024.100831
The chip preparation protocols, spatial transcriptomics protocol, and the computational pipeline are available on online, allowing the scientific community to implement Nova-ST in their research. Additional details can be found at nova-st.aertslab.org.