Nova-ST, a new spatial transcriptomics technique, has been introduced by researchers based at Vlaams Instituut voor Biotechnologie (VIB), Katholieke Universiteit (KU) Leuven. According to the researchers, who were led by bioengineer and computational biologist Stein Aerts, PhD, Nova-ST promises to transform gene expression profiling in tissue samples.
The researchers presented Nova-ST in Cell Reports Methods, in an article titled, “Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics.”
“Nova-ST [is an] open-source spatial transcriptomics workflow on Illumina NovaSeq 6000 or X flow cells,” the article’s authors wrote. “[It] enables customized, low-cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods at a reduced cost.”
Transcriptomics, the study of gene expression in a cell or a population of cells, usually lacks information about where genes are active. This omission limits our understanding of complex biological processes that rely on specific gene activity patterns within tissues. Fortunately, spatial transcriptomics has emerged as a powerful tool, allowing scientists to capture spatial context. However, existing techniques often suffer from high costs, limited resolution, or compatibility issues.
These drawbacks motivated the Aerts laboratory to develop Nova-ST. At the heart of Nova-ST lies a clever adaptation of Illumina NovaSeq 6000 S4 or the new generation Novaseq X sequencing flow cells, commonly used for large-scale DNA sequencing. These flow cells contain a dense nano-patterned surface riddled with tiny, randomly barcoded nanowells arranged in a hexagonal lattice. Each well acts as a capture site for mRNA molecules from a specific location within the tissue sample. This dense nano-patterned surface allows Nova-ST to achieve high spatial resolution, potentially capturing the footprint of single cells.
“We then use these capture sites to snag mRNA molecules while preserving their spatial coordinates,” explained Suresh Poovathingal, PhD, single-cell and microfludics platform leader at VIB, KU Leuven. “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.”
According to the researchers, the new platform boasts several key advantages. First, it is cost-effective. By leveraging readily available Illumina flow cells and employing a novel chip-cutting technique, multiple Nova-ST chips can be created from a single flow cell, significantly reducing costs compared to existing methods. Second, the dense nano-patterned surface allows Nova-ST to achieve high spatial resolution, potentially capturing gene expression at the single-cell level. Third, Nova-ST is compatible with various tissue types, making it a versatile tool for studying diverse biological systems. Additionally, the compatibility with next-generation Illumina flow cells suggests that Nova-ST can benefit from advancements in sequencing technology.
“Importantly, Nova-ST’s open-source nature makes the protocol accessible to a wider range of researchers and allows for further customization,” noted Kristofer Davie, PhD, head of the single-cell bioinformatics expertise unit at VIB, KU Leuven. “Our workflow is designed to be user-friendly and adaptable, ensuring that researchers can tailor the technique to their specific needs.”
Nova-ST is the latest example of broader efforts within the spatial transcriptomics research community to democratize access and build platforms that advance a wide range of biomedical research, including Seq-Scope and its recent variants developed at the University of Michigan, as well as the recently published Open-ST platform developed by scientists at Max Delbrück Center in Germany.
The Aerts laboratory and the expertise units are already applying Nova-ST to advance their colleagues’ research in neurodegeneration and cancer biology. For example, they processed muscle samples for the Sandrine Da Cruz laboratory (VIB, KU Leuven) to study the effects of neurodegenerative diseases on neuromuscular junctions. Additionally, they are working with the Diether Lambrechts laboratory (VIB, KU Leuven) to expand the Nova-ST platform. This expansion will allow the simultaneous spatial analysis of immune cell receptors and gene expression, enabling the study of immune cell distribution in tumors undergoing immunotherapy. These collaborations highlight Nova-ST’s practical applications and its potential to impact various fields.
“Nova-ST is a game-changer for research across multiple fields, from cancer biology to plant biology,” Aerts declared. “By making this platform open source, we aim to empower scientists worldwide to explore and innovate.”
