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Combining genomic technologies enable spatial gene expression analyses to better understand tissue function and malfunction

Much biomedical research over the last decade has relied on single-cell transcriptomics — technology used to study gene expression within individual cells.

Within the past five years, a new method called spatial transcriptomics enabled the analysis of gene expression in space using thin slices from intact tissues. This technology can provide a molecular map of a sample, allowing researchers to better understand tissue function and malfunction.

However, commercially available spatial transcriptomics technology is expensive, and it can only analyze small tissue samples.

At the University of Chicago Pritzker School of Molecular Engineering, Assoc. Prof. Nicolas Chevrier and his research group wanted to understand gene expression within whole human organs or the whole body of mice which are used to model human disease. They quickly realized that current technology didn’t allow for such large samples.

Assoc. Prof. Nicolas Chevrier
Assoc. Prof. Nicolas Chevrier.

So they created their own spatial transcriptomics platform by combining next-generation sequencing technology with an older technology: microarrays, which they outfitted with custom-designed probes.

The design, dubbed “Array-seq” and published in Nature Methods, can analyze tissue samples as big as nearly 12 square centimeters at a cost that is 50 times cheaper than commercially available systems.

“My hope is that anyone who needs spatial transcriptomics will find this technique useful for higher-throughput and less-expensive research,” Chevrier said. “This could help democratize and enhance the reach of spatiomolecular profiling.”

Combining two technologies

Measuring gene expression at the tissue level is important for understanding the body’s response to both disease and potential therapies. “The structure of a tissue is related to its function,” Chevrier said. “If you can’t examine gene expression at the tissue level, then you don’t understand how each cell relates to and communicate with its neighbors, and how the tissue is functioning as a whole.”

When the team realized that commercially available spatial transcriptomics technology wouldn’t fit their needs — the largest tissue sample it could accommodate was about 1 square centimeter — they knew they needed to create their own solution. They turned their attention to microarrays, technology developed in the late 1990s to measure gene expression that has since fallen out of favor, due to better next-generation sequencing technologies.

Chevrier and his team wondered if they could repurpose these microarrays to better suit their needs. By working with an industrial partner expert in microarray printing, Agilent Technologies, they reconfigured microarrays on a slide with 1 million probes that, with a simple chemical reaction, can capture mRNA information across a ~12-centimeter-square specimen. “Each of these probes allows us to decode the location of the expression of all genes in the genome across all spots on the microarray,” Chevrier said.

Because the probes are on a glass microscopy slide, tissue samples are also compatible with hematoxylin and eosin (H&E) staining, the standard dyeing technique used to identify different parts of tissues and cells under a microscope in both basic research and clinical pathology.

The team tested its system using sections from various mouse organs and a human spleen. They found that a single slide could capture information from tissue slices covering up to 20 million cells. That information can also be recombined into a 3D molecular cartography of the sample when combined with serial sectioning of a tissue block.

Both larger and cheaper

Not only does the system allow for spatial transcriptomics of larger samples — it also does so much more cheaply. Chevrier estimates that this system is 50 times cheaper than similar gold standard, commercially available technology.

Because of the slide’s large size, the system also allows for higher throughput of specimens, leading to potentially bigger studies of tissues. For example, it could be used to profile biopsies from hundreds of patients to better understand drug responses or disease mechanisms in humans.

And the system is big enough to measure spatial changes in gene expression across sections from the whole body of a mouse — something the Chevrier team has done and will publish soon. They also hope to continue to make the slides higher resolution and larger, for even bigger specimens.

“We started with a dream of analyzing samples from whole body sections of mice, and now we hope to make our arrays large enough to analyze entire human organs and model organisms,” Chevrier said.

Other authors on the paper include Denis Cipurko, Tatsuki Ueda, and Linghan Mei.

Citation: “Repurposing Large-Format Microarrays for Scalable Spatial Transcriptomics,” Cipurko et al, Nature Methods. November 19, 2024. DOI: 10.1038/s41592-024-02501-5

Funding: National Institutes of Health, Chan Zuckerberg Initiative, Agilent Technologies, Robert Lavichant Faculty Innovation Award