Mapping Development and Disease With Spatial Biology Technologies

The study of cells, tissues and organs in their 2- or 3-D context – known as spatial biology – offers insights into their organization and function that cannot be gleaned from studying the components in isolation or analyzing them in bulk.

Spatial biology has an integral role in understanding biological processes involving the activation of genes in specific locations and tissue reorganization, such as those driving embryonic development and many diseases.

While traditional single-cell genomic and transcriptomic studies enable researchers to investigate every cell within an organ or tissue in unprecedented detail, they do not provide any information about the spatial context of individual cells or their interactions with each other.

“Spatial profiling is important because only knowing the cell types within a tissue or organ is not sufficient to understand how it functions; the whole is more than the sum of the parts,” says developmental and stem-cell biologist Elie Farah, at the University of California San Diego, USA.

Farah and colleagues have combined RNA-sequencing and imaging technologies to map communities of cells that comprise functional structures of the heart. “The organization of the cells is a critical part of the assembly process to create a fully functioning organ,” he explains.

They found that the cellular ecosystem and anatomical region influences cardiac cell specialization and organization in the developing human heart. Their heart cell atlas offers new insights into congenital defects – a leading cause of death in infants – and common adult structural heart diseases, such as aortic valve disease and hypertrophic cardiomyopathy.^1,2

Advances in technology are also enabling the examination of multiple-omics data modalities in complex tissues. Prof. Gonçalo Castelo-Branco at the Karolinska Institutet in Stockholm, Sweden, with Prof. Rong Fan and colleagues at Yale University, USA, recently co-profiled the epigenome and transcriptome at near-single-cell resolution in mouse and human brain tissue.³

“By layering epigenomic and transcriptomic data, in a spatially resolved manner we can glean information about gene regulation that is not possible from spatial mono-omics approaches,” Castelo-Branco says.

This article examines how next-generation sequencing (NGS) and state-of-the-art imaging technologies are being combined to characterize and map the spatial organization of cell types in tissues.

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Since spatial transcriptomics was crowned Method of the Year in 2020 by Nature Methods, there has been remarkable progress in the development and use of spatial molecular technologies.⁴ Platforms can now provide diverse coverage of transcripts (100s to genome-wide) and spatial resolution.

Two main types of spatial profiling technologies are used to uncover the relationships between cells within tissues and organs: imaging-based methods and sequencing-based methods. As Farah explains, “imaging-based methods require a microscope and image molecules (RNA) in situ within the tissue, whereas sequencing-based methods rely on spatially barcoded probes which spatially tag the molecules that are subsequently identified using NGS.”

While in situ hybridization (ISH) or in situ sequencing (ISS) based technologies can capture a limited number of transcripts, spatial barcode-based technologies have been used to perform genome-wide analysis of gene expression with spatial resolution, drastically increasing the breadth of analysis.

The process of In situ sequencing. Credit: Technology Networks.

Each type of spatial profiling technology has its limitations. “Imaging-based methods are limited by the capabilities of the microscope and challenges related to imaging area, image processing pipelines, imaging time, digital size of the imaging data as well as a lower number of genes that can be profiled compared to sequencing-based methods,” Farah says.

Challenges to sequencing-based methods include the capture efficiency of the targeted molecules and lower spatial resolution compared to imaging-based methods. “Each of these challenges is being overcome by improving the respective technology’s capabilities, such as improved chemistry and microscopes for imaging-based methods and higher resolution arrays of spatial tags for sequencing-based methods,” he adds.

Castelo-Branco is impressed with the pace at which the field is advancing.

“We are getting to a stage where we can carry out spatial genome-wide investigations at near-cell resolution.”

The power of data integration and the emergence of spatial multiomics

To uncover the spatio-temporal dynamics of gene expression researchers are combining different data modalities. For example, to characterize cell types that make up the human heart and their interactions to form and maintain functional cardiac structures, Farah and colleagues combined single-cell RNA sequencing (scRNA-seq) data with an image-based single-cell transcriptomics approach. Known as multiplexed error-robust fluorescence in situ hybridization (MERFISH), 238 RNA species localized in individual cells were measured while preserving the native spatial context of RNAs.

“Our study greatly expands the number of cell types and states involved in the developing human heart, particularly in the cardiac valves and conduction system regions,” he says. Importantly, their analysis of the interactions between neighboring cells highlighted a novel migration signal for ventricular cardiomyocytes to form the ventricular wall that scRNA-seq alone would not have revealed.

Castelo-Branco’s research group focuses on the role of oligodendrocytes in multiple sclerosis (MS), an autoimmune disease that damages the protective myelin sheath that surrounds nerves causing a wide range of symptoms including muscle weakness and vision changes. “Our work on RNA sequencing and epigenomics in single cells has shown that oligodendrocytes transition to an immune-like state in both mouse models of MS and in patient material,” he says. “With Rong Fan’s microfluidic-based method, DBiT-seq, we were able to deliver a unique combination of barcodes to the surface of a tissue slide that act like a GPS signal, allowing for spatial multiomics sequencing at every spot.”

By using two microfluidic channel array chips perpendicular to each other, Castelo-Branco and Fan co-barcoded the same tissue section for epigenomic and transcriptomic analysis. As described in their recent publication, they combined epigenomic profiling using previously described methodologies for measuring chromatin accessibility (ATAC-seq, assay for transposase accessible chromatin with sequencing) or for measuring histone modifications (CUT&Tag, cleavage under targets and tagmentation) with RNA sequencing (RNA-seq).

“The technology is very versatile as it allows to combine different omic modalities in the same tissue section with a spatial resolution ranging from 50 to 10-micron,” Castelo-Branco says.

Spatial ATAC–RNA-seq and spatial CUT&Tag–RNA-seq, offer a glimpse into the before and after of gene expression. “As I see it, the epigenetic profile offers a snapshot of the past or future of the cell, whereas the RNA status is the present,” he says. “We can see areas where the chromatin is open or there are activating histone modifications coinciding with gene expression and, more interestingly, others where there is no concordance, which could indicate that the cell is undergoing a transition to a new state or reflect epigenetic memory.”

So far, the team has applied the technology to mouse brain tissue at different stages of development and to adult human hippocampal tissue. Castelo-Branco’s team is interested in investigating the spatial relationships between peripheral immune cells and brain resident cells in patients with MS and how lesions evolve.

“We are starting to apply this technology to archival tissue of MS patients and mouse models of the disease to gain insights into transcriptomic and epigenomic changes driving lesion formation and recovery,” he says.

Future directions

As the technology for spatial profiling improves, researchers will be able to image larger areas and collect multiple data modalities (DNA, RNA, protein) within the same cell to produce high-resolution 3D reconstructions of tissues and organs. Moreover, by applying these technologies at different time points, they will also be able to effectively create 4D atlases of tissues and organs as they develop or as a disease progresses.

“Spatial biology technologies are following the same trajectory as the single-cell field, starting with transcriptomics but rapidly expanding to include epigenomics and proteomics data,” Castelo-Branco says. “As the depth of coverage and single-cell resolution improves, it will become increasingly powerful for studying any disease that has a solid tissue component.”

Castelo-Branco’s team is now focusing on capturing more types of epigenetic data on the same tissue section to create a timeline of events in MS lesion formation and on applying spatial biology technologies to other contexts such as high-grade gliomas.

“Many things we thought wouldn’t be possible a few years ago can now be done; as companies start to commercialize these technologies and they become more widely accessible, I expect the application of spatial biology in life sciences will explode,” he concludes.

About the interviewees:

Elie Farah is a postdoctoral scholar at the University of California San Diego, USA. He is interested in cardiac development and regeneration and uses spatial biology technologies to investigate human heart ventricular wall morphogenesis.

Gonçalo Castelo-Branco is professor of glial cell biology at Karolinska Institutet in Stockholm, Sweden. His research focuses on the molecular mechanisms that define the epigenetic state of cells of the oligodendrocyte lineage in development and disease. The long-term aim of his research group is to design epigenetic-based therapies for demyelinating diseases such as MS.