10x Visium: A Breakthrough Enabling Omics Analysis at Spatial Level

Contributors: Aditya Mahadevan Iyer, Philge Philip, Debamitra Chakravorty, Tahseen Abbas, Shashi Rekha Thummala, Indu Gangwar, Jeffin Rockey, Prathik KV, Akshay Subramanian, Uzma Saeed, Jitesh Pillai, Puneet Saxena, Chandra Sekhar Pedamallu

Cell-cell interactions have played a significant role in the development of multicellular organisms. Understanding the spatial location of genes along with their expression can provide valuable insights for dissecting cellular functions and phenotypic state. This has been enabled by spatial transcriptomics that unravel the tissue architecture and provide a clear picture of the biological landscape.

Interestingly, recent technological advancements have made spatial transcriptomics more accessible. The need for Spatial Transcriptomics (ST) technology can be understood in the context of its application to crucial areas such as the tumor microenvironment (TME), tumor heterogeneity, developmental biology, neuroscience, and regenerative medicine.

Out of the three broad Spatial transcriptomics technologies (namely, Laser capture microdissection (LCM) based approaches, Image-based in situ transcriptomics and Spatial barcoding-based transcriptomics), the barcoding-based ST methods that employ next-generation sequencing are at the forefront.

While our earlier whitepaper provides a generic sense of the Spatial omics, its application benefits and how Excelra takes it further by providing custom solutions, this collateral focusses sharply on the 10x Visium spatial transcriptomics technology, detailing on technical aspects as well as certain use-cases where the Visium comes handy.

Spatial barcoding-based transcriptomics

The spatial barcode-based transcriptomic approaches involve the sequencing of the RNA species at the whole transcriptome level. They offer unbiased and high-throughput analytical solutions. In this technology, the tissue sections are immobilized on the glass slides along with the reverse transcription primers with poly-T, which bind to the poly-A of the mRNA from the tissue sections.

The primers also contain the spatial barcodes and unique molecular identifiers (UMIs) that represent the coordinates of each array. When the tissue is permeabilized, the mRNA molecules in the tissue cells get diffused into microwells (100 μm in size) on the slides and get hybridized with primers.

The reverse transcription reagents will be added to the tissue to synthesize the cDNA molecules, which are then visualized using the Cy3-labeled nucleotides. The tissue section is removed by enzymes and the cDNA molecules remain hybridized on the glass side (Stahl et al. 2016).

Visium is the most widely applied spatial omics technologies that can sequence tissues of 6mm × 6mm in size. Each spot on the chip can be measured at the resolution of ~100 µm containing about 2–10 cells.

In 2019, this method got further developed by 10× Genomics and commercialized as “10× Genomics Visium”. Its application benefits lead to exploring the new functionality of the organelles and may enhance our understanding in the field of spatiotemporal molecular medicine (Figure 1).

The latest Visium HD technology offers high sensitivity and single-cell scale resolution by improvement in spot resolution to 2 x 2 um squares, providing even more granular insights into tissue composition and cellular interactions. This high-definition mapping is crucial for identifying rare cell types and understanding complex biological processes.

Figure 1: Flowchart of 10X Visium technology and its related analyses [Adapted from Plant biotechnology research with single-cell transcriptome: recent advancements and prospects (Ali et al., Plant Cell Reports, 2024)]

Potential solutions & applications

Thanks to the growing interest in the ST domain, wherein in the last 5 years tremendous amount of work has been done while exploring application benefits of Visium technology. The following section highlights some of the use cases where Visium has opened new frontiers in the research field.

Exploring the spatial and temporal dimensions of tissue formation and growth

10X Visium technology has garnered extensive usage in studying the development of embryos, tissues, and organs across various species, supported by a substantial body of literature. By analyzing tissues at different developmental stages, Visium can provide insights into the temporal dynamics of gene expression crucial for studying molecular processes like embryonic development, wound healing, and tissue regeneration.

Visium supports both fresh-frozen and formalin-fixed, paraffin-embedded (FFPE) tissue sections, making it suitable for a wide range of studies. This versatility allows for the examination of archived clinical samples and the study of various tissue types.

Creating detailed maps of tissues or anatomical areas

Visium offers unbiased means to create spatial maps of tissues, leading to the development of comprehensive reference tissue atlases. Examples include human kidney tissues in various health and disease states, spatial multi-omics maps detailing cardiac remodeling, and detailed atlases of human lung structures.

Moreover, Visium has also contributed to identifying spatial distribution of gene expression signatures in human dorsolateral prefrontal cortex.

Investigating the underlying genetic and cellular disruptions that lead to various diseases.

The 10X Visium platform has significantly advanced our understanding of genetic and cellular disruptions in various diseases by preserving the spatial context of gene expression within tissues. This is particularly valuable for cancer research and complex disease biology.

In diseases like Alzheimer’s, Visium has been used to identify specific gene expression changes near amyloid plaques, providing insights into inflammation and myelination processes. 10X Visium is thus assisting in more targeted and effective treatments.

Examining the diverse cell populations and their surrounding environments within tumors

The interplay between extrinsic immune cells and intrinsic tumor cells plays a pivotal role in shaping tumor progression and metastasis. Spatially, different tumors vary amongst themselves in tumor microenvironment organization and hierarchy, emphasizing the need for understanding spatial architecture of TME.

10X Visium has been used to characterize stromal and immune cell distribution in the tumor microenvironment, enabling identification of spatial heterogeneities and metastatic drivers.

Mapping disease and treatment-related biomarkers with spatial precision

Biomarkers identified through spatial transcriptomics can be prognostic or predictive of therapeutic response, highlighting the translational application of precision medicine.

In hepatocellular carcinoma, gene signatures identified using spatial transcriptomics have been shown to predict patient survival. Spatial organization of immune cells and identification of tumor invasive fronts further act as biomarkers of prognosis and treatment response.

Future perspectives and conclusions

Advancements in 10X Visium underscore the transformative potential of the technology in unraveling spatially defined biomarkers and translating findings into clinical practice. The spatial dimension provided by 10X Visium enables precise analysis of cell populations, neighboring cell interactions, and overall cellular structural organization.

Other than transcriptomics, the proteome, neuronal connectome, and 3D chromatin conformation are crucial to cell function, and methods like DBiT-seq and MERFISH have been developed to profile these along with the transcriptome in the same cells.

The future holds promise in integrating spatial omics data into comprehensive databases supported by AI-driven querying and visualization techniques. Despite progress, integration of such high-dimensional technologies into routine clinical use remains challenging.

Excelra, where “data means more”, is aiming to contribute towards this growth by supporting clients with customized Nextflow pipelines, domain expertise, and advanced analytics to navigate complex spatial transcriptomics datasets and build actionable insights.

References

• Stahl PL, Salmen F, Vickovic S, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353(6294):78–82 (2016).
• Rao A, Barkley D, Franca GS, Yanai I, Exploring tissue architecture using spatial transcriptomics, Nature 596 211–220 (2021).
• Garcia-Alonso L, Lorenzi V, Mazzeo CI, Alves-Lopes JP, Roberts K, Sancho-Serra C, Engelbert J, Mareckova M, Gruhn WH, Botting RA, Li T, Crespo B, van Dongen S, Kiselev VY, Prigmore E, Herbert M, Moffett A, Chedotal A, Bayraktar OA, Surani A, Haniffa M, Vento-Tormo R, Single-cell roadmap of human gonadal development, Nature 607 540–547 (2022).
• Liu C, Li R, Li Y, Lin X, Zhao K, Liu Q, Wang S, Yang X, Shi X, Ma Y, Pei C, Wang H, Bao W, Hui J, Yang T, Xu Z, Lai T, Berberoglu MA, Sahu SK, Esteban MA, Ma K, Fan G, Li Y, Liu S, Chen A, Xu X, Dong Z, Liu L, Spatiotemporal mapping of gene expression landscapes and developmental trajectories during zebrafish embryogenesis, Cell 57, 1284–1298 e1285 (2022).
• Maynard, K.R., Collado-Torres, L., Weber, L.M. et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex, Nat Neurosci 24, 425–436 (2021).
• Satilmis B, Sahin TT, Cicek E, Akbulut S, Yilmaz S. Hepatocellular Carcinoma Tumor Microenvironment and Its Implications in Terms of Anti-tumor Immunity: Future Perspectives for New Therapeutics. J Gastrointest Cancer. Dec;52(4):1198-1205. (2021).
• Wu Y, Yang S, Ma J, Chen Z, Song G, Rao D, Cheng Y, Huang S, Liu Y, Jiang S, Liu J, Huang X, Wang X, Qiu S, Xu J, Xi R, Bai F, Zhou J, Fan J, Zhang X, Gao Q, Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level, Cancer Discov. 12 134–153 (2022).
• Zhao N, Zhang Y, Cheng R, Zhang D, Li F, Guo Y, Qiu Z, Dong X, Ban X, Sun B, Zhao X, Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival, Cancer Cell Int. 22 57 (2022).
• Zugazagoitia J, Gupta S, Liu Y, Fuhrman K, Gettinger S, Herbst RS, Schalper KA, Rimm DL, Biomarkers associated with beneficial PD-1 checkpoint blockade in non-small cell lung Cancer (NSCLC) identified using high-Plex digital spatial Profiling, Cancer Res. 26 4360– 4368 (2020).
• Gouin KH, Ing N, Plummer JT, Rosser CJ, Ben Cheikh B, Oh C, Chen SS, Chan KS, Furuya H, Tourtellotte WG, Knott SRV, Theodorescu D, An N-cadherin 2 expressing epithelial cell subpopulation predicts response to surgery, chemotherapy and immunotherapy in bladder cancer, Commun. 12 4906 (2021).