Unlocking the Power of Spatial Biology
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Single-cell analysis is an incredibly useful tool that enables the study of cell-to-cell variation across populations, with applications in fields such as tumor biology and microbiology. However, cells do not exist in isolation – they are heavily influenced by their surroundings and context within a tissue. In this regard, spatial biology techniques can improve upon single-cell analysis, offering insights into a cell’s environment and interactions and providing a more detailed look at its biological functions.
Sarah Whelan (SW): Can you give us an introduction to what spatial biology is and its significance?
Vikram Devgan (VD): Spatial biology is the study of cells within their native tissue environment with an unprecedented level of “-plex” and resolution. Spatial biology combines morphological assessment of the tissue with quantification of high-plex gene and protein expression at cellular resolution. The term “spatial” is used most often today to describe approaches that retain information on morphologically intact context while providing very large amounts of information on the biology of cells. The “spatial” part of spatial biology has been around for a long time. It is the “large amount of information” and “high-plex” part that is new. Spatial omics refers to assays that simultaneously and comprehensively measure hundreds to thousands of transcripts or proteins within cells and tissues, generating high-content data on the expression profiles, states and functions of cells while retaining spatial context.
Spatial biology approaches have opened a new frontier for discovery by enabling high-plex biomarker expression analysis of cells in a histological context. When you can measure thousands of biomarkers directly in cells while retaining spatial context, this empowers researchers to uncover biological relationships and mechanisms within cells and tissues that have been too complex or subtle to reveal with any other technology. As this exciting new field develops further, it will be transformative for delivering a new of understanding of human health and disease, as well as a more comprehensive study of biology in general.
SW: What are the benefits of spatial imaging technologies over other types of single-cell or microscope analysis?
VD: The benefit of spatial imaging technologies over other single-cell methods is that all cells are analyzed in situ, so no cells are left behind. The molecular analytes are assayed directly from within the cells, and these cells are analyzed within their histological context. All the information is captured and integrated to provide a complete picture. High-plex spatial imaging methods utilize cyclic fluorescence microscopy to assay very large numbers of analytes in parallel. This allows the integration of morphological and histological information to generate high-resolution and high-information content maps of tissues. Importantly, spatial imaging technologies enable cell segmentation based on nuclear and cell boundary markers, so analytes can be assigned specifically to the cell they belong to and morphological information such as shape, size, position and volume are captured in the data along with images of the cells. This allows the data to capture spatial distributions and diversity of cell types within tissues, rare cell discovery, spatial patterns/gradients of expression and microenvironments.
Other types of transcriptomic and proteomic single-cell analysis (such as single-cell RNA sequencing, flow cytometry, mass cytometry, single-cell western blotting, droplet-based microfluidic immunoassays, etc.) can provide large amounts of information on the biology of individual cells, but they lack spatial information and introduce tissue dissociation-associated bias.
Other types of microscopy-based analysis for RNA and protein expression such as immunohistochemistry (IHC), immunofluorescence (IF) or in situ hybridization (ISH) can provide spatial context but have limited breadth and depth of information, lacking the workflows, automation and analysis approaches to enable high-plex analysis and single-cell data processing.
SW: Can you explain how NanoString’s innovative CosMx™ Spatial Molecular Imager (SMI) system functions and walk us through its workflow?
VD: The CosMx Spatial Molecular Imager (SMI) is the first spatial biology platform to provide unprecedented high-plex multiomics for intact formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) samples at a cellular and sub-cellular resolution. The CosMx SMI platform enables spatially resolved, high-plex digital quantitation of more than 1,000 RNA and over 64 protein targets.
The CosMx RNA and protein assay chemistry is an amplification-free single-molecule encoding methodology, that relies on ISH probes and fluorescent readout probes to detect single RNA molecules or spatially defined protein signals in intact tissue sections. The assays utilize recombinant antibodies and/or ISH RNA probes that are covalently linked to small (~20 nm) high-information content (64-bit encoded) single-molecule imaging barcodes. The CosMx workflow consists of a streamlined overnight sample preparation protocol that includes the hybridization of ISH probes to tissue on glass slides and then the assembly of the slides into flow cells. These are placed within a fluidic nest on the SMI instrument that can accommodate up to four slides. The CosMx SMI uniquely offers true cell boundary detection using protein imaging coupled with high-plex RNA detection. CosMx SMI is a comprehensive technology offering customizable pre-defined panels, sample prep kits, integrated readouts and intuitive data analysis (including automated cell-type identification, UMAP, differential expression analysis, sub-cellular localization, etc.) with an interactive viewer to serve end-to-end research needs.
SW: What are some of the main applications of the CosMx system?
VD: With high-plex in situ analysis, CosMx SMI allows researchers to look at which cells are present, where they are located in the tissue, their biomarker co-expression patterns and how they organize and interact to influence the tissue microenvironment, all with a single experiment. The key applications enabled by CosMx SMI are:
- Cell atlas/cell typing. Easy discovery and mapping of cell types using the expression profile of known RNA and protein targets.
- Tissue microenvironment mapping. Understanding cellular neighborhoods by examining individual cells and their interacting neighboring cells.
- Uncovering ligand-receptor interactions. Analyzing the expression and interactions of up to 100 classic ligand-receptor pairs between interacting cells.
- Biomarker discovery. Reveals differential gene expression and pathways in the same cell types depending on their spatial location.
- Disease state assessment. Visualizes and quantifies molecular (RNA/protein) and cellular organizational changes in healthy vs diseased tissues.
SW: What are the difficulties with analyzing FFPE tissue, and how does NanoString’s technology overcome this?
VD: FFPE samples are notoriously difficult for molecular analysis with high variability, low yield and in many cases, high degradation. NanoString has been addressing the FFPE challenge with success for more than a decade, starting with the nCounter® gene expression system, then with the GeoMx® digital spatial profiler (DSP) system and now we are applying that knowledge to the CosMx SMI system. Mechanistically, amplification-based methods like rolling cycle amplifications require transcripts to be largely intact and accessible to be efficiently detected. NanoString’s unique probe-based detection eliminates the challenges of FFPE by utilizing molecular “barcodes” and single molecule imaging to directly hybridize and detect hundreds of unique transcripts in a single reaction without any amplification steps that might introduce bias.
SW: I understand that NanoString is releasing a cloud-based informatics solution called AtoMx™ Spatial Informatics Platform (SIP). Can you tell me a little more about how the AtoMx solution and why it is one of a kind?
VD: The AtoMx SIP is the first cloud-based informatics platform to provide the secure, scalable storage and analysis that spatial biology researchers need to drive their workflow from study design to peer-reviewed publication. AtoMx SIP is compatible with both the CosMx SMI platform and the GeoMx DSP, supporting research that spans the relevant scales of biology across multiple laboratories and institutions. AtoMx obviates the need for laboratories to invest in their own costly informatics infrastructure and reduces spatial biology analysis compute times from days to hours. Users have the flexibility to apply one of AtoMx’s pre-defined data analysis pipelines, to customize these pipelines using their own code or to access open-source tools developed by the bioinformatics community. Additionally, users can easily access the data from anywhere and share it with anyone.
Dr. Vikram Devgan was speaking to Sarah Whelan, Science Writer for Technology Networks.