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Beyond Sequencing: The Spatial Dimensions of the Transcriptome


  • Beyond Sequencing: The Spatial Dimensions of the Transcriptome

    Click image for larger version  Name:	Transcriptomics Article2.jpg Views:	0 Size:	1.75 MB ID:	325140

    Spatial technologies have improved our understanding of the transcriptome by providing insights into the spatial organization and interactions of cells. While next-generation sequencing (NGS) remains an important approach and is the main focus of our community, its data alone is unable to resolve unique spatial information. Jacob Stern, Director of Product Management at 10X Genomics, emphasized how numerous researchers choose to use both spatial platforms and single-cell sequencing in their work. The combination of these technologies allows for a holistic view of cell signatures, their locations, and their interactions within a tissue environment.

    This integration of sequencing and spatial technologies is becoming more prevalent, underscoring the need to understand the evolving spatial landscape. In this article, we’ll review the various spatial transcriptomics tools and techniques, spotlighting sequencing-based and image-based solutions from leading organizations in the field.

    10X Genomics

    Technology: Widely acknowledged for their acclaimed single-cell sequencing tools, 10X Genomics has carved a place for itself in the spatial omics domain with their Visium and Xenium platforms. Visium is an NGS-based technology that performs thorough mapping of the whole transcriptome and can be coupled with protein detection. In comparison, Xenium is an imaging-based platform that can characterize 100’s to soon 1,000s of RNAs and multiplexed proteins.

    How it works: Visium's core technology is a slide with spatially barcoded RNA-binding oligonucleotides. During library construction, the spatial barcode is transferred to the cDNA, which allows for the localization of transcripts to their original tissue position post-sequencing.

    The Xenium workflow uses padlock probes tagged with gene-specific barcodes, which undergo enzymatic amplification. Then, fluorophore-labeled oligo probes bind to these tags, and through successive imaging rounds, an optical signature is generated for precise gene identification.

    Elaborating on the capabilities and differences between the platforms, Stern noted that Visium leverages NGS for the ability to profile the whole transcriptome for truly unbiased discovery work. For Xenium, users have the advantage of a high-resolution imaging-based workflow that provides readouts of hundreds to thousands of transcripts with remarkable clarity, along with a streamlined workflow for designing and ordering custom gene panels.

    Highlights: In addition to their high plex and resolution, Stern highlighted the multimodal nature of both platforms. In the Visium workflow, standard H&E or immunofluorescence imaging techniques can be applied to the very same tissue section prior to gene sequencing. As for Xenium, these types of techniques are available on the same tissue slide post-run. Facilitating these complementary methods allows researchers to cross-validate their results and provide a more comprehensive picture of the same tissue sample.

    Recent advances: In the previous year, 10X Genomics introduced the Visium CytAssist instrument. This device not only simplifies the Visium workflow but also offers NGS-based, highly multiplexed protein detection and whole transcriptome discovery from the same tissue section. The upcoming Visium HD array will be exclusively available on the CytAssist instrument and promises even greater resolution than the existing platform. Enhancements to the Xenium platform are anticipated to increase its throughput to a notable 5,000-plex. Stern also described 10X's ongoing commitment to refining important processes like cell segmentation. He explained that their vision emphasizes expanding modalities, accommodating more tissue types, and including more analytes, all aimed at broadening the versatility of their systems in support of their user base.


    Technology: Originating from a Harvard University spin-out, Vizgen evolved the core MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridization) technology1 from the Zhuang lab to create their MERSCOPE Platform. This refined method allows for advanced spatial transcriptomics in native tissues, enabling the analysis of up to 500 genes within single cells.

    How it works: MERFISH expands upon smFISH (single-molecule fluorescence in situ hybridization)2,3 by utilizing combinatorial labeling, multiple rounds of imaging, and error-robust barcoding. During this process, each gene is given a unique binary barcode, which is read out through the binding of specific probes to their targeted genes. After multiple rounds of imaging, these barcodes are read by observing fluorescence patterns, producing high-resolution spatial identification and quantification of diverse RNA species.

    Highlights: Terry Lo, CEO and President of Vizgen, emphasized the importance of data quality in their work, stating, “Our strengths are in the data quality.” He outlined several primary benefits of their MERFISH technology. First, employing multiple probes against a single target ensures a stronger signal and improved specificity. Lo also stressed the value of combinatorial barcoding. Through successive rounds of imaging, this feature increases multiplexing far beyond what typical imaging techniques can offer. Finally, these barcodes serve as an “error-robust” feature, which prevents optical crowding and aids in error correction. Complementing their offerings, Vizgen provides a custom Gene Panel Design software, allowing researchers to tailor their studies to specific genes.

    Recent advances: In addition to their custom gene panels, Vizgen introduced the MERSCOPE PanNeuro Cell Type Predesigned Panel, a 500-gene tool that identifies and explores major cell types, subtypes, and interactions in the mouse brain. They also released the MERSCOPE PanCancer Pathways Panel, a gene list targeting key cancer signaling pathways and designed to identify both healthy and disease states across various cancer types. During AGBT 2023, Vizgen announced plans to increase their multiplexing capabilities to allow the analysis of up to 1,000 genes at high resolution.

    Resolve Biosciences

    Technology: Founded by former Qiagen executives, Resolve Biosciences developed their Molecular Cartography platform for high-resolution, spatially-resolved transcriptomic insights within tissue samples.

    How it works: Molecular Cartography employs combinatorial single-molecule fluorescent in situ hybridization (smFISH) to hybridize numerous transcript-specific probes to target RNA, allowing the analysis of up to 100 different RNA types per sample4. Using a unique colorizing and de-colorizing chemistry across multiple imaging rounds, the technology decodes the barcodes specific to each transcript type, resulting in the visualization and pinpoint identification of millions of individual transcripts in each sample.

    Highlights: The uniqueness of Resolve's technology lies in its proficiency in handling shorter transcripts (minimum 500nt), identifying extra coding genes, and retaining tissue health, making it compatible with downstream applications such as immunohistochemistry.

    Recent advances: At AGBT 2023, Resolve announced an expansion to their Meridian lab services, allowing scientists to submit various tissue samples for spatial transcriptomics data analysis through the company's Molecular Cartography technology. Future plans for Molecular Cartography include the integration of DNA, protein, and metabolomic data.

    NanoString Technologies

    Technology: Following the success of the nCounter Analysis System, NanoString introduced two spatial multiomic systems: the GeoMx Digital Spatial Profiler (DSP) and the CosMx Spatial Molecular Imager (SMI). The GeoMx DSP has the capability to analyze the complete transcriptome and over 570 protein markers, with quantification facilitated through Illumina instrumentation or the nCounter System. On the other hand, the CosMx SMI offers a standalone imaging-based solution, quantifying up to 1000 RNAs and 100 proteins with single-cell and sub-cellular precision.

    How it works: The GeoMx DSP employs a distinct approach where gene-specific probes linked to a unique DSP barcode via a UV-cleavable linker are hybridized to mRNA targets on tissue slides. After selecting regions of interest based on fluorescent staining, UV light releases the DSP barcodes, facilitating library construction, sequencing, and spatial gene expression analysis.

    Utilizing a dual-probe hybridization method, the CosMx SMI platform features a primary probe having 16 read-out domains, complemented by a secondary probe infused with multiple dyes for optimal signal strength. Through a sequence of hybridization rounds, the combination of fluorescent markers generated is specific to the targeted gene, enabling the platform to simultaneously image and quantify RNA with subcellular precision.

    Highlights: Standout features of the GeoMx DSP include its ability to profile the whole transcriptome along with a significant number of proteins in a non-destructive manner. The CosMX SMI excels in offering both high multiplexing and subcellular resolution for RNA and proteins within preserved FFPE and fresh frozen tissue samples.

    Recent advances: This year, NanoString launched the GeoMx IO Proteome Atlas (IPA), a spatial proteomics tool capable of analyzing over 500 immuno-oncology (IO) relevant markers from FFPE. By pairing GeoMx IPA with GeoMx WTA, users can now study both the human transcriptome and IO proteome from just one slide. NanoString also announced an increase in plex on the CosMx SMI platform with the expectation of 6,000-plex assays in the coming year.

    Future of Spatial Transcriptomics
    While these technologies are central in the spatial transcriptomics field, it’s important to recognize other platforms like the Veranome Spatial Analyzer by Veranome Biosystems and the Rebus Esper spatial omics platform from Rebus Biosystems. Akoya Biosciences, once primarily dedicated to spatial proteomics, has also expanded into spatial RNA analysis. Moreover, there’s been a surge of sequencing-based techniques such as Slide-seq5, DBiT-seq6, and Stereo-seq7, with many leading to commercial development.

    Each of the discussed technologies varies in aspects like resolution, approach, throughput, costs, and multiplexing capabilities. However, our emphasis is on their unique strengths that show the rise and integration of spatial transcriptomics. As these technologies continue to develop and become more widespread, we can anticipate new discoveries that will reshape our understanding of biology and have the potential to transform therapeutics and diagnostics.

    Recommended Further Reading
    While this overview only scratches the surface of spatial transcriptomic technologies, the resources below are invaluable for researchers wanting to learn more about these exciting developments.
    1. Chen KH, Boettiger AN, Moffitt JR, et al. Spatially resolved, highly multiplexed RNA profiling in single cells. Science. 2015;348(6233):aaa6090. doi:
    2. Femino AM, Fay FS, Fogarty K, et al. Visualization of Single RNA Transcripts in Situ. Science. 1998;280(5363):585-590. doi:
    3. Raj A, van, Rifkin SA, Oudenaarden van, Tyagi S. Imaging individual mRNA molecules using multiple singly labeled probes. Nature Methods. 2008;5(10):877-879. doi:
    4. Groiss S, Pabst D, Faber C, et al. Highly resolved spatial transcriptomics for detection of rare events in cells. bioRxiv. Published online January 1, 2021:2021.10.11.463936. doi:
    5. Rodriques SG, Stickels RR, Goeva A, et al. Slideseq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463-1467. doi:
    6. Liu Y, Yang M, Deng Y, et al. HighSpatialResolution MultiOmics Sequencing via Deterministic Barcoding in Tissue. Cell. 2020;183(6):1665-1681.e18. doi:
    7. Chen A, Liao S, Cheng M, et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell. 2022;185(10):1777-1792.e21. doi:

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    About the Author


    seqadmin Benjamin Atha holds a B.A. in biology from Hood College and an M.S. in biological sciences from Towson University. With over 9 years of hands-on laboratory experience, he's well-versed in next-generation sequencing systems. Ben is currently the editor for SEQanswers. Find out more about seqadmin

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