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New Commercial Developments in Spatial Transcriptomics

This feature on spatial transcriptomics technology is adapted from parts of Chapters 1 & 2 of the 2023 Spatial and Single-cell Analysis Playbook.

Spatial transcriptomics is an area seeing rapid development. The levels of resolution are improving, and the number of markers and molecules quantified in a single experiment is also expanding. Furthermore, multiomics capacities are a new addition to these spatial techniques. In this feature, we will briefly look back over the historical development of spatial transcriptomic technology before summarising the latest commercial and technological developments.

Historical Recap of Spatial Transcriptomics

Compared to single-cell sequencing, spatial transcriptomics has not reached the same level of maturity, despite a similar timeframe of development (see Figure 1). This is partly because current spatial technologies can be divided into four different categories, all of which are being developed. These include:

  1. Microdissection methods – this ‘brute-force’ method involves dissecting out small regions of interest and sequencing them traditionally. This limits the size of area one can investigate. Methods include: LCM1, TIVA2, NICHE-Seq3 and, most recently, ProximID4.
  2. In situ Hybridisation (ISH) methods – these methods visualise RNA directly in their environment through binding probes and fluorescent markers to RNA. A historical challenge has been the limitation on the number of markers in one experiment due to spectral overlap.
  3. In situ Sequencing (ISS) methods – these methods perform RNA sequencing inside the cell while it remains in tissue context. Due to the spatial limits of the cell, there is a limit to the number of transcripts that can be discriminated simultaneously.
  4. In situ Capture (ISC) methods – these methods capture transcripts in situ using barcodes, which historically limits RNA capture efficiency.

Figure 1. Timeline of the key developments in spatial transcriptomic technologies. The principles of several exemplar technologies are demonstrated including: (A)  ProximID, (B) seqFISH+, (C) Stereo-seq, (D) sci-Space, (E) STARmap, (F) 10x Genomics Visium; (G) Slide-seqV2 and (H) Seq-Scope. Image Credit: Zhang, et al. 5

Figure 2 displays a timeline of landmark technologies within these four categories. We will review some of the major advances in ISH, ISS and ISC methodologies.

The first RNA ISH was performed in the early 1990s and what followed was a series of advances that improved the resolution. In 1998, the first single molecule FISH6 (smFISH) allowed the first subcellular RNA visualisation with singly labelled oligonucleotide probes. This 1998 method suffered technical issues, which meant the first reliable smFISH was published in 20087. This was followed in 2011/12 by the first RNAscope, which used a novel ‘Z’ probe to bind to RNA transcripts. Later in 2014, seqFISH8 was published, which used sequential hybridisations to expand the number of targets and in 2015, MERFISH9 improved on the time and effort of seqFISH using multiple readout hybridisations. SeqFISH+10 and MERFISH+11, both published in 2019, mark the current pinnacle of ISH transcript detection allowing for ~10,000 genes to be visualised with confocal microscopy. The historical limitation on the number of markers is overcome using multiple bindings sites and multiple rounds of binding.

For in situ sequencing, the first approach, called In Situ Sequencing12 (ISS) was published in 2013 and used padlock probes to sequence targeted genes in tissue sections. This approach achieved subcellular resolution but was limited to ~100 targets. The 2019 release of HybISS13 saw radical improvement of the target limit using sequencing-by-hybridisation instead of by ligation. ISS is continually seeing improvement, with this year’s publication of Improved ISS14 (IISS) using new probing, barcoding and imaging for better gene profiling. Other methods of in situ sequencing including FISSEQ15, published in 2015, use fluorescence methods to capture genome-wide RNA in an unbiased manner, but, again, do not have the capacity for whole transcriptome level sequencing. More recent methods such as STARmap16 use padlocks without reverse transcription and DNA nanoballs to sequence an expanded range of targets.

The most recent and most rapidly advancing set of approaches are the in situ capture/barcoding methods. These methods capture transcripts in situ that are then sequenced ex-situ, which avoids the limits of visualising and sequencing targets in situ. However, the challenge for this technology is RNA capture efficiency, particularly with the drive to achieve higher resolution with smaller capture areas. Spatial transcriptomics18 (ST) was the first of these approaches published in 2016, which was later released commercially as 10x Genomics Visium. It uses barcoded RT primers printed onto glass slides for RNA capture, but initial resolution was 100 micrometres, improving to 55 micrometres with the Visium. Slide-seqV1 and V219,20 radically improved the resolution to 10 micrometres and use barcoded beads on a slide.

High-definition spatial transcriptomics21 (HDST) was released shortly after SlideseqV1 using smaller beads, enabling an impressive two micrometre resolution. Very recent techniques such as Seq-Scope22, Pixel-seq23 and Stereo-seq24 represent the current cutting edge, having refined spatial resolution to under one micrometer. Stereo-seq used DNA nanoballs to achieve this and is the first technology to have achieved subcellular resolution and a centimetre-scale field of view. Finally, techniques such as DBiT-seq25 and sci-Space26 differ in that they use deterministic barcoding, and the latter method allows for large fields of view at the cost of spatial resolution.

Figure 2. Timeline of major landmarks in spatial genomic methods. Methodologies are categorised based on type (red, in situ sequencing-based method; green, in situ hybridization based method; orange: micro-dissection based method; purple: in situ spatial barcoding based method). In situ spatial barcoding approaches are quantified by spatial resolution and by Field of View (size of circle). Dashed box indicates single-cell/nuclei resolution. Image Credit: Cheng, et al. 17

While barcoding methods seem promising and the current direction of future progress, especially given the impressive spatial resolution, RNA capture efficiency is still poor compared to isolating the cells and sequencing them with single-cell sequencing technology. Brand new techniques, such as Slide-tags27, could perhaps address this issue. Slide-tags first barcodes nuclei within tissues with a high spatial resolution. These nuclei can then be dissociated and isolated, meaning the mature single-nuclei technology can be used to sequence them. However, the nuclei still have the spatial barcodes and can be mapped back to their tissue context.

New Commercial developments in Spatial Omics

As summarised above, spatial biology has drastically improved over the last decade. For researchers, large-scale single-cell spatial multiomics is the ultimate short-term goal. The past two years have seen commercial advancements in spatial multiomics methods as well as increases in capacity, multiplexing and resolution to make this a reality.

In the following sections we will highlight a selection of commercial advances that have happened in the past two years, providing an overview of the directions of progress. This list is not exhaustive and was compiled in August 2023.

Spatial multiomics co-detection of RNA and protein in one experiment

Some of the most established companies in the spatial transcriptomics space have made the same move in the last 24 months; to diversify their core spatial transcriptomics products to co-visualize proteins within a single experiment, making true multiomics spatial platforms. Some key examples include:

  • 10x Genomics Visium Cyt Assist™ – first launched in 2022 to improve sample preparation, has now released a whole transcriptome and 31-plex proteinassay as of May 2023. This allows the study of protein and RNA in a single tissue section as well as H&E/IF staining for tissue morphology.
  • Nanostring CosMx™ SMI – launched in December 2022 as the highest plex in situ imager with 1000-plex RNAs and 64-plex proteins analysed in the same tissue at subcellular resolution. This joins Nanostring’s other products including the first cloud-based spatial data analysis resource, AtoMx™ and their established GeoMx™, which has broader protein and RNA capability with low resolution.
  • Vizgen MERSCOPE™ – launched a protein co-detection kit in September 2022, allowing users to take full advantage of the subcellular hi-plex nature of the instrument while detecting up to five proteins.
  • Akoya Bioscience’s PhenoCycler®-Fusion – released in January 2022 and offers a high throughput workflow at sub-cellular resolution for 100+ markers, either RNA or protein biomarkers. It is one of the fastest single-cell spatial biology solutions, able to map a million cells in 10 minutes.
  • ACD Biotechne and Standard Biotools have created a workflow (May 2023) to combine the 12-plex RNAscope™ assay with the 40-plus protein Imaging Mass Cytometry™ assay, to create RNA and protein multiomics outputs.

Spatial transcriptomics – more targets, more resolution

New spatial transcriptomics tools are increasing the speed, capacity and scope of this technique. This provides researchers with a variety of options to meet their spatial needs. Whether they provide access to more cells, more targets to produce a higher-plex assay or a high resolution to pinpoint tiny molecules, here we highlight a few of the mRNA visualization technologies released in the last 24 months that expand the horizons of spatial biology:

  • 10x Genomics released the Xenium™ platform in December 2022, which is an in situ sequencing platform to compliment the in situ capture platform – Visium™. The Xenium™ can sequence the transcripts of 1000s of genes in a high throughput non-destructive manner, which allows proteomics and histopathology to be conducted on the same slide.
  • Vizgen MERSCOPE™ was released in January 2022 and commands an impressive capacity to visualize 10,000s of RNAs in situ with sub-cellular resolution and high sensitivity.
  • ACD Biotechne’s RNAscope™ recently passed a milestone of 40,000 probes (currently over 44,000) in its probe library, making it the broadest in situ technology with high sensitivity.
  • Curio Bioscience released the Curio Seeker in February 2023, based off of Slide-seq v2 technology, which enables large scale whole transcriptome spatial tissue mapping at single-cell resolution. This in situ barcoding approach does not require any specific hardware but simply requires the mounting of your tissue on the Curio Seeker Tile. It boasts a 10 micron resolution and no gaps between spots.
  • The Molecular Cartography™ platform, released by Resolve Biosciences in June 2022, is a multi-analyte, highly multiplexed spatial solution to visualise 100s of genes with subcellular resolution in a single run. The approach uses high-quality optics, which provides the highest resolution and can assess 100s of genes at once. Resolve have stated that future solutions will incorporate additional data layers of analysis (DNA, Protein and Metabolome).
  • The GenePS system was released by Spatial Genomics in May 2023 and is an automated instrument with capacity to panel over 1,000 genes at exceptional resolution using seqFISH technology. The analysis suite allows easy visualization of molecules from the tissue to the subcellular level as well as multiomics capacity.

Spatial proteomics solutions are coming in fast

While spatial proteomics still lags behind spatial transcriptomics for number, variety and capacity of solutions, advances were still aplenty in the last 24 months. Highlights include:

  • Navinci Diagnostic’s Naviniflex™ launched the Triflex Cell (November 2022) and Tissue (January 2023) solutions, allowing the visualization of protein-protein interactions and post-translation modifications, revealing the hidden interactions of proteins.
  • With the launch of Spyre™ antibody panel kits and the HORIZON™ analysis software (in March 2023), Lunaphore’s Comet became the first end-end spatial proteomic solution able to visualize up to 40 markers on one tissue sample in under a day. The plex-capacity is essentially unlimited, as tissue can be re-run with a new panel of markers. 
  • Canopy Biosciences® launched CellScape™ in March 2022, a benchtop imaging system using ChipCytometry™ technology. It can process 4 samples at once and is technically unlimited-plex due to iterative staining. This presents a rapid, fully automated multiplex spatial proteomics solution.
  • Standard Biotools released the Hyperion™ XTi Imaging system in April 2023. Relying on the Imaging Mass Cytometry™ technology, it both expands the number of samples and reduces the time taken to perform spatial proteomics. This tool detects 40-plus biomarkers with no autofluorescence interference.
  • Pixelgen Technologies® launched the first molecular pixelation kit (June 2023) to visualize spatial polarization and colocalization of cell surface proteins at high multiplex in 3D.

These instruments join more established instruments such as Rarecyte’s Orion™, Mitenyi Biotec’s MACSima™ Imaging platform and Ionpath’s MIBIscope™ in a suite of spatial proteomic solutions.

References

1.         Emmert-Buck, M.R. et al. Laser capture microdissection. Science 274, 998-1001 (1996).

2.         Lovatt, D. et al. Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue. Nat Methods 11, 190-6 (2014).

3.         Medaglia, C. et al. Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq. Science 358, 1622-1626 (2017).

4.         Boisset, J.C. et al. Mapping the physical network of cellular interactions. Nat Methods 15, 547-553 (2018).

5.         Zhang, L. et al. Clinical and translational values of spatial transcriptomics. Signal Transduction and Targeted Therapy 7, 111 (2022).

6.         Femino, A.M., Fay, F.S., Fogarty, K. & Singer, R.H. Visualization of single RNA transcripts in situ. Science 280, 585-590 (1998).

7.         Raj, A., van den Bogaard, P., Rifkin, S.A., van Oudenaarden, A. & Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat Methods 5, 877-9 (2008).

8.         Lubeck, E., Coskun, A.F., Zhiyentayev, T., Ahmad, M. & Cai, L. Single-cell in situ RNA profiling by sequential hybridization. Nat Methods 11, 360-1 (2014).

9.         Chen, K.H., Boettiger, A.N., Moffitt, J.R., Wang, S. & Zhuang, X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015).

10.       Eng, C.L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH. Nature 568, 235-239 (2019).

11.       Xia, C., Fan, J., Emanuel, G., Hao, J. & Zhuang, X. Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression. Proc Natl Acad Sci U S A 116, 19490-19499 (2019).

12.       Ke, R. et al. In situ sequencing for RNA analysis in preserved tissue and cells. Nat Methods 10, 857-60 (2013).

13.       Gyllborg, D. et al. Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue. Nucleic acids research 48, e112-e112 (2020).

14.       Tang, X. et al. Improved in situ sequencing for high-resolution targeted spatial transcriptomic analysis in tissue sections. Journal of Genetics and Genomics (2023).

15.       Lee, J.H. et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nature Protocols 10, 442-458 (2015).

16.       Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361(2018).

17.       Cheng, M. et al. Spatially resolved transcriptomics: A comprehensive review of their technological advances, applications, and challenges. Journal of Genetics and Genomics (2023).

18.       Ståhl, P.L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78-82 (2016).

19.       Rodriques, S.G. et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463-1467 (2019).

20.       Stickels, R.R. et al. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat Biotechnol 39, 313-319 (2021).

21.       Vickovic, S. et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat Methods 16, 987-990 (2019).

22.       Cho, C.-S. et al. Microscopic examination of spatial transcriptome using Seq-Scope. Cell 184, 3559-3572. e22 (2021).

23.       Fu, X. et al. Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain. Cell 185, 4621-4633. e17 (2022).

24.       Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777-1792. e21 (2022).

25.       Liu, Y., Enninful, A., Deng, Y. & Fan, R. Spatial transcriptome sequencing of FFPE tissues at the cellular level. bioRxiv, 2020.10. 13.338475 (2020).

26.       Srivatsan, S.R. et al. Embryo-scale, single-cell spatial transcriptomics. Science 373, 111-117 (2021).

27.       Russell, A.J.C. et al. Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics. bioRxiv, 2023.04.01.535228 (2023).