Singapore, October 2024 - We are thrilled to announce the latest performance upgrade of M20 Genomics' M20 Spatial technology, a revolutionary spatial transcriptomics technology that offers comprehensive spatial transcriptomic data across multiple species and sample types. This upgrade significantly enhances the technology's sensitivity, resolution and data interrogation capabilities, providing researchers a more powerful tool to investigate spatial cell interactions and molecular mechanisms in both research and clinical applications.
Unmatched Flexibility in Spatial Transcriptomics
Unveiled in October 2023, the M20 Spatial stands as the world’s first technology for whole-sample spatial transcriptomics based on random priming (https://www.m20genomics.com/1085.html). This groundbreaking technology accommodates a wide range of sample types, including fresh, frozen, and formalin-fixed paraffin-embedded (FFPE) tissues. By harnessing random priming, M20 Spatial captures spatial RNA with unbiased full-length transcript coverage, empowering researchers to delve into complete transcriptomes across diverse species and tissue types.
M20 Spatial Workflow
Compared to traditional spatial transcriptomics technologies, M20 Spatial heralds a new era of innovation, achieving remarkable breakthroughs in applicable species, sample types, RNA capture methods, and comprehensive full-length transcript coverage. These advancements not only elevate the technology’s significance in research and clinical applications but also vastly expand the horizons of information and insights available through spatial transcriptomics research.
Today, we are excited to announce the latest technological upgrade to M20 Spatial. We have introduced a in house-developed chip and optimized the technology across multiple dimensions. This upgrade delivers key improvements in gene detection sensitivity, resolution, and data analysis while maintaining the technology’s hallmark features of multi-species compatibility, full-sample, full-transcriptome, and full-length transcript coverage. These enhancements provide more sensitive and precise spatial transcriptome data, broadening the technology’s versatility for diverse research applications and facilitating cutting-edge discoveries in life sciences and biomedical research.
Key Technological Advancements
The recent updates to the M20 Spatial technology introduce three major advancements that build upon its core strengths:
The upgraded M20 Spatial technology exhibits a substantial increase in gene detection for FFPE samples. With a 50 µm spot size, the median gene count now exceeds 5,000, offering richer datasets that can unveil spatial cellular relationships and molecular mechanisms.
The technology now includes a high-resolution chip, developed in-house, that elevates spatial resolution to 15 µm. This improvement applies to all sample types, including FFPE, and enables the capture of full-transcriptome information with greater precision, providing more comprehensive data for advanced spatial analysis.
M20 Spatial data can now be seamlessly integrated with single-cell transcriptome platform, which allows for more precise spatial cell-type annotations, providing deeper insights into cellular heterogeneity and spatial molecular mechanisms.
Superior Performance: A Case Study
To demonstrate the enhanced capabilities of the M20 Spatial, we evaluated its performance using FFPE samples from various tissues. Below, we present the data from mouse embryo and olfactory bulb, which highlighted several significant advancements:
1. Enhanced Sensitivity for Superior Gene Detection
In the mouse embryo FFPE sample, M20 Spatial achieved high transcriptome capture sensitivity, detecting a total of 40,276 genes across 2,389 spots with a median UMI counts of 17,901 and 5,360 genes per spot (50 µm) (Figure 1). This performance is on par with the elevated levels observed in conventional spatial transcriptomics technologies utilizing fresh and frozen samples. Moreover, as M20 Spatial captures the full-length transcriptome, the total gene count markedly exceeds that of spatial transcriptomics platforms relying on polyA capture.
H&E Stain UMI Count Gene Number
Figure 1. Left: H&E staining image of mouse embryo FFPE sample. Middle: Spatial UMI count map. Right: Spatial gene count map.
The M20 Spatial chip used here measures 6.4mm x 6.4mm, and a larger size chip will be available in near future.
2. Elevated Resolution for Unmatched Spatial Accuracy
At the new 15 µm resolution, M20 Spatial maintained exceptional performance. In the olfactory bulb FFPE sample, over 40,276 genes were detected across 4,418 spots, with a median of 4,440 UMIs and 1,171 genes per spot (15 µm) (Figure 2). This performance ranks among the highest levels achieved in existing spatial transcriptomics technologies, while the total gene count significantly exceeds that of other spatial transcriptomics platforms based on polyA capture.
H&E Stain UMI Count Gene Number
Figure 2. Left: H&E staining image of mouse olfactory bulb FFPE sample. Middle: Spatial UMI count map. Right: Spatial gene count map.
At higher resolutions, M20 Spatial offers more precise and comprehensive data, facilitating deeper analysis and exploration of the data.
3. Comprehensive Unbiased Full-Length Transcript Coverage
Leveraging random priming, M20 Spatial achieves unbiased full-length coverage of gene body sequences in spatial transcriptomics without the need for third-generation sequencing. This feature remains consistent at both 50 µm (Figure 3) and 15 µm (Figure 4) resolutions, ensuring comprehensive and accurate transcriptomic data.
Figure 3. Read coverage along the gene body at 50 µm resolution in mouse embryo FFPE sample.
Figure 4. Read coverage along the gene body at 15 µm resolution in mouse olfactory bulb FFPE sample.
4. Advanced Capture of lncRNA and Non-Coding RNA
Since its initial launch, M20 Spatial has revolutionized spatial transcriptomics by overcoming the limitation of only detecting coding regions, making it the first to capture the full transcriptome in spatial RNA sequencing. This upgrade continues to lead the field, enabling the detection of both coding and non-coding RNAs at various resolutions.
Across all resolutions, M20 Spatial demonstrates the capability to capture a diverse array of RNA molecules, with mRNA constituting the highest proportion. Additionally, it effectively detects a variety of non-coding RNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) (Figures 5, 6).
Figure 5. Detected gene number of different types of RNA captured by M20 Spatial in mouse embryo FFPE sample.
Figure 6. Detected gene number of different types of RNA captured by M20 Spatial in mouse olfactory bulb FFPE sample.
Among these, lncRNAs represent the largest proportion of non-coding RNAs. LncRNAs play a pivotal role in cellular growth, disease progression, and immune regulation, making them a prominent focus of current research. At all resolutions, M20 Spatial is capable of capturing lncRNAs from various spatial locations within the tissue (Figures 7, 8), with the detected lncRNAs representing approximately 60% to 80% of the total lncRNA species in mice.
Figure 7. The spatial distribution of lncRNA detected in mouse embryo FFPE sample.
Figure 8. The spatial distribution of lncRNA detected in mouse olfactory bulb FFPE sample.
Interestingly, non-coding RNA expression also exhibits spatial specificity within tissues. Even clustering based solely on non-coding RNA or just lncRNA data reflects a certain degree of tissue spatial structure (Figure 9, 10), underscoring the potential of non-coding RNA in spatial transcriptomics.
Figure 9. Spatial mapping based on lncRNA information in mouse embryo FFPE sample.
Figure 10. Spatial mapping based on lncRNA information in mouse olfactory bulb FFPE sample.
The capability to concurrently capture both non-coding RNAs and mRNAs equips M20 Spatial to deliver more comprehensive and in-depth molecular insights. We are committed to the continuous optimization of this technology to further improve data acquisition for miRNAs and other important RNA species.
5. Integrated Single-Cell Profiling: Achieving Precision in Spatial and Single-Cell Analysis
By integrating spatial and single-cell transcriptomic data, M20 Spatial provides an unprecedented level of precision in cell-type annotation within its spatial context.
For instance, in the mouse embryo FFPE sample (50 µm resolution) and olfactory bulb FFPE sample (15 µm resolution), M20 Spatial data alone can identify multiple cell subpopulations based on transcriptomic differences. High-resolution spatial mapping shows that these subpopulations correspond to distinct tissue origins (Figure 11,12).
Figure 11. Unsupervised cell clustering (upper left), spatial mapping (upper right) and marker expression in each cluster (lower panel) in mouse embryo FFPE sample.
Figure 12. Unsupervised cell clustering (upper left), spatial mapping (upper right) and marker expression in each cluster (lower panel) in mouse olfactory bulb FFPE sample.
Moreover, M20 Spatial data can be combined with single-cell transcriptomics data for more accurate spatial heterogeneity analysis. This integration further clarifies the precise spatial distribution of different cell types, offering deeper insights into tissue microenvironments (Figure 13,14).
Figure 13. Spatial distribution of characteristic cell type in mouse embryo FFPE sample based on the integration of spatial transcriptome and GEO mouse embryo single-cell transcriptome dataset GSE1199451.
Figure 14. Spatial distribution of characteristic cell type in mouse olfactory bulb FFPE sample based on the integration of spatial transcriptome and public mouse nervous system single-cell transcriptome dataset SRP1359602. (The public dataset is reannotated with MapMyCells 3)
Looking Ahead: Future Prospects
The upgraded M20 Spatial technology, with its improved resolution, gene detection sensitivity, and integrated single-cell profiling capabilities, offers an advanced toolset for dissecting cellular heterogeneity within tissue environments. This technology is poised to support deeper exploration of the spatial molecular mechanisms underlying biological processes and diseases. We are eager to collaborate with the research community to push the boundaries of spatial transcriptomics, and we invite you to stay tuned for more updates.
Unlock new dimensions in spatial transcriptomics with M20 Spatial. Contact us at info@m20genomics.com to learn more details.
Reference:
1. Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
2. Zeisel, A. et al. Molecular Architecture of the Mouse Nervous System. Cell 174, 999-1014.e22 (2018).
3. Allen Institute for Brain Science. MapMyCells (2023). Available from https://knowledge.brain-map.org/mapmycells/process