How to Choose Spatial Transcriptomic Technologies?
InquiryBiological tissues, encompassing humans, animals, and plants, are intricate systems composed of potentially trillions of cells exhibiting variations in type, time, and space. Despite this complexity, these cells coordinate to establish unique microenvironments crucial for organ function and information processing, ultimately determining cellular identity. The diverse array of cells, coupled with developmental and regional disparities, contributes to the transcriptional heterogeneity observed in organs.
Choosing the right spatial transcriptome technology is a crucial yet challenging task. To aid in this decision-making process, we have compiled a set of techniques to guide you in selecting the most appropriate methods.
What Are the Techniques for Spatial Transcriptomics?
While single-cell RNA sequencing (scRNA-seq) has made significant strides in inferring cell types and differentiation trajectories, particularly in developmental biology studies, it grapples with the challenge of preserving spatial information once cells are dissociated in suspension. Recent advancements in high-throughput spatial transcriptome technology have addressed this issue by propelling the study of the transcriptome to a third stage. This technology enables simultaneous acquisition of gene expression profiles and spatial distribution locations at the tissue in situ level, thereby enhancing the understanding of real gene expression in cells at the spatial level.
Table 1 Overview of Spatial Transcriptomic Technologies
| Technique | Principle | Advantages | Considerations |
|---|---|---|---|
| In Situ Sequencing | Performs sequencing directly within tissue sections for spatially resolved transcriptomics | High spatial resolution; precise localization of transcripts | Technically challenging; may require specialized equipment |
| Slide-seq | Utilizes spatially barcoded beads on a tissue section for high-throughput spatial transcriptomics | Improved sensitivity and throughput | Relatively new; evolving methodologies |
| SeqFISH (Sequential Fluorescence In Situ Hybridization) | Performs sequential rounds of fluorescence in situ hybridization for multiplexed imaging | High multiplexing capability; compatible with standard fluorescence microscopes | Time-consuming due to sequential hybridization steps |
| CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) | Combines transcriptomic and proteomic information using antibodies against cell surface proteins | Integrates transcriptomic and proteomic data; enables cell type identification | Limited to cell surface proteins |
| RNA-scope | Employs dual "Z" probe design and signal amplification for high specificity and single-molecule detection | High specificity and sensitivity; single-cell RNA expression data | Ideal for single-cell level; may not capture intracellular proteins |
| 10X Visium | Uses specific primers with spatial barcodes to capture RNA at precise tissue locations in situ | Enables in situ capture of transcripts followed by off-site sequencing; unbiased analysis of the complete transcriptome | Technical limitations of microdissection; lower resolution; difficulty in maintaining RNA quality and cell integrity; time-consuming and high demand for operating techniques |
CD Genomics specializes in spatial transcriptomics technology, delivering high-quality solutions for life sciences. We help researchers simultaneously analyze the sequence and location information of RNA in fresh or FFPE tissue sections. With our technology services, researchers can obtain location-specific transcriptional information of tissues, which provides richer and more effective data support for research and diagnosis.
Spatial Transcriptome Technology Leveraging In Situ Capture
In situ capture technology represents a cutting-edge method employing specific primers with spatial barcodes to capture RNA at precise tissue locations in situ. This technique involves sequencing the captured RNA in situ and utilizing algorithms for the visualization and analysis of spatial barcodes carried on the RNA. The outcome is the construction of a spatiotemporal transcriptional map of the tissue, providing valuable insights into gene expression patterns.
This technology allows for the in situ capture of transcripts, followed by off-site sequencing. Notably, it overcomes the typical limitations associated with direct in situ visualization or in situ sequencing, enabling an unbiased analysis of the complete transcriptome.
One notable implementation of in situ capture technology is found in 10x Genomics' Visium. The Visium platform features over a thousand spots on the slide, each designated as a capture region with a distinct spatial barcode. After capturing mRNA in situ and reverse transcribing it from tissue sections, the resulting cDNA-mRNA complexes undergo extraction for library preparation and next-generation sequencing (NGS) readout. Through a computational and analytical process, the spatial barcodes are then mapped back onto the tissue image, providing a spatially resolved representation of the entire transcriptome. Several other technologies, including DBiT-seq, Slide-Seq, and HDST, follow a similar approach, emphasizing the versatility and applicability of this innovative spatial transcriptome technology.
Please read our article: Introduction to 10x Spatial Transcriptomics for more information about 10x Visium technology.
Spatial Transcriptome Technology Based on In Situ Hybridization
A technique, single-molecule fluorescence in situ hybridization (smFISH), allowed the binding of a limited number of fluorescent probes to a fixed sample, detecting only a small set of mRNA types. Subsequently, seqFISH (sequential fluorescence in situ hybridization) emerged, enabling the visualization of multiple mRNA types. SeqFISH involves iterative rounds of hybridization, imaging, and probe stripping across the entire tissue RNA. Each hybridization round generates binary coding information (0 or 1), forming a multi-digit barcode that is decoded to identify individual RNAs, facilitating the simultaneous detection of numerous genes in a single run.
In situ hybridization is a method employing a labeled probe (e.g., fluorescent or antigen-antibody probe) to selectively hybridize with target transcripts within their native cellular environment for visualization.
Technologies like MERFISH (multiplexed error-robust fluorescence in situ hybridization), seqFISH (smHCR), and seqFISH+ have evolved from seqFISH, enhancing cell throughput, resolution, and operational efficiency.
In contrast to barcode-based approaches, non-barcoded techniques have been developed. RNA-scope, employing a dual "Z" probe design and signal amplification system, achieves RNA in situ hybridization with high specificity, single-molecule sensitivity, and an impressive signal-to-noise ratio. This technique allows simultaneous quantification of multiple RNAs at the single-cell level, providing comprehensive histomorphometric information while obtaining single-copy RNA expression data in individual cells. It stands out as an ideal research tool in the NGS and microarray era.
Challenges and Considerations
- Optical Pathway Overlaps: Grasp the technical challenge of overlapping optical pathways caused by fluorescent signal fragments emitted by transcripts.
- False-Positive Concerns: Recognize the impact of false-positive results due to background fluorescent signals from tissue and cell samples on experimental accuracy and confidence.
Application Areas
- Research Domains: Explore diverse research domains benefiting from spatial transcriptomics, including developmental biology, neuroscience, and disease pathology.
- Integration with Other Technologies: Understand how spatial transcriptome technology complements and extends the capabilities of other molecular biology techniques.
Spatial Transcriptome Technology through Microanatomical Gene Expression
Spatial transcriptome technology, rooted in microanatomical gene expression, employs innovative methods to precisely dissect and capture cells at specific spatial locations within tissues. This approach facilitates subsequent gene expression profiling, enabling a nuanced understanding of microanatomical structures and localized gene expression information.
The pioneering technique, laser-capture microdissection (LCM), emerged as an early method utilizing a laser to meticulously cut cells of interest under a microscope for subsequent gene expression analysis. Researchers later expanded this concept, performing RNA-seq on individual frozen sections to obtain regionalized transcriptome data. Building upon this foundation, tomo-seq (RNA tomo-graphy) further refined the cDNA library preparation method, enhancing RNA quantification and spatial resolution. Transcriptome in vivo analysis (TIVA) then introduced spatiotemporal transcriptomics for live cells, utilizing a cell-penetrating peptide to carry the TIVA tag into cells and capturing mRNA under laser activation for subsequent RNA-seq.
Geo-seq (geographical position sequencing), another technology based on LCM, integrates emerging single-cell RNA-seq capabilities to target specific regions for transcriptome sequencing. Additionally, two other spatial transcriptomic technologies, NICHE-seq and proximiD, focus on specific ecological niches.
Microanatomical gene expression-based spatial transcriptome technologies offer the ability to concentrate on microanatomical structures and gene expression within specific regions through physical dissection or optical methods for labeling. The former, known for its simplicity and compatibility, is widely employed. In contrast, the latter introduces real-time study capabilities for live cells and tissue sections. While this lower-resolution strategy covers more tissue regions, it faces challenges such as lower resolution due to microdissection limitations.
Technical constraints, including the difficulty in maintaining RNA quality and cell integrity during laser capture, the time-consuming nature of microdissection, and high operational demands, impact the throughput and capacity of this technology. Despite its capability to cover extensive tissue regions, achieving a comprehensive tissue image remains challenging. This balance between coverage and resolution underscores the ongoing complexities in spatial transcriptome technology based on microanatomical gene expression.
Spatial Transcriptome Technology Harnessing In Situ Sequencing
In situ sequencing technology is a groundbreaking method that enables the capture of transcripts at subcellular resolution within the natural organizational environment of cells. This technique utilizes micron- or nano-sized DNA spheres to amplify signals for subsequent sequencing. However, inherent spatial constraints within cells limit the simultaneous detection of only a limited number of transcripts. To overcome these limitations, spatial transcriptome technologies based on in situ sequencing employ diverse strategies, categorized as targeted and untargeted.
Representative examples of targeted strategies include STARmap and FISSEQ. STARmap, short for spatially-resolved transcript amplicon readout mapping, employs a lock probe featuring a barcode to directly target the RNA of interest. This method involves adding a second barcode to the target RNA, introducing a second primer to replace the reverse transcription step, and ultimately generating single-stranded DNA nanorods through rolling circle amplification (RCA) for subsequent signal readout.
On the other hand, fluorescent in situ sequencing (FISSEQ) stands out as the first non-targeted in situ sequencing technology. FISSEQ utilizes a combination of conventional and modified amine bases along with labeled random hexamers as reverse transcription primers. The process involves cyclization of all obtained cDNAs through single-stranded DNA cyclase, cross-linking the synthesized cDNAs with their cellular environment, and cross-linking the RCA-generated RNA-cDNA hybrids to the cellular matrix, culminating in signal readout.
These spatial transcriptome technologies not only offer insights into the targeted profiling of specific transcripts (as exemplified by STARmap) but also enable a broader, untargeted exploration of the transcriptome (as demonstrated by FISSEQ). As the field continues to evolve, innovations in in situ sequencing methodologies hold great promise for unraveling the intricacies of spatial gene expression at the subcellular level.
