It is essential to comprehend normal growth and development, and disease pathology to understand the link between cells and their relative positions within a tissue. Space-based transcriptomics is a revolutionary molecular profiling technique that enables scientists to map a tissue sample gene activity and determine the activity’s location. This technique has already led to new findings that assist scientists in gaining a deeper knowledge of biological mechanisms and illness.
Why Space-Based Transcriptomics?
Recent technical advancements have allowed scientists to go beyond merely sequencing ‘omes. Lundeberg, Frisen, and Stahl pioneered spatially resolved transcriptomics at the KHL Royal Institute of Technology in Sweden in 2016. This method added positional context to gene expression data for many cells. It is currently possible to analyze hundreds of thousands of genes in a small slice of tissue. Spatial information concerning molecular traits of these genes helps explain the differences between cells and gives important clues about the causes and effects of certain diseases.
Emerging approaches for genome-wide spatial transcriptomics have the potential to generate comprehensive molecular maps. They adopt an on-slide complementary DNA synthesis technique to capture gene expression patterns in intact tissue. This ensures that data from critical factors is maintained. Compared to the prior generation of spatially resolved transcriptomics technologies, 10x Genomics’ new Visium platform boasts a fivefold increase in resolution.
By retaining the spatial interactions between cells, the Visium Spatial Gene Expression technique helps researchers to decipher the biological architecture of normal and diseased tissues by providing insights not only at the level of the individual cell but also at the tissue level. Researchers can now trace the spatiotemporal expression of the entire transcriptome across numerous cells in complicated tissue samples.
Although currently, spatial analysis doesn’t routinely offer transcriptome-wide data, the discipline is advancing. One of the upcoming hot subjects is anticipated to be “spatial single-cell transcriptomics,” which will be very valuable for investigating various diseases, which frequently begin in a single cell and propagate spatially.
How is Spatially Resolved Transcriptomic Implemented?
A typical transcriptomics process starts with tissue section isolation and staining. The portion is then juxtaposed with a slide containing RNA-binding capture probes. The attached RNA is barcoded and then used to synthesize complementary DNA sequenced. The data is then visualized to determine where the target genes are expressed in the tissue slice.
Step-by-step: process for spatial gene expression
- Permeabilization of cells.
- The mRNA is captured and bound by a dense carpet of specialized probes on the glass slide surface. Each capture probe has a spatial barcode that is specific to a certain location on the slide.
- The fluorescent labeling of mRNA generates a footprint that matches the tissue’s shape.
- The attached tissue serves as a model for a reverse transcription step, which produces a complementary DNA library.
- The complementary DNA, containing spatial barcodes, is excised from the slide’s surface and collected for routine sequencing.
- The barcoded capture probes then link the generated RNA sequences back to their original positions on the slide, a process known as ‘de-multiplexing.’
- The RNA data is linked with a high-resolution microscope imaging of the tissue segment to map it back to its origin.
- The spatial dimension of mRNA expression can then be visualized.
Techniques Used in Transcriptomics
Spatial gene expression involves four methods. Note that not all spatial approaches yield single-cell resolution or transcriptome data.
Microdissection separates regions of interest within a sample through lasering or cutting. RNA is extracted, processed, and sequenced from tissue samples.
In situ hybridization
Fluorescent in situ hybridization visualizes RNA at its original cell site. This doesn’t involve sequencing and doesn’t offer transcriptome data. However, these methods can typically attain great resolution.
In situ sequencing
In situ sequencing is RNA sequencing in a tissue environment. Fluorescent probes show sequenced RNAs. This approach can’t analyze the entire transcriptome.
In situ capturing
In situ capturing captures and barcode transcripts in tissue. Then sequencing is done outside of the tissue. Transcriptomics data are overlaid on tissue pictures.
In silico construction
These methods digitally map single sequenced cells back into space with minimal or no prior knowledge regarding the position of the sequenced cells. Therefore, these approaches are suitable for single-cell RNA sequencing.
Spatial Gene Expression Problems
- identifying and verifying the appropriate disease biomarkers
- Combining sequencing information with imaging readings
- Visualizing the phenotype of a slice of a tissue
- Catching the cell state precisely
- Identifying the function of a cell in the microenvironment of a tissue
To solve some of these problems, it is vital to increase the number of assays and analytical techniques available to researchers while ensuring that the infrastructures remain cost-effective, objective, and precise. In addition, high resolution and vast information assessed in a spatial context are required to appropriately permit the comparison of datasets collected by different labs at different time points.