Spatial transcriptomics
[1] The historical precursor to spatial transcriptomics is in situ hybridization,[2] where the modernized omics terminology refers to the measurement of all the mRNA in a cell rather than select RNA targets.
[7] Microdisecction techniques were first developed in the late 1990's (Laser Capture Microdissection) and combined with RNA-seq profiling in 2013 in Michael Eisen's lab using fruit fly embryos.
This method had difficulties in obtaining high-quality RNA-seq libraries from every section due to the material loss as a result of the small amount of total RNA in each slice.
The GeoMx DSP technology centers around a user's ability to perform "microdissection" based on histological structures, functional compartments, and cell types.
However, unlike LCM, gene expression profiling is performed in a nondestructive manner through light, due to a UV-photocleavable barcode engineered into the in situ hybridization probe.
[22] Selection of region of interests occurs through automated segmentation on flurorescent signal intensities or drawing tools, including geometric or free hand shapes.
[22] Each region of interest is precisely exposed to UV light and the barcodes are cleaved, collected, and used to identify RNAs or proteins present in the tissue.
[23] The defined regions of interest can vary in size, between ten and six hundred micrometers, allowing a wide variety of structures and cells in the histological sample.
[27] Then, streptavidin capture of the biotin group is used to extract poly(A)-tailed mRNA molecules bound to unblocked tags, after which these mRNAs are analyzed by RNA sequencing.
[28] It is also based on tissue cryosectioning with further RNA sequencing of individual sections, yielding genome-wide expression data and preserving spatial information.
[4] LCM-seq utilizes laser capture microdissection (LCM) coupled with Smart-Seq2 RNA sequencing and is applicable down to the single cell level and can even be used on partially degraded tissues.
The workflow includes cryosectioning of tissues followed by laser capture microdissection, where cells are collected directly into lysis buffer and cDNA is generated without the need for RNA isolation, which both simplifies the experimental procedures as well as lowers technical noise.
[34] Geo-seq is a method that utilizes both laser capture microdissection and single-cell RNA sequencing procedures to determine the spatial distribution of the transcriptome in tissue areas approximately ten cells in size.
The NICHE-seq method uses photoactivatable fluorescent markers and two-photon laser scanning microscopy to provide spatial data to the transcriptome generated.
It enables rapid quantification and visualization of up to whole transcriptome[39] and 64 validated protein analytes and is the flexible, spatial single-cell imaging platform for cell atlasing, tissue phenotyping, cell-cell interactions, cellular processes, and biomarker discovery.
[40] One of the first techniques able to achieve spatially resolved RNA profiling of individual cells was single-molecule fluorescent in situ hybridization (smFISH).
[41] It implemented short (50 base pairs) oligonucleotide probes conjugated with 5 fluorophores which could bind to a specific transcript yielding bright spots in the sample.
[4][43] Sequential fluorescence in situ hybridization (seqFISH) is another method that provides identification of mRNA directly in single cells with preservation of their spatial context.
[47] Multiplexed Error-Robust FISH (MERFISH) greatly increases the number of RNA species that can be simultaneously imaged in single cells employing binary code gene labeling in multiple rounds of hybridization.
Single-molecule RNA detection at depth by hybridization chain reaction (smHCR) is an advanced seqFISH technique that can overcome typical complication of autofluorescent background in thick and opaque tissue samples.
[49] In multiplexed studies, the same two-stage protocol described above is used: all probe sets are introduced simultaneously, just as all HCR amplifiers are; spectrally distinct fluorophores are used for further imaging.
[51] Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) optimizes and builds on ExFISH with improved detection accuracy and robust multi-round processing across samples thicker (300 μm) than what was previously possible.
[4] DNA microscopy is a distinct imaging method for optics-free mapping of molecules’ positions with simultaneous preservation of sequencing data carried out in several consecutive in situ reactions.
[55] Algorithm then generates images of the original transcripts based on decoded molecular proximities from the obtained concatenated sequences, while target's single nucleotide information is being recorded as well.
[4] Positions of both product of reverse transcription and clonally amplified RCPs are maintained via cross-linkage to cellular matrix components mentioned previously, creating a 3D in situ RNA-seq library within the cell.
This methodology relies on diffusion of mRNA from a fresh frozen tissue section for capture of the polyadenylated mRNAs via hybridization to oligo(dT) sequence attached to a glass slide.
[64] As a result, spatially marked complementary DNA (cDNA) is synthesized, providing information about gene expression in the exact location of the tissue section.
[67] High-Definition Spatial Transcriptomics (HDST) begins with decoding the location of mRNA capture beads in wells on a glass slide.
[70] Mapping the transcriptome using the Distmap algorithm requires high-throughput single cell sequencing and an existing in situ hybridization atlas for the tissue of interest.
[4][72] The transcriptomes can be clustered into cell types using t-distributed stochastic neighbour embedding and mapped to the 3D model using virtual in situ hybridization.
