Spatial transcriptomics

in situ hybridization was developed in the late 1960's by Joseph G. Gall and Mary-Lou Pardue and saw major developments in the 1980's with single molecule FISH (smFISH) and 2010's with RNAscope, seqFISH, MERFISH and osmFISH, seqFISH+, and DNA microscopy. Spatial genomics as a technique, or now referred to as spatial transcriptomics, was initiated in 1990s by Michael Doyle (of Eolas), Maurice Pescitelli (of the University of Illinois at Chicago), Betsey Williams (of Harvard), and George Michaels (of George Mason University), as part of the Visible Embryo Project. Doyle and his co-investigators described a method called Spatial Analysis of Genomic Activity (SAGA). This spatial indexing concept was expanded upon in 2016 by Jonas Frisén, Joakim Lundeberg, Patrik Ståhl and their colleagues in Stockholm, Sweden. In 2019, the first commercial platforms for spatial transcriptomics were launched with GeoMx Digital Spatial Profiler (DSP) by Nanostring Technologies and Visium by 10X Genomics. In 2019, at the Broad Institute, the labs of Fei Chen and Evan Macosko developed Slide-seq, which used barcoded oligos on beads. == Applications ==

Defining the spatial distribution of mRNA molecules allows for the detection of cellular heterogeneity in tissues, tumours, and immune cells as well as determining the subcellular distribution of transcripts in various conditions. == Microdissection ==

Laser capture microdissection Laser capture microdissection enables capturing single cells without causing morphologic alterations. It exploits transparent ethylene vinyl acetate film apposed to the histological section and a low-power infrared laser beam. This method is carried out without laser capture microdissection. It was first used to determine genome-wide spatial patterns of gene expression in cryo-sliced Drosophila embryos. FFPE is a common sample type in the field of pathology and histology due to its long term preservation of tissue structure. 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. To do this, tissue sections on microscope slides are stained with fluorescent antibodies and nuclear dye to visualize the whole tissue section at single cell resolution on the DSP instrument. 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. GeoMx DSP can spatially resolve and measure human or mouse whole transcriptomes, more than 1200 proteins, or both RNA and protein in multiomic same slide protocols. TIVA Transcriptome in vivo analysis (TIVA) is a technique that enables capturing mRNA in live single cells in intact live tissue sections. It uses a photoactivatable tag. It is also based on tissue cryosectioning with further RNA sequencing of individual sections, yielding genome-wide expression data and preserving spatial information. As the positional identity of each cell is recorded during the LCM procedure, the transcriptome of each cell after RNA sequencing of the corresponding cDNA library can be inferred to the position where it was isolated from. interneurons, dopamine neurons, and chondrocytes. Geo-seq 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 workflow involves removal and cryosectioning of tissue followed by laser capture microdissection. The extracted tissue is then lysed, and the RNA is purified and reverse transcribed into a cDNA library. The cells bound by the fluorescent marker are photoactivated, dissociated and sorted via fluorescence-activated cell sorting. Initial mild digestion steps preserve small interacting structures that are recorded prior to continued digestion. The clustered cells can be mapped to physical interactions based on the interacting structures prior to the micro digestions. While the throughput of this technique is relatively low it provides information on physical interaction between cells to the dataset. == Fluorescent in situ hybridization ==

CosMx The CosMx Spatial Molecular Imager (NanoString Technologies) is the first high-plex in situ analysis platform to provide spatial multiomics with formalin-fixed paraffin-embedded (FFPE) and fresh frozen (FF) tissue samples at cellular and subcellular resolution. It enables rapid quantification and visualization of up to the whole transcriptome 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. smFISH One of the first techniques able to achieve spatially resolved RNA profiling of individual cells was single-molecule fluorescent in situ hybridization (smFISH). 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. by substituting the above described probes with those of 20 bp length, coupled to only one fluorophore and complementary in tandem to an mRNA sequence of interest, meaning that those would collectively bind to the targeted mRNA. One such probe itself wouldn't produce a strong signal, but the cumulative fluorescence of the congregated probes would show a bright spot. Since single misbound probes are unlikely to co-localize, false-positive signals in this method are limited. It allows for the visualization of single RNA in a variety of cellular types. Most steps of RNAScope are similar to the classic ISH protocol. This method is carried out in multiple rounds; each of them includes fluorescent probe hybridization, imaging, and consecutive probe stripping. 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. This approach can measure 140 RNA species at a time using an encoding scheme that both detects and corrects errors. In this method, multiple readout probes are bound with the target region of mRNA. In osmFISH, transcripts are visualized, and an image is acquired before the probe is stripped and a new transcript is visualized with a different fluorescent probe. It supports both single-molecule and multiplexed readouts. It also includes a turn-key computational analysis pipeline. seqFISH+ SeqFISH+ resolved optical issues related to spatial crowding by subsequent rounds of fluorescence. First, a primary probe anneals to targeted mRNA and then subsequent probes bind to flanking regions of the primary probe resulting in a unique barcode. First, cells are fixed and cDNA is synthesized. Randomized nucleotides then tag target cDNAs in situ, providing unique labels for each molecule. Tagged transcripts are amplified in the second in situ reaction, retrieved copies are concatenated, and new randomized nucleotides are added. Each consecutive concatenation event is labeled, yielding unique event identifiers. 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. == in situ sequencing ==

ISS using padlock probes The ISS padlock method is based on padlock probing, rolling-circle amplification (RCA), and sequencing by ligation chemistry. Within intact tissue sections, mRNA is reversely transcribed to cDNA, which is followed by mRNA degradation by RNase H. like ISS padlock, is a method that uses reverse transcription, rolling-circle amplification, and sequencing by ligation techniques. Similar to other padlock probe based methods amplification occurs via rolling circle amplification. The DNA amplicons are chemically modified and embedded into a polymerized hydrogel within the cell. Captured RNA can then be sequenced in situ providing three dimensional locations of the mRNA within each cell. == in situ capture ==

Stereo-seq(STOmics) STOmics is a pioneer in advancing spatially-resolved transcriptomic analysis through its proprietary SpaTial Enhanced REsolution Omics-Sequencing (Stereo-seq) technology. It combines in situ capture with DNB-seq, DNB sequencing is based on lithographically etched chips (patterned arrays) for in situ sequencing. Unlike other um-level in situ capture technologies, standard DNB chips have spots with approximately 220 nm diameter and a center-to-center distance of 500 nm, providing up to 20000 spots for tissue RNA capture per 10mm linear distance, or 4×108 spots per 1 cm2. Therefore, STOmics can show higher resolution and wider field of view than other in situ capture technologies. Spatial transcriptomics The first widely-adopted method was described by Ståhl et al. in a landmark 2016 paper in Science, as the foundation for the 10X Visium platform. Slide-seq Slide-seq relies on the attachment of RNA binding, DNA-barcoded micro beads to a rubber coated glass coverslip. The method utilizes the APEX2 gene, expressed in live cells which are incubated with biotin-phenol and hydrogen peroxide. This is accomplished by sequential hybridization to the barcode oligonucleotide sequence of each bead. Takara Bio SEEKER The assay is similar in concept to the 10X Genomics Visium but has a higher density of spots. Contrary to the 10X Genomics Visium HD, which uses RNA probes that have to be pre-defined for species like human or mouse, SEEKER has a similar density and resolution, but will assay any fresh frozen tissue sample, using poly-A adaptation of all the mRNAs in the sample. == in silico construction ==

Reconstruction using ISH in silico Spatial Reconstruction with ISH implies computational spatial reconstruction of cells' locations according to their expression profiles. They co-analyze single-cell transcriptomics and available ISH-based gene expression atlases of the same cell type. The Distmap algorithm generates a virtual 3D model of the tissue of interest using the transcriptomes of sequenced cells and said reference atlas. Essentially, this algorithm takes data generated from single cells in a dissociated tissue and is able to map individual transcripts to where the cell type exists in the tissue using virtual in situ hybridization. == See also ==