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Spatial transcriptomics: gene expression, in three dimensions

When DNA or scRNA analyses are performed at the individual cell level, researchers tend to follow a series of key steps. The first one, the isolation and classification of the cells of interest, requires the extraction of the various cell types and destruction, in most cases, of their local environment. The second and third stages consist of preparing libraries and in later sequencing, fundamental to obtain gene expression information.

In the resulting data, however, significant details on the context in which each cell is situated are lacking, such as their spatial environment and position, as highlighted in a publication in Genome Biology.  “Since the physical location of a cell within the tissue is a key determinant of its molecular identity, tissue-level systems biology requires obtaining whole-genome measurements while accounting for the spatial localization of cells,” states another recent study published in Current Opinion in Biotechnology. The need for a more complete picture of the cells and the environment they live in has spurred the development of new methods in transcriptomics, with the aim of capturing three-dimensional information that may be useful.

Cell culture in a Petri dish
Source: kaibara87 (Wikimedia)

FISSEQ, pinpointing and reading thousands of mRNAs at once

One of the most striking techniques in spatial transcriptomics is called Fluorescent In Situ Sequencing (FISSEQ). This method lets researchers locate thousands of mRNAs (and other types of RNA) at once in intact cells, while also determining the sequence of bases that identify each of them. In other words, this technology, created at Harvard—and later marketed by ReadCoor—allows scientists to read the sequences of the mRNAs viewing their three-dimensional coordinates at the same time.

“By looking comprehensively at gene expression within cells, we can now spot numerous important differences in complex tissues like the brain that are invisible today. This will help us understand like never before how tissues develop and function in health and disease,” states George Church, of the Wyss Institute, forerunner of other revolutionary tools such as the genome editing. The protocol designed by his team, published in Nature Methods makes it possible, for example, to complete the libraries and sequencing in two weeks, while the analysis of images takes approximately two more days.

Source: Yakuzakorat (Wikimedia)

For example, a research project by Church's group used the FISSEQ technique to analyze the spatial organization of the gene expression in cultured fibroblasts. Their results, published in Science, proved it was possible to detect over 8,000 RNAs across cultured fibroblasts by reading 27 bases of each transcript. Nonetheless, this technique also faces certain limitations. as suggested in a recent study by a Karolinska Institute and Allen Institute for Brain Science researcher, the method, “has not been demonstrated on tissue sections, and currently, the number of transcripts detected in each cell is low. It is estimated that a maximum of ~90 products fit in the optical space of a cell, limiting the total number of reads per cell,” state the authors of the study, also published in Science.


The future of spatial transcriptomics

FISSEQ is not the only method designed to simultaneously study gene expression and spatial organization. Another possible option is the Single-molecule RNA Fluorescence in situ Hybridization, also known as smFISH, which visualizes individual RNA molecules using multiple fluorescently-labeled oligonucleotide probes specific to the target RNA, already successfully used in animal models such as C.elegans. The technique known as seqFISH, which identifies the gene expression profiles of hundreds of genes at the single-cell level while offering a map of spatial heterogeneity, has also enabled the study of part of the brain such as the hippocampus, as revealed in a study published in Neuron.

There is yet another possible technique, known as MERFISH. The technology, disseminated by the team of Chen in Science is good for determining the identity, the copy numbers, and locations of thousands of RNA molecules inside a single cell, as they wrote in an article published in Human Mutation. The last notable technique in the emerging field of spatial transcriptomics is called TIVA, an acronym that stands for “Transcriptome in vivo analysis”. This method has been tested in cultured neurons as well as murine and human tissues, as is related in a study published in Nature Methods. All of these tools will help the scientific community to discover details about cells unknown up to now. For example, in cancer research or neuroscience they will lead to better understanding by scientists of the genomic heterogeneity existing over various cell types, simultaneously mapping them in space.