Spatial Biology Revealed with the GeoMx DSP by NanoString
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- Опубликовано: 24 авг 2024
- Curious about using spatial transcriptomics? The GeoMx Digital Spatial Profiler enables multiplexed profiling of RNA and protein in two dimensions in fixed or fresh frozen tissue or FFPE sections.
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Script:
We all understand the value of quantitating protein or gene expression levels in cancer, neuroscience, and more. However, in addition to quantitative data, spatial context is central to gaining deeper insights into the tissue biology.
What if you could see both spatial context and quantitative expression data all from one slide?
NanoString's GeoMx Digital Spatial Profiler platform provides morphological context with high plex protein or gene expression profiling from just one slide. A single slide sample is manually or automatically stained with fluorescent reagents to targeted areas of the tissue which allows the GeoMx DSP instrument to capture images with morphological context.
With an intuitive interface, you can then select areas of interest for profiling using several approaches: by tissue morphology, by phenotype, by individual cells, by gridding, or by contouring the area.
The key to the GeoMx DSP technology lies with the photocleavable oligonucleotide tags that are attached to the antibodies via a light-sensitive linker. UV light is used to decouple the High Plex oligo tags from the antibodies or RNA in the selected regions of interest. Oligos are then retrieved from the surface of the tissue, without disturbing the tissue, thus allowing the sample to be reused. The oligos are then deposited into a microtiter plate where they can then be put on an analyzer for quantitative analysis.
Now it is possible to get both morphological context with high profiling protein and gene expression data from just one slide sample. Experience GeoMx Digital Spatial Profiling technology by NanoString.
#SpatialTranscriptomics #SpatialProteomics #SpatialBiology #SpatialMultiOmics #DigitalSpatialProfiling #NanoString #Biotechnology #Pathology #FFPE #SpatialGenomics