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Mapping the total transcriptome at near cellular resolution

ABSTRACT: Spatial transcriptomics provides context to gene expression information, however most methods are only sensitive to a subset of the RNA species. Many noncoding and microbial RNA molecules lack the poly(A) tail which is used to capture RNAs in sequencing-based methods. These transcripts represent valuable analytes for studying gene regulation and host-microbe interactions, respectively. We and others recently showed that in situ polyadenylation combined with poly(dT) capture enables broad analysis of coding, noncoding, and non-host RNAs. However, current implementations neither attain single-cell resolution or retain spatial information. Recent commercialization of spatial transcriptomics tools have enabled broad adoption of these technologies. Several new tools have been developed which can attain near cellular resolution, including SlideSeq (Seeker, Takara/Curio Bioscience) and StereoSeq (STOmics, BGI). Here we adapt in situ polyadenylation to two commerical spatial transcriptomics platforms with near cellular resolution and show the spatial heterogeneity of the total transcriptome in the infected murine heart and testis.

ORGANISM(S): Mus musculus

PROVIDER: GSE316962 | GEO | 2026/01/21

REPOSITORIES: GEO

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Project description:Highly specialized cells are fundamental for proper functioning of complex organs. Variations in cell-type specific gene expression and protein composition have been linked to a variety of diseases. Although single cell technologies have emerged as valuable tools to address this cellular heterogeneity, a majority of these workflows lack sufficient in situ resolution for functional classification of cells and are associated with extremely long analysis time, especially when it comes to in situ proteomics. In addition, lack of understanding of single cell dynamics within their native environment limits our ability to explore the altered physiology in disease development. This limitation is particularly relevant in the mammalian brain, where different cell types perform unique functions and exhibit varying sensitivities to insults. The hippocampus, a brain region crucial for learning and memory, is of particular interest due to its obvious involvement in various neurological disorders. Here, we present a combination of experimental and data integration approaches for investigation of cellular heterogeneity and functional disposition within the mouse brain hippocampus using MALDI Imaging mass spectrometry (MALDI-IMS) and shotgun proteomics (LC-MS/MS) coupled with laser-capture microdissection (LCM) along with spatial transcriptomics. Within the dentate gyrus granule cells we identified two proteomically distinct cellular subpopulations that are characterized by a substantial number of discriminative proteins. These cellular clusters contribute to the overall functionality of the dentate gyrus by regulating redox homeostasis, mitochondrial organization, RNA processing, and microtubule organization. Importantly, most of the identified proteins matched their transcripts, verifying the in situ protein identification and supporting their functional analyses. By combining high-throughput spatial proteomics with transcriptomics, our approach enables reliable near-single-cell scale identification of proteins and profiling of inter-cellular heterogeneity within similar cell-types in tissues. This methodology has the potential to be applied to different biological conditions and tissues, providing a deeper understanding of cellular subpopulations in situ.

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Mapping the total transcriptome at near cellular resolution

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