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accession-icon SRP158633
Single-cell profiling of the myeloid landscape identifies cell subsets with distinct fates during neuroinflammation
  • organism-icon Mus musculus
  • sample-icon 55 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 3000

Description

The innate immune cell compartment is highly diverse in the healthy central nervous system (CNS) including parenchymal and non-parenchymal macrophages. However, this complexity is increased in inflammatory settings by the recruitment of circulating myeloid cells. It is unclear which disease-specific myeloid subsets exist and what their transcriptional profiles and dynamics during CNS pathology are. By combining deep single-cell transcriptome analysis, fate mapping, in vivo imaging, clonal analysis, and transgenic lines, we comprehensively characterized unappreciated myeloid subsets in several CNS compartments during neuroinflammation. During inflammation, CNS macrophage subsets undergo self-renewal, and random proliferation shifted towards clonal expansion. Finally, functional studies demonstrated that endogenous CNS tissue macrophages are redundant for antigen presentation. Our results highlight myeloid cell diversity and provide insights into the brain's innate immune system. Overall design: CD45+ cells isolated from different CNS compartments (including leptomeninges, perivascular space and parenchyma, and choroid plexus) and Ly6Chigh and Ly6Clow monocytes from blood were FACS-sorted in 384-well plates and used for scRNAseq. All myeloid cells were sorted from C57BL/6N mice with 8-10 weeks of age at naive stage or at different stages of Experimental Autoimmune Encephalomyelitis (preclinical, onset and peak of the disease). Data are representative of 16-18 mice from three independent experiments. mCEL-Seq2 protocol was used for single cell sequencing (Hashimshony et al. 2016, Herman et al. 2018).

Publication Title

Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation.

Sample Metadata Fields

Age, Specimen part, Disease, Disease stage, Cell line, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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