Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin.

Richard S Ahn, Keyon Taravati, Kevin Lai, Kristina M Lee, Joanne Nititham, Rashmi Gupta, David S Chang, Sarah T Arron, Michael Rosenblum, Wilson Liao
Author Information
  1. Richard S Ahn: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States. richard.ahn@ucsf.edu. ORCID
  2. Keyon Taravati: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  3. Kevin Lai: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  4. Kristina M Lee: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  5. Joanne Nititham: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  6. Rashmi Gupta: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  7. David S Chang: Department of Plastic Surgery, California Pacific Medical Center, San Francisco, CA, United States.
  8. Sarah T Arron: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  9. Michael Rosenblum: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
  10. Wilson Liao: Department of Dermatology, University of California, San Francisco, San Francisco, CA, United States.

Abstract

Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture. However, transcriptomic analysis of bulk skin tends to drown out expression signals from relatively rare cells while cell culture methods may significantly alter cellular phenotypes and gene expression profiles. To identify distinct transcriptomic profiles of multiple cell populations without substantially altering cell phenotypes, we employed a fluorescence activated cell sorting method to isolate keratinocytes, dendritic cells, CD4+ T effector cells, and CD8+ T effector cells from healthy skin samples, followed by RNA-seq of each cell population. Principal components analysis revealed distinct clustering of cell types across samples, while differential expression and coexpression network analyses revealed transcriptional profiles of individual cell populations distinct from bulk skin, most strikingly in the least abundant CD8+ T effector population. Our work provides a high resolution view of cutaneous cellular gene expression and suggests that transcriptomic profiling of bulk skin may inadequately capture the contribution of less abundant cell types.

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Grants

  1. L30 AR068704/NIAMS NIH HHS
  2. U01 AI119125/NIAID NIH HHS
  3. R01 AR065174/NIAMS NIH HHS
  4. R21 AR066821/NIAMS NIH HHS
  5. K08 AR062064/NIAMS NIH HHS
  6. DP2 AR068130/NIAMS NIH HHS
  7. T32 AR007175/NIAMS NIH HHS

MeSH Term

Adult
CD4-Positive T-Lymphocytes
CD8-Positive T-Lymphocytes
Dendritic Cells
Female
Flow Cytometry
Gene Expression Profiling
Humans
Keratinocytes
Male
Middle Aged
Sequence Analysis, RNA
Skin
Transcriptome

Word Cloud

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