4.4 Article

Computational flow cytometry analysis reveals a unique immune signature of the human maternal-fetal interface

Journal

Publisher

WILEY
DOI: 10.1111/aji.12774

Keywords

adaptive immunity; decidua; dendritic cells; flow cytometry; machine learning; pregnancy immunology; T lymphocytes

Funding

  1. Eunice Kennedy Shriver National Institute of Child Health and Human Development [K12HD000849-28]
  2. National Institute of General Medical Sciences [R25 GM083252]
  3. March of Dimes Foundation
  4. American Association of Immunologists
  5. UW SciMed GRS Fellowship
  6. WISE Summer Research Grant
  7. UWCCC Flow Core Grant [1S100OD018202-01]
  8. Burroughs Wellcome Fund

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ProblemDecidual immune dysregulation is thought to underlie major pregnancy disorders; however, incomplete understanding of the decidual immune interface has hampered the mechanistic investigation. Method of studyHuman term decidua was collected, and single-cell phenotypic information was acquired by highly polychromatic flow cytometry. Cellular identity analysis was performed with t-distributed stochastic neighbor embedding, DensVM clustering, and matched to CellOntology database. ResultsTraditional analytical methods validated known cellular T and dendritic cell subsets in human term decidua. Computational analysis revealed a complex and tissue-specific decidual immune signature in both the innate and adaptive immune compartments. ConclusionPolychromatic flow cytometry with a streamlined computational analysis pipeline is a feasible approach to comprehensive immunome mapping of human term decidua. As an unbiased, standardized method of investigation, computational flow cytometry promises to unravel the immune pathology of pregnancy disorders.

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