Optimized isolation of renal plasma cells for flow cytometric analysis

J Immunol Methods. 2019 Nov:474:112628. doi: 10.1016/j.jim.2019.06.019. Epub 2019 Jun 26.

Abstract

Plasma cells (PCs) secrete antibodies and play an essential role in protective immunity, but also in pathogenesis of antibody-mediated diseases. Physiologically, PCs mainly reside within bone marrow and spleen. In autoimmune diseases such as systemic lupus erythematosus (SLE) autoantibody-producing PCs can also be found at sites of inflammation, e.g. in nephritic kidneys. Therefore, efficient methods are required to reliably analyze and compare PCs at different sites. Flow cytometry and ELISpot analyses are frequently employed for PC characterization and require the preparation of single cell suspensions. To that end, enzymatic digestion is commonly used to isolate immune cells from solid organs like kidneys, occasionally also from lymphoid organs. In this study we show that enzymatic digestion using collagenase may lead to a loss of certain surface markers, e.g. the PC markers CD138 and CD267 (TACI). Therefore, we established an optimized protocol for preparing renal single cells by merely applying mechanical tissue disruption. Omitting enzymatic digestion, this method enables a reliable characterization of viable renal PCs by flow cytometry and cell sorting. We further show that mechanic cell preparation is favorable for lymphocytic immune cell enrichment, while enzymatic disruption improves the yield of digitating or stroma cell populations.

Keywords: Autoimmunity; Flow cytometry; Kidney; Plasma cell; Tissue dissociation.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers / metabolism
  • Cell Separation / methods*
  • Cell Survival
  • Collagenases / metabolism
  • Dissection*
  • Female
  • Flow Cytometry*
  • Kidney / cytology
  • Kidney / immunology*
  • Kidney / metabolism
  • Mice, Inbred MRL lpr
  • Mice, Inbred NZB
  • Plasma Cells / immunology*
  • Plasma Cells / metabolism
  • Time Factors
  • Workflow

Substances

  • Biomarkers
  • Collagenases