Identification of organ-specific T cell populations by analysis of multiparameter flow cytometry data using DNA-chip analysis software

Authors

  • Matthias Hofmann,

    Corresponding author
    1. Autoimmunity and Transplantation, Novartis Institutes for BioMedical Research, Basel, Switzerland
    • Novartis Institutes for BioMedical Research, Autoimmunity and Transplantation, Novartis Pharma AG, Lichtstrasse 35, WSJ-386.516, CH-4002 Basel, Switzerland
    Search for more papers by this author
  • Hans-Günter Zerwes

    1. Autoimmunity and Transplantation, Novartis Institutes for BioMedical Research, Basel, Switzerland
    Search for more papers by this author

Abstract

Background:

The analysis of cells from multiple experimental groups by multiparameter flow cytometry leads to the generation of complex data sets, for which adequate analysis tools are not commonly available. We report here that software designed for transcriptomics applications can be used in multiparameter flow cytometry.

Methods:

Lymphocytes isolated from nine different mouse organs were stained and subjected to 10-parameter flow cytometry. The resulting data set contained 594 different T cell subsets per organ per mouse and was organized into a so-called flow cytometry array (FCA).

Results:

Computation of a hierarchical tree revealed that lymph nodes and spleen were populated by similar T cell subsets, while T cells from peripheral organs displayed a diverse subset composition. Furthermore, organ-specific T cell subsets were identified.

Conclusions:

This new FCA concept in flow cytomics proved to be a valuable tool for the fast and unbiased analysis of complex multiparameter flow cytometry data sets. It can be used for assessing disease progression and therapeutic intervention, and for the association of disease-related biomarkers on the protein level. © 2006 International Society for Analytical Cytology

Ancillary