Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells

Natasja Wulff Pedersen, P. Anoop Chandran, Yu Qian, Jonathan Rebhahn, Nadia Viborg Petersen, Mathilde Dalsgaard Hoff, Scott White, Alexandra J. Lee, Rick Stanton, Charlotte Halgreen, Kivin Jakobsen, Tim Mosmann, Cécile Gouttefangeas, Cliburn Chan, Richard H. Scheuermann, Sine Reker Hadrup

    Research output: Contribution to journalJournal articleResearchpeer-review

    410 Downloads (Pure)

    Abstract

    Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8(+) T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (
    Original languageEnglish
    Article number858
    JournalFrontiers in Immunology
    Volume8
    Number of pages12
    ISSN1664-3224
    DOIs
    Publication statusPublished - 2017

    Keywords

    • Antigen-specific T cells
    • Automated gating
    • Computational analysis
    • Flow cytometry
    • Major histocompatibility complex dextramers
    • Major histocompatibility complex multimers

    Fingerprint Dive into the research topics of 'Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells'. Together they form a unique fingerprint.

    Cite this