Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

Andrea Cossarizza1, Hyun-Dong Chang2, Andreas Radbruch2

  • 1Department of Medical and Surgical Sciences for Children and Adults, Univ. of Modena and Reggio Emilia School of Medicine, Modena, Italy.

Insights

This consensus guideline provides essential flow cytometry (FC) theory and practical methods for immunologists. It aims to prevent common errors in immunological data and details immune cell phenotyping for reliable research.

Area of Science:

  • Immunology
  • Cell Biology
  • Biotechnology

Background:

  • Flow cytometry (FC) is a critical tool in immunology for analyzing immune cells.
  • Inconsistent application of FC techniques can lead to unreliable immunological data.
  • A need exists for standardized guidelines to ensure accuracy and reproducibility in FC experiments.

Purpose of the Study:

  • To establish consensus guidelines for the effective use of flow cytometry in immunology.
  • To provide practical advice and theoretical background for immunologists utilizing FC.
  • To minimize common errors and enhance the quality of immunological data derived from FC.

Main Methods:

  • Consensus-based development involving experts in immunology and flow cytometry.
  • Compilation of theoretical principles and practical aspects of FC techniques.
  • Inclusion of detailed immune cell phenotyping for murine and human samples.
  • Description of the latest FC applications and data analysis strategies.

Main Results:

  • Comprehensive guidelines covering major immune cell types and their phenotypes.
  • Detailed tables of murine and human immune cell phenotypes.
  • Explanation of current FC techniques, applications, and data analysis.
  • Inclusion of expert tips, tricks, and common pitfalls to avoid.

Conclusions:

  • These guidelines serve as an essential resource for immunologists using flow cytometry.
  • Adherence to these guidelines will improve the reliability and reproducibility of immunological research.
  • The document empowers researchers to avoid common errors and optimize FC data generation and analysis.