Quantification of CD95-induced apoptosis and NF-κB activation at the single cell level

Jörn H Schmidt1, Sabine Pietkiewicz1, Michael Naumann2

  • 1Department of Translational Inflammation Research, Institute of Experimental Internal Medicine, Otto von Guericke University, Pfälzer Platz, 39106 Magdeburg, Germany.

Insights

Researchers developed a new imaging flow cytometry method to quantify CD95 signaling, apoptosis, and NF-κB activation in single cells. This technology aids understanding cell fate decisions in diseases like cancer and inflammation.

Area of Science:

  • Cell Biology
  • Molecular Biology
  • Immunology

Background:

  • CD95 (also known as Fas/APO-1) is a death receptor crucial for apoptosis and NF-κB signaling.
  • The interplay between apoptosis and NF-κB pathways influences cell fate and is implicated in inflammatory diseases and cancer.
  • Understanding these pathways at a single-cell level is vital for disease research.

Purpose of the Study:

  • To develop a novel quantitative method for analyzing CD95 signaling pathways in single cells.
  • To enable simultaneous detection of apoptosis and NF-κB activation.
  • To facilitate a deeper understanding of cell fate decisions and their role in disease.

Main Methods:

  • Utilized imaging flow cytometry for high-throughput single-cell analysis.
  • Developed a quantitative detection method for CD95 signaling, apoptosis, and NF-κB activation.
  • Enabled simultaneous measurement of multiple signaling events within individual cells.

Main Results:

  • Successfully quantified apoptosis and NF-κB activation in a large number of single cells.
  • Demonstrated the capability to analyze distinct CD95 signaling pathways concurrently.
  • Established a method for detailed single-cell characterization of these critical cellular processes.

Conclusions:

  • The developed imaging flow cytometry method offers a powerful tool for quantitative analysis of apoptosis and NF-κB signaling.
  • This technology provides new insights into cell fate determination at the single-cell level.
  • Potential applications include quantitative network analysis in systems biology and disease research.

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