The temporal and stimuli-specific effects of LPS and IFNγ on microglial activation

Christina N Heiss1, Andrew S Naylor1, Ida Pesämaa1

  • 1Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

PubMed

Insights

Microglia activation by lipopolysaccharide (LPS) and interferon gamma (IFNγ) is time- and stimulus-dependent. LPS triggers stronger responses, while IFNγ modulates these effects, offering insights into neuroinflammation.

Area of Science:

  • Neuroscience
  • Immunology
  • Cell Biology

Background:

  • Microglia are central nervous system immune cells crucial for homeostasis and neuroinflammation.
  • Microglial activation is context-dependent, with diverse phenotypic states.
  • Lipopolysaccharide (LPS) is a common stimulus, but Interferon gamma (IFNγ) may better mimic CNS inflammation.

Purpose of the Study:

  • To systematically investigate the temporal activation profiles of human iPSC-derived microglia (hiMG).
  • To compare responses to LPS, IFNγ, and their combination.
  • To understand the time- and stimulus-dependency of microglial activation.

Main Methods:

  • Human iPSC-derived microglia (hiMG) were treated with LPS, IFNγ, or both.
  • Transcriptomic analysis (RNA-seq) was performed at 24 hours.
  • Cytokine expression, morphology, and protein secretion (mass spectrometry, western blot) were analyzed over time.

Main Results:

  • LPS and LPS/IFNγ induced robust differential gene expression, partially overlapping with disease-associated microglia (DAM) signatures.
  • Cytokine expression changes occurred as early as 1 hour, with distinct temporal patterns.
  • LPS elicited the strongest transcriptomic and protein responses; IFNγ modulated LPS effects and showed stimulus-specific protein secretion.

Conclusions:

  • Microglial activation is highly dependent on both time and stimulus.
  • LPS is a potent activator, while IFNγ plays a modulatory role.
  • Temporal resolution is critical for accurately modeling microglial activation in neurodegenerative diseases.