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Parasite worm antigens instruct macrophages to release immunoregulatory extracellular vesicles.

Amin ZakeriBradley J WhiteheadAllan StensballeClarize de KorneAndrew R WilliamsBart EvertsPeter Nejsum
Published in: Journal of extracellular vesicles (2021)
Emerging evidence suggests that immune cells not only communicate with each other through cytokines, chemokines, and cell surface receptors, but also by releasing small membranous structures known as extracellular vesicles (EVs). EVs carry a variety of different molecules that can be taken up by recipient cells. Parasitic worms are well known for their immunomodulatory properties, but whether they can affect immune responses by altering EV-driven communication between host immune cells remains unclear. Here we provide evidence that stimulation of bone marrow-derived macrophages (BMDMs) with soluble products of Trichuris suis (TSPs), leads to the release of EVs with anti-inflammatory properties. Specifically, we found that EVs from TSP-pulsed BMDMs, but not those from unstimulated BMDMs can suppress TNFα and IL-6 release in LPS-stimulated BMDMs and BMDCs. However, no polarization toward M1 or M2 was observed in macrophages exposed to EVs. Moreover, EVs enhanced reactive oxygen species (ROS) production in the exposed BMDMs, which was associated with a deregulated redox homeostasis as revealed by pathway analysis of transcriptomic data. Proteomic analysis identified cytochrome p450 (CYP450) as a potential source of ROS in EVs from TSP-pulsed BMDMs. Finally, pharmacological inhibition of CYP450 activity could suppress ROS production in those BMDMs. In summary, we find that TSPs can modulate immune responses not only via direct interactions but also indirectly by eliciting the release of EVs from BMDMs that exert anti-inflammatory effects on recipient cells.
Keyphrases
  • reactive oxygen species
  • anti inflammatory
  • immune response
  • induced apoptosis
  • cell death
  • cell cycle arrest
  • dna damage
  • mesenchymal stem cells
  • electronic health record
  • single cell
  • machine learning