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bioRxiv · 10.1101/2023.10.01.560380

Dectin-1 ligands produce distinct training phenotypes in human monocytes through differential activation of signaling networks

Abstract

Cells of the innate immune system retain memory of prior exposures through a process known as innate immune training. {beta}-glucan, a Dectin-1 ligand purified from the Candida albicans cell wall, has been one of the most widely u:lized and well-characterized ligands for inducing innate immune memory. However, many Dectin-1 agonists exist, and it is not known whether all Dectin-1 ligands produce the same phenotype. Using a well-established in vitro model of trained immunity, we compared two commercially available Dectin-1 agonists, zymosan and depleted zymosan, with the gold standard {beta}-glucan in the literature. We found that depleted zymosan, a {beta}-glucan purified from Saccharomyces cerevisiae cell wall through alkali treatment, produced near identical training effects as C. albicans {beta}-glucan. However, untreated zymosan produced a distinct training effect from {beta}-glucans at both the transcript and cytokine level. Training with zymosan diminished, rather than potentiated, induction of key cytokines such as TNF, IL-12, and IL-6. Zymosan activated NFB and AP-1 transcription factors more strongly than {beta}-glucans. The addition of the toll-like receptor (TLR) ligand Pam3CSK4 was sufficient to convert the training effect of {beta}-glucans to a phenotype resembling training with zymosan. We conclude that differential activation of TLR signaling pathways determines the phenotype of innate immune training induced by Dectin-1. These findings bring clarity to the specific question of which Dectin-1 agonists produce prototypical training effects and provide broader insight into how signaling networks regulate innate immune training.

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BibTeXRIS

Cheng, Q. J., Farrell, K., Fenn, J., Ma, Z., Makanani, S. K., Siemsen, J.. 2023-10-01. Dectin-1 ligands produce distinct training phenotypes in human monocytes through differential activation of signaling networks. https://doi.org/10.1101/2023.10.01.560380

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