Back

Constitutive Interferon Epsilon Expression Shapes Antiviral Epithelial States in the Female Reproductive Tract and Intestine

Casazza, R. L.; Skavicusa, S.; Hare, D.; Cooley, K. A.; Heaton, N.; Coyne, C.

2025-09-22 immunology Community evaluation
10.1101/2024.11.15.623843 bioRxiv
Show abstract

Antiviral defenses at mucosal barriers are essential for preventing viral entry and systemic infection. Interferon epsilon (IFN{varepsilon}) is a unique type I IFN that, unlike other family members, is not induced by infection but is constitutively expressed in epithelial tissues. IFN{varepsilon} was initially characterized in the female reproductive tract (FRT), where it provides broad antiviral protection, but its roles outside the FRT remain poorly defined. Here, we used Ifn{varepsilon}-/- mice and single-cell RNA sequencing to delineate IFN{varepsilon} function across distinct mucosal surfaces. In the FRT, Ifn{varepsilon} expression was restricted to specific epithelial subsets, was independent of estrous stage, and maintained basal ISG expression. IFN{varepsilon} was also retained intracellularly in primary human FRT-derived cells. Extending these analyses to the intestine, we found that IFN{varepsilon} is highly expressed in villous-tip enterocytes of the small intestine in vivo, where it sustains inflammatory enterocyte subsets and maintains type III IFN expression. Loss of Ifn{varepsilon} depleted these subsets and rendered mice more susceptible to enteric viral infection. Together, these findings establish IFN{varepsilon} as a constitutively expressed, spatially restricted IFN that coordinates mucosal antiviral defenses across both reproductive and gastrointestinal epithelial tissues.

Published in mBio (predicted rank #23) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.