Back

Type I IFN dynamics define an early checkpoint for survival and orchestrate systemic neutrophil heterogeneity in lethal viral infection

Saito, R.; Satomi, A.; Sugishita, H.; Gotoh, Y.; Okazaki, T.

2026-01-24 immunology
10.64898/2026.01.22.701212 bioRxiv
Show abstract

The early host response is critical for protection against viral infections, yet the systemic events that dictate individual differences in outcomes remain poorly defined. Here, we leveraged variability in survival following intranasal vesicular stomatitis virus (VSV) challenge in genetically identical mice to retrospectively profile systemic immune responses associated with survival or lethality. Survival was strongly associated with a robust systemic type I interferon (IFN) surge within 24 hours of infection, and blockade of type I IFN signaling during this narrow early window markedly reduced survival, establishing early IFN induction as a key determinant of outcome. This protective IFN surge rapidly remodeled the systemic immune landscape. Single-cell profiling revealed a transcriptionally and functionally distinct ICAM1 neutrophil subset as the strongest early correlate of survival, primed within the bone marrow. ICAM1 neutrophils exhibited a pro-inflammatory signature and enhanced phagocytic activity compared with ICAM1- neutrophils, which predominated in lethal outcomes. Together, these findings define a type I IFN-driven early checkpoint that governs survival in lethal viral infection and identify ICAM1 neutrophils as a blood-accessible biomarker of protective immunity, highlighting the critical role of early innate immune dynamics in shaping disease trajectories and providing a framework for early prognostic markers and host-directed therapies.

Matching journals

The top 7 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.