Back

Axonal entry and retrograde transport define HSV-1 latency establishment and reactivation potential in neurons

Pantoja, C.; Loaiza, A. D. D.; Luong, K. T. Y.; Koyuncu, O. O.

2026-09-25 microbiology
10.64898/2026.09.24.754144 bioRxiv
Show abstract

Herpes simplex virus 1 (HSV-1) establishes life-long latency in peripheral neurons following neuroinvasion, yet the early determinants governing latency versus productive infection remain poorly understood. Available in vitro models bypass the physiological route of infection by directly infecting neuronal cell bodies under antiviral suppression. Here, we established a compartmented axonal infection model that recapitulates HSV-1 neuroinvasion and latency establishment without pharmacological inhibitors. Using primary superior cervical ganglion (SCG) neurons, we demonstrated that low-dose axonal infection consistently establishes latency, whereas higher axonal doses or direct somatic infection led to productive replication. Latently infected neurons exhibit accumulation of the latency-associated transcript (LAT) and can be efficiently reactivated by UV-inactivated virus or VP16 expression. Remarkably, productive infection can be induced during low-dose axonal infection by simultaneous exposure of neuronal cell bodies, but not axons, to replication-deficient virions, implicating tegument delivery in soma overrides latency establishment. Conversely, excess replication-incompetent particles in axons suppress productive outcomes and subsequent reactivations, suggesting competition for retrograde transport. Together, these findings identify axonal entry and transport as critical regulatory checkpoints in HSV-1 latency establishment and suggest that interference with retrograde trafficking may represent a strategy to limit neuroinvasion and life-long reactivations.

Matching journals

The top 3 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.