Back

The core herpes simplex-1 fusion complex drives cell-to-cell spreading of pathological Tau

Heumueller, S.-E.; Sushkin, M.; Sanchez-Sendin, E.; Hossinger, A.; Stappert, D.; Altinisik, N.; Seiwert, L.; Paulsen, L.; Krawczyk, A.; Klupp, B. G.; Mettenleiter, T. C.; Denner, P.; Pruess, H.; Vorberg, I. M.

2026-01-21 neuroscience
10.64898/2026.01.21.700770 bioRxiv
Show abstract

Neurodegenerative diseases such as Alzheimers disease (AD) are characterized by the pathological aggregation of the host-encoded protein Tau into amyloid fibrils. Pathologic protein aggregates composed of Tau are able to spread from cell-to-cell, thereby contributing to disease progression. The exact mechanisms of intercellular dissemination remain ill-defined. Mounting evidence links the herpes simplex virus-1 (HSV-1) to the aetiology of AD. HSV-1 is a prevalent neurotropic virus that replicates in epithelial cells at the site of infection, and subsequently establishes lifelong latency in the peripheral and central nervous systems. In the quiescent latent state, AD brains show elevated expression of structural viral proteins in the absence of virus production. We hypothesized that HSV-1 glycoproteins involved in viral attachment and fusion facilitate the intercellular spreading of proteopathic seeds. Using cellular models, we demonstrate that expression of the HSV-1 core fusion complex, essential for viral entry and direct cell-to-cell transmission, is sufficient to promote aggregate dissemination between cells. Moreover, anti-HSV-1 antibodies present in the cerebrospinal fluid of patients with HSV-1 encephalitis efficiently neutralize viral infection, block viral cell-to-cell transmission, and inhibit propagation of pathological Tau. Thus, latent HSV-1 infection of the brain could contribute to neurodegenerative disease progression, and antiviral antibodies may represent a potential therapeutic strategy.

Matching journals

The top 4 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.