Back

Mitochondrial protein import stress causes progressive neurodegeneration opposed by PERK - eIF2α signalling

Ebding, J.; Barth, M.; Lion, L. M.; Gackstatter, A.; Link, S.; Pirritano, M.; Gasparoni, G.; Simon, M.; Herrmann, J.; Pielage, J.

2026-04-14 neuroscience
10.64898/2026.04.10.717732 bioRxiv
Show abstract

Mitochondrial dysfunction and impairments of the mitochondrial protein import system are often linked to neurodegenerative disease, but whether import stress per se causes neurodegeneration has not been tested. Here, we adapted the yeast clogger system to Drosophila motoneurons to block TOM-TIM23-mediated import with temporal control. Sustained import stress converts somatic mitochondria into donut-shaped structures, depletes functional mitochondria from synaptic terminals, and causes progressive neurodegeneration with impaired neurotransmitter release and locomotor dysfunction. This neurodegeneration is mechanistically distinct from mitochondrial absence, as miro mutant neurons that completely lack presynaptic mitochondria do not degenerate. Import-stressed motoneurons activate multiple protective programmes, including chaperone remodelling, metabolic repression, and translational control through the eIF2 kinase PERK. Both pharmacological PERK inhibition and reversal of translational attenuation via ISRIB accelerate neurodegeneration, whereas PERK overexpression alone is sufficient to cause it, defining a protective range of eIF2-dependent translational control. The observation that PERK inhibition is protective in protein misfolding models but detrimental during import stress shows that the nature of mitochondrial dysfunction determines the molecular consequence of translational control in neurodegeneration.

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.