Identification of novel therapeutic targets for polyglutamine toxicity disorders that target mitochondrial fragmentation
Traa, A.; Machiela, E.; Rudich, P.; Soo, S.; Senchuk, M.; Van Raamsdonk, J.
Show abstract
Huntingtons disease (HD) is one of at least nine polyglutamine toxicity disorders caused by a trinucleotide CAG repeat expansion, all of which lead to age-onset neurodegeneration. Mitochondrial dynamics and function are disrupted in HD and other polyglutamine toxicity disorders. While multiple studies have found beneficial effects from decreasing mitochondrial fragmentation in HD models by disrupting the mitochondrial fission protein DRP1, disrupting DRP1 can also have detrimental consequences in wild-type animals and HD models. In this work, we examine the effect of decreasing mitochondrial fragmentation in a neuronal C. elegans model of polyglutamine toxicity called Neur-67Q. We find that Neur-67Q worms have deficits in mitochondrial morphology in GABAergic neurons and decreased mitochondrial function. Disruption of drp-1 eliminates differences in mitochondrial morphology and rescues deficits in both movement and longevity in Neur-67Q worms. In testing twenty-four RNA interference (RNAi) clones that decrease mitochondrial fragmentation, we identified eleven clones that increase movement and extend lifespan in Neur-67Q worms. Overall, we show that decreasing mitochondrial fragmentation may be an effective approach to treat polyglutamine toxicity disorders and identify multiple novel genetic targets that circumvent the potential negative side effects of disrupting the primary mitochondrial fission gene drp-1. Significance StatementPolyglutamine toxicity disorders are caused by a trinucleotide CAG repeat expansion that leads to neurodegeneration. Both mitochondrial dynamics and function are disrupted in these disorders. In this work we use a simple genetic model organism, the worm C. elegans, to define the role of mitochondrial morphology in polyglutamine toxicity disorders. We show that CAG repeat expansion is sufficient to disrupt mitochondrial morphology and that genetic strategies that decrease mitochondrial fragmentation are beneficial in a neuronal model of polyglutamine toxicity. This work identifies multiple novel genes that are protective in worm models of polyglutamine toxicity, which may serve as potential therapeutic targets for Huntingtons disease and other polyglutamine toxicity disorders.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Bacterial processing of glucose modulates C. elegans lifespan and healthspan 94%
- Dendrite injury, but not axon injury, triggers neuroprotection in Drosophila models of neurodegenerative disease. 94%
- Split-ends is modulating lipid droplet content in adult Drosophila glial cells and is protective against paraquat toxicity. 93%
Similar papers in this journal
- Developmental and physiological impacts of pathogenic human huntingtin protein in the nervous system 96%
- Insights into Dentatorubral-Pallidoluysian Atrophy from a new Drosophila model of disease 95%
- A C. elegans model of familial Alzheimer's disease shows age-dependent synaptic degeneration independent of amyloid β-peptide 94%
Similar papers in this journal
- Juvenile and adult expression of polyglutamine expanded huntingtin produce distinct aggregate distributions in Drosophila muscle 95%
- Familial ALS/FTD-associated RNA-Binding deficient TDP-43 mutants cause neuronal and synaptic transcript dysregulation in vitro 93%
- Slc9a6 mutation causes Purkinje cell loss and ataxia in the shaker rat 92%
Similar papers in this journal
- Regulation of polyamine interconversion enzymes affects α-Synuclein levels and toxicity in a Drosophila model of Parkinsons disease 96%
- Parkin is not required to sustain OXPHOS function in adult mammalian tissues 95%
- Protection from α-synuclein-induced dopaminergic neurodegeneration by overexpression of the mitochondrial import receptor TOM20 in the rat midbrain 93%
"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.