Novel KIF1A Mutations Perturb Axonal TDP-43 Localization and Presynaptic Proteostasis

Axonal trafficking is a key feature unique to the morphology of neurons, facilitating the movement of proteins bidirectionally between the soma and the presynaptic terminal, at times over significantly long distances. In neurons, kinesin motor proteins facilitate the anterograde axonal trafficking of key cargos, including mitochondria, synaptic vesicles, dense core vesicles, and endolysosomes. Kinesin dysfunction has been linked to a variety of neurodevelopmental and neurodegenerative disorders. Here, we investigate novel mutations to kinesin family member 1A KIF1A) in patient derived induced pluripotent stem cell neurons, and their collective role in neuropathology and trafficking mechanisms. Our data suggests that KIF1A is a candidate kinesin motor protein mediating the anterograde axonal trafficking of TAR DNA Binding Protein 43KDa (TDP-43) and RNA, wherein mutations to KIF1A impair the association with and axonal localization of TDP-43. While contemporary research has hypothesized the link between TDP-43 and KIF1A to be conferred through annexin-11 and lysosomes, our data suggests an alternative link between annexin-5 and synaptic vesicles. Additionally, this research infers that these novel KIF1A mutations play pathogenic roles in the loss of synaptic vesicle proteins in the axons, likely leading to deprecated synaptic transmission. Furthermore, we demonstrate that the loss of axonal TDP-43 as a result of mutagenic, and other RNA-binding proteins, leads to a loss of presynaptic transcriptomic and proteostasis. The subsequent loss of axonal proteostasis was found to be in part a result of loss of RNA processing and transcriptional machinery. Lastly, we show that the gross synaptic architecture of axonal protein recovery of neurons is corrupted by mutations in KIF1A and the downstream effects on the axonal transcriptome and proteome. While this data does not identify novel therapeutic targets to address KIF1A associated neurological disorders, the data provides a holistic template to measure the success of future therapies.