SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

Novel autophagy inducers by accelerating lysosomal clustering against Parkinson's disease.

Elife · 2024-07-03

DOI: 10.7554/elife.98649PMID: 38899618

Open accessresearch-article; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

The autophagy-lysosome pathway plays an indispensable role in the protein quality control by degrading abnormal organelles and proteins including α-synuclein (αSyn) associated with the pathogenesis of Parkinson's disease (PD). However, the activation of this pathway is mainly by targeting lysosomal enzymic activity. Here, we focused on the autophagosome-lysosome fusion process around the microtubule-organizing center (MTOC) regulated by lysosomal positioning. Through high-throughput chemical screening, we identified 6 out of 1200 clinically approved drugs enabling the lysosomes to accumulate around the MTOC with autophagy flux enhancement. We further demonstrated that these compounds induce the lysosomal clustering through a JIP4-TRPML1-dependent mechanism. Among them, the lysosomal-clustering compound albendazole promoted the autophagy-dependent degradation of Triton-X-insoluble, proteasome inhibitor-induced aggregates. In a cellular PD model, albendazole boosted insoluble αSyn degradation. Our results revealed that lysosomal clustering can facilitate the breakdown of protein aggregates, suggesting that lysosome-clustering compounds may offer a promising therapeutic strategy against neurodegenerative diseases characterized by the presence of aggregate-prone proteins.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.