Back

Model-independent reorganization of translation in TDP-43 Amyotrophic Lateral Sclerosis

Lauria, F.; Maniscalco, F.; Perrucci, C.; Marchioretto, M.; Bruno, I.; Tome, G.; Cella, F.; Busarello, E.; Sevegnani, M.; Lunelli, L.; Donini, L.; Tebaldi, T.; D Antoni, M.; Pollini, D.; Peroni, D.; Pisciottani, A.; Croci, L.; Badaloni, A.; Arnese, R.; Provenzani, A.; Quattrone, A.; Consalez, G. G.; Clamer, M.; Siciliano, V.; Basso, M.; Viero, G.

2025-05-16 molecular biology
10.1101/2025.05.15.654227 bioRxiv
Show abstract

The RNA-binding protein TDP-43 is a major contributor and a pathological hallmark of Amyotrophic Lateral Sclerosis (ALS), yet how TDP-43 dysregulation mechanistically alters protein synthesis across neuronal compartments and disease models remains unclear. Here, we dissected TDP-43-driven translational alterations in both in vitro and in vivo TDP-43 models of ALS. Through ribosome and polysome profiling, computational, and biochemical analyses, we observed robust TDP-43-associated translational remodelling at cellular and subcellular resolution. Our findings reveal a conserved mechanism across models, characterized by enhanced ribosome recruitment on polysomes, elongation impairment, axonal downregulation and instability of TDP-43 target mRNAs and redistribution toward non-target transcripts. Notably, TDP-43 dysregulation alters ribosome dynamics and selectively impairs translation of TDP-43 target mRNAs, whilst favouring the translation of other transcripts. This process reflects a compensatory but maladaptive response to TDP-43-induced mRNA destabilization. Together, these data demonstrate that alterations in TDP-43 disrupts neuronal proteostasis through ribosome reorganization and loss of mRNA homeostasis, providing a unifying mechanistic framework for translational imbalance in ALS and revealing early molecular events that may underlie motor neuron vulnerability.

Matching journals

The top 8 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.