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Quantitative Proteomics Reveals Distinct Molecular Signatures of Different Cerebellum-Dependent Learning Paradigms.

Yong Gyu KimJongmin WooJoonho ParkSooyong KimYong-Seok LeeYoungsoo KimSang Jeong Kim
Published in: Journal of proteome research (2020)
The cerebellum improves motor performance by adjusting motor gain appropriately. As de novo protein synthesis is essential for the formation and retention of memories, we hypothesized that motor learning in the opposite direction would induce a distinct pattern of protein expression in the cerebellum. We conducted quantitative proteomic profiling to compare the level of protein expression in the cerebellum at 1 and 24 h after training from mice that underwent different paradigms of cerebellum-dependent oculomotor learning from specific directional changes in motor gain. We quantified a total of 43 proteins that were significantly regulated in each of the three learning paradigms in the cerebellum at 1 and 24 h after learning. In addition, functional enrichment analysis identified protein groups that were differentially enriched or depleted in the cerebellum at 24 h after the three oculomotor learnings, suggesting that distinct biological pathways may be engaged in the formation of three oculomotor memories. Weighted correlation network analysis discovered groups of proteins significantly correlated with oculomotor memory. Finally, four proteins (Snca, Sncb, Cttn, and Stmn1) from the protein group correlated with the learning amount after oculomotor training were validated by Western blot. This study provides a comprehensive and unbiased list of proteins related to three cerebellum-dependent motor learning paradigms, suggesting the distinct nature of protein expression in the cerebellum for each learning paradigm. The proteomics data have been deposited to the ProteomeXchange Consortium with identifiers <PXD008433>.
Keyphrases
  • network analysis
  • transcription factor
  • metabolic syndrome
  • computed tomography
  • dna methylation
  • south africa
  • single cell
  • big data
  • skeletal muscle
  • drug induced