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Orchestrated translation specializes dinoflagellate metabolism three times per day

Many cells specialize for different metabolic tasks at different times over their normal ZT cycle by changes in gene expression. However, in most cases, circadian gene expression has been assessed at the mRNA accumulation level, which may not faithfully reflect protein synthesis rates. Here, we use...

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Detalles Bibliográficos
Autores principales: Bowazolo, Carl, Song, Bo, Dorion, Sonia, Beauchemin, Mathieu, Chevrier, Samuel, Rivoal, Jean, Morse, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335273/
https://www.ncbi.nlm.nih.gov/pubmed/35858433
http://dx.doi.org/10.1073/pnas.2122335119
Descripción
Sumario:Many cells specialize for different metabolic tasks at different times over their normal ZT cycle by changes in gene expression. However, in most cases, circadian gene expression has been assessed at the mRNA accumulation level, which may not faithfully reflect protein synthesis rates. Here, we use ribosome profiling in the dinoflagellate Lingulodinium polyedra to identify thousands of transcripts showing coordinated translation. All of the components in carbon fixation are concurrently regulated at ZT0, predicting the known rhythm of carbon fixation, and many enzymes involved in DNA replication are concurrently regulated at ZT12, also predicting the known rhythm in this process. Most of the enzymes in glycolysis and the TCA cycle are also regulated together, suggesting rhythms in these processes as well. Surprisingly, a third cluster of transcripts show peak translation at approximately ZT16, and these transcripts encode enzymes involved in transcription, translation, and amino acid biosynthesis. The latter has physiological consequences, as measured free amino acid levels increase at night and thus represent a previously undocumented rhythm in this model. Our results suggest that ribosome profiling may be a more accurate predictor of changed metabolic state than transcriptomics.