Back

Boosting chloroplast ribosome biogenesis by a plastidial DEAD-box RNA helicase is critical for high light acclimation

Djouani-Tahri, E. B.; Nellaepalli, S.; Auroy, P.; Billon, E.; Burlacot, A.; Chaux-Jukic, F.; Cuine, S.; Epting, V.; Huleux, M.; Ghysels, B.; Schulz-Raffelt, M.; Te, I.; Brugiere, S.; Coute, Y.; Takahashi, Y.; Li-Beisson, Y.; Peltier, G.

2022-05-19 plant biology
10.1101/2022.05.16.492170 bioRxiv
Show abstract

Photosynthetic organisms have developed sophisticated strategies to fine-tune light energy conversion to meet the metabolic demand, thereby optimizing growth in fluctuating light environments. Although mechanisms such as energy dissipation, photosynthetic control, or the photosystem II (PSII) damage and repair have been widely studied, little is known about the regulation of protein synthesis capacity during light acclimation. By screening a Chlamydomonas reinhardtii insertional mutant library using chlorophyll fluorescence imaging, we isolated a high chlorophyll fluorescence mutant (hf0) defected in a gene encoding a putative plastid targeted DEAD-box RNA helicase called CreRH22. CreRH22 is rapidly induced upon illumination and belongs to the GreenCut, a set of proteins specific to photosynthetic organisms. While photosynthesis is slightly affected in the mutant under low light (LL), exposure to high light (HL) induces a marked decrease in both PSII and PSI, and a strong alteration of the light-induced gene expression pattern. These effects are explained by the inability of hf0 to increase plastid ribosome amounts under HL. We conclude that CreRH22, by promoting ribosomal RNA precursor maturation in a light-dependent manner, enables the assembly of extra-ribosomes required to synthesize photosystem subunits at a higher rate, a critical step in the acclimation of algae to HL.

Matching journals

The top 5 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.