The yellow-in-the-dark chIL Chlamydomonas mutant as a model for time-resolved chloroplast biogenesis and physiological responses to lincomycin
Ruiz-Sola, M. A.; De Silvio, M. A.; Becerra-Tinoco, M.; Quintero-Moreno, A. M.; Crespo, J. L.; Monte, E.
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Understanding chloroplast biogenesis is key given the importance of photosynthesis and chloroplast metabolism. Chloroplast assembly has been extensively studied in angiosperms, where the main hallmarks have been established, including the need for nuclear and plastid genome coordination through anterograde and retrograde signals. However, recent works in other photosynthetic lineages have revealed both divergent and conserved regulators. These differences likely represent adaptive strategies that emerged during the evolution of the green lineage, and highlight the need for evolutionary studies to fully elucidate the mechanisms controlling chloroplast biogenesis, a light-promoted process. Here, we characterize the yellow-in-the-dark chIL mutant of Chlamydomonas reinhardtii, which carries a mutation in the CHLL subunit of the dark-operative POR enzyme. Dark-adapted chIL cells cannot synthesize chlorophylls and display a de-differentiated chloroplast, and our results show that upon exposure to light, chloroplast biogenesis is initiated very rapidly based on starch reserves. We demonstrate that accumulation of pigments, photosynthesis-related proteins, and functional chloroplast activity is detected within 1-3 hours of illumination. Additionally, we show that lincomycin, an inhibitor of plastid translation, specifically affects chloroplast physiology, and blocks light-induced chloroplast biogenesis and cell growth, establishing lincomycin as a valuable tool for investigating chloroplast physiology and plastid-to-nucleus signals in Chlamydomonas. Together, this study introduces the chIL mutant as a powerful model system to dissect light-induced, time-resolved chloroplast biogenesis, as well as the responses and signaling triggered by lincomycin. By promoting broader adoption of this model, we aim to help inform strategies to enhance photosynthesis and stress tolerance, and optimize bioproduct production.
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