Details

Autor(en) / Beteiligte

• Wang, Lianyong
• Patena, Weronika
• Van Baalen, Kelly A.
• Xie, Yihua
• Singer, Emily R.
• Gavrilenko, Sophia
• Warren-Williams, Michelle
• Han, Linqu
• Harrigan, Henry R.
• Hartz, Linnea D.
• Chen, Vivian
• Ton, Vinh T.N.P.
• Kyin, Saw
• Shwe, Henry H.
• Cahn, Matthew H.
• Wilson, Alexandra T.
• Onishi, Masayuki
• Hu, Jianping
• Schnell, Danny J.
• McWhite, Claire D.
• Jonikas, Martin C.

Titel

A chloroplast protein atlas reveals punctate structures and spatial organization of biosynthetic pathways

Ist Teil von

• Cell, 2023-08, Vol.186 (16), p.3499-3518.e14

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2023

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Chloroplasts are eukaryotic photosynthetic organelles that drive the global carbon cycle. Despite their importance, our understanding of their protein composition, function, and spatial organization remains limited. Here, we determined the localizations of 1,034 candidate chloroplast proteins using fluorescent protein tagging in the model alga Chlamydomonas reinhardtii. The localizations provide insights into the functions of poorly characterized proteins; identify novel components of nucleoids, plastoglobules, and the pyrenoid; and reveal widespread protein targeting to multiple compartments. We discovered and further characterized cellular organizational features, including eleven chloroplast punctate structures, cytosolic crescent structures, and unexpected spatial distributions of enzymes within the chloroplast. We also used machine learning to predict the localizations of other nuclear-encoded Chlamydomonas proteins. The strains and localization atlas developed here will serve as a resource to accelerate studies of chloroplast architecture and functions. [Display omitted] •1,034 candidate chloroplast proteins localized by fluorescent tagging•This protein atlas reveals chloroplast structures, functional regions, and components•Dual-organelle localizations suggest extensive cross-compartment coordination•Atlas-trained machine learning predicts localizations of all C. reinhardtii proteins Localization analyses of 1,034 candidate chloroplast proteins reveal insights into chloroplast architecture and functions in Chlamydomonas reinhardtii.