A Chloroplast Protein Atlas Reveals Novel Structures and Spatial Organization of Biosynthetic Pathways

Lianyong Wang(Princeton University), Weronika Patena(Princeton University), Kelly A. Van Baalen(Princeton University), Yihua Xie(Princeton University), Emily Singer(Princeton University), Sophia Gavrilenko(Princeton University), Michelle Warren-Williams(Princeton University), Linqu Han(Michigan State University), Henry R. Harrigan(Princeton University), Vivian Chen(Princeton University), Vinh T.N.P. Ton(Princeton University), Saw Kyin(Princeton University), Henry H. Shwe(Princeton University), Matthew H. Cahn(Princeton University), Alexandra T. Wilson(Princeton University), Jianping Hu(Michigan State University), Danny J. Schnell(Michigan State University), Claire D. McWhite(Princeton University), Martin C. Jonikas(Howard Hughes Medical Institute)
bioRxiv (Cold Spring Harbor Laboratory)
May 31, 2022
Cited by 13Open Access
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Abstract

Summary 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 1,032 candidate chloroplast proteins by using fluorescent protein tagging in the model alga Chlamydomonas reinhardtii . The localizations provide insights into the functions of hundreds of poorly-characterized proteins, including identifying novel components of nucleoids, plastoglobules, and the pyrenoid. We discovered and further characterized novel organizational features, including eleven chloroplast punctate structures, cytosolic crescent structures, and diverse unexpected spatial distributions of enzymes within the chloroplast. We observed widespread protein targeting to multiple organelles, identifying proteins that likely function in multiple compartments. We also used machine learning to predict the localizations of all Chlamydomonas proteins. The strains and localization atlas developed here will serve as a resource to enable studies of chloroplast architecture and functions. Graphical Abstract Highlights 1,032 candidate chloroplast proteins localized by fluorescent tagging. This protein atlas reveals novel chloroplast structures, functional regions, and components. Prevalent dual-organelle localization suggests extensive cross-compartment coordination. Atlas-trained machine learning predicts localizations of all C. reinhardtii proteins.


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