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

Abstract

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 O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/493820v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@19c871eorg.highwire.dtl.DTLVardef@16ac46corg.highwire.dtl.DTLVardef@859b7dorg.highwire.dtl.DTLVardef@1a3446e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI1,032 candidate chloroplast proteins localized by fluorescent tagging. C_LIO_LIThis protein atlas reveals novel chloroplast structures, functional regions, and components. C_LIO_LIPrevalent dual-organelle localization suggests extensive cross-compartment coordination. C_LIO_LIAtlas-trained machine learning predicts localizations of all C. reinhardtii proteins. C_LI