Systematic identification and characterization of genes in the regulation and biogenesis of photosynthetic machinery.

Photosynthesis is central to food production and the Earth's biogeochemistry, yet the molecular basis for its regulation remains poorly understood. Here, using high-throughput genetics in the model eukaryotic alga Chlamydomonas reinhardtii, we identify with high confidence (false discovery rate [FDR] < 0.11) 70 poorly characterized genes required for photosynthesis. We then enable the functional characterization of these genes by providing a resource of proteomes of mutant strains, each lacking one of these genes. The data allow assignment of 34 genes to the biogenesis or regulation of one or more specific photosynthetic complexes. Further analysis uncovers biogenesis/regulatory roles for at least seven proteins, including five photosystem I mRNA maturation factors, the chloroplast translation factor MTF1, and the master regulator PMR1, which regulates chloroplast genes via nuclear-expressed factors. Our work provides a rich resource identifying regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level understanding of photosynthesis.

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

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.

Modelling the pyrenoid-based CO2-concentrating mechanism provides insights into its operating principles and a roadmap for its engineering into crops.

Many eukaryotic photosynthetic organisms enhance their carbon uptake by supplying concentrated CO2 to the CO2-fixing enzyme Rubisco in an organelle called the pyrenoid. Ongoing efforts seek to engineer this pyrenoid-based CO2-concentrating mechanism (PCCM) into crops to increase yields. Here we develop a computational model for a PCCM on the basis of the postulated mechanism in the green alga Chlamydomonas reinhardtii. Our model recapitulates all Chlamydomonas PCCM-deficient mutant phenotypes and yields general biophysical principles underlying the PCCM. We show that an effective and energetically efficient PCCM requires a physical barrier to reduce pyrenoid CO2 leakage, as well as proper enzyme localization to reduce futile cycling between CO2 and HCO3-. Importantly, our model demonstrates the feasibility of a purely passive CO2 uptake strategy at air-level CO2, while active HCO3- uptake proves advantageous at lower CO2 levels. We propose a four-step engineering path to increase the rate of CO2 fixation in the plant chloroplast up to threefold at a theoretical cost of only 1.3 ATP per CO2 fixed, thereby offering a framework to guide the engineering of a PCCM into land plants.