A spatial atlas of the seaweed CO2-fixation machinery reveals a unique Rubisco condensation mechanism
Barrett, J.; Degut, C.; Sebiani Calvo, A.; Hodgkinson, M.; Derry, H.; Salter, A.; Coulembier Vandelannoote, E.; Beveridge, R.; Bothwell, J.; Jacobs, T.; De Clerck, O.; Blaza, J.; Plevin, M.; Mackinder, L.; Blomme, J.
Show abstract
Seaweeds (macroalgae) are important primary producers that sustain food webs in coastal ecosystems. Most algae accelerate inorganic carbon assimilation by actively concentrating CO2 in a Rubisco-rich specialized organelle called the pyrenoid. However, the molecular composition of this pathway is unknown in seaweeds. Here, we investigated the intracellular localization of 160 proteins associated with CO2 acquisition in the green seaweed Ulva (Sea lettuce). We assign 68 proteins to different pyrenoid subdomains and identify a consensus Ulva Rubisco binding motif revealing the molecular logic of the Ulva pyrenoid. We reveal Seaweed Ulva Pyrenoid Assembly 1 (SUPA1) as the core pyrenoid assembly factor. We show that Rubisco condensation is driven by a unique mechanism: the helical folding of SUPA1 motifs upon Rubisco binding, combined with steric hindrance that halves the available Rubisco binding sites from eight to four. Our data gives an unprecedented sub-cellular spatial understanding on seaweed carbon fixation and provides insights into the evolution of this important pathway in the global carbon cycle.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Lateral gene transfer of anion-conducting channelrhodopsins between green algae and giant viruses 95%
- The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae 95%
- The genomes and epigenomes of aquatic plants (Lemnaceae) promote triploid hybridization and clonal reproduction 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.