Back

Proteomic changes orchestrate metabolic acclimation of a unicellular diazotrophic cyanobacterium during light-dark cycle and nitrogen fixation states

Panda, P.; Giri, S. J.; Sherman, L. A.; Kihara, D.; Aryal, U. K.

2024-07-30 microbiology
10.1101/2024.07.30.605809 bioRxiv
Show abstract

Cyanobacteria have developed an impressive array of proteins and pathways, each tailored for specific metabolic attributes, to execute photosynthesis and biological nitrogen (N2)-fixation. An understanding of these biologically incompatible processes provides important insights into how they can be optimized for renewable energy. To expand upon our current knowledge, we performed label-free quantitative proteomic analysis of the unicellular diazotrophic cyanobacterium Crocosphaera subtropica ATCC 51142 grown with and without nitrate under 12-hour light-dark cycles. Results showed significant shift in metabolic activities including photosynthesis, respiration, biological nitrogen fixation (BNF), and proteostasis to different growth conditions. We identified 14 nitrogenase enzymes which were among the most highly expressed proteins in the dark under nitrogen-fixing conditions, emphasizing their importance in BNF. Nitrogenase enzymes were not expressed under non nitrogen fixing conditions, suggesting a regulatory mechanism based on nitrogen availability. The synthesis of key respiratory enzymes and uptake hydrogenase (HupSL) synchronized with the synthesis of nitrogenase indicating a coordinated regulation of processes involved in energy production and BNF. Data suggests alternative pathways that cells utilize, such as oxidative pentose phosphate (OPP) and 2-oxoglutarate (2-OG) pathways, to produce ATP and support bioenergetic BNF. Data also indicates the important role of uptake hydrogenase for the removal of O2 to support BNF. Overall, this study expands upon our knowledge regarding molecular responses of Crocosphaera 51142 to nitrogen and light-dark phases, shedding light on potential applications and optimization for renewable energy.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.