Back

Dynamic assembly of malate dehydrogenase-citrate synthase multienzyme complex in the mitochondria

Omini, J.; Krassovskaya, I.; Dele-Osibanjo, T.; Pedersen, C.; Obata, T.

2025-06-20 biochemistry
10.1101/2025.06.16.659985 bioRxiv
Show abstract

The tricarboxylic acid (TCA) cycle enzymes, malate dehydrogenase (MDH1) and citrate synthase (CIT1), form a multienzyme complex called metabolon that channels intermediate, oxaloacetate, between the reaction centers of the enzymes. Since the MDH1-CIT1 metabolon enhances the pathway reactions in vitro, it is postulated to regulate the TCA cycle flux through dynamic assembly in response to cellular metabolic demands. Here, we demonstrated that yeast mitochondrial MDH1 and CIT1 dissociated when aerobic respiration was suppressed by the Crabtree effect and associated when the pathway flux was enhanced by acetate. Pharmacological TCA cycle inhibitions dissociated the complex, while electron transport chain inhibition enhanced the interaction. The multienzyme complex assembly was related to the mitochondrial matrix acidification and oxidation, as well as cellular levels of malate, fumarate, and citrate. These factors significantly affected the MDH1-CIT1 complex affinity in vitro. Especially the buffer pH significantly changed the MDH1-CIT1 affinity within the pH range between 6.0 and 7.0, which is observed in the mitochondrial matrix under physiological conditions. These results show a dynamic association and dissociation of a metabolon in the mitochondria and its relationship with pathway flux, supporting the metabolons role in metabolic regulation. Multiple factors, including pH and metabolite availabilities, possibly regulate MDH1-CIT1 interaction.

Published in eLife (predicted rank #1) · training set

Matching journals

The top 4 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.