Organization of a functional glycolytic metabolon on mitochondria for metabolic efficiency.

Glucose, the primary cellular energy source, is metabolized through glycolysis initiated by the rate-limiting enzyme hexokinase (HK). In energy-demanding tissues like the brain, HK1 is the dominant isoform, primarily localized on mitochondria, and is crucial for efficient glycolysis-oxidative phosphorylation coupling and optimal energy generation. This study unveils a unique mechanism regulating HK1 activity, glycolysis and the dynamics of mitochondrial coupling, mediated by the metabolic sensor enzyme O-GlcNAc transferase (OGT). OGT catalyses reversible O-GlcNAcylation, a post-translational modification influenced by glucose flux. Elevated OGT activity induces dynamic O-GlcNAcylation of the regulatory domain of HK1, subsequently promoting the assembly of the glycolytic metabolon on the outer mitochondrial membrane. This modification enhances the mitochondrial association with HK1, orchestrating glycolytic and mitochondrial ATP production. Mutation in HK1's O-GlcNAcylation site reduces ATP generation in multiple cell types, specifically affecting metabolic efficiency in neurons. This study reveals a previously unappreciated pathway that links neuronal metabolism and mitochondrial function through OGT and the formation of the glycolytic metabolon, providing potential strategies for tackling metabolic and neurological disorders.

Neuronal activity-driven O-GlcNAcylation promotes mitochondrial plasticity.

Neuronal activity is an energy-intensive process that is largely sustained by instantaneous fuel utilization and ATP synthesis. However, how neurons couple ATP synthesis rate to fuel availability is largely unknown. Here, we demonstrate that the metabolic sensor enzyme O-linked N-acetyl glucosamine (O-GlcNAc) transferase regulates neuronal activity-driven mitochondrial bioenergetics in hippocampal and cortical neurons. We show that neuronal activity upregulates O-GlcNAcylation in mitochondria. Mitochondrial O-GlcNAcylation is promoted by activity-driven glucose consumption, which allows neurons to compensate for high energy expenditure based on fuel availability. To determine the proteins that are responsible for these adjustments, we mapped the mitochondrial O-GlcNAcome of neurons. Finally, we determine that neurons fail to meet activity-driven metabolic demand when O-GlcNAcylation dynamics are prevented. Our findings suggest that O-GlcNAcylation provides a fuel-dependent feedforward control mechanism in neurons to optimize mitochondrial performance based on neuronal activity. This mechanism thereby couples neuronal metabolism to mitochondrial bioenergetics and plays a key role in sustaining energy homeostasis.

FluxNorm: Toolbox for metabolic flux assay normalization by in situ cell counting.

Plate-based quantitative metabolic flux analysis has emerged as the central technology to examine cellular metabolism and mitochondrial bioenergetics. However, accurate interpretation of metabolic activity between different experimental conditions in multi-well microplates requires data normalization based on in situ cell counts. Here, we describe FluxNorm, a platform-independent semi-automated computational workflow, validated for three different cell types, to normalize cell density for accurate assessment of cellular bioenergetics.

Mitochondrial DNA Dynamics in Reprogramming to Pluripotency.

Mammalian cells, with the exception of erythrocytes, harbor mitochondria, which are organelles that provide energy, intermediate metabolites, and additional activities to sustain cell viability, replication, and function. Mitochondria contain multiple copies of a circular genome called mitochondrial DNA (mtDNA), whose individual sequences are rarely identical (homoplasmy) because of inherited or sporadic mutations that result in multiple mtDNA genotypes (heteroplasmy). Here, we examine potential mechanisms for maintenance or shifts in heteroplasmy that occur in induced pluripotent stem cells (iPSCs) generated by cellular reprogramming, and further discuss manipulations that can alter heteroplasmy to impact stem and differentiated cell performance. This additional insight will assist in developing more robust iPSC-based models of disease and differentiated cell therapies.