Iron Deficiency Impairs Mitochondrial Energetics and Early Axonal Growth and Branching in Developing Hippocampal Neurons
Mendez, D. C.; Devgun, K.; Monko, T. R.; Carlson, L. H.; Mickelson, D. J.; Lanier, L. M.; Georgieff, M. K.; Bastian, T. W.
Show abstract
Each stage of neuronal development (i.e., proliferation, differentiation, migration, neurite outgrowth and synapse formation) requires functional and highly coordinated metabolic activity to ultimately ensure proper sculpting of complex neural networks. Energy deficits underlie many neurodevelopmental, neuropsychiatric and neurodegenerative diseases implicating mitochondria as a potential therapeutic target. Iron is necessary for neuronal energy output through its direct role in mitochondrial oxidative phosphorylation. Iron deficiency (ID) reduces mitochondrial respiratory and energy capacity in developing hippocampal neurons, causing permanently simplified dendritic arbors and impaired learning and memory. However, the effect of ID on early axonogenesis has not been explored. We used an embryonic mixed-sex primary mouse hippocampal neuron culture model of developmental ID to evaluate mitochondrial respiration and dynamics and effects on axonal morphology. At 7 days in vitro (DIV), ID impaired mitochondrial oxidative phosphorylation capacity and stunted growth of both the primary axon and branches, without affecting branch number. Mitochondrial motility was not altered by ID, suggesting that mitochondrial energy production --- not trafficking --- underlie the axon morphological deficits. These findings provide the first link between iron-dependent neuronal energy production and early axon structural development and emphasize the importance of maintaining sufficient iron during gestation to prevent the negative consequences of ID on brain health across the lifespan. Significance StatementThis study used a primary mouse hippocampal neuron culture model of iron deficiency to address how disruption of iron-regulated mitochondrial activities affects axonal development. After axon initiation but prior to rapid dendrite outgrowth, iron chelation reduced mitochondrial oxidative phosphorylation capacity and stunted the growth of the primary axon and branches but without affecting branch number. Mitochondrial motility was not altered in iron-deficient axons, indicating that reduced neuronal energetic capacity and not impaired axonal mitochondrial trafficking may underlie these morphological deficits. Many neurodevelopmental, neuropsychiatric, and neurodegenerative disorders are characterized by iron and/or mitochondrial dysregulation, highlighting the importance of advancing knowledge on the effects of mitochondrial deficits in early life as it pertains to optimizing brain health throughout the lifespan.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- MicroRNA-210 Knockout Alters Dendritic Density and Behavioural Flexibility 95%
- Knockdown of astrocytic monocarboxylate transporter 4 (MCT4) in the motor cortex leads to loss of dendritic spines and a deficit in motor learning 94%
- HDAC4 Inhibits NMDA Receptor-Mediated Stimulation of Neurogranin Expression 93%
Similar papers in this journal
Similar papers in this journal
- Dopamine-iron homeostasis interaction rescues mitochondrial fitness in Parkinson's disease 94%
- Feed-forward metabotropic signaling by Cav1 Ca2+ channels supports pacemaking in pedunculopontine cholinergic neurons 93%
- Induced long-term potentiation improves synaptic stability and restores network function in ALS motor neurons 93%
Similar papers in this journal
- BDNF/TrkB signaling endosomes in axons coordinate CREB/mTOR activation and protein synthesis in the cell body to induce dendritic growth in cortical neurons. 94%
- Presynaptic APP levels and synaptic homeostasis are regulated by Akt phosphorylation of Huntingtin 93%
- SNARE protein tomosyn regulates dense core vesicle composition but not exocytosis in mammalian neurons 93%
"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.