Metabolism is increasingly appreciated for its active role in tissue development during embryogenesis, particularly its discrete instruction in brain growth and formation. Catabolic programs are essential for the breakdown of nutrients to provide energy for anabolic processes that construct macromolecules and cell structures required for tissue expansion and organization (Rajan and Fame, 2024). Nutrient availability and environmental factors influence the bioenergetic state of developing cells, and instruct cellular and tissue-specific niches throughout embryogenesis (Traxler et al., 2021; Andrews and Pearson, 2024). Intracellular metabolism uses external cues from the maternal and embryonic environments to modify gene expression through epigenetic modifications and genomic accessibility (Reid et al., 2017; Sánchez-Ramírez et al., 2024). Therefore, assessing the relationship between the cell metabolome and developmental programs can provide insights into the mechanisms that regulate proliferation, differentiation and maturation during brain formation.
Energy metabolism changes in neural progenitors influence gliogenesis
A recent preprint by Saha and colleagues highlights the importance of nutrient availability for brain development by examining the effects of methionine restriction on cellular- and tissue-level changes (Saha et al., 2024 preprint). Methionine, in conjunction with other metabolites, is interconnected with numerous metabolic pathways and signaling cascades that coordinate cell function and developmental programs (Sanderson et al., 2019). This study evaluated the impact of maternal dietary methionine restriction in mice from embryonic day (E) 9.5 throughout gestation or exclusively during neurogenesis. The results demonstrate that neural progenitors display particular vulnerability, leading to downstream differentiation decreases in neurons or astrocytes. Progenitors display indicators of quiescence suggested by changes in proliferation, differentiation, epigenetic and metabolic markers. While restoring methionine levels rescued neuron production, there were continued differences in energy metabolism and methylation marks, presumably leading to compromised or delayed gliogenesis. These findings prompt further questions about how metabolic substrates coordinate developmental timing and impact cell fate decisions.
Mitochondrial fission impacts astrocyte morphology and organization of tiling in the cortex
In addition to nutrient availability, a recent preprint by Rodriguez Salazar and colleagues evaluates how mitochondrial dynamics influence astrocyte morphology and maturation in mice and rats (Salazar et al., 2024 preprint). During postnatal development, astrocytes undergo structural and functional changes to progress to a mature state, shifting from anabolic growth to catabolic support of increased energy demands (Zehnder et al., 2021; Marina et al., 2018). The balance of mitochondria fission, fusion and transport is essential for coordinating energy metabolism and specialized functions of astrocytes (Tábara et al., 2024). The authors discovered that Drp-1-mediated mitochondrial fission enables the localization of mitochondria to distal astrocyte processes to support higher degrees of branching and more-complex morphologies. The resulting high distal mitochondrial content is required to establish proper Cx43 gap junction protein abundance and an evenly dispersed astrocyte domain organization across the cortex. Their results indicate the importance of mitochondria dynamics to support structural changes in maturing astrocytes, which mediate complex intercellular, synaptic and metabolic regulation. Notably, mitochondria fission drives high glycolytic activity due to decreased oxidative phosphorylation efficiency and high ROS production (Zong et al., 2024; Chen and Chan, 2017). Mature astrocytes have high glycolysis influx and lactate production that provides metabolic fuel for surrounding neurons. The relationship between mitochondria fission, glycolytic activity and morphological complexity during astrocyte maturation supports cortical development.
Metabolism impacts cell composition and maturation, with implications for tissue organization
Collectively, these studies highlight the unique metabolic requirements of discrete cellular populations based on their specialized functions in the rodent cortex. Each study indicates how metabolic rewiring is required to accommodate dynamic changes in cell activities throughout development. Metabolic changes to progenitor cells and their progeny influence their capacity for self-renewal or differentiation (Zhang et al., 2018; Folmes et al., 2012). Saha and colleagues demonstrate the impact of nutrient availability on progenitor development and the consequences for neuron and astrocyte production. Their results point to epigenetic modifications in response to methionine restriction that correspond to altered progenitor quiescence, resulting in decreased proliferation and impaired neurogenesis or gliogenesis, depending on duration. Rodriguez Salazar and colleagues focus on the supportive role of mitochondria in the maturation of terminally differentiated astrocytes. Their results demonstrate the importance of mitochondria dynamics during later stages of development to support increasingly complex astrocytic activities during cortical maturation. Together, these studies clarify the importance of metabolism across developmental stages. While the metabolic change, developmental window, duration of perturbation and assessments are distinct, both manuscripts observe the consequences of metabolic disturbances on glial development, whether in production or maturation. In addition to cell changes, both indicate tissue-level alterations, either through cortical tiling of astrocyte territory organization or spatial changes to cortical laminae. Collectively, these studies point to unique cell-specific metabolic activity that regulates neural tissue development and may have a longitudinal impact on brain health and homeostasis.
Why metabolism matters and next steps
As these studies describe, changes in brain metabolism affect cell composition and tissue organizational features. Of note, maternal dietary methionine restriction had the largest effect on brain weight, compared to other organs, suggesting that neurodevelopmental programs may be particularly vulnerable to nutrient availability changes. In particular, astrocytes may be preferentially impacted, perhaps due to their unique metabolic role in the central nervous system (CNS) (Marina et al., 2018; Xiong et al., 2022). While a proportional decrease of cell types during development can be catastrophic for long-term function (Jourdon et al., 2023; Klingler et al., 2021), these studies also suggest a certain pliability to metabolic fluctuations and capacity to rescue changes, if reversed during relevant developmental windows. Restoration of methionine rescued the loss of neurons after dietary reversal, and rescue of Drp1 restored mitochondrial fission-regulated morphology. These changes highlight the capacity to modulate metabolic activities and potentially therapeutically target dysfunctional pathways implicated in neurological disease. A variety of neurodevelopmental disorders, including autism and attention deficit hyperactivity disorder (ADHD), have errors in energy metabolism; thus, understanding the origins and potential for treatment are valuable (Oyarzábal et al., 2021; Pinto Payares et al., 2024).
Moving forward, functional measurements of metabolic shifts throughout development are required to determine how bioenergetics are affected by environmental changes and the consequences for cell and tissue development. Mitochondrial dynamics indicators and biosensors can assess real-time, cell-specific changes using microscopy (Cambronne et al., 2016; Glancy, 2020). Metabolomic methods using magnetic resonance (quantifiable) or mass spectrometry (targeted or untargeted) can comprehensively characterize metabolic profiles of cells or map shifts in pathway activity with isotopic tracers (Johnson et al., 2016; Antoniewicz, 2018). The use of gold-standard and cutting-edge technologies paired with a temporal lens of development will continue to illuminate how metabolism orchestrates neurodevelopmental programs.
Footnotes
Funding
This work was supported by the National Institutes of Health (R00MH125329) and by an Arizona Biomedical Research Centre grant (RFGA2022-010-16).
References
- Andrews, M. G. and Pearson, C. A. (2024). Toward an understanding of glucose metabolism in radial glial biology and brain development. Life. Sci. Alliance 7, e202302193. 10.26508/lsa.202302193 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Antoniewicz, M. R. (2018). A guide to 13C metabolic flux analysis for the cancer biologist. Exp. Mol. Med. 50, 1-13. 10.1038/s12276-018-0060-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cambronne, X. A., Stewart, M. L., Kim, D. H., Jones-Brunette, A. M., Morgan, R. K., Farrens, D. L., Cohen, M. S. and Goodman, R. H. (2016). Biosensor reveals multiple sources for mitochondrial NAD+. Science 352, 1474-1477. 10.1126/science.aad5168 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen, H. and Chan, D. C. (2017). Mitochondrial dynamics in regulating the unique phenotypes of cancer and stem cells. Cell Metab. 26, 39-48. 10.1016/j.cmet.2017.05.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Folmes, C. D. L., Dzeja, P. P., Nelson, T. J. and Terzic, A. (2012). Metabolic plasticity in stem cell homeostasis and differentiation. Cell Stem Cell 11, 596-606. 10.1016/j.stem.2012.10.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Glancy, B. (2020). Visualizing mitochondrial form and function within the cell. Trends Mol. Med. 26, 58-70. 10.1016/j.molmed.2019.09.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnson, C. H., Ivanisevic, J. and Siuzdak, G. (2016). Metabolomics: beyond biomarkers and towards mechanisms. Nat. Rev. Mol. Cell Biol. 17, 451-459. 10.1038/nrm.2016.25 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jourdon, A., Wu, F., Mariani, J., Capauto, D., Norton, S., Tomasini, L., Amiri, A., Suvakov, M., Schreiner, J. D., Jang, Y.et al. (2023). Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis. Nat. Neurosci. 26, 1505-1515. 10.1038/s41593-023-01399-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Klingler, E., Francis, F., Jabaudon, D. and Cappello, S. (2021). Mapping the molecular and cellular complexity of cortical malformations. Science 371, eaba4517. 10.1126/science.aba4517 [DOI] [PubMed] [Google Scholar]
- Marina, N., Turovsky, E., Christie, I. N., Hosford, P. S., Hadjihambi, A., Korsak, A., Ang, R., Mastitskaya, S., Sheikhbahaei, S., Theparambil, S. M.et al. (2018). Brain metabolic sensing and metabolic signaling at the level of an astrocyte. Glia 66, 1185-1199. 10.1002/glia.23283 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Oyarzábal, A., Musokhranova, U., Barros, L. and García-Cazorla, A. (2021). Energy metabolism in childhood neurodevelopmental disorders. EBioMedicine 69, 103474. 10.1016/j.ebiom.2021.103474 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pinto Payares, D. V., Spooner, L., Vosters, J., Dominguez, S., Patrick, L., Harris, A. and Kanungo, S. (2024). A systematic review on the role of mitochondrial dysfunction/disorders in neurodevelopmental disorders and psychiatric/behavioral disorders. Front. Psychiatry 15, 1389093. 10.3389/fpsyt.2024.1389093 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rajan, A. and Fame, R. M. (2024). Brain development and bioenergetic changes. Neurobiol. Dis. 199, 106550. 10.1016/j.nbd.2024.106550 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Reid, M. A., Dai, Z. and Locasale, J. W. (2017). The impact of cellular metabolism on chromatin dynamics and epigenetics. Nat. Cell Biol. 19, 1298-1306. 10.1038/ncb3629 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Saha, S., Debacq, C., Audouard, C., Jungas, T., Dupre, P., Fawal, M.-A., Chapat, C., Michaud, H.-A., Le Cam, L., Lacroix, M.et al. (2024). Acute dietary methionine restriction highlights sensitivity of neocortex development to metabolic variations. bioRxiv. 10.1101/2024.09.10.612174 [DOI] [Google Scholar]
- Salazar, M. P. R., Kolanukuduru, S., Ramirez, V., Lyu, B., Sejourne, G., Sesaki, H., Yu, G. and Eroglu, C. (2024). Mitochondrial fission controls astrocyte morphogenesis and organization in the cortex. bioRxivorg. 10.1101/2024.10.22.619706 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sánchez-Ramírez, E., Ung, T. P. L., Stringari, C. and Aguilar-Arnal, L. (2024). Emerging functional connections between metabolism and epigenetic remodeling in neural differentiation. Mol. Neurobiol 61, 6688-6707. 10.1007/s12035-024-04006-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sanderson, S. M., Gao, X., Dai, Z. and Locasale, J. W. (2019). Methionine metabolism in health and cancer: a nexus of diet and precision medicine. Nat. Rev. Cancer 19, 625-637. 10.1038/s41568-019-0187-8 [DOI] [PubMed] [Google Scholar]
- Tábara, L.-C., Segawa, M. and Prudent, J. (2024). Molecular mechanisms of mitochondrial dynamics. Nat. Rev. Mol. Cell Biol. 10.1038/s41580-024-00785-1 [DOI] [PubMed] [Google Scholar]
- Traxler, L., Lagerwall, J., Eichhorner, S., Stefanoni, D., D'alessandro, A. and Mertens, J. (2021). Metabolism navigates neural cell fate in development, aging and neurodegeneration. Dis. Model. Mech. 14, dmm048993. 10.1242/dmm.048993 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Xiong, X.-Y., Tang, Y. and Yang, Q.-W. (2022). Metabolic changes favor the activity and heterogeneity of reactive astrocytes. Trends Endocrinol. Metab. 33, 390-400. 10.1016/j.tem.2022.03.001 [DOI] [PubMed] [Google Scholar]
- Zehnder, T., Petrelli, F., Romanos, J., De Oliveira Figueiredo, E. C., Lewis, T. L., Déglon, N., Polleux, F., Santello, M. and Bezzi, P. (2021). Mitochondrial biogenesis in developing astrocytes regulates astrocyte maturation and synapse formation. Cell Rep. 35, 108952. 10.1016/j.celrep.2021.108952 [DOI] [PubMed] [Google Scholar]
- Zhang, J., zhao, J., Dahan, P., Lu, V., Zhang, C., Li, H. and Teitell, M. A. (2018). Metabolism in pluripotent stem cells and early mammalian development. Cell Metab. 27, 332-338. 10.1016/j.cmet.2018.01.008 [DOI] [PubMed] [Google Scholar]
- Zong, Y., Li, H., Liao, P., Chen, L., Pan, Y., Zheng, Y., Zhang, C., Liu, D., Zheng, M. and Gao, J. (2024). Mitochondrial dysfunction: mechanisms and advances in therapy. Signal Transduct. Target. Ther. 9, 124. 10.1038/s41392-024-01839-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
