Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons

Geiszler, Philippine C. and Ugun-Klusek, Aslihan and Lawler, Karen and Pardon, Marie-Christine and Yuchun, Ding and Bai, Li and Daykin, Clare and Auer, Dorothee P. and Bedford, Lynn (2018) Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons. Scientific Reports, 8 . 4833/1-4833/13. ISSN 2045-2322

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Abstract

Metabolite profiling is an important tool that may better capture the multiple features of neurodegeneration. With the considerable parallels between mouse and human metabolism, the use of metabolomics in mouse models with neurodegenerative pathology provides mechanistic insight and ready translation into aspects of human disease. Using 400 MHz nuclear magnetic resonance spectroscopy we have carried out a temporal region-specific investigation of the metabolome of neuron-specific 26S proteasome knockout mice characterised by progressive neurodegeneration and Lewy-like inclusion formation in the forebrain. An early significant decrease in N-acetyl aspartate revealed evidence of neuronal dysfunction before cell death that may be associated with changes in brain neuroenergetics, underpinning the use of this metabolite to track neuronal health. Importantly, we show early and extensive activation of astrocytes and microglia in response to targeted neuronal dysfunction in this context, but only late changes in myo-inositol; the best established glial cell marker in magnetic resonance spectroscopy studies, supporting recent evidence that additional early neuroinflammatory markers are needed. Our results extend the limited understanding of metabolite changes associated with gliosis and provide evidence that changes in glutamate homeostasis and lactate may correlate with astrocyte activation and have biomarker potential for tracking neuroinflammation.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine > Division of Clinical Neuroscience
University of Nottingham, UK > Faculty of Science > School of Computer Science
University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Life Sciences
University of Nottingham, UK > Faculty of Science > School of Pharmacy
Identification Number: 10.1038/s41598-018-23155-2
Depositing User: Eprints, Support
Date Deposited: 19 Mar 2018 13:32
Last Modified: 19 Mar 2018 13:39
URI: http://eprints.nottingham.ac.uk/id/eprint/50317

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