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

Geiszler, P.C., Ugun-Klusek, A. ORCID: 0000-0002-0199-0275, Lawler, K., Pardon, M.-C., Yuchun, D., Bai, L., Daykin, C.A., Auer, D.P. and Bedford, L., 2018. Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons. Scientific Reports, 8: 4833. ISSN 2045-2322

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Abstract

Metabolite profling 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 400MHz nuclear magnetic resonance spectroscopy we have carried out a temporal region-specifc investigation of the metabolome of neuron-specifc 26S proteasome knockout mice characterised by progressive neurodegeneration and Lewy-like inclusion formation in the forebrain. An early signifcant 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 neuroinfammatory 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 neuroinfammation.

Item Type: Journal article
Publication Title: Scientific Reports
Creators: Geiszler, P.C., Ugun-Klusek, A., Lawler, K., Pardon, M.-C., Yuchun, D., Bai, L., Daykin, C.A., Auer, D.P. and Bedford, L.
Publisher: Springer Nature
Date: 19 March 2018
Volume: 8
ISSN: 2045-2322
Identifiers:
NumberType
10.1038/s41598-018-23155-2DOI
Rights: Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018.
Divisions: Schools > School of Science and Technology
Depositing User: Jill Tomkinson
Date Added: 27 Mar 2018 09:18
Last Modified: 27 Mar 2018 09:18
URI: http://irep.ntu.ac.uk/id/eprint/33101

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