Current technical approaches to brain energy metabolism

L. Felipe Barros*, Juan P. Bolaños, Gilles Bonvento, Anne Karine Bouzier-Sore, Angus Brown, Johannes Hirrlinger, Sergey Kasparov, Frank Kirchhoff, Anne N. Murphy, Luc Pellerin, Michael B. Robinson, Bruno Weber

*Corresponding author for this work

Research output: Contribution to journalReview article (Academic Journal)peer-review

19 Citations (Scopus)
323 Downloads (Pure)

Abstract

Neuroscience is a technology-driven discipline and brain energy metabolism is no exception. Once satisfied with mapping metabolic pathways at organ level, we are now looking to learn what it is exactly that metabolic enzymes and transporters do and when, where do they reside, how are they regulated, and how do they relate to the specific functions of neurons, glial cells, and their subcellular domains and organelles, in different areas of the brain. Moreover, we aim to quantify the fluxes of metabolites within and between cells. Energy metabolism is not just a necessity for proper cell function and viability but plays specific roles in higher brain functions such as memory processing and behavior, whose mechanisms need to be understood at all hierarchical levels, from isolated proteins to whole subjects, in both health and disease. To this aim, the field takes advantage of diverse disciplines including anatomy, histology, physiology, biochemistry, bioenergetics, cellular biology, molecular biology, developmental biology, neurology, and mathematical modeling. This article presents a well-referenced synopsis of the technical side of brain energy metabolism research. Detail and jargon are avoided whenever possible and emphasis is given to comparative strengths, limitations, and weaknesses, information that is often not available in regular articles.

Original languageEnglish
Pages (from-to)1138-1159
Number of pages22
JournalGlia
Volume66
Issue number6
Early online date7 Nov 2017
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • in vitro
  • in vivo
  • organization level
  • spatio-temporal resolution

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