TY - JOUR
T1 - The mouse brain metabolome
T2 - Region-specific signatures and response to excitotoxic neuronal injury
AU - Jaeger, Christian
AU - Glaab, Enrico
AU - Michelucci, Alessandro
AU - Binz, Tina M.
AU - Koeglsberger, Sandra
AU - Garcia, Pierre
AU - Trezzi, Jean Pierre
AU - Ghelfi, Jenny
AU - Balling, Rudi
AU - Buttini, Manuel
N1 - Funding Information:
Supported by internal funding from the Luxembourg Centre for Systems Biomedicine , University of Luxembourg.
Publisher Copyright:
© 2015 American Society for Investigative Pathology.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - Neurodegeneration is a multistep process characterized by a multitude of molecular entities and their interactions. Systems analyses, or omics approaches, have become an important tool in characterizing this process. Although RNA and protein profiling made their entry into this field a couple of decades ago, metabolite profiling is a more recent addition. The metabolome represents a large part or all metabolites in a tissue, and gives a snapshot of its physiology. By using gas chromatography coupled to mass spectrometry, we analyzed the metabolic profile of brain regions of the mouse, and found that each region is characterized by its own metabolic signature. We then analyzed the metabolic profile of the mouse brain after excitotoxic injury, a mechanism of neurodegeneration implicated in numerous neurological diseases. More important, we validated our findings by measuring, histologically and molecularly, actual neurodegeneration and glial response. We found that a specific global metabolic signature, best revealed by machine learning algorithms, rather than individual metabolites, was the most robust correlate of neuronal injury and the accompanying gliosis, and this signature could serve as a global biomarker for neurodegeneration. We also observed that brain lesioning induced several metabolites with neuroprotective properties. Our results deepen the understanding of metabolic changes accompanying neurodegeneration in disease models, and could help rapidly evaluate these changes in preclinical drug studies.
AB - Neurodegeneration is a multistep process characterized by a multitude of molecular entities and their interactions. Systems analyses, or omics approaches, have become an important tool in characterizing this process. Although RNA and protein profiling made their entry into this field a couple of decades ago, metabolite profiling is a more recent addition. The metabolome represents a large part or all metabolites in a tissue, and gives a snapshot of its physiology. By using gas chromatography coupled to mass spectrometry, we analyzed the metabolic profile of brain regions of the mouse, and found that each region is characterized by its own metabolic signature. We then analyzed the metabolic profile of the mouse brain after excitotoxic injury, a mechanism of neurodegeneration implicated in numerous neurological diseases. More important, we validated our findings by measuring, histologically and molecularly, actual neurodegeneration and glial response. We found that a specific global metabolic signature, best revealed by machine learning algorithms, rather than individual metabolites, was the most robust correlate of neuronal injury and the accompanying gliosis, and this signature could serve as a global biomarker for neurodegeneration. We also observed that brain lesioning induced several metabolites with neuroprotective properties. Our results deepen the understanding of metabolic changes accompanying neurodegeneration in disease models, and could help rapidly evaluate these changes in preclinical drug studies.
UR - http://www.scopus.com/inward/record.url?scp=84929966371&partnerID=8YFLogxK
U2 - 10.1016/j.ajpath.2015.02.016
DO - 10.1016/j.ajpath.2015.02.016
M3 - Article
C2 - 25934215
AN - SCOPUS:84929966371
SN - 0002-9440
VL - 185
SP - 1699
EP - 1712
JO - American Journal of Pathology
JF - American Journal of Pathology
IS - 6
ER -