Characterization of the Lipidome of Neurons in Mouse Brain Nuclei Using Imaging Mass Spectrometry

Understanding the molecular composition of the brain at cellular level is essential for deciphering the metabolic alterations associated with brain diseases. Furthermore, the different prevalence of some neurological diseases between males and females highlight the importance of incorporating gender factor in such studies. Here, we demonstrate that using imaging mass spectrometry in negative polarity it is possible to isolate and characterize the lipidome of specific neuronal populations in the mouse brain, including the locus coeruleus (LC), mesencephalic neurons and the substantia nigra pars compacta (SNc). Neuronal identity was validated through immunofluorescence on adjacent serial sections. Comparative analysis revealed that each neuronal population presents a distinct and well-defined lipidic profile, with differences extending across all lipid classes analyzed. Regarding sex-based differences, we found discrete differences in phosphatidylcholine/phosphatidylethanolamine-ether, phosphatidylinositol and sphingomyelin LC neurons. Lipidomic differences were more pronounced in mesencephalic neurons, whereas no significant sex-dependant differences were observed in SNc lipid composition. These findings lay the groundwork for future studies aimed at identifying lipid metabolic dysregulations in the context of neurodegenerative diseases.

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Journal
Analytical Chemistry
Published
2026-01-13
DOI
https://doi.org/10.1021/acs.analchem.5c08016
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
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article

Characterization of the Lipidome of Neurons in Mouse Brain Nuclei Using Imaging Mass Spectrometry

Yuri Freddy Peña Rueda, Laura De Las Heras-García, J. Arístegui Fernández, Cristina Huergo et al.
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
article

Characterization of the Lipidome of Neurons in Mouse Brain Nuclei Using Imaging Mass Spectrometry

Yuri Freddy Peña Rueda, Laura De Las Heras-García, J. Arístegui Fernández, Cristina Huergo, Jone Razquin, Cristina Miguélez
article en

Abstract

Understanding the molecular composition of the brain at cellular level is essential for deciphering the metabolic alterations associated with brain diseases. Furthermore, the different prevalence of some neurological diseases between males and females highlight the importance of incorporating gender factor in such studies. Here, we demonstrate that using imaging mass spectrometry in negative polarity it is possible to isolate and characterize the lipidome of specific neuronal populations in the mouse brain, including the locus coeruleus (LC), mesencephalic neurons and the substantia nigra pars compacta (SNc). Neuronal identity was validated through immunofluorescence on adjacent serial sections. Comparative analysis revealed that each neuronal population presents a distinct and well-defined lipidic profile, with differences extending across all lipid classes analyzed. Regarding sex-based differences, we found discrete differences in phosphatidylcholine/phosphatidylethanolamine-ether, phosphatidylinositol and sphingomyelin LC neurons. Lipidomic differences were more pronounced in mesencephalic neurons, whereas no significant sex-dependant differences were observed in SNc lipid composition. These findings lay the groundwork for future studies aimed at identifying lipid metabolic dysregulations in the context of neurodegenerative diseases.

Analytical ChemistryVol. 98(3)
Centre National de la Recherche Scientifique (FR), Université de Bordeaux (FR), University of the Basque Country (ES), German Center for Neurodegenerative Diseases (DE), Institut des Maladies Neurodégénératives (FR), BioCruces Health research Institute (ES), Institute for Neurodegenerative Disorders (US)
Gender equality
Openalex Percentile: Top 90%
Metabolomics and Mass Spectrometry Studies
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Characterization of the Lipidome of Neurons in Mouse Brain Nuclei Using Imaging Mass Spectrometry — Yuri Freddy Peña Rueda, Laura De Las Heras-García, et al. · Analytical Chemistry (2026) | TGRS Research Map | TGRS