Elsevier

Analytica Chimica Acta

Volume 1136, 1 November 2020, Pages 168-177
Analytica Chimica Acta

Parallel metabolomics and lipidomics enables the comprehensive study of mouse brain regional metabolite and lipid patterns

https://doi.org/10.1016/j.aca.2020.09.051Get rights and content

Highlights

  • A parallel metabolomics and lipidomics analytical pipeline was developed to profile brain regions with minimal tissue weight.

  • The integrated analytical workflow allows for the study of brain regional metabolite and lipid patterns.

  • The comprehensive region-specific metabolomic and lipidomic profiles enables systems-level brain regional study.

Abstract

Global profiling of the metabolome and lipidome of specific brain regions is essential to understanding the cellular and molecular mechanisms regulating brain activity. Given the limited amount of starting material, conventional mouse studies comparing brain regions have mainly targeted a set of known metabolites in large brain regions (e.g., cerebrum, cortex). In this work, we developed a multimodal analytical pipeline enabling parallel analyses of metabolomic and lipidomic profiles from anatomically distinct mouse brain regions starting with less than 0.2 mg of protein content. This analytical pipeline is composed of (1) sonication-based tissue homogenization, (2) parallel metabolite and lipid extraction, (3) BCA-based sample normalization, (4) ultrahigh performance liquid chromatography-mass spectrometry-based multimodal metabolome and lipidome profiling, (5) streamlined data processing, and (6) chord plot-based data visualization. We applied this pipeline to the study of four brain regions in males including the amygdala, dorsal hippocampus, nucleus accumbens and ventral tegmental area. With this novel approach, we detected over 5000 metabolic and 6000 lipid features, among which 134 metabolites and 479 lipids were directly confirmed via automated MS2 spectral matching. Interestingly, our analysis identified unique metabolic and lipid profiles in each brain regions. Furthermore, we identified functional relationships amongst metabolic and lipid subclasses, potentially underlying cellular and functional differences across all four brain regions. Overall, our novel workflow generates comprehensive region-specific metabolomic and lipidomic profiles using very low amount of brain sub-regional tissue sample, which could be readily integrated with region-specific genomic, transcriptomic, and proteomic data to reveal novel insights into the molecular mechanisms underlying the activity of distinct brain regions.

Section snippets

Author contribution

Huaxu YuNathaniel VillanuevaThibault BittarEric ArsenaultBenoit LabontéTao Huan

Materials and methods

Overall workflow. The schematic analytical workflow is presented in Fig. 1. Brain tissue was collected and preserved according to standard operating procedure (SOP) optimized to assure sample quality. The collected tissue sample was then mixed with methanol (MeOH) and sonicated for 30 min for tissue homogenization. Subsequently, methyl tert-butyl ether (MTBE) followed by water (H2O) was added to separate the homogenized solution into two layers, in which the upper layer was enriched with

Tissue homogenization and dual extraction

An appropriate tissue homogenization method should be able to efficiently break down tissue and release its metabolome content for omics-level profiling. Considering that the brain is a soft tissue and smaller brain regions are limited in tissue amount (0.2 mg of protein content), we developed a homogenization method based on sonication in an ice bath. Briefly, the brain tissue was first mixed with 270 μL methanol then sonicated in an ice bath for 30 min. During the homogenization process, we

Conclusion

Metabolites and lipids play an essential role in modulating the activity of neuronal populations across brain regions. In this work, we developed a robust and sensitive analytical workflow, requiring less than 0.2 mg of protein content, to compare metabolomic and lipidomic profiles across brain regions and provide unique information about localized metabolic activity. In our proof-of-principle, over 5000 metabolic and 6000 lipid features were detected from each brain region. Our quantitative

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was funded by University of British Columbia Start-up Grant (F18-03001), Canada Foundation for Innovation [CFI 38159]. UBC Support for Teams to Advance Interdisciplinary Research Award [F19-05720], New Frontiers in Research Fund/Exploration [NFRFE-2019-00789], National Science and Engineering Research Council (NSERC) Discovery Grant [RGPIN-2020-04895], and NSERC Discovery Launch Supplement [DGECR-2020-00189]. BL holds a Sentinelle Nord Research Chair, is supported by a NARSAD young

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