Mass spectrometry imaging of lipids: Untargeted consensus spectra reveal spatial distributions in Niemann-Pick disease type C1

Fernando Tobias, Matthew T. Olson, Stephanie M. Cologna*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Mass spectrometry imaging (MSI) is a tool to rapidly map the spatial location of analytes without the need for tagging or a reporter system. Niemann-Pick disease type C1 (NPC1) is a neurodegenerative, lysosomal storage disorder characterized by accumulation of unesterified cholesterol and sphingolipids in the endo-lysosomal system. Here, we use MSI to visualize lipids including cholesterol in cerebellar brain tissue from the NPC1 symptomatic mouse model and unaffected controls. To complement the imaging studies, a data-processing pipeline was developed to generate consensus mass spectra, thereby using both technical and biological image replicates to assess differences. The consensus spectra are used to determine true differences in lipid relative abundance; lipid distributions can be determined in an unbiased fashion without prior knowledge of location. We show the cerebellar distribution of gangliosides GM1, GM2, and GM3, including variants of lipid chain length. We also performed MALDI-MSI of cholesterol. Further analysis of lobules IV/V and X of the cerebellum gangliosides indicates regional differences. The specificity achieved highlights the power of MSI, and this new workflow demonstrates a universal approach for addressing reproducibility in imaging experiments applied to NPC1.

Original languageEnglish (US)
Pages (from-to)2446-2455
Number of pages10
JournalJournal of lipid research
Volume59
Issue number12
DOIs
StatePublished - 2018

Funding

This work was supported by the University of Illinois at Chicago and the Ara Parseghian Medical Research Foundation. Manuscript received 14 April 2018 and in revised form 24 September 2018. Published, JLR Papers in Press, September 28, 2018 DOI https://doi.org/10.1194/jlr.D086090 This work was supported by the University of Illinois at Chicago and the Ara Parseghian Medical Research Foundation.

Keywords

  • Cholesterol
  • Gangliosides
  • Lipidomics
  • Statistics

ASJC Scopus subject areas

  • Endocrinology
  • Biochemistry
  • Cell Biology

Fingerprint

Dive into the research topics of 'Mass spectrometry imaging of lipids: Untargeted consensus spectra reveal spatial distributions in Niemann-Pick disease type C1'. Together they form a unique fingerprint.

Cite this