Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
MALDI-TOF mass spectrometry imaging of sulfatide lipid expression in the CNS of mice with experimental autoimmune encephalomyelitis
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 28 February 2026

MALDI-TOF mass spectrometry imaging of sulfatide lipid expression in the CNS of mice with experimental autoimmune encephalomyelitis

  • Krista A. Berlin1,
  • Carol Chase Huizar2,
  • Celeste Garza2,3,
  • Thomas G. Forsthuber2 na1 &
  • …
  • Stephan B. H. Bach1 na1 

Scientific Reports , Article number:  (2026) Cite this article

  • 913 Accesses

  • 1 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biological techniques
  • Diseases
  • Neurology
  • Neuroscience

Abstract

Changes in the composition and distribution of the lipids comprising the myelin sheath surrounding neuronal axons have been under-explored in neuroinflammatory diseases such as multiple sclerosis due to the complexities in the analysis of lipids in biological tissues. The application of mass spectrometry-based molecular imaging enables the study of the molecular components of demyelinating tissue. This provides a much better understanding of the complex molecular processes involved in lipid metabolism and the underlying neuroinflammatory demyelinating processes. Uncovering alterations in the lipid profiles during the demyelination processes can potentially elucidate new molecular targets for novel MS drug therapies. We have utilized mass spectrometry imaging (MSI) of in-situ sulfatide lipids in mouse CNS tissue to reveal their spatial distribution and relative abundance. We show that they are generally confined to the white matter region of the cerebellum. We provide a molecular snapshot of lipid alterations at different disease stages of experimental autoimmune encephalomyelitis (EAE), the animal model for MS. Our results suggest that alterations in sulfatide expression are greatest prior to the onset of clinical disease symptoms and are systemic through the white matter and not restricted to the focal inflammatory lesions pathognomonic of EAE and human MS. The lipid mass maps generated by MSI provide novel insights into the dynamics of lipid alterations during neuroinflammation.

Data availability

The datasets used during the current study are available from the corresponding author upon reasonable request.

References

  1. Meghrajani, V., Bakre, A., Acharya, S. & Kumar, S. Multiple sclerosis: diagnosis and treatment management in allopathy. J. Pharm. Res. Int. 33, 1227–1234. https://doi.org/10.9734/jpri/2021/v33i60B34736 (2021).

    Google Scholar 

  2. Hamidi, V., Couto, E., Ringerike, T. & Klemp, M. A Multiple Treatment Comparison of Eleven Disease-Modifying Drugs Used for Multiple Sclerosis (Springer, 2017).

  3. Saab, A. S. & Nave, K. A. Myelin dynamics: protecting and shaping neuronal functions. Curr. Opin. Neurobiol. 47, 104–112. https://doi.org/10.1016/j.conb.2017.09.013 (2017).

    Google Scholar 

  4. Beyer, B. A. et al. Metabolomics-based discovery of a metabolite that enhances oligodendrocyte maturation. Nat. Chem. Biol. 14, 22–28. https://doi.org/10.1038/nchembio.2517 (2018).

    Google Scholar 

  5. Schaeren-Wiemers, N., van der Bijl, P. & Schwab, M. E. The UDP-galactose:ceramide galactosyltransferase: expression pattern in oligodendrocytes and Schwann cells during myelination and substrate preference for hydroxyceramide. J. Neurochem. 65, 2267–2278. https://doi.org/10.1046/j.1471-4159.1995.65052267.x (1995).

    Google Scholar 

  6. Grassi, S. et al. The role of 3-O-sulfogalactosylceramide, sulfatide, in the lateral organization of myelin membrane. Neurochem. Res. 41, 130–143. https://doi.org/10.1007/s11064-015-1747-2 (2016).

    Google Scholar 

  7. Chrast, R., Saher, G., Nave, K. A. & Verheijen, M. H. G. Lipid metabolism in myelinating glial cells: lessons from human inherited disorders and mouse models. J. Lipid Res. 52, 419–434. https://doi.org/10.1194/jlr.R009761 (2011).

    Google Scholar 

  8. Ryan, C. B., Choi, J. S., Al-Ali, H. & Lee, J. K. Myelin and non-myelin debris contribute to foamy macrophage formation after spinal cord injury. Neurobiol. Dis. 163, 105608. https://doi.org/10.1016/j.nbd.2021.105608 (2022).

    Google Scholar 

  9. Haidar, M. et al. Targeting lipophagy in macrophages improves repair in multiple sclerosis. Autophagy 18, 2697–2710. https://doi.org/10.1080/15548627.2022.2047343 (2022).

    Google Scholar 

  10. Peter, M. et al. Cerebrospinal fluid lipidomic biomarker signatures of demyelination for multiple sclerosis and Guillain-Barre syndrome. Sci. Rep. 10, 18380. https://doi.org/10.1038/s41598-020-75502-x (2020).

    Google Scholar 

  11. Nogueras, L. et al. Lipid profile of cerebrospinal fluid in multiple sclerosis patients: a potential tool for diagnosis. Sci. Rep. 9, 11313. https://doi.org/10.1038/s41598-019-47906-x (2019).

    Google Scholar 

  12. Eckhardt, M. The role and metabolism of sulfatide in the nervous system. Mol. Neurobiol. 37, 93–103. https://doi.org/10.1007/s12035-008-8022-3 (2008).

    Google Scholar 

  13. Thudichum, J. L. W. A treastise on the chemical constitution of the brain: based throughout upon original researches. Glasg. Med. J. 22, 363–364 (1884).

    Google Scholar 

  14. Blomqvist, M., Zetterberg, H., Blennow, K. & Mansson, J. E. Sulfatide in health and disease. The evaluation of sulfatide in cerebrospinal fluid as a possible biomarker for neurodegeneration. Mol. Cell. Neurosci. 116, 103670. https://doi.org/10.1016/j.mcn.2021.103670 (2021).

    Google Scholar 

  15. Takahashi, T. & Suzuki, T. Role of sulfatide in normal and pathological cells and tissues. J. Lipid Res. 53, 1437–1450. https://doi.org/10.1194/jlr.R026682 (2012).

    Google Scholar 

  16. Hirahara, Y. et al. Sulfatide species with various fatty acid chains in oligodendrocytes at different developmental stages determined by imaging mass spectrometry. J. Neurochem. 140, 435–450. https://doi.org/10.1111/jnc.13897 (2017).

    Google Scholar 

  17. Honke, K. Biosynthesis and biological function of sulfoglycolipids. Proc. Jpn Acad. Ser. B Phys. Biol. Sci. 89, 129–138. https://doi.org/10.2183/pjab.89.129 (2013).

    Google Scholar 

  18. Tracey, T. J., Steyn, F. J., Wolvetang, E. J. & Ngo, S. T. Neuronal lipid metabolism: multiple pathways driving functional outcomes in health and disease. Front. Mol. Neurosci. 11, 10. https://doi.org/10.3389/fnmol.2018.00010 (2018).

    Google Scholar 

  19. Kaya, I. et al. Delineating amyloid plaque associated neuronal sphingolipids in transgenic alzheimer’s disease mice (tgArcSwe) using MALDI imaging mass spectrometry. ACS Chem. Neurosci. 8, 347–355. https://doi.org/10.1021/acschemneuro.6b00391 (2017).

    Google Scholar 

  20. Magnusson, R. et al. RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases. Front. Mol. Biosci. 9, 916128. https://doi.org/10.3389/fmolb.2022.916128 (2022).

    Google Scholar 

  21. Liu, H. et al. Label-free quantitative proteomic analysis of cerebrospinal fluid and serum in patients with relapse-remitting multiple sclerosis. Front. Genet. 13, 892491. https://doi.org/10.3389/fgene.2022.892491 (2022).

    Google Scholar 

  22. Huang, J. et al. Inflammation-related plasma and CSF biomarkers for multiple sclerosis. Proc. Natl. Acad. Sci. U S A. 117, 12952–12960. https://doi.org/10.1073/pnas.1912839117 (2020).

    Google Scholar 

  23. Chase Huizar, C., Raphael, I. & Forsthuber, T. G. Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis. Cell. Immunol. 358, 104219. https://doi.org/10.1016/j.cellimm.2020.104219 (2020).

    Google Scholar 

  24. Ziemssen, T., Akgun, K. & Bruck, W. Molecular biomarkers in multiple sclerosis. J. Neuroinflamm. 16, 272. https://doi.org/10.1186/s12974-019-1674-2 (2019).

    Google Scholar 

  25. Avasarala, J. R., Wall, M. R. & Wolfe, G. M. A distinctive molecular signature of multiple sclerosis derived from MALDI-TOF/MS and serum proteomic pattern analysis: detection of three biomarkers. J. Mol. Neurosci. 25, 119–125. https://doi.org/10.1385/JMN:25:1:119 (2005).

    Google Scholar 

  26. Westman, A., Nilsson, C. L. & Ekman, R. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis of proteins in human cerebrospinal fluid. Rapid Commun. Mass. Spectrom. 12, 1092–1098. https://doi.org/10.1002/(SICI)1097-0231(19980831)12:16%3C1092::AID-RCM286%3E3.0.CO;2-N (1998).

    Google Scholar 

  27. Cerruti, C. D., Benabdellah, F., Laprevote, O., Touboul, D. & Brunelle, A. MALDI imaging and structural analysis of rat brain lipid negative ions with 9-aminoacridine matrix. Anal. Chem. 84, 2164–2171. https://doi.org/10.1021/ac2025317 (2012).

    Google Scholar 

  28. Yang, E., Dufresne, M. & Chaurand, P. Enhancing ganglioside species detection for MALDI-TOF imaging mass spectrometry in negative reflectron mode. Int. J. Mass Spectrom. 437, 3–9. https://doi.org/10.1016/j.ijms.2017.09.011 (2019).

    Google Scholar 

  29. Djambazova, K. V. et al. Resolving the complexity of spatial lipidomics using MALDI TIMS imaging mass spectrometry. Anal. Chem. 92, 13290–13297. https://doi.org/10.1021/acs.analchem.0c02520 (2020).

    Google Scholar 

  30. Miyawaki, S. et al. Imaging mass spectrometry detects dynamic changes of phosphatidylcholine in rat hippocampal CA1 after transient global ischemia. Neuroscience 322, 66–77. https://doi.org/10.1016/j.neuroscience.2016.02.013 (2016).

    Google Scholar 

  31. Chen, K., Baluya, D., Tosun, M., Li, F. & Maletic-Savatic, M. Imaging mass spectrometry: a new tool to assess molecular underpinnings of neurodegeneration. Metabolites 9, 2563. https://doi.org/10.3390/metabo9070135 (2019).

  32. Ceuppens, R. et al. Direct profiling of myelinated and demyelinated regions in mouse brain by imaging mass spectrometry. Int. J. Mass Spectrom. 260, 185–194. https://doi.org/10.1016/j.ijms.2006.09.007 (2007). https://doi.org/https://doi.

    Google Scholar 

  33. Jackson, S. N., Wang, H. Y. & Woods, A. S. Direct profiling of lipid distribution in brain tissue using MALDI-TOFMS. Anal. Chem. 77, 4523–4527. https://doi.org/10.1021/ac050276v (2005).

    Google Scholar 

  34. Bredehoft, J. et al. Visualizing and profiling lipids in the OVLT of Fat-1 and wild type mouse brains during LPS-induced systemic inflammation using AP-SMALDI MSI. ACS Chem. Neurosci. 10, 4394–4406. https://doi.org/10.1021/acschemneuro.9b00435 (2019).

    Google Scholar 

  35. Yuki, D. et al. Hydroxylated and non-hydroxylated sulfatide are distinctly distributed in the human cerebral cortex. Neuroscience 193, 44–53. https://doi.org/10.1016/j.neuroscience.2011.07.045 (2011).

    Google Scholar 

  36. Kaya, I. et al. Spatial lipidomics reveals region and long chain base specific accumulations of monosialogangliosides in amyloid plaques in familial alzheimer’s disease mice (5xFAD) brain. ACS Chem. Neurosci. 11, 14–24. https://doi.org/10.1021/acschemneuro.9b00532 (2020).

    Google Scholar 

  37. Kaya, I. et al. Brain region-specific amyloid plaque-associated myelin lipid loss, APOE deposition and disruption of the myelin sheath in familial Alzheimer’s disease mice. J. Neurochem. 154, 84–98. https://doi.org/10.1111/jnc.14999 (2020).

    Google Scholar 

  38. Kaya, I. et al. Brain-region-specific lipid dysregulation in L-DOPA-induced dyskinesia in a primate model of Parkinson’s disease. npj Parkinson’s Dis. 11, 258. https://doi.org/10.1038/s41531-025-01109-6 (2025).

    Google Scholar 

  39. Pathmasiri, K. C. et al. Mass spectrometry imaging and LC/MS reveal decreased cerebellar phosphoinositides in Niemann-Pick type C1-null mice. J. Lipid Res. 61, 1004–1013. https://doi.org/10.1194/jlr.RA119000606 (2020).

    Google Scholar 

  40. Constantinescu, C. S., Farooqi, N., O’Brien, K. & Gran, B. Experimental autoimmune encephalomyelitis (EAE) as a model for multiple sclerosis (MS). Br. J. Pharmacol. 164, 1079–1106. https://doi.org/10.1111/j.1476-5381.2011.01302.x (2011).

    Google Scholar 

  41. Curtis II, D. A. Experimental autoimmune encephalomyelitis as a model of Multiple Sclerosis : pathogenesis of atypical disease and tolerance induction in chronic progressive disease Ph.D. thesis, Eastern Carolina University (2015).

  42. Murphy, R. C. & Axelsen, P. H. Mass spectrometric analysis of long-chain lipids. Mass Spectrom. Rev. 30, 579–599. https://doi.org/10.1002/mas.20284 (2011).

    Google Scholar 

  43. Hartler, J., Tharakan, R., Kofeler, H. C., Graham, D. R. & Thallinger, G. G. Bioinformatics tools and challenges in structural analysis of lipidomics MS/MS data. Brief. Bioinform. 14, 375–390. https://doi.org/10.1093/bib/bbs030 (2013).

    Google Scholar 

  44. Leopold, J., Popkova, Y., Engel, K. M. & Schiller, J. Recent developments of useful MALDI matrices for the mass spectrometric characterization of lipids. Biomolecules 8, 2563. https://doi.org/10.3390/biom8040173 (2018).

  45. Kyle, J. E. et al. Uncovering biologically significant lipid isomers with liquid chromatography, ion mobility spectrometry and mass spectrometry. Analyst 141, 1649–1659. https://doi.org/10.1039/c5an02062j (2016).

    Google Scholar 

  46. Kister, A. & Kister, I. Overview of myelin, major myelin lipids, and myelin-associated proteins. Front. Chem. 10, 1041961. https://doi.org/10.3389/fchem.2022.1041961 (2022).

    Google Scholar 

  47. Ikeda, K. & Taguchi, R. Highly sensitive localization analysis of gangliosides and sulfatides including structural isomers in mouse cerebellum sections by combination of laser microdissection and hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry with theoretically expanded multiple reaction monitoring. Rapid Commun. Mass. Spectrom. 24, 2957–2965. https://doi.org/10.1002/rcm.4716 (2010).

    Google Scholar 

  48. Taylor, C. M., Marta, C. B., Bansal, R. & Pfeiffer, S. E. Myelin Biology and Disorders 57–88 (Academic, 2004).

  49. O’Brien, J. S. & Sampson, E. L. Lipid composition of the normal human brain: gray matter, white matter, and myelin. J. Lipid Res. 6, 537–544 (1965).

    Google Scholar 

  50. Bittner, S., Afzali, A. M., Wiendl, H. & Meuth, S. G. Myelin oligodendrocyte glycoprotein (MOG35-55) induced experimental autoimmune encephalomyelitis (EAE) in C57BL/6 mice. J. Vis. Exp. https://doi.org/10.3791/51275 (2014).

    Google Scholar 

  51. Graulich, D. M., Kaiser, S., Sachser, N. & Richter, S. H. Looking on the bright side of bias—validation of an affective bias test for laboratory mice. Appl. Anim. Behav. Sci. 181, 173–181. https://doi.org/10.1016/j.applanim.2016.05.011 (2016).

    Google Scholar 

  52. Cumming, G., Fidler, F. & Vaux, D. L. Error bars in experimental biology. J. Cell. Biol. 177, 7–11. https://doi.org/10.1083/jcb.200611141 (2007).

    Google Scholar 

  53. Shin, K. C., Moussa, A., Park, Y. & H. Y. & Cholesterol imbalance and neurotransmission defects in neurodegeneration. Exp. Mol. Med. 56, 1685–1690. https://doi.org/10.1038/s12276-024-01273-4 (2024).

    Google Scholar 

  54. Quarles, R. H. Myelin sheaths: glycoproteins involved in their formation, maintenance and degeneration. Cell. Mol. Life Sci. 59, 1851–1871. https://doi.org/10.1007/pl00012510 (2002).

    Google Scholar 

  55. Tobias, F., Pathmasiri, K. C. & Cologna, S. M. Mass spectrometry imaging reveals ganglioside and ceramide localization patterns during cerebellar degeneration in the Npc1(-/-) mouse model. Anal. Bioanal Chem. 411, 5659–5668. https://doi.org/10.1007/s00216-019-01989-7 (2019).

    Google Scholar 

  56. Sekera, E. R., Saraswat, D., Zemaitis, K. J., Sim, F. J. & Wood, T. D. MALDI mass spectrometry imaging in a primary demyelination model of murine spinal cord. J. Am. Soc. Mass. Spectrom. 31, 2462–2468. https://doi.org/10.1021/jasms.0c00187 (2020).

    Google Scholar 

  57. Stoffel, W. & Bosio, A. Myelin glycolipids and their functions. Curr. Opin. Neurobiol. 7, 654–661. https://doi.org/10.1016/s0959-4388(97)80085-2 (1997).

    Google Scholar 

  58. Ramakrishnan, H. et al. Increasing sulfatide synthesis in myelin-forming cells of arylsulfatase A-deficient mice causes demyelination and neurological symptoms reminiscent of human metachromatic leukodystrophy. J. Neurosci. 27, 9482–9490. https://doi.org/10.1523/JNEUROSCI.2287-07.2007 (2007).

    Google Scholar 

  59. Okuda, D. T. Radiologically Isolated syndrome: MR imaging features suggestive of multiple sclerosis prior to first symptom onset. Neuroimaging Clin. N Am. 27, 267–275. https://doi.org/10.1016/j.nic.2016.12.008 (2017).

    Google Scholar 

  60. Raphael, I. et al. TNFR2 limits proinflammatory astrocyte functions during EAE induced by pathogenic DR2b-restricted T cells. JCI Insight. 4, 2563. https://doi.org/10.1172/jci.insight.132527 (2019).

  61. Ji, N. et al. Small molecule inhibitor of antigen binding and presentation by HLA-DR2b as a therapeutic strategy for the treatment of multiple sclerosis. J. Immunol. 191, 5074–5084. https://doi.org/10.4049/jimmunol.1300407 (2013).

    Google Scholar 

  62. Nelson, K. A., Daniels, G. J., Fournie, J. W. & Hemmer, M. J. Optimization of whole-body zebrafish sectioning methods for mass spectrometry imaging. J. Biomol. Tech. 24, 119–127. https://doi.org/10.7171/jbt.13-2403-002 (2013).

    Google Scholar 

  63. Angel, P. M., Spraggins, J. M., Baldwin, H. S. & Caprioli, R. Enhanced sensitivity for high spatial resolution lipid analysis by negative ion mode matrix assisted laser desorption ionization imaging mass spectrometry. Anal. Chem. 84, 1557–1564. https://doi.org/10.1021/ac202383m (2012).

    Google Scholar 

  64. Yang, J. & Caprioli, R. M. Matrix sublimation/recrystallization for imaging proteins by mass spectrometry at high spatial resolution. Anal. Chem. 83, 5728–5734. https://doi.org/10.1021/ac200998a (2011).

    Google Scholar 

  65. Thomas, A., Charbonneau, J. L., Fournaise, E. & Chaurand, P. Sublimation of new matrix candidates for high spatial resolution imaging mass spectrometry of lipids: enhanced information in both positive and negative polarities after 1,5-diaminonapthalene deposition. Anal. Chem. 84, 2048–2054. https://doi.org/10.1021/ac2033547 (2012).

    Google Scholar 

  66. Sladkova, K., Houska, J. & Havel, J. Laser desorption ionization of red phosphorus clusters and their use for mass calibration in time-of-flight mass spectrometry. Rapid Commun. Mass. Spectrom. 23, 3114–3118. https://doi.org/10.1002/rcm.4230 (2009).

    Google Scholar 

Download references

Acknowledgements

The authors would also like to thank Dr. Erin Seeley, from the UT Mass Spectrometry Imaging center for her mentorship, MSI expertise, and assistance in performing timsTOF MS/MS lipid identification. Thank you to Dr. Grace Samenuk for her cryogenic sectioning assistance, MALDI-TOF MSI guidance, and Dr. Andrea Kelley and Dr. Madeline Colley for their MALDI expertise. This project was supported by grant NS137101 from the National Institute of Health (T.G.F., S.B.B.). Finally, the authors thank the UTSA RISE program for its research funding and professional development support.

Author information

Author notes
  1. Thomas G. Forsthuber and Stephan B. H. Bach contributed equally to this work.

Authors and Affiliations

  1. Department of Chemistry, the University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Krista A. Berlin & Stephan B. H. Bach

  2. Department of Molecular Microbiology and Immunology, the University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Carol Chase Huizar, Celeste Garza & Thomas G. Forsthuber

  3. Department of Allergy Research, The University of California San Francisco, San Francisco, CA, 94143, USA

    Celeste Garza

Authors
  1. Krista A. Berlin
    View author publications

    Search author on:PubMed Google Scholar

  2. Carol Chase Huizar
    View author publications

    Search author on:PubMed Google Scholar

  3. Celeste Garza
    View author publications

    Search author on:PubMed Google Scholar

  4. Thomas G. Forsthuber
    View author publications

    Search author on:PubMed Google Scholar

  5. Stephan B. H. Bach
    View author publications

    Search author on:PubMed Google Scholar

Contributions

K.A.B.: Conducted all MSI analysis, data processing, figure generation, and manuscript writing and editing. C.C.H. performed all murine immunizations, cell culturing, disease scoring, and tissue acquisition. C.G. assisted with animal monitoring and disease scoring and carried out immunofluorescent staining. T.G.F. conceived the studies and reviewed and edited all manuscript drafts. S.B.H.B. Contributed to the design of the mass spectrometry studies, manuscript editing, and final manuscript review.

Corresponding authors

Correspondence to Thomas G. Forsthuber or Stephan B. H. Bach.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (download DOCX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Berlin, K.A., Huizar, C.C., Garza, C. et al. MALDI-TOF mass spectrometry imaging of sulfatide lipid expression in the CNS of mice with experimental autoimmune encephalomyelitis. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41147-5

Download citation

  • Received: 07 October 2025

  • Accepted: 18 February 2026

  • Published: 28 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-41147-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Mass spectrometry imaging
  • Lipid imaging
  • Neuroinflammation
  • EAE
  • CNS
  • Multiple sclerosis
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing