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INCREASE IMAGE CLARITY AND SPECIFICITY USING DUAL MSI SOURCES AND MULTI-REFLECTING TIME-OF-FLIGHT ANALYZING METABOLITES IN MOUSE TESTIS

Posters | 2022 | Waters | ASMSInstrumentation
MS Imaging, LC/HRMS, LC/MS/MS, LC/MS, LC/TOF
Industries
Metabolomics
Manufacturer
Waters

Summary

Significance of the Topic


Mapping lipid distributions in complex tissues like the mouse testis is crucial to understanding germ cell development, male fertility and lipid homeostasis. Mass spectrometry imaging (MSI) techniques such as DESI and MALDI enable direct spatial localization of molecular species, but conventional approaches are limited by insufficient mass resolution and specificity in heterogeneous samples.

Study Objectives and Overview


This work integrates dual MSI sources (DESI and MALDI) on a high-resolution multi-reflecting time-of-flight (MRT) mass spectrometer to investigate lipid metabolites in distinct testicular compartments. Key aims are to enhance image clarity, resolve fine isotopic structure, achieve sub-500 ppb mass accuracy and compare performance against DESI on a SYNAPT G2-Si platform.

Methodology and Instrumentation


Sample Preparation and Ionization
  • Mouse testis cryosections mounted on glass slides and stored at –80 °C.
  • DESI imaging: direct desorption by charged microdroplets (95 % MeOH/5 % H2O with Leu-enkephalin standard).
  • MALDI imaging: successive coatings of α-Cyano-4-hydroxycinnamic acid matrix applied via HTX M5 nebulizing sprayer.

Mass Spectrometry Platforms
  • SELECT SERIES™ MRT (quadrupole multi-reflecting TOF) achieving ~200 000 FWHM resolution and sub-500 ppb mass accuracy.
  • SYNAPT™ G2-Si Q-oaTOF (≈25 000 FWHM) for comparative DESI analyses.

Data Processing
  • Acquisition and visualization with MassLynx™ and High Definition Imaging™ (HDI v1.6).
  • ROI averaging, TIC normalization and export to .csv for multivariate analysis in MetaboAnalyst.
  • Putative lipid identification via LIPID MAPS database searches (mass tolerance ≤500 ppb).

Results and Discussion


High-Resolution Imaging
  • MRT MSI distinguishes lipids with mass differences <20 mDa, resolving isotope fine structure and potassium or sodium adducts unambiguously.
  • DESI MRT spectral data show clear separation of peaks at m/z 848.55676 (potassiated PC 38:4) versus overlapping signals in SYNAPT G2-Si.

Spatial Distribution of Lipids
  • Glycerophospholipids (PC, PS, PI, PG) and seminolipids localized to Sertoli cells, early/mature germ cells and Leydig/blood vessel regions.
  • Main seminolipid peak (m/z 795.53) mapped along seminiferous tubules, corroborating prior biochemical studies.

Statistical Analysis
  • PCA score plots from MetaboAnalyst separate the three major testis compartments based on lipid profiles.
  • Loading plots identify key lipid species driving tissue differentiation.

Mass Accuracy and Identification Confidence
  • Sub-500 ppb mass accuracy and RMS error ~203 ppb increase confidence in putative identifications.
  • MALDI and DESI MSI complement each other by enhancing ionization efficiency across lipid classes.

Practical Benefits and Applications


  • Enables detailed, cell-type specific lipid profiling in reproductive biology and pathology research.
  • High mass resolution imaging clarifies complex isotopic patterns, improving biomarker discovery and QA/QC workflows.
  • Dual ionization strategies broaden the detectable molecular range for comprehensive lipidomics.

Future Trends and Applications


  • Extension to other tissues and disease models to map lipidomic changes at subcellular resolution.
  • Integration with single-cell analysis, liquid chromatography-MS and multi-omics platforms for holistic molecular mapping.
  • Automation and AI-driven data analysis to accelerate biomarker identification and translational studies.

Conclusion


The combination of DESI and MALDI on a high-resolution MRT TOF instrument markedly improves spatial specificity, mass accuracy and the ability to resolve fine isotopic structure in complex tissues. This approach advances lipid MSI applications in biological research and clinical diagnostics by delivering robust, high-confidence molecular images.

References


  1. Rodemer C et al. Human Molecular Genetics. 2003;12:1881–1885.
  2. Vos JP et al. Biochimica et Biophysica Acta. 1994;1211:125–149.
  3. Siangcham T et al. PLoS ONE. 2015;10(3):e0120412.
  4. Ishizuka I et al. Journal of Biochemistry. 1973;73(1):77–87.
  5. Goto-Inoue N et al. Glycobiology. 2009;19(9):950–957.

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