Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning

Area of Science:

• Environmental Health Sciences
• Biochemistry
• Toxicology

Background:

• Understanding regional lung responses to inhaled toxicants like air pollution is crucial for lung disease pathogenesis.
• Asthma exacerbations can be influenced by environmental factors such as ozone exposure.

Purpose of the Study:

• To investigate the spatial differences in lipid distribution within the mouse lung following combined allergen sensitization and ozone exposure.
• To explore how these lipid alterations may contribute to ozone-induced asthma exacerbations.

Main Methods:

• High-resolution mass spectrometry imaging (MSI) was used on cryosectioned mouse lung lobes.
• Lipidomic data from MSI were validated using liquid chromatography-tandem mass spectrometry (LC-MS/MS).
• Image segmentation and statistical analysis were performed on morphologically relevant lung regions.

Main Results:

• Spatially distinct lipids showed a higher degree of unsaturated fatty acids in distal lung regions compared to proximal regions.
• Females exhibited significantly decreased sphingolipid and glycerophospholipid abundance in airway and alveolar epithelium, unlike males.
• The study identified sex-specific regional lipid distribution changes post-ozone exposure.

Conclusions:

• Lipid saturation may play a role in healthy lung function.
• Significant sex differences exist in regional lung lipid distribution after ozone exposure.
• The study provides a framework for future MSI experiments, including human tissue analysis.