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

Journal: Nature communications
PMID: 40140638

Abstract

Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lipid distribution in the mouse lung that may contribute to ozone-induced exacerbations in asthma. We demonstrate the ability to normalize and segment high resolution mass spectrometry imaging data by applying established machine learning algorithms. Interestingly, our segmented regions overlap with histologically validated lung regions, enabling regional analysis across biological replicates. Our data reveal differences in the abundance of spatially distinct lipids, support the potential role of lipid saturation in healthy lung function, and highlight sex differences in regional lung lipid distribution following ozone exposure. Our study provides a framework for future mass spectrometry imaging experiments capable of relative quantification across biological replicates and expansion to multiple sample types, including human tissue.

Authors

  • Nathanial C Stevens
    Genome Center, University of California Davis, Davis, CA, USA.
  • Tong Shen
    Beijing Key Laboratory for Magnetoelectric Materials and Devices (BKL-MMD), School of Materials Science and Engineering, Peking University, Beijing 100871, China.
  • Joshua Martinez
    Center for Health and the Environment, University of California Davis, Davis, CA, USA.
  • Veneese J B Evans
    Center for Health and the Environment, University of California Davis, Davis, CA, USA.
  • Morgan C Domanico
    Center for Health and the Environment, University of California Davis, Davis, CA, USA.
  • Elizabeth K Neumann
    Department of Chemistry, University of California Davis, Davis, CA, USA.
  • Laura S Van Winkle
    Center for Health and the Environment, University of California Davis, Davis, CA, USA.
  • Oliver Fiehn
    University of California, One Shields Avenue, Davis, CA 95616, USA. Electronic address: ofiehn@ucdavis.edu.

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