Abstract
A method is described using desorption electrospray ionization (DESI) mass spectrometry (MS) to obtain phospholipid mass spectral profiles from crude lung tissue extracts. The measured DESI mass spectral lipid fingerprints were then analyzed by unsupervised learning principal components analysis (PCA). This combined approach was used to differentiate the effect(s) of two vaccination routes on lipid composition in mouse lungs. Specifically, the two vaccination routes compared were intranasal (i.n.) and intradermal (i.d.) inoculation of the Francisella tularensis live vaccine strain (Ft-LVS). Lung samples of control and LVS-inoculated mice were quickly extracted with a methanol/chloroform solution, and the crude extract was directly analyzed by DESI-MS, with a total turnaround time of less than 10 min/sample. All of the measured DESI mass spectra (in both positive and negative ion mode) were compared via PCA, resulting in clear differentiation of mass spectral profiles of i.n.-inoculated mouse lung tissues from those of i.d.-inoculated and control mouse lung tissues. Lipid biomarkers responsible for sample differentiation were identified via tandem MS (MS/MS) measurements or by comparison with mass spectra of lipid standards. The DESI-MS approach described here provided a practical and rapid means to analyze tissue samples without extensive extractions and solvent changes.