Identification and imaging different lipid species within phase-separated model membranes by integration of TOF-SIMS and principal component analysis

摘要

Time of flight secondary ion mass spectrometry (TOF-SIMS) enables chemically imaging the distributions of various lipid species in model membranes. However, discriminating the TOF-SIMS spectra of structurally similar lipids is very difficult because the low mass fragment ions that are abundant in the spectra are common to multiple lipid species. Here we demonstrate that principal component analysis (PCA) can discriminate the TOF-SIMS spectra of four unlabeled saturated phosphatidylcholine species, 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), and 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), according to variations in the relative intensities of their fragment ions. PCA of TOF-SIMS spectra acquired slightly above the static limit enabled imaging the distributions of these phosphatidylcholine species in phase-separated membranes composed of DLPC/DSPC and DLPC/DPPC with higher contrast and specificity than that in the individual TOF-SIMS ion images. Comparison to atomic force microscopy images that were acquired at the same membrane location prior to TOF-SIMS analysis confirmed that the PC scores images reveal the sizes and shapes of the phase-separated membrane domains. The lipid composition within these domains was identified by projection of their TOF-SIMS spectra onto PC models developed using pure lipid standards. This approach may enable the routine chemical imaging of more complex membranes. The feasibility of detecting and imaging membrane glycans using TOF-SIMS has also been investigated. Glycans are complex carbohydrates attached to lipids and proteins on the surface of animal cells. Since changes in glycosylation are correlated with tumor invasion and cancer metastasis, knowledge of glycan structures and locations on individual cells is required to determine their normal and disease-related functions. Here we combined PCA with matrix-enhanced SIMS (ME-SIMS), which is the combination of MALDI sample preparation with TOF-SIMS analysis, for the goal of identifying spectral features that encode for glycan composition. We demonstrate that ME-SIMS can increase the efficiency of ionization of glycosphingolipids, such as galactosyceramide (GalCer) and glucosylceramide (GlcCer), and PCA of the resulting spectra enables distinguishing and identifying these components according to combinations of mass spectral peaks that are characteristic to each component.