Influence of Lipid Fragmentation in the Data Analysis of Imaging Mass Spectrometry Experiments

Abstract

Imaging mass spectrometry (IMS) is becoming an essential technique in lipidomics. Still, many questions remain open, precluding it from achieving its full potential. Among them, identification of species directly from the tissue is of paramount importance. However, it is not an easy task, due to the abundance and variety of lipid species, their numerous fragmentation pathways, and the formation of a significant number of adducts, both with the matrix and with the cations present in the tissue. Here, we explore the fragmentation pathways of 17 lipid classes, demonstrating that in-source fragmentation hampers identification of some lipid species. Then, we analyze what type of adducts each class is more prone to form. Finally, we use that information together with data from on-tissue MS/MS and MS 3 to refine the peak assignment in a real experiment over sections of human nevi, to demonstrate that statistical analysis of the data is significantly more robust if unwanted peaks due to fragmentation, matrix, and other species that only introduce noise in the analysis are excluded.

Polyunsaturated Fatty Acid-Enriched Lipid Fingerprint of Glioblastoma Proliferative Regions Is Differentially Regulated According to Glioblastoma Molecular Subtype

“…. HD-RCA number of segments was set from 2 to 5, with prior background noise filtration using in-house MATLAB algorithms [43].…”

“…Healthy brain and GBM biopsy sections were prepared after incubating fresh biopsies in DMSO (vehicle) or TMZ (10 mg/mL, 4 h) and analyzed by MALDI-IMS at 50–100 µm lateral resolution. Brain proliferation zones were determined by MKI67+ IF staining and used to select the MALDI-IMS cluster, generated by HD-RCA from consecutive tissue sections [ 43 ]. HD-RCA clustering enabled the identification of the IMS regions of interest (Cluster*) with greater correlation (evaluated by direct visual inspection) with the MKI67+ IFs, based on the similarity of lipidomic content in each MALDI-IMS experiment.…”

“…Color scale indicates the intensity of the PI 38:4 -H distribution (0, black; 1, white). HD-RCA number of segments was set from 2 to 5, with prior background noise filtration using in-house MATLAB algorithms [ 43 ].…”

Uncovering the interference from lipid fragments on the qualification and quantification of serum metabolites in matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometric analysis

“…The diagnostic accuracy may be compromised if these fragment peaks are mistakenly taken as the signals of metabolites. The impact of ISD and PSD on the identification of lipids has been reported over conventional matrices 19–21,24 . However, the influence of lipid fragments on the qualitative and quantitative analysis of LMW metabolites in biological samples has not been systematically investigated.…”

“…18 Nevertheless, the coexisting molecules like proteins and lipids, commonly seen in many biofluids, can undergo in-source fragmentation (ISD) and/or postsource fragmentation (PSD) after gaining energy directly or indirectly from the laser. [19][20][21][22][23][24] Fragment ions generated in the ISD or the PSD process will arrive at the detector along with intact molecular ions, resulting in "fake" metabolite peaks that lead to misinterpretation of mass spectra. The diagnostic accuracy may be compromised if these fragment peaks are mistakenly taken as the signals of metabolites.…”