Browsing by Subject "data-analysis"

Lipidomics is a quickly growing trend in metabolomics research: not only seen as passive cell membrane building blocks, lipids contribute actively to cell signaling and identification, thus seen as potential biomarkers (e.g. for early stage cancer diagnostics). The literature part includes a review of 63 articles on UHPLC/MS-methods in the time frame of 2017-05/2019. The following literature is focused especially on glycerophospholipids (GPs). In addition, an overview to basic glycerolipids (GLs) and sphingolipids (SPs) is established, which evidently affects the emphasis and narration of lipid class representations in this review. Chromatographic methods in lipidomics are used to achieve either very selective or all-encompassing analyses for lipid classes. Since HPLC/MS is an insufficient method for fully encompassing low-abundance lipids, UHPLC/MS was mostly used for metabolic profiling where its large analyte range due to high sensitivity, separation efficiency and resolution excels in performance compared to other methods. Imaging techniques have further diverted towards DIMS and other novel non-chromatographic methods, e.g. Raman techniques with single cell resolution. The field of mass-spectral lipidomics is divided between studies using isotope-labeled standards or fully standardless algorithm-based analyses, furthermore, machine learning and statistical analysis has increased. The experimental part focused on LC-IMS-MS and plasma-based in-house database method development for targeted analysis of ascites. Method development included optimization of the chromatography, adduct species selection and data-independent/-dependent fragmentation. Totally, 130 potential species from the LIPID MAPS database were used for the identification at the minimum score of 79% for identification in the Qualitative Workflows with retention times (RTs) and Mass Profiler-program with collision cross-sections (CCSs). Plasma sample analyses resulted in the documentation of 70 RTs and 36 CCS values. Two lipid extraction methods (Folch and BUME) with pre-sampling surrogates and post-sampling internal standards were compared with each other. The process resulted in confirming the BUME method in lipidomics to be superior in ecology-, workload-, health- and extraction-related properties. The lipidome of ascites has rarely been studied due to its availability only in diseased patients. Also, limiting factors for these studies are the logistics to realise such a representative analysis.