In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MS n ) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative mode analyses, requiring two separate runs or polarity switching during a single analysis. MS 3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently, functionality has been introduced on several Orbitrap Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream MS n to improve structural characterization with lessened impacts on analysis depth. Here, we describe a novel lipidomics real-time library search (RTLS) approach, which utilizes the lipid class of real-time identifications to trigger class-targeted MS n and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to the current methodology of triggering MS n in the presence of characteristic ions or neutral losses.
Type 2 diabetes is a challenge in modern healthcare, and animal models are necessary to identify underlying mechanisms, where we can achieve much better environmental control than what is practical in human studies. The Nile rat (Arvicanthis niloticus) develops diet-induced diabetes rapidly on a conventional rodent chow diet without genetic or chemical manipulation. Unlike common laboratory models, the outbred Nile rat model is diurnal and can progress to advanced diabetic complications, better mimicking the human condition. Some human studies indicate that compared to fasting glucose, post-prandial blood glucose is more sensitive to the initial stages of diabetes, suggesting that we should capture the non-fasted state to study early diabetes. However, it is unknown if ad libitum feeding in the Nile rats leads to increased variance thus masking diabetes-related metabolic changes in the plasma. In this study, we compared the repeatability within triplicate non-fasted or fasted plasma samples and assessed prediction of impaired glucose tolerance in fasted and non-fasted plasma. We used liquid chromatography-mass spectrometry lipidomics and polar metabolomics to measure relative metabolite abundances in the plasma samples. Metabolite measurements in non-fasted plasma were less variable than measurements in fasted plasma. We detected 66 metabolites in non-fasted plasma associated with glucose tolerance in elastic net and individual metabolite linear regression models. Low metabolite replicate variance was reproduced in a cohort of mature 30-week male and female Nile rats. Our results support using non-fasted plasma metabolomics for early detection of impaired glucose tolerance in Nile rats.
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