Department of Chemistry, University of Florida, 214 Leigh Hall, Gainesville, FL, 32611, USA.
Published: May 2017
AI Article Synopsis
Article Abstract
Untargeted omics analyses aim to comprehensively characterize biomolecules within a biological system. Changes in the presence or quantity of these biomolecules can indicate important biological perturbations, such as those caused by disease. With current technological advancements, the entire genome can now be sequenced; however, in the burgeoning fields of lipidomics, only a subset of lipids can be identified. The recent emergence of high resolution tandem mass spectrometry (HR-MS/MS), in combination with ultra-high performance liquid chromatography, has resulted in an increased coverage of the lipidome. Nevertheless, identifications from MS/MS are generally limited by the number of precursors that can be selected for fragmentation during chromatographic elution. Therefore, we developed the software IE-Omics to automate iterative exclusion (IE), where selected precursors using data-dependent topN analyses are excluded in sequential injections. In each sequential injection, unique precursors are fragmented until HR-MS/MS spectra of all ions above a user-defined intensity threshold are acquired. IE-Omics was applied to lipidomic analyses in Red Cross plasma and substantia nigra tissue. Coverage of the lipidome was drastically improved using IE. When applying IE-Omics to Red Cross plasma and substantia nigra lipid extracts in positive ion mode, 69% and 40% more molecular identifications were obtained, respectively. In addition, applying IE-Omics to a lipidomics workflow increased the coverage of trace species, including odd-chained and short-chained diacylglycerides and oxidized lipid species. By increasing the coverage of the lipidome, applying IE to a lipidomics workflow increases the probability of finding biomarkers and provides additional information for determining etiology of disease. Graphical Abstract ᅟ.
Background: Perfluoroalkyl and polyfluoroalkyl substances (PFAS) exposure has been associated with metabolic diseases, however, the underlying molecular pathogenesis remains to be understood. Integrated PFAS and lipidomic analysis has the potential to identify alterations in lipid metabolism pathways for exposome research.
Methods: A targeted LC-MS/MS method was developed for the quantification of 14 PFAS from human plasma samples (n = 96).
It is challenging to have comprehensive spatial lipidomic analysis by mass spectrometry imaging (MSI) due to the strong ion suppression and peak interference from high-abundance polar lipids to low-abundance poorly ionizable lipids. In this work, we proposed a new MSI approach via ambient liquid extraction techniques assisted by a new mixed-mode adsorptive material, graphene oxide (GO)/TiO nanocomposite. The material combines chelation affinity from TiO and hydrophobic interaction from GO.
Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, 1 Xiangshanzhi Ln., Hangzhou, 310024 China.
Unlabelled: Little is known about the links of disturbed lipid metabolism with hyperuricemia (HUA). We aimed to investigate the associations of lipidomic profiles with uric acid (UA)/HUA and their modifying factors in middle-aged and elderly Chinese. A total of 350 lipids were quantified in 2247 community-based Chinese aged 50-70 years by high-coverage targeted lipidomics.
Background: Schizophrenia is a psychiatric disorder known to affect brain structure and functionality. Structural changes in the brain at the level of gross anatomical structures have been fairly well studied, while microstructural changes, especially those associated with changes in the molecular composition of the brain, are still being investigated. Of special interest are lipids and metabolites, for which some previous studies have shown association with schizophrenia.
Patients with adult growth hormone deficiency (AGHD) are at a higher risk for metabolic syndrome, but their lipid metabolism has not been thoroughly studied.
*The study analyzed fasting serum samples from 30 AGHD patients and 30 matched healthy controls, identifying significant differences in various lipid subclasses.
*Results showed increased levels of specific lipids in AGHD patients, which may contribute to metabolic issues, and findings could inform future research and treatment strategies.*
