Project description:We report a new method for fast and sensitive analyses of biologically relevant fatty acids (FAs) in red blood cells (RBC) by liquid chromatography mass spectrometry (LC-MS). A new chemical derivatization approach was developed forming picolylamides from FAs in a quantitative reaction. Fourteen derivatized FA standards, including saturated and unsaturated FAs from C14 to C22, were efficiently separated within 15 min. In addition, the use of a recently introduced benchtop orbitrap mass spectrometer under positive electrospray ionization (ESI) full scan mode showed a 2-10-fold improvement in sensitivity compared with a conventional tandem MS method, with a limit of detection in the low femtomole range for saturated and unsaturated FAs. The developed method was applied to determine FA concentrations in RBC with intra- and interday coefficients of variation below 10%.
Project description:Sarcopenia, a multifactorial systemic disorder, has attracted extensive attention, yet its pathogenesis is not fully understood, partly due to limited research on the relationship between lipid metabolism abnormalities and sarcopenia. Lipidomics offers the possibility to explore this relationship. Our research utilized LC/MS-based nontargeted lipidomics to investigate the lipid profile changes as-sociated with sarcopenia, aiming to enhance understanding of its underlying mechanisms. The study included 40 sarcopenia patients and 40 control subjects matched 1:1 by sex and age. Plasma lipids were detected and quantified, with differential lipids identified through univariate and mul-tivariate statistical analyses. A weighted correlation network analysis (WGCNA) and MetaboAna-lyst were used to identify lipid modules related to the clinical traits of sarcopenia patients and to conduct pathway analysis, respectively. A total of 34 lipid subclasses and 1446 lipid molecules were detected. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 80 differen-tial lipid molecules, including 38 phospholipids. Network analysis revealed that the brown module (encompassing phosphatidylglycerol (PG) lipids) and the yellow module (containing phosphati-dylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM) lipids) were closely associated with the clinical traits such as maximum grip strength and skeletal muscle mass (SMI). Pathway analysis highlighted the potential role of the glycerophospholipid metabolic pathway in lipid me-tabolism within the context of sarcopenia. These findings suggest a correlation between sarcopenia and lipid metabolism disturbances, providing valuable insights into the disease's underlying mechanisms and indicating potential avenues for further investigation.
Project description:Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.
Project description:Metabolism is important for the regulation of hematopoietic stem cells (HSCs) and drives cellular fate. Due to the scarcity of HSCs, it has been technically challenging to perform metabolome analyses gaining insight into HSC metabolic regulatory networks. Here, we present two targeted liquid chromatography-mass spectrometry approaches that enable the detection of metabolites after fluorescence-activated cell sorting when sample amounts are limited. One protocol covers signaling lipids and retinoids, while the second detects tricarboxylic acid cycle metabolites and amino acids. For complete details on the use and execution of this protocol, please refer to Schönberger et al. (2022).
Project description:BackgroundNonpuerperal mastitis (NPM) is a disease that presents with redness, swelling, heat, and pain during nonlactation and can often be confused with breast cancer. The etiology of NPM remains elusive; however, emerging clinical evidence suggests a potential involvement of lipid metabolism.MethodLiquid chromatography‒mass spectrometry (LC/MS)-based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the NPM lipid change in breast tissue. Twenty patients with NPM and 10 controls were enrolled in this study.ResultsThe results revealed significant differences in lipidomics profiles, and a total of 16 subclasses with 14,012 different lipids were identified in positive and negative ion modes. Among these lipids, triglycerides (TGs), phosphatidylethanolamines (PEs) and cardiolipins (CLs) were the top three lipid components between the NPM and control groups. Subsequently, a total of 35 lipids were subjected to screening as potential biomarkers, and the chosen lipid biomarkers exhibited enhanced discriminatory capability between the two groups. Furthermore, pathway analysis elucidated that the aforementioned alterations in lipids were primarily associated with the arachidonic acid metabolic pathway. The correlation between distinct lipid populations and clinical phenotypes was assessed through weighted gene coexpression network analysis (WGCNA).ConclusionsThis study demonstrates that untargeted lipidomics assays conducted on breast tissue samples from patients with NPM exhibit noteworthy alterations in lipidomes. The findings of this study highlight the substantial involvement of arachidonic acid metabolism in lipid metabolism within the context of NPM. Consequently, this study offers valuable insights that can contribute to a more comprehensive comprehension of NPM in subsequent investigations.Trial registrationShuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (Number: 2019-702-57; Date: July 2019).
Project description:SummaryWe introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS-based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species. LIQUID was compared to other freely available software commonly used to identify lipids and other small molecules (e.g. CFM-ID, MetFrag, GNPS, LipidBlast and MS-DIAL), and was found to have a faster processing time to arrive at a higher number of validated lipid identifications.Availability and implementationLIQUID is available at http://github.com/PNNL-Comp-Mass-Spec/LIQUID .Contactjennifer.kyle@pnnl.gov or thomas.metz@pnnl.gov.Supplementary informationSupplementary data are available at Bioinformatics online.
Project description:IntroductionLipidomics analysis or lipid profiling is a system-based analysis of all lipids in a sample to provide a comprehensive understanding of lipids within a biological system. In the last few years, lipidomics has made it possible to better understand the metabolic processes associated with several rare disorders and proved to be a powerful tool for their clinical investigation. Fabry disease is a rare X-linked lysosomal storage disorder (LSD) caused by a deficiency in α-galactosidase A (α-GAL A). This deficiency results in the progressive accumulation of glycosphingolipids, mostly globotriaosylceramide (Gb3), globotriaosylsphingosine (lyso-Gb3), as well as galabiosylceramide (Ga2) and their isoforms/analogs in the vascular endothelium, nerves, cardiomyocytes, renal glomerular podocytes, and biological fluids.ObjectivesThe primary objective of this study was to evaluate lipidomic signatures in renal biopsies to help understand variations in Fabry disease markers that could be used in future diagnostic tests.MethodsLipidomic analysis was performed by ultra-high pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) on kidney biopsies that were left over after clinical pathology analysis to diagnose Fabry disease.ResultsWe employed UHPLC-HRMS lipidomics analysis on the renal biopsy of a patient suspicious for Fabry disease. Our result confirmed α-GAL A enzyme activity declined in this patient since a Ga2-related lipid biomarker was substantially higher in the patient's renal tissue biopsy compared with two controls. This suggests this patient has a type of LSD that could be non-classical Fabry disease.ConclusionThis study shows that lipidomics analysis is a valuable tool for rare disorder diagnosis, which can be conducted on leftover tissue samples without disrupting normal patient care.
Project description:The goal of this research was to find the most comprehensive lipid extraction of blood plasma, while also providing adequate aqueous preparation for metabolite analysis. Comparisons have been made previously of the Folch, Bligh-Dyer, and Matyash lipid extractions; furthermore, this paper provides an additional comparison of a phospholipid removal plate for analysis. This plate was used for lipid extraction rather than its intended use in lipid removal for polar analysis, and it proves to be robust for targeted lipid analysis. Folch and Matyash provided reproducible recovery over a range of lipid classes, however the Matyash aqueous layer compared well to a typical methanol preparation for polar metabolite analysis. Thus, the Matyash method is the best choice for an untargeted biphasic extraction for metabolomics and lipidomics in blood plasma.