A normalized signal calibration with a long-term reference improves the robustness of RPLC-MRM/MS lipidomics in plasma.

Improving the reliability of quantification in lipidomic analyses is crucial for its successful application in the discovery of new biomarkers or in clinical practice. In this study, we propose a workflow to improve the accuracy and precision of lipidomic results issued by the laboratory. Lipid species from 11 classes were analyzed by a targeted RPLC-MRM/MS method. The peak areas of species were used to estimate concentrations by an internal standard calibration approach (IS-calibration) and by an alternative normalization signal calibration schema (NS-calibration). The latter uses a long-term reference plasma material as a matrix-matched external calibrator whose accuracy was compared to the NIST SRM-1950 mean consensus values reported by the Interlaboratory Lipidomics Comparison Exercise. The bias of lipid concentrations showed a good accuracy for 69 of 89 quantified lipids. The quantitation of species by the NS-calibration schema improved the within- and between-batch reproducibility in quality control samples, in comparison to the usual IS-calibration approach. Moreover, the NS-calibration workflow improved the robustness of the lipidomics measurements reducing the between-batch variability (relative standard deviation <10% for 95% of lipid species) in real conditions tested throughout the analysis of 120 plasma samples. In addition, we provide a free access web tool to obtain the concentration of lipid species by the two previously mentioned quantitative approaches, providing an easy follow-up of quality control tasks related to lipidomics.

A UPLC-MRM-MS method for comprehensive profiling of Amadori compound-modified phosphatidylethanolamines in human plasma.

Phosphatidylethanolamines (PEs) are targets of non-enzymatic glycation, a chemical process that occurs between glucose and primary amine-containing biomolecules. As the early-stage non-enzymatic glycation products of PE, Amadori-PEs are implicated in the pathogenesis of various diseases. However, only a few Amadori-PE molecular species have been identified so far; a comprehensive profiling of these glycated PE species is needed to establish their roles in disease pathology. Herein, based on our previous work using liquid chromatography-coupled neutral loss scanning and product ion scanning tandem mass spectrometry (LC-NLS-MS and LC-PIS-MS) in tandem, we extend identification of Amadori-PE to the low-abundance species, which is facilitated by using plasma lipids glycated in vitro. The confidence of identification is improved by high-resolution tandem mass spectrometry and chromatographic retention time regression. A LC-coupled multiple reaction monitoring mass spectrometry (LC-MRM-MS) assay is further developed for more sensitive quantitation of the Amadori compound-modified lipids. Using synthesized stable isotope-labeled Amadori lipids as internal standards, levels of 142 Amadori-PEs and 33 Amadori-LysoPEs are determined in the NIST human plasma standard reference material. These values may serve as an important reference for future investigations of Amadori-modified lipids in human diseases.

Preparative supercritical fluid chromatography for lipid class fractionation-a novel strategy in high-resolution mass spectrometry based lipidomics.

In this work, a lipidomics workflow based on offline semi-preparative lipid class-specific fractionation by supercritical fluid chromatography (SFC) followed by high-resolution mass spectrometry was introduced. The powerful SFC approach offered separation of a wide polarity range for lipids, enabled enrichment (up to 3 orders of magnitude) of lipids, selective fractionation of 14 lipid classes/subclasses, and increased dynamic range enabling in-depth characterization. A significantly increased coverage of low abundant lipids improving lipid identification by numbers and degree (species and molecular level) was obtained in Pichia pastoris when comparing high-resolution mass spectrometry based lipidomics with and without prior fractionation. Proof-of-principle experiments using a standard reference material (SRM 1950, NIST) for human plasma showed that the proposed strategy enabled quantitative lipidomics. Indeed, for 70 lipids, the consensus values available for this sample could be met. Thus, the novel workflow is ideally suited for lipid class-specific purification/isolation from milligram amounts of sample while not compromising on omics type of analysis (identification and quantification). Finally, compared with established fractionation/pre-concentration approaches, semi-preparative SFC is superior in terms of versatility, as it involved only volatile modifiers and salt additives facilitating any follow-up use such as qualitative or quantitate analysis or further purification down to the single lipid species level. Graphical Abstract.

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values.

BACKGROUND: Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows. RESULTS: LMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine. CONCLUSIONS: LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

Comprehensive analysis of oxylipins in human plasma using reversed-phase liquid chromatography-triple quadrupole mass spectrometry with heatmap-assisted selection of transitions.

Oxylipins, a subclass of lipid mediators, are metabolites of various polyunsaturated fatty acids with crucial functions in regulation of systemic inflammation. Elucidation of their roles in pathological conditions requires accurate quantification of their levels in biological samples. We refined an ultra-performance liquid chromatography-multiple reaction monitoring-mass spectrometry (UPLC-MRM-MS)-based workflow for comprehensive and specific quantification of 131 endogenous oxylipins in human plasma, in which we optimized LC mobile phase additives, column, and gradient conditions. We employed heatmap-assisted strategy to identify unique transitions to improve the assay selectivity and optimized solid phase extraction procedures to achieve better analyte recovery. The method was validated according to FDA guidelines. Overall, 94.4% and 95.7% of analytes at tested concentrations were within acceptable accuracy (80-120%) and precision (CV < 15%), respectively. Good linearity for most analytes was obtained with R2 > 0.99. The method was also validated using a standard reference material-SRM 1950 frozen human plasma to demonstrate inter-lab compatibility. Graphical abstract ᅟ.

A comprehensive UHPLC-MS/MS method for metabolomics profiling of signaling lipids: Markers of oxidative stress, immunity and inflammation.

Signaling lipids (SLs) play a crucial role in various signaling pathways, featuring diverse lipid backbone structures. Emerging evidence showing the biological significance and biomedical values of SLs has strongly spurred the advancement of analytical approaches aimed at profiling SLs. Nevertheless, the dramatic differences in endogenous abundances across lipid classes as well as multiple isomers within the same lipid class makes the development of a generic analytical method challenging. A better analytical method that combines comprehensive coverage and high sensitivity is needed to enable us to gain a deeper understanding of the biochemistry of these molecules in health and disease. In this study, we developed a fast and comprehensive targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for profiling SLs. The platform enables analyses of 260 metabolites covering oxylipins (isoprostanes, prostaglandins and other oxidized lipids), free fatty acids, lysophospholipids, sphingoid bases (C16, C18), platelet activating factors (C16, C18), endocannabinoids and bile acids. Various validation parameters including linearity, limit of detection, limit of quantification, extraction recovery, matrix effect, intra-day and inter-day precision were used to characterize this method. Metabolite quantitation was successfully achieved in both NIST Standard Reference Material for human plasma (NIST SRM 1950) and pooled human plasma, with 109 and 144 metabolites quantitated. The quantitation results in NIST SRM 1950 plasma demonstrated good correlations with certified or previously reported values in published literature. This study introduced quantitative data for 37 SLs for the first time. Metabolite concentrations measured in NIST SRM 1950 will serve as essential reference data for facilitating interlaboratory comparisons. The methodology established here will be the cornerstone for in-depth profiling of signaling lipids across diverse biological samples and contexts.

Development of a targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry based lipidomics platform applied to a coronavirus disease severity study.

The importance of lipids seen in studies of metabolism, cancer, the recent COVID-19 pandemic and other diseases has brought the field of lipidomics to the forefront of clinical research. Quantitative and comprehensive analysis is required to understand biological interactions among lipid species. However, lipidomic analysis is often challenging due to the various compositional structures, diverse physicochemical properties, and wide dynamic range of concentrations of lipids in biological systems. To study the comprehensive lipidome, a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method with 1200 lipid features across 19 (sub)classes, including both nonpolar and polar lipids, has been developed. HILIC-MS/MS was selected due to its class separation property and fatty acyl chain level information. 3D models of class chromatographic retention behavior were established and evaluations of cross-class and within-class interferences were performed to avoid over-reporting these features. This targeted HILIC-MS/MS method was fully validated, with acceptable analytical parameters in terms of linearity, precision, reproducibility, and recovery. The accurate quantitation of 608 lipid species in the SRM 1950 NIST plasma was achieved using multi-internal standards per class and post-hoc correction, extending current databases by providing lipid concentrations resolved at fatty acyl chain level. The overall correlation coefficients (R2) of measured concentrations with values from literature range from 0.64 to 0.84. The applicability of the developed targeted lipidomics method was demonstrated by discovering 520 differential lipid features related to COVID-19 severity. This high coverage and targeted approach will aid in future investigations of the lipidome in various disease contexts.

In-Needle Pre-Column Derivatization for Amino Acid Quantification (iPDAQ) Using HPLC.

Pre-column fluorescent derivatization has been used for the fast quantification of amino acids using high-performance liquid chromatography (HPLC) systems. However, it generally requires an offline in-vial derivatization process with multiple derivatization reagents. The offline derivatization requires the same number of reaction vials as the number of sample vials for use as a reaction chamber for the derivatization reaction in an autosampler. Therefore, the number of samples analyzed per batch using the pre-column derivatization method is halved. To benefit from the pre-column derivatization method, we transformed the derivatization process from an offline chamber process to an online in-needle process (in-needle Pre-column Derivatization for Amino acids Quantification; iPDAQ). Fluorescent derivatization in the injection needle obviated the need for vacant vials as reaction chambers. Consequently, the throughput per batch improved up to two times, and the consumption of derivatization reagents was reduced to less than one-tenth of that in the conventional vial method. We demonstrated to separate and quantify the amino acids in various biological samples. Herein, we presented a novel HPLC-based amino acid quantification method that enables the continuous analysis of a large number of samples. The iPDAQ facilitates accurate amino acid quantification due to the automation of derivatization and achieves improvement in the throughput and reduction of analysis labor.

Plasma and serum oxylipin, endocannabinoid, bile acid, steroid, fatty acid and nonsteroidal anti-inflammatory drug quantification in a 96-well plate format.

The goal of this research was to develop a high-throughput, cost-effective method for metabolic profiling of lipid mediators and hormones involved in the regulation of inflammation and energy metabolism, along with polyunsaturated fatty acids and common over-the-counter non-steroidal anti-inflammatory drugs (NSAIDs). We describe a 96-well plate protein precipitation and filtration procedure for 50 µL of plasma or serum in the presence of 37 deuterated analogs and 2 instrument internal standards. Data is acquired in two back-to-back UPLC-MS/MS analyses using electrospray ionization with positive/negative switching and scheduled multiple reaction monitoring for the determination of 145 compounds, including oxylipins, endocannabinoids and like compounds, bile acids, glucocorticoids, sex steroids, polyunsaturated fatty acids, and 3 NSAIDs. Intra- and inter-batch variability was <25% for >70% of metabolites above the LOQ in both matrices, but higher inter-batch variability was observed for serum oxylipins and some bile acids. Results for NIST Standard Reference Material 1950, compared favorably with the 20 certified metabolite values covered by this assay, and we provide new data for oxylipins, N-acylethanolamides, glucocorticoids, and 17-hydroxy-progesterone in this material. Application to two independent cohorts of elderly men and women showed the routine detection of 86 metabolites, identified fasting state influences on essential fatty acid-derived oxylipins, N-acylethanolamides and conjugated bile acids, identified rare presence of high and low testosterone levels and the presence of NSAIDs in ∼10% of these populations. The described method appears valuable for investigations in large cohort studies to provide insight into metabolic cross-talk between the array of mediators assessed here.

Calibration-Curve-Locking Database for Semi-Quantitative Metabolomics by Gas Chromatography/Mass Spectrometry.

Calibration-Curve-Locking Databases (CCLDs) have been constructed for automatic compound search and semi-quantitative screening by gas chromatography/mass spectrometry (GC/MS) in several fields. CCLD felicitates the semi-quantification of target compounds without calibration curve preparation because it contains the retention time (RT), calibration curves, and electron ionization (EI) mass spectra, which are obtained under stable apparatus conditions. Despite its usefulness, there is no CCLD for metabolomics. Herein, we developed a novel CCLD and semi-quantification framework for GC/MS-based metabolomics. All analytes were subjected to GC/MS after derivatization under stable apparatus conditions using (1) target tuning, (2) RT locking technique, and (3) automatic derivatization and injection by a robotic platform. The RTs and EI mass spectra were obtained from an existing authorized database. A quantifier ion and one or two qualifier ions were selected for each target metabolite. The calibration curves were obtained as plots of the peak area ratio of the target compounds to an internal standard versus the target compound concentration. These data were registered in a database as a novel CCLD. We examined the applicability of CCLD for analyzing human plasma, resulting in time-saving and labor-saving semi-qualitative screening without the need for standard substances.

A rapid and simple method to quantify per- and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates.

Per- and polyfluoroalkyl substances (PFAS) are synthetic organic compounds that over the past several years, have witnessed a dramatic increase in scientific attention. As PFAS are predominantly accumulated in plasma, monitoring individual burden levels in plasma are typically achieved via some combination of protein precipitation and/or solid phase extraction (SPE), either in online or offline modes. This work describes an updated PFAS extraction workflow, using 96-well plate technology and protein precipitation that is rapid, simple, inexpensive, and amenable for large cohort studies. In brief, plasma proteins were precipitated using methanol and the resulting centrifuged supernatant was directly analyzed using UHPLC-MS/MS. We monitored 51 PFAS, which were quantified via isotope dilution and the effectiveness of the method was demonstrated by using NIST blood-based Standard Reference Materials (SRMs). This method resulted in recoveries ranging between 70 and 89% for all analytes. The 96-well design exhibited low limits of detection and only required sample volumes of 100 µL, thus resulting in an amenable method for high-throughput plasma/serum PFAS screening. • PFAS were directly quantified in plasma and serum samples; • No SPE needed after protein precipitation; • SRMs can be used to validate PFAS measurement in plasma/serum.

Optimization of Folch, Bligh-Dyer, and Matyash sample-to-extraction solvent ratios for human plasma-based lipidomics studies.

In order to profile the lipidome for untargeted lipidomics applications, analysis by ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC-HRMS) typically requires the extraction of lipid content from sample matrices using matrix-specific conditions. The Folch, Bligh-Dyer, and Matyash extraction methods, while promising approaches, were originally tailored to specific matrices (brain tissue, fish muscle, and E. coli, respectively). Each of these methods have specific solvent ratios that must be adhered to achieve optimal extraction. Thus, the sample-to-solvent ratios for these methods should be optimized for the sample matrix of interest prior to employment. This study evaluated the appropriate sample-to-extraction solvent ratios for human plasma-based lipidomics studies. An advantage of employing biphasic lipid extractions is the ability to investigate both the aqueous and organic layers for increased analyte coverage in untargeted studies. Therefore, this work also evaluated the multi-omic capability of each lipid extraction method for plasma in an effort to provide a workflow capable of increasing analyte coverage in a single extraction, thus providing a more complete understanding of complex biological systems. In plasma, a decrease in sample-to-solvent ratios from 1:4, 1:10, 1:20, to 1:100 (v/v) resulted in a gradual increase in the peak area of a diverse range of metabolite (aqueous layer) and lipid (organic layer) species for each extraction method up to the 1:20(v/v) sample-to-solvent ratio. The Bligh-Dyer and Folch methods yielded the highest peak areas at every plasma sample-to-solvent ratios for both metabolite and lipid species. Depending on the lipid class of interest, the Folch or Bligh-Dyer method is best suited for analysis of human plasma at a 1:20 (v/v) sample to total solvent ratio.

Interlaboratory analytical comparison of fatty acid concentrations in serum or plasma.

BACKGROUND: There are a large number of clinical studies focusing on the measurement of individual fatty acids in serum or plasma; however, few studies have focused on the interlaboratory comparisons of these measurements. The National Institutes of Standards and Technology (NIST), in collaboration with the National Institutes of Health Office of Dietary Supplements (NIH-ODS) and the Centers for Disease Control and Prevention (CDC), has initiated a quality assurance program for assessing and improving the comparability of individual fatty acid measurements in serum and plasma. METHODS: This is a performance-based study so participants are encouraged to use their laboratory's methods for the quantification of the individual fatty acids that they typically measure in the unknown serum or plasma samples along with a control material. The control materials used to date are SRM 1950 Metabolites in Human Plasma and SRM 2378 Fatty Acids in Frozen Human Serum. RESULTS: To date, two studies of the Fatty Acid Quality Assurance Program (FAQAP) have been completed with 11 and 14 participants, respectively. The agreement among the laboratories for individual fatty acids was within 20% for 70% of the data submitted. Laboratories were also requested to run triplicate analyses for each unknown sample. The precision of the individual laboratory data was generally good, with relative standard deviations <20%. CONCLUSIONS: The results from the first two exercises indicate the need for additional assessment of the comparability among laboratories doing these measurements. Future studies will be conducted with the goals of increasing the number of participating laboratories, increasing awareness of the need to use control materials, and improving the comparability among laboratories.