Advances in sample preparation and analytical techniques for lipidomics study of clinical samples

Serum lipoprotein subfractions are associated with the periodontal status: Results from the population-based cohort SHIP-TREND

AIM

To investigate the medium-term associations of serum protein subfractions derived from proton nuclear magnetic resonance (1 H-NMR) spectroscopy with periodontitis and tooth loss.

MATERIALS AND METHODS

A total of 3031 participants of the cohort Study of Health in Pomerania (SHIP-TREND) were included. In addition to conventional serum testing, serum lipoprotein contents and subfractions were analysed by 1 H-NMR spectroscopy. Confounder-adjusted associations of lipoprotein variables with periodontitis and the number of missing teeth variables were analysed using mixed-effects models with random intercepts for time across individuals, accounting for multiple testing.

RESULTS

While only spurious associations between lipoprotein levels from conventional blood tests were found-that is, triglycerides were associated with mean clinical attachment level (CAL) and low-density lipoprotein cholesterol/high-density lipoprotein cholesterol (LDL-C/HDL-C) ratio with the number of missing teeth - several associations emerged from serum lipoprotein subfractions derived from 1 H-NMR analysis. Specifically, elevated LDL triglycerides were associated with higher levels of mean probing depth (PD), mean CALs, and increased odds of having <20 teeth. HDL-4 cholesterol levels were inversely associated with mean PD. Systemic inflammation (C-reactive protein) might mediate the effects of LDL and HDL triglyceride contents on periodontitis severity.

CONCLUSIONS

Several associations between serum lipoprotein subfractions and periodontitis were observed. As the underlying biochemical mechanisms remain unclear, further research is needed.

Recent Analytical Methodologies in Lipid Analysis

Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

Exploring biomarkers associated with severity of knee osteoarthritis in Southern China using widely targeted metabolomics

BACKGROUND

Metabolomics is a tool to study the pathogenesis of diseases and their associated metabolites, but there are still insufficient metabolomic studies on severe knee osteoarthritis.To investigate the differences in serum metabolites between healthy populations and knee osteoarthritis (KOA) patients in Southern China using widely targeted metabolomics, and to explore biomarkers and their metabolic pathways that could be associated with the severity of KOA.

METHODS

There were 10 healthy individuals in the control group and 32 patients with KOA. According to the Kellgren-Lawrence (KL) grading system, KOA was further divided into mild (n = 13, KL grade 1 and 2) and severe (n = 19, KL grade 3 and 4). Serum samples from all participants were collected and analyzed metabolomics based on ultra-performance liquid chromatography/electrospray ionization/tandem mass spectrometry. We screened for differential metabolites between patients and controls, and between mild and severe KOA. We explored the metabolic pathways involved in differential metabolism using the Kyoto Encyclopedia of Genes and Genomes database.

RESULTS

Sixty-one metabolites were differentially expressed in the sera of the patient group compared with the control group (45 upregulated and 16 downregulated). Analysis of the mild and severe KOA groups showed a total of 12 differential metabolites. Receiver operating characteristic curve analysis showed N-alpha-acetyl-L-asparagine was a good predictor of advanced osteoarthritis(OA).Differential metabolites are enriched in multiple pathways such as arachidonic acid metabolism.

CONCLUSION

Widely targeted metabolomics found that upregulation of the amino acid metabolite N-α-acetyl-L-asparagine was significantly associated with severe KOA and could be a biomarker for predicting severity of KOA. Arachidonic acid metabolism may play an important role in patients with severe KOA.

Removal of multiple lipids from human plasma using a hydroxyl-functionalized covalent organic framework aerogel as a new sorbent

A hydroxyl-functionalized covalent organic framework aerogel COFTHB-TAPB-aerogel was designed and prepared as an adsorbent for the removal of multiple lipids from human plasma. The applications of 1,3,5-tris(4'-hydroxy-5'-formylphenyl)benzene (THB) and 1,3,5-tris(4-aminophenyl)benzene (TAPB) as monomers, DMSO/mesitylene (v/v, 4/1) as reaction solvent, and n-propylamine as reaction regulator endow COFTHB-TAPB-aerogel with good adsorption performance for multiple lipids. The morphology, phase purity, specific surface area, pore size, surface charge, and stability of COFTHB-TAPB-aerogel were characterized. Adsorption thermodynamics and adsorption kinetics studies showed that COFTHB-TAPB-aerogel had high equilibrium adsorption capacities (> 15913 mg g-1) and fast adsorption equilibrium (≤ 10 s) for the four model lipids tested. COFTHB-TAPB-aerogel had good reusability with the removal of the model lipids being still more than 91% after 10 use cycles. The sample pretreatment conditions and adsorbent amounts used in lipids removal experiments were optimized. Under the optimized conditions, the method of ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) using COFTHB-TAPB-aerogel as solid-phase extraction sorbent was validated with negligible matrix effects (0.4-3.0%) and good accuracy (86.7-110%) and was applied to determine  20 amino acids in human plasma samples from healthy individuals and gastric adenocarcinoma (GA) patients. The established method has been proved to have good application potential for the removal of multiple lipids in human plasma to reduce the matrix effects and improve the accuracy of clinical LC-MS analysis.

Clinical lipidomics in the era of the big data

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

Applications of lipidomics in goat meat products: Biomarkers, structure, nutrition interface and future perspectives

Goat meat, as a superior product including low lipids, low cholesterol contents and high-quality proteins, becomes the superior food for the national market. With the increasing demand for goat meat, the production, sensory quality and physicochemical properties of goat meat are also widely observed. Following significant discoveries on the mechanism determining goat meat quality, further research on complex and interactive factors leading to changes of goat meat quality is increasingly based on data-driven "omics" methods, such as lipidomics, which can rapidly identify and quantify >1000 lipid species at same time facilitating comprehensive analyses of lipids in tissues. Molecular mechanism and biomarkers indicating the changes of goat meat quality, authentication, meat analogue, nutrition and health by lipidomics are feasible. According to the analysis results of the classes and of different biomarkers lipids of goat meat quality, the main processes involved the biosynthesis of unsaturated fatty acids, associations with lipids and proteins, lipid oxidation, lipid hydrolysis, lipid degradation, lipid deposition and lipid denaturation, which have been translated into advanced technologies for identifying the goat meat adulteration and faux meat rapidly and accurately. SIGNIFICANCE: In this review, the research of lipidomics technology, past applications, recent findings and common on the recent advances of lipidomics in the quality assessment of mutton products by lipidomics with MS approaches have been summarized. The information reported in review can serve as a reference to characterize the lipids found in mutton, clarify the application of lipidomics to the field of mutton products and provide new perspectives in producing superior quality mutton products.

Effects of perfluorobutane sulfonate and perfluorooctane sulfonate on lipid homeostasis in mouse liver

Perfluorobutane sulfonate (PFBS), an alternative to perfluorooctane sulfonate (PFOS), has been increasingly used in recent years. However, emerging evidence has raised concerns about the potential health risks of PFBS. Here, the toxicityof low-dose PFBS on livers was explored and compared with that of PFOS. Adult C57BL/6 mice were exposed to 10 μg/L, 500 μg/L PFBS, or 500 μg/L PFOS for 28 days through drinking water. At the phenotypic level, no liver damage was observed in the 10 μg/L PFBS group. The cell apoptosis and decrease of CAT activities were observed in the 500 μg/L PFBS group, while accumulation of lipid droplets, increase of CAT activities and TAG levels were found in the 500 μg/L PFOS group. Lipidomics analysis revealed that 138, 238, and 310 lipids were significantly changed in the 10 μg/L, 500 μg/L PFBS and 500 μg/L PFOS groups, respectively. The two PFBS-treated groups induced similar global lipid changes in a dose-dependent manner, which were distinct from PFOS. Overall, PFBS exposure induced an increase in phosphatidylcholines and sphingomyelins, but a decrease in phosphatidylinositol. PFOS exposure caused an increase in triacylglycerols. This study provides more evidence on the health hazards caused by exposure to low-dose PFBS.

Preliminary Investigation of the Effect of Maceration Procedures on Bone Metabolome and Lipidome

The study of post-mortem changes is a crucial component of forensic investigation. Human forensic taphonomic facilities (HFTFs) are the only institutions allowing the design and execution of controlled human decomposition experiments. When bodies are skeletonized, bones are normally stored in skeletal collections and used for anthropological studies. However, HFTFs apply chemical and/or thermal treatments to the remains prior bone long-term storage. These treatments are believed to alter heavily the original biochemical and molecular signature of bone material. The present study aims to evaluate the effect of these procedures on the bone metabolome and lipidome by using an animal bone model. Three intact bovine tibiae were processed using three protocols routinely applied at HFTFs, and their three counterparts were used as non-treated controls. Bone powder samples were subjected to biphasic extraction and both metabolites and lipids were analysed via liquid chromatography tandem mass-spectrometry. Results showed severe reductions in the abundances of both metabolites and lipids, and the presence of contamination introduced by cleaning agents. Despite the preliminary nature of the study, we demonstrated that the biochemical profile of bone is heavily affected by the maceration procedures. Ideally, these treatments should be avoided, or replaced by minimally invasive procedures agreed across HFTFs.

Probing Herbicide Toxicity to Algae (Selenastrum capricornutum) by Lipid Profiling with Machine Learning and Microchip/MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS)-based lipid profiling is a powerful method to study the cytotoxicity of chemical exposure to microorganisms at the single cell level. We report here a combined approach of machine learning (ML) and microchip-based MALDI-time of flight (TOF) mass spectrometry to investigate the cytotoxic effect of herbicides on algae through single cell lipid profiling. Algal species Selenastrum capricornutum was chosen as the target system, and its exposure to different doses of common chemical herbicides and the resulting cytotoxic behaviors under various stress conditions were characterized. A lipid library for S. capricornutum has been established with 63 identified lipids that include glycosyldiacylglycerols and triacylglycerols. We demonstrated that major alternations occurred for lipids with functional groups of digalactosyldiacylglycerol (DGDG), triacylglycerol (TAG), and monogalactosyldiacylglycerol (MGDG). DGDG was shown to decrease upon exposure to herbicides of norflurazon and atrazine, while some MGDG and TAG lipids would increase for norflurazon. Compared to other algae, S. capricornutum was more strongly impacted by norflurazon than atrazine while the latter was observed to have a greater effect on C. reinhardtii. Machine learning algorithms have been applied to improve the classification of herbicide impact and help identify lipid species affected by the chemical exposure. A total of 69 machine learning models were trained and tested for the identification of ideal algorithms in the classification process, in which flexible discriminant analysis and support vector machine model were found to be the most accurate and consistent. The ML algorithms accurately differentiated herbicide impact and have identified cytotoxic differences that were previously hidden. The results suggest that herbicides express toxicity among different algae likely on the basis of metabolic differences. The ML-assisted method proves to be highly effective and can provide an advanced technological platform for probing cytotoxicity for bacterial species and in metabolic pathway analysis.

Discovery and quantification of lipoamino acids in bacteria

Improving knowledge about metabolites produced by the microbiota is a key point to understand its role in human health and disease. Among them, lipoamino acid (LpAA) containing asparagine and their derivatives are bacterial metabolites which could have an impact on the host. In this study, our aim was to extend the characterization of this family. We developed a semi-targeted workflow to identify and quantify new candidates. First, the sample preparation and analytical conditions using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) were optimized. Using a theoretical homemade database, HRMS raw data were manually queried. This strategy allowed us to find 25 new LpAA conjugated to Asn, Gln, Asp, Glu, His, Leu, Ile, Lys, Phe, Trp and Val amino acids. These metabolites were then fully characterized by MS², and compared to the pure synthesized standards to validate annotation. Finally, a quantitative method was developed by LC coupled to a triple quadrupole instrument, and linearity and limit of quantification were determined. 14 new LpAA were quantified in gram positive bacteria, Lactobacilus animalis, and 12 LpAA in Escherichia coli strain Nissle 1917.

Enantioselective metabolomics by liquid chromatography-mass spectrometry

Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.

Lipidomic Profiling of Algae with Microarray MALDI-MS toward Ecotoxicological Monitoring of Herbicide Exposure

Misuse of agrochemicals has a long-lasting negative impact on aquatic systems. Mismanagement of herbicides in agri-food sectors is often linked to a simultaneous decline in the health of downstream waterways. However, monitoring the herbicide levels in these areas is a laborious task, and modern analytical approaches, such as solid-phase extraction-liquid chromatography-mass spectrometry (SPE-LC-MS) and enzyme-linked immunosorbent assay, are low-throughput and require significant sample preparation. We report here the use of microchip technology in combination with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) for the assessment of the ecotoxicological effect of agrochemicals on aquatic species at the single-cell level. This approach quantifies the fluctuations in lipid content in sentinel organisms and targets the microalga, Chlamydomonas reinhardtii (C. reinhardtii), as the model system. Specifically, we investigated the cytotoxicity of three herbicides (atrazine, clomazone, and norflurazon) on C. reinhardtii by analyzing the lipid component variation upon assorted herbicide exposure. Lipidomic profiling reveals a significantly altered lipid content at >EC₅₀ in atrazine-exposed cells. The response for norflurazon showed similar trends but diminished in magnitude, while the result for clomazone was near muted. At lower herbicide concentrations, digalactosyldiacylglycerols showed a rapid decrease in abundance, while several other lipids displayed a moderate increase. The microchip-based MALDI technique demonstrates the ability to achieve lipidomic profiling of aquatic species exposed to different stressors, proving effective for high-throughput screening and single-cell analysis in ecotoxicity studies.

An improved strategy for analysis of lipid molecules utilising a reversed phase C30 UHPLC column and scheduled MS/MS acquisition

Measuring physiochemically diverse molecules (including lipids) which vary significantly in their concentrations poses a great analytical challenge. In untargeted lipidomics studies, reversed phase chromatography coupled with data-dependent MS/MS acquisition (DDA) is frequently applied. The optimal assay should deliver a high number of detected compounds with associated fragmentation data. In this work, we introduce novel 30 and 50 min UHPLC assays utilising lipid separation on a C30 stationary phase with a modified DDA strategy using smaller precursor m/z ranges scheduled for different lipid classes across the retention time range (defined as scheduled MS/MS). To evaluate the efficiency of the novel assays, mammalian tissue extracts (lamb liver, kidney and heart) were analysed and data were compared to a 15 min reversed phase C18 assay with multiple traditional DDA injections. The 30 min C30 assay detected double the number of detected compounds compared to the 15 min C18 assay. Applying the scheduled MS/MS DDA strategy with a single injection, a similar number of annotated lipids were reported compared to the traditional DDA strategy applied with five replicate injections on a C18 column. A longer 50 min C30 chromatographic assay did not result in an expected improvement in the chromatographic separation of overlapping isomer peaks compared to the 30 min method but did result in loss of accuracy of peak picking algorithms. We recommend the 30 min C30 assay with scheduled MS/MS acquisition as an efficient tool to analyse complex biological matrices and to annotate lipid species based on MS/MS data.

Determination of inflammation-related lipids in depressive rats by on-line supercritical fluid extraction-supercritical fluid chromatography-tandem mass spectrometry

An on-line supercritical fluid extraction coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry method was developed to determine lipids related to inflammation in brain tissues of depressed rats. The analysis of 23 lipids from extraction to separation and detection only took 15 min and required 1 mg of brain tissue powder. The matrix effect of the on-line method for endogenous lipids was systematically investigated, and targeted lipids were quantified by matrix effect corrected calibration curves in this study. The on-line method was comprehensively optimized and evaluated. All calibration curves for lipids showed good linearity (correlation coefficient >0.99). The limits of detection and the limits of quantification were in the range of 0.0261-0.396 pg and 0.0791-1.20 pg. The recoveries and the matrix effect were in the range of 85.3-117.5% and 51.9-176.6%, respectively. The relative standard deviations of precision ranged from 2.7 to 14.2%, with accuracies higher than 87.2%. Compared with liquid-liquid extraction coupled with liquid chromatography-tandem mass spectrometry method, the on-line method obtained higher recovery and sensitivity with significantly reduced analytical time, manual operations, and sample amounts. Finally, this on-line method was applied to analyses of brain tissues of depressed rats. Six pro-inflammatory lipids increased in depressed rats, while six anti-inflammatory lipids decreased. Liquiritin and fluoxetine were presumed to promote a similar synthesis of anti-inflammatory lipids. Based on the results, this on-line method showed great promise in analyzing lipids in complex biological samples.

Untargeted Lipidomic Profiling of Dry Blood Spots Using SFC-HRMS

Lipids are essential cellular constituents that have many critical roles in physiological functions. They are notably involved in energy storage and cell signaling as second messengers, and they are major constituents of cell membranes, including lipid rafts. As a consequence, they are implicated in a large number of heterogeneous diseases, such as cancer, diabetes, neurological disorders, and inherited metabolic diseases. Due to the high structural diversity and complexity of lipid species, the presence of isomeric and isobaric lipid species, and their occurrence at a large concentration scale, a complete lipidomic profiling of biological matrices remains challenging, especially in clinical contexts. Using supercritical fluid chromatography coupled with high-resolution mass spectrometry, we have developed and validated an untargeted lipidomic approach to the profiling of plasma and blood. Moreover, we have tested the technique using the Dry Blood Spot (DBS) method and found that it allows for the easy collection of blood for analysis. To develop the method, we performed the optimization of the separation and detection of lipid species on pure standards, reference human plasma (SRM1950), whole blood, and DBS. These analyses allowed an in-house lipid data bank to be built. Using the MS-Dial software, we developed an automatic process for the relative quantification of around 500 lipids species belonging to the 6 main classes of lipids (including phospholipids, sphingolipids, free fatty acids, sterols, and fatty acyl-carnitines). Then, we compared the method using the published data for SRM 1950 and a mouse blood sample, along with another sample of the same blood collected using the DBS method. In this study, we provided a method for blood lipidomic profiling that can be used for the easy sampling of dry blood spots.

A high coverage pseudotargeted lipidomics method based on three-phase liquid extraction and segment data-dependent acquisition using UHPLC-MS/MS with application to a study of depression rats

Pseudotargeted analysis combines the advantages of untargeted and targeted lipidomics methods based on chromatography-mass spectrometry (MS). This study proposed a comprehensive pseudotargeted lipidomics method based on three-phase liquid extraction (3PLE) and segment data-dependent acquisition (SDDA). We used a 3PLE method to extract the lipids with extensive coverage from biological matrixes. 3PLE was composed of one aqueous and two organic phases. The upper and middle organic phases enriched neutral lipids and glycerophospholipids, respectively, combined and detected together. Besides, the SDDA strategy improved the detection of co-elution ions in the lipidomics analysis. A total of 554 potential lipids were detected by the developed approach in both positive and negative modes using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the conventional liquid-liquid extraction (LLE) approaches, including methyl tert-butyl ether (MTBE) and Bligh-Dyer (BD) methods, 3PLE combined with SDDA significantly increased the lipid coverage 87.2% and 89.7%, respectively. Also, the proposed pseudotargeted lipidomics approach exhibited higher sensitivity and better repeatability than the untargeted approach. Finally, we applied the established pseudotargeted method to the plasma lipid profiling from the depressed rats and screened 61 differential variables. The results demonstrated that the pseudotargeted method based on 3PLE and SDDA broadened lipid coverage and improved the detection of co-elution ions with excellent sensitivity and precision, indicating significant potential for the lipidomics analysis.

Recent applications of microextraction sample preparation techniques in biological samples analysis

Analysis of biological samples is affected by interfering substances with chemical properties similar to those of the target analytes, such as drugs. Biological samples such as whole blood, plasma, serum, urine and saliva must be properly processed for separation, purification, enrichment and chemical modification to meet the requirements of the analytical instruments. This causes the sample preparation stage to be of undeniable importance in the analysis of such samples through methods such as microextraction techniques. The scope of this review will cover a comprehensive summary of available literature data on microextraction techniques playing a key role for analytical purposes, methods of their implementation in common biological samples, and finally, the most recent examples of application of microextraction techniques in preconcentration of analytes from urine, blood and saliva samples. The objectives and merits of each microextration technique are carefully described in detail with respect to the nature of the biological samples. This review presents the most recent and innovative work published on microextraction application in common biological samples, mostly focused on original studies reported from 2017 to date. The main sections of this review comprise an introduction to the microextraction techniques supported by recent application studies involving quantitative and qualitative results and summaries of the most significant, recently published applications of microextracion methods in biological samples. This article considers recent applications of several microextraction techniques in the field of sample preparation for biological samples including urine, blood and saliva, with consideration for extraction techniques, sample preparation and instrumental detection systems.

LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring

Lipidomics is developing as an important area in biomedical and clinical research. Reliable quantification of lipid species is required for clinical translation of lipidomic studies. Hydrophilic interaction chromatography (HILIC), normal-phase liquid chromatography (NPLC), and supercritical fluid chromatography (SFC) are commonly used techniques in lipidomics and provide class-based separation of lipids. While co-elution of lipid species and their internal standards is an advantage for accurate quantification, it leads to isotopic overlap between species of the same lipid class. In shotgun lipidomics, isotopic correction is typically done based on elemental formulas of precursor ions. In multiple reaction monitoring (MRM) analyses, however, this approach should not be used, as the overall contribution of heavy isotopes to the MRM transitions' intensities depends on their location in the molecule with respect to the fragmentation pattern. We present an algorithm, provided in the R programming language, for isotopic correction in class-based separation using MRM, extracting relevant structural information from MRM transitions to apply adequate isotopic correction factors. Using standards, we show that our algorithm accurately estimates the isotopic contribution of isotopologues to MRM transitions' measured intensities. Using human plasma as an example, we demonstrate the necessity of adequate isotopic correction for accurate quantitation of lipids measured by MRM with class-based chromatographic separation. We show that over a third of the measured phosphatidylcholine species had their intensity corrected by more than 10%. This isotopic correction algorithm and R-implemented application enable a more accurate quantification of lipids in class-based separation-MRM, a prerequisite for successful translation of lipidomic applications.

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

Altered lipid metabolism has been associated with the progression of various cancers, and aberrant expression of enzymes involved in the lipid metabolism has been detected in different stages of cancer. Breast cancer (BC) is one of the cancer types known to be associated with alterations in the lipid metabolism and overexpression of enzymes involved in this metabolism. It has been demonstrated that inhibition of the activity of certain enzymes, such as that of phospholipase A₂ in BC cell lines sensitizes these cells and decreases the IC₅₀ values for forthcoming therapy with traditional drugs, such as doxorubicin and tamoxifen. Moreover, other phospholipases, such as phospholipase C and D, are involved in intracellular signal transduction, which emphasizes their importance in cancer development. Finally, BC is assumed to be dependent on the diet and the composition of lipids in nutrients. Despite their importance, analytical approaches that can associate the activity of phospholipases with changes in the lipid composition and distribution in cancer tissues are not yet standardized. In this review, an overview of various analytical platforms that are applied on the study of lipids and phospholipase activity in BC tissues will be given, as well as their association with cancer diagnosis and tumor progression. The methods that are applied to tissues obtained from the BC patients will be emphasized and critically evaluated, regarding their applicability in oncology.

Sample Preparation Methods for Lipidomics Approaches Used in Studies of Obesity

Obesity is associated with alterations in the composition and amounts of lipids. Lipids have over 1.7 million representatives. Most lipid groups differ in composition, properties and chemical structure. These small molecules control various metabolic pathways, determine the metabolism of other compounds and are substrates for the syntheses of different derivatives. Recently, lipidomics has become an important branch of medical/clinical sciences similar to proteomics and genomics. Due to the much higher lipid accumulation in obese patients and many alterations in the compositions of various groups of lipids, the methods used for sample preparations for lipidomic studies of samples from obese subjects sometimes have to be modified. Appropriate sample preparation methods allow for the identification of a wide range of analytes by advanced analytical methods, including mass spectrometry. This is especially the case in studies with obese subjects, as the amounts of some lipids are much higher, others are present in trace amounts, and obese subjects have some specific alterations of the lipid profile. As a result, it is best to use a method previously tested on samples from obese subjects. However, most of these methods can be also used in healthy, nonobese subjects or patients with other dyslipidemias. This review is an overview of sample preparation methods for analysis as one of the major critical steps in the overall analytical procedure.

A green and efficient pseudotargeted lipidomics method for the study of depression based on ultra-high performance supercritical fluid chromatography-tandem mass spectrometry

The pseudotargeted lipidomics method integrates the advantages of untargeted andtargeted lipidomics methods as a novel emerging approach. In this study, a green andefficient pseudotargeted lipidomics method based on ultra-high performancesupercritical fluid chromatography-tandem mass spectrometry (UHPSFC-MS/MS) wasdeveloped. The tandem mass spectra of the analytes were obtained by using UHPSFCwith quadrupole-time of flight MS (Q-TOF MS) in MS E mode and the multiplereaction monitoring (MRM) transitions of the lipidome were defined. Then, thecandidate MRM transitions were verified by UHPSFC with triple quadrupole massspectrometry (QqQ MS) in the scheduled MRM mode. In total, 758 potential lipidscorresponding to 509 and 249 MRM transitions were detected within 8 min in positiveand negative modes, respectively. The established pseudotargeted lipidomics methodwas validated to have excellent analytical characteristics. Compared with thepseudotargeted method based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), the UHPSFC-MS/MS-basedpseudotargeted method not only reduced the analytical time by half but also improvedthe sensitivity and resolution for most analytes, especially had better separation forlipid isomers. Besides, the UHPSFC-MS/MS-based pseudotargeted method showedhigher sensitivity and better repeatability for most analytes than the UHPSFC-MS/MS-based untargeted method. The established method was finally applied to investigatingthe lipid profiles of the plasma from the depressed rats and 33 differential variableswere screened, which related to three metabolic pathways. The results indicated thatthe UHPSFC-MS/MS-based pseudotargeted method is reliable and efficient and couldbe used in the lipidomics studies.

Structure determination of conjugated linoleic and linolenic acids

Conjugated linoleic and linolenic acids (CLA and CLnA) can be found in dairy, ruminant meat and oilseeds, these types of unsaturated fatty acids consist of various positional and geometrical isomers, and have demonstrated health-promoting potential for human beings. Extensive reviews have reported the physiological effects of CLA, CLnA, while little is known regarding their isomer-specific effects. However, the isomers are difficult to identify, owing to (i) the similar retention time in common chromatographic methods; and (ii) the isomers are highly sensitive to high temperature, pH changes, and oxidation. The uncertainties in molecular structure have hindered investigations on the physiological effects of CLA and CLnA. Therefore, this review presents a summary of the currently available technologies for the structural determination of CLA and CLnA, including the presence confirmation, double bond position determination, and the potential stereo-isomer determination. Special focus has been projected to the novel techniques for structure determination of CLA and CLnA. Some possible future directions are also proposed.

Mass spectrometry-based untargeted metabolomics approach for differentiation of beef of different geographic origins

Beef is a common staple food in many countries, and there is a growing concern over misinformation of beef products, such as false claims of origin, species and production methods. In this study, we used a mass spectrometry-based metabolomics approach to study the metabolite profiles of beef samples purchased from local retailers in Hong Kong. Using multivariate analysis, beef samples from different a) geographical origins, namely the United States (US), Japan and Australia, and b) feeding regimes could be differentiated. We identified twenty-four metabolites to distinguish beef samples from different countries, ten metabolites to identify Angus beef samples from others and seven metabolites to discriminate Australian beef produced by the organic farming from that produced using other farming modes. Based on results of this study, it is concluded that metabolomics provides an efficient strategy for tracing and authenticating beef products to ensure their quality and to protect consumer rights.

Advances in lipidomics

The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.

Compensate for or Minimize Matrix Effects? Strategies for Overcoming Matrix Effects in Liquid Chromatography-Mass Spectrometry Technique: A Tutorial Review

In recent decades, mass spectrometry techniques, particularly when combined with separation methods such as high-performance liquid chromatography, have become increasingly important in pharmaceutical, bio-analytical, environmental, and food science applications because they afford high selectivity and sensitivity. However, mass spectrometry has limitations due to the matrix effects (ME), which can be particularly marked in complex mixes, when the analyte co-elutes together with other molecules, altering analysis results quantitatively. This may be detrimental during method validation, negatively affecting reproducibility, linearity, selectivity, accuracy, and sensitivity. Starting from literature and own experience, this review intends to provide a simple guideline for selecting the best operative conditions to overcome matrix effects in LC-MS techniques, to obtain the best result in the shortest time. The proposed methodology can be of benefit in different sectors, such as pharmaceutical, bio-analytical, environmental, and food sciences. Depending on the required sensitivity, analysts may minimize or compensate for ME. When sensitivity is crucial, analysis must try to minimize ME by adjusting MS parameters, chromatographic conditions, or optimizing clean-up. On the contrary, to compensate for ME analysts should have recourse to calibration approaches depending on the availability of blank matrix. When blank matrices are available, calibration can occur through isotope labeled internal standards and matrix matched calibration standards; conversely, when blank matrices are not available, calibration can be performed through isotope labeled internal standards, background subtraction, or surrogate matrices. In any case, an adjusting of MS parameters, chromatographic conditions, or a clean-up are necessary.

Dual mass spectrometry as a tool to improve annotation and quantification in targeted plasma lipidomics

INTRODUCTION

High quality data, based on reliable quantification and clear identification of the reported lipid species, are required for the clinical translation of human plasma lipidomic studies.

OBJECTIVE

Lipid quantification can be efficiently performed on triple quadrupole (QqQ) mass spectrometers in targeted multiple reaction monitoring (MRM) mode. However, a series of issues can be encountered when aiming at unambiguous identification and accurate quantification, including (i) resolving peaks of polyunsaturated species, (ii) discriminating between plasmanyl-, plasmenyl- and odd chain species and (iii) resolving the isotopic overlap between co-eluting lipid species.

METHODS

As a practical tool to improve the quality of targeted lipidomics studies, we applied a Dual MS platform by simultaneously coupling a reversed-phase liquid chromatography separation to a QqQ and a quadrupole-time of flight (Q-ToF) mass spectrometers. In one single experiment, this platform allows to correctly identify, by high-resolution MS and MS/MS, the peaks that are quantified by MRM.

RESULTS

As proof of concept, we applied the platform on glycerophosphocholines (GPCs) and sphingomyelins (SMs), which are highly abundant in human plasma and play crucial roles in various physiological functions. Our results demonstrated that Dual MS could provide a higher level of confidence in the identification and quantification of GPCs and SMs in human plasma. The same approach can also be applied to improve the study of other lipid classes and expanded for the identification of novel lipid molecular species.

CONCLUSIONS

This methodology might have a great potential to achieve a better specificity in the quantification of lipids by targeted lipidomics in high-throughput studies.

Analysis of Lipids in Single Cells and Organelles Using Nanomanipulation-Coupled Mass Spectrometry

The ability to discriminately analyze the chemical constituents of single cells and organelles is highly sought after and necessary to establish true biomarkers. Some major challenges of individual cell analysis include requirement and expenditure of a large sample of cells as well as extensive extraction and separation techniques. Here, we describe methods to perform individual cell and organelle extractions of both tissues and cells in vitro using nanomanipulation coupled to mass spectrometry. Lipid profiles display heterogeneity from extracted adipocytes and lipid droplets, demonstrating the necessity for single cell analysis. The application of these techniques can be applied to other cell and organelle types for selective and thorough monitoring of disease progression and biomarker discovery.

Production of conjugated fatty acids: A review of recent advances

Conjugated fatty acids (CFAs) have received a deal of attention due to the increasing understanding of their beneficial physiological effects, especially the anti-cancer effects and metabolism-regulation activities. However, the production of CFAs is generally difficult. Several challenges are the low CFAs content in natural sources, the difficulty to chemically synthesize target CFA isomers in high purity, and the sensitive characteristics of CFAs. In this article, the current technologies to produce CFAs, including physical, chemical, and biotechnical approaches were summarized, with a focus on the conjugated linoleic acids (CLAs) and conjugated linolenic acids (CLNAs) which are the most common investigated CFAs. CFAs usually demonstrate stronger physiological effects than other non-conjugated fatty acids; however, they are more sensitive to heat and oxidation. Consequently, the quality control throughout the entire production process of CFAs is significant. Special attention was given to the micro- or nano-encapsulation which presented as an emerging technique to improve the bioavailability and storage stability of CFAs. The current applications of CFAs and the potential research directions were also discussed.

Qualitative analysis of phospholipids and their oxidised derivatives - used techniques and examples of their applications related to lipidomic research and food analysis

Phospholipids (PLs) are important biomolecules that not only constitute structural building blocks and scaffolds of cell and organelle membranes but also play a vital role in cell biochemistry and physiology. Moreover, dietary exogenous PLs are characterised by high nutritional value and other beneficial health effects, which are confirmed by numerous epidemiological studies. For this reason, PLs are of high interest in lipidomics that targets both the analysis of membrane lipid distribution as well as correlates composition of lipids with their effects on functioning of cells, tissues and organs. Lipidomic assessments follow-up the changes occurring in living organisms, such as free radical attack and oxidative modifications of the polyunsaturated fatty acids (PUFAs) build in PL structures. Oxidised PLs (oxPLs) can be generated exogenously and supplied to organisms with processed food or formed endogenously as a result of oxidative stress. Cellular and tissue oxPLs can be a biomarker predictive of the development of numerous diseases such as atherosclerosis or neuroinflammation. Therefore, suitable high-throughput analytical techniques, which enable comprehensive analysis of PL molecules in terms of the structure of hydrophilic group, fatty acid (FA) composition and oxidative modifications of FAs, have been currently developed. This review addresses all aspects of PL analysis, including lipid isolation, chromatographic separation of PL classes and species, as well as their detection. The bioinformatic tools that enable handling of a large amount of data generated during lipidomic analysis are also discussed. In addition, imaging techniques such as confocal microscopy and mass spectrometry imaging for analysis of cellular lipid maps, including membrane PLs, are presented.

Current Progress of Lipid Analysis in Metabolic Diseases by Mass Spectrometry Methods

BACKGROUND

Obesity, insulin resistance, diabetes, and metabolic syndrome are associated with lipid alterations, and they affect the risk of long-term cardiovascular disease. A reliable analytical instrument to detect changes in the composition or structures of lipids and the tools allowing to connect changes in a specific group of lipids with a specific disease and its progress, is constantly lacking. Lipidomics is a new field of medicine based on the research and identification of lipids and lipid metabolites present in human organism. The primary aim of lipidomics is to search for new biomarkers of different diseases, mainly civilization diseases.

OBJECTIVE

We aimed to review studies reporting the application of mass spectrometry for lipid analysis in metabolic diseases.

METHOD

Following an extensive search of peer-reviewed articles on the mass spectrometry analysis of lipids the literature has been discussed in this review article.

RESULTS

The lipid group contains around 1.7 million species; they are totally different, in terms of the length of aliphatic chain, amount of rings, additional functional groups. Some of them are so complex that their complex analyses are a challenge for analysts. Their qualitative and quantitative analysis of is based mainly on mass spectrometry.

CONCLUSION

Mass spectrometry techniques are excellent tools for lipid profiling in complex biological samples and the combination with multivariate statistical analysis enables the identification of potential diagnostic biomarkers.

Investigation of the relationships between knee osteoarthritis and obesity via untargeted metabolomics analysis

OBJECTIVE

Osteoarthritis (OA), the most encountered arthritis form, result from degeneration of articular cartilage. Obesity is accepted as a significant risk factor for knee OA (KOA). In this study, it is aimed to determine the variation of metabolites between control and patients with KOA and observe the effect of obesity on KOA via untargeted metabolomics method.

METHODS

Serum samples of following groups were collected: patient group including 14 obesity (OKOA) and 14 non-obesity (NOKOA) (n = 28) and control group (n = 15) from orthopedics and traumatology policlinic. Serum proteins were denatured by acetonitrile and chromatographic separation of metabolites was achieved by LC/Q-TOF/MS/MS method. Data acquisition, classification, and identification were achieved by METLIN database. Cluster analysis was performed with MATLAB2017a-PLS Toolbox 7.2.

RESULTS

Obtained results showed that 244 (patient vs control) and 274 (OKOA vs NOKOA) m/z ratios were determined in accordance with LC/Q-TOF/MS/MS analysis. Multivariate data analysis was applied 41 and 36 m/z signal (p ≤ 0.01; fold analysis > 1.5) were filtered for patient vs control group and OKOA vs NOKOA, respectively. Twenty-one different metabolites were identified for patient vs control group and 15 metabolites were determined for OKOA vs NOKOA group.

CONCLUSION

Acid concentration and oxidative stress agents were high in inflammation group and their levels were much higher in obesity. It is claimed that obesity cause oxidative stress and acidosis in arthritis patients. Valine was found to be the only BCAA molecule whose concentration has significantly different in KOA patients. The relation between KOA and obesity was firstly investigated with metabolomics method.

Recent applications of on-line supercritical fluid extraction coupled to advanced analytical techniques for compounds extraction and identification

In a previous review (Sánchez-Camargo et al., J. Sep. Sci. 40 (2017) 213-227), we discussed the application of on-line supercritical fluid extraction coupled to chromatographic techniques. This review includes an update of the most recent publications (from January 2016 till June 2018) on this topic, which employs advanced analytical techniques for extracting and identifying valuable analytes. Supercritical fluid extraction has been widely recognized as a green sample preparation technique, because it is efficient, environmentally friendly, powerful, and faster, offering the possibility of direct coupling to analytical instrumental techniques. Among those techniques, supercritical fluid chromatography has experienced an innovative progression in the last 10 years, and the most recent applications of supercritical fluid extraction are coupled to this advanced analytical tool. The general principles, both methodological and instrumental of on-line supercritical fluid extraction coupled to supercritical fluid chromatography are described here. Besides, applications of the mentioned coupling for analysing biological fluids, food, soil, and botanical samples are also presented and discussed. Finally, a brief description about the very recent on-line coupling of supercritical fluid extraction to ion mobility spectrometry is presented, as well as concluding remarks about the importance of using these coupled techniques in the near future.

Integrated Omics: Tools, Advances, and Future Approaches

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

One- vs two-phase extraction: re-evaluation of sample preparation procedures for untargeted lipidomics in plasma samples

Lipidomics is a rapidly developing field in modern biomedical research. While LC-MS systems are able to detect most of the known lipid classes in a biological matrix, there is no single technique able to extract all of them simultaneously. In comparison with two-phase extractions, one-phase extraction systems are of particular interest, since they decrease the complexity of the experimental procedure. By using an untargeted lipidomics approach, we explored the differences/similarities between the most commonly used two-phase extraction systems (Folch, Bligh and Dyer, and MTBE) and one of the more recently introduced one-phase extraction systems for lipid analysis based on the MMC solvent mixture (MeOH/MTBE/CHCl₃). The four extraction methods were evaluated and thoroughly compared against a pooled extract that qualitatively and quantitatively represents the average of the combined extractions. Our results show that the lipid profile obtained with the MMC system displayed the highest similarity to the pooled extract, indicating that it was most representative of the lipidome in the original sample. Furthermore, it showed better extraction efficiencies for moderate and highly apolar lipid species in comparison with the Folch, Bligh and Dyer, and MTBE extraction systems. Finally, the technical simplicity of the MMC procedure makes this solvent system highly suitable for automated, untargeted lipidomics analysis.

Lipidomics study of the protective effects of isosteviol sodium on stroke rats using ultra high-performance supercritical fluid chromatography coupling with ion-trap and time-of-flight tandem mass spectrometry

Isosteviol sodium (STV-Na) was reported to possess significant protective effects on ischemic stroke in recent years. However, the protective mechanism of STV-Na against stroke was still unclear. In this work, an untargeted lipidomics approach based on the ultra high-performance supercritical fluid chromatography coupling with ion-trap and time-of-flight tandem mass spectrometry (UHSFC-IT-TOF/MS) was employed to investigate the lipid profiles of stroke rats with STV-Na treatment for the first time. The possible mechanism of STV-Na was further elucidated. The UHSFC-IT-TOF/MS-based method achieved a fast separation of various lipids within 9 min with a qualified repeatability. Multivariate statistical analysis was used to show differences in lipid profiles induced by stroke and STV-Na treatment. The results showed a clear separation of the model group and the sham group, with the STV-Na group as well as EDA group located much closer to the sham group than the model group, which was consistent with the results of physiological and pathological assays, indicating the protective effects of STV-Na. Fifteen differential lipids that presented significant differences between the sham group and the model group were screened and identified. With the treatment of STV-Na, 15 differential lipids in stroke rats showed a tendency to the normal levels. Among them, 6 lipids were significantly reversed to the normal levels by STV-Na. The results of pathway analysis suggested the protective effects of STV-Na might be related to the regulation of several metabolic pathways including glycerophospholipid metabolism, arachidonic acid metabolism and sphingolipid metabolism. This work demonstrated that the UHSFC-IT-TOF/MS-based lipidomics profiling method was a useful tool to investigate the protective effects of STV-Na against stroke.

Tissue storage affects lipidome profiling in comparison to in vivo microsampling approach

Low-invasive in vivo solid-phase microextraction (SPME) was used to investigate the lipid profiles of muscle tissue of living fish. Briefly, mixed mode SPME fibers were inserted into the muscle for 20 min extraction, and then the fibers were desorbed in an optimal mixture of solvents. The obtained lipid profile was then compared and contrasted to that obtained with employment of ex vivo SPME and solid-liquid extraction (SLE) from fish muscle tissue belonging to the same group of fish, following a one-year storage period. Ex vivo SPME analysis of stored muscle samples revealed 10-fold decrease in the number of detected molecular features in comparison to in vivo study. Moreover, in vivo microsampling enabled the identification of different classes of bioactive lipids, including fatty acyls, not present in the lipid profile obtained through ex vivo SPME and SLE, suggesting the alterations occurring in the unbound lipid fraction of the system under study during the storage and also indicating the advantage of the in vivo extraction approach.

Examining heat treatment for stabilization of the lipidome

AIM

To confidently determine lipid-based biomarkers, it is important to minimize variation introduced during preanalytical steps. We evaluated reducing variation associated with lipid measurements in invertebrate sentinel species using a state-of-the-art heat treatment technique.

MATERIALS AND METHODS

Earthworms (Eisenia fetida), house crickets (Acheta domestica) and ghost shrimp (Palaemonetes paludosus) were euthanized either by flash freezing or heat treatment. For both experiments, samples were either immediately extracted after removal from -80°C storage or incubated on ice for one hour prior to sample weighing and extraction. Lipidomics was performed on resulting extracts using liquid chromatography high resolution tandem mass spectrometry. LipidMatch and LipidSearch were used for lipid identification.

RESULTS

Lipid enzymatic products (e.g., phosphatidylmethanols, diglycerides, lysoglycerophospholipids and ether-linked/oxidized lysoglycerophospholipids), were in higher concentrations in flash-frozen samples, when compared with heat-treated samples. Results suggest that heat treatment reduces phospholipase A and phospholipase D activity.

CONCLUSION

Heat treatment reduced enzymatic products and increased precursors of these enzymatic products. We believe heat treatment warrants a closer interrogation for improving the robustness of lipid biomarker research, especially in tissue samples, where enzyme stabilizers are difficult to apply, and for use in field studies, where the stabilization of the collected sample is critical.

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

Potential Application of 1H NMR for Routine Serum Lipidome Analysis -Evaluation of Effects of Bariatric Surgery

Routine laboratory lipid assays include simple measurements of total cholesterol, triacylglycerols and HDL. However, lipids are a large group of compounds involved in many metabolic pathways, and their alterations may have serious health consequences. In this study, we used 1H NMR to analyze lipids extracted from sera of 16 obese patients prior to and after bariatric surgeries. We observed a post-surgery decrease in serum concentrations of lipids from various groups. The hereby presented findings imply that 1H NMR is suitable for rapid, simple and non-invasive detection of lipids from 30 structural groups, among them triacylglycerols, phosphatidylcholine, phosphatidylethanolamine, sphingomyelin, total phospholipids, total, free and esterified cholesterol, total and unsaturated fatty acids. NMR-based analysis of serum lipids may contribute to a substantial increase in the number of routinely determined markers from this group; therefore, it may find application in clinical assessment of obese subjects prior to and after bariatric surgeries, as well as in the examination of patients with other metabolic diseases.