Lipidomics from sample preparation to data analysis: a primer

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

Integrating multi-omics approaches in deciphering atopic dermatitis pathogenesis and future therapeutic directions

Atopic dermatitis (AD), a complex and heterogeneous chronic inflammatory skin disorder, manifests in a spectrum of clinical subtypes. The application of genomics has elucidated the role of genetic variations in predisposing individuals to AD. Transcriptomics, analyzing gene expression alterations, sheds light on the molecular underpinnings of AD. Proteomics explores the involvement of proteins in AD pathophysiology, while epigenomics examines the impact of environmental factors on gene expression. Lipidomics, which investigates lipid profiles, enhances our understanding of skin barrier functionalities and their perturbations in AD. This review synthesizes insights from these omics approaches, highlighting their collective importance in unraveling the intricate pathogenesis of AD. The review culminates by projecting future trajectories in AD research, particularly the promise of multi-omics in forging personalized medicine and novel therapeutic interventions. Such an integrated multi-omics strategy is poised to transform AD comprehension and management, steering towards more precise and efficacious treatment modalities.

Structure Revision of a Widespread Marine Sulfonolipid Class Based on Isolation and Total Synthesis

The cosmopolitan marine Roseobacter clade is of global biogeochemical importance. Members of this clade produce sulfur-containing amino lipids (SALs) involved in biofilm formation and marine surface colonization processes. Despite their physiological relevance and abundance, SALs have only been explored through genomic mining approaches and lipidomic studies based on mass spectrometry, which left the relative and absolute structures of SALs unresolved, hindering progress in biochemical and functional investigations. Herein, we report the structural revision of a new group of SALs, which we named cysteinolides, using a combination of analytical techniques, isolation and degradation experiments and total synthetic efforts. Contrary to the previously proposed homotaurine-based structures, cysteinolides are composed of an N,O-acylated cysteinolic acid-containing head group carrying various different (α-hydroxy)carboxylic acids. We also performed the first validated targeted-network based analysis, which allowed us to map the distribution and structural diversity of cysteinolides across bacterial lineages. Beyond offering structural insight, our research provides SAL standards and validated analytical data. This information holds significance for forthcoming investigations into bacterial sulfonolipid metabolism and biogeochemical nutrient cycling within marine environments.

Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials

Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.

Excipient-related impurities in liposome drug products

Liposomes are widely used in the pharmaceutical industry as drug delivery systems to increase the efficacy and reduce the off-target toxicity of active pharmaceutical ingredients (APIs). The liposomes are more complex drug delivery systems than the traditional dosage forms, and phospholipids and cholesterol are the major structural excipients. These two excipients undergo hydrolysis and/or oxidation during liposome preparation and storage, resulting in lipids hydrolyzed products (LHPs) and cholesterol oxidation products (COPs) in the final liposomal formulations. These excipient-related impurities at elevated concentrations may affect liposome stability and exert biological functions. This review focuses on LHPs and COPs, two major categories of excipient-related impurities in the liposomal formulations, and discusses factors affecting their formation, and analytical methods to determine these excipient-related impurities.

Determination of fatty acid uptake and desaturase activity in mammalian cells by NMR-based stable isotope tracing

BACKGROUND

Mammalian cells both import exogenous fatty acids and synthesize them de novo. Palmitate, the end product of fatty acid synthase (FASN) is a substrate for stearoyl-CoA desaturases (Δ-9 desaturases) that introduce a single double bond into fatty acyl-CoA substrates such as palmitoyl-CoA and stearoyl-CoA. This process is particularly upregulated in lipogenic tissues and cancer cells. Tracer methodology is needed to determine uptake versus de novo synthesis of lipids and subsequent chain elongation and desaturation. Here we describe an NMR method to determine the uptake of 13C-palmitate from the medium into HCT116 human colorectal cancer cells, and the subsequent desaturation and incorporation into complex lipids.

RESULTS

Exogenous 13C16-palmitate was absorbed from the medium by HCT116 cells and incorporated primarily into complex glycerol lipids. Desaturase activity was determined from the quantification of double bonds in acyl chains, which was greatly reduced by ablation of the major desaturase SCD1.

SIGNIFICANCE

The NMR approach requires minimal sample preparation, is non-destructive, and provides direct information about the level of saturation and incorporation of fatty acids into complex lipids.

Improved lipid analysis using a 2D-LC-MS system with a novel injection procedure

The aim of this study was to improve analysis of nonpolar lipidomics sample extracts using reversed phase (RP) chromatography. A 4/3/3 (v/v/v) mixture of methanol/methyl tert-butyl ether/chloroform (MeOH/MTBE/CHCl3, MMC) was chosen for sample extraction solvent based on its proven extraction capability for several lipid classes. To avoid carry over, loss of analytes and peak distortion the loops and all capillaries of the presented LC system were flushed and filled up with methanol until the analytical column. The choice of methanol was due to its weak elution strength and being infinitely miscible with MMC and several other nonpolar solvents. This allowed injection of a 100 μl sample that was 20 μl nonpolar extraction solvent diluted fivefold with methanol. All lipids of 25 lipid classes were transferred quantitatively to the column head where the online dilution of methanol was carried out with aqueous eluent for focusing the lipid analytes. The weak elution strength of methanol prevented peak distortions. The consecutive reversed phase elution resulted in remarkably narrow peaks (full width at half maximum was 0.07-0.08 min typically) and enhanced sensitivity (limit of detection usually in sub nM region) because of increased sample injection volume and narrow peaks. Calibration and quality control samples made by diluting commercial lipid standards 200-50000 times confirmed the applicability of this approach both for targeted lipid quantification and for untargeted quantitative comparison of lipids from different sources.

Changes in Lipid Profiles with the Progression of Pregnancy in Black Women

Background/Objectives: Lipid metabolism plays an important role in maternal health and fetal development. There is a gap in the knowledge of how lipid metabolism changes during pregnancy for Black women who are at a higher risk of adverse outcomes. We hypothesized that the comprehensive lipidome profiles would show variation across pregnancy indicative of requirements during gestation and fetal development. Methods: Black women were recruited at prenatal clinics. Plasma samples were collected at 8-18 weeks (T1), 22-29 weeks (T2), and 30-36 weeks (T3) of pregnancy. Samples from 64 women who had term births (≥37 weeks gestation) were subjected to "shotgun" Orbitrap mass spectrometry. Mixed-effects models were used to quantify systematic changes and dimensionality reduction models were used to visualize patterns and identify reliable lipid signatures. Results: Total lipids and major lipid classes showed significant increases with the progression of pregnancy. Phospholipids and glycerolipids exhibited a gradual increase from T1 to T2 to T3, while sphingolipids and total sterol lipids displayed a more pronounced increase from T2 to T3. Acylcarnitines, hydroxy acylcarnitines, and Lyso phospholipid levels significantly decreased from T1 to T3. A deviation was that non-esterified fatty acids decreased from T1 to T2 and increased again from T2 to T3, suggestive of a potential role for these lipids during the later stages of pregnancy. The fatty acids showing this trend included key fatty acids-non-esterified Linoleic acid, Arachidonic acid, Alpha-linolenic acid, Eicosapentaenoic acid, Docosapentaenoic acid, and Docosahexaenoic acid. Conclusions: Mapping lipid patterns and identifying lipid signatures would help develop intervention strategies to reduce perinatal health disparities among pregnant Black women.

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

JAK/STAT Inhibition Normalizes Lipid Composition in 3D Human Epidermal Equivalents Challenged with Th2 Cytokines

Derangement of the epidermal barrier lipids and dysregulated immune responses are key pathogenic features of atopic dermatitis (AD). The Th2-type cytokines interleukin IL-4 and IL-13 play a prominent role in AD by activating the Janus Kinase/Signal Transduction and Activator of Transcription (JAK/STAT) intracellular signaling axis. This study aimed to investigate the role of JAK/STAT in the lipid perturbations induced by Th2 signaling in 3D epidermal equivalents. Tofacitinib, a low-molecular-mass JAK inhibitor, was used to screen for JAK/STAT-mediated deregulation of lipid metabolism. Th2 cytokines decreased the expression of elongases 1, 3, and 4 and serine-palmitoyl-transferase and increased that of sphingolipid delta(4)-desaturase and carbonic anhydrase 2. Th2 cytokines inhibited the synthesis of palmitoleic acid and caused depletion of triglycerides, in association with altered phosphatidylcholine profiles and fatty acid (FA) metabolism. Overall, the ceramide profiles were minimally affected. Except for most sphingolipids and very-long-chain FAs, the effects of Th2 on lipid pathways were reversed by co-treatment with tofacitinib. An increase in the mRNA levels of CPT1A and ACAT1, reduced by tofacitinib, suggests that Th2 cytokines promote FA beta-oxidation. In conclusion, pharmacological inhibition of JAK/STAT activation prevents the lipid disruption caused by the halted homeostasis of FA metabolism.

Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

Metabolic Profiling as an Approach to Differentiate T-Cell Acute Lymphoblastic Leukemia Cell Lines Belonging to the Same Genetic Subgroup

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30-45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.

Lipidome Changes Associated with a Diet-Induced Reduction in Hepatic Fat among Adolescent Boys with Metabolic Dysfunction-Associated Steatotic Liver Disease

Little is known about lipid changes that occur in the setting of metabolic-dysfunction-associated steatotic liver disease (MASLD) regression. We previously reported improvements in hepatic steatosis, de novo lipogenesis (DNL), and metabolomic profiles associated with oxidative stress, inflammation, and selected lipid metabolism in 40 adolescent boys (11-16 y) with hepatic steatosis ≥5% (98% meeting the definition of MASLD). Participants were randomized to a low-free-sugar diet (LFSD) (n = 20) or usual diet (n = 20) for 8 weeks. Here, we employed untargeted/targeted lipidomics to examine lipid adaptations associated with the LFSD and improvement of hepatic steatosis. Our LC-MS/MS analysis revealed decreased triglycerides (TGs), diacylglycerols (DGs), cholesteryl esters (ChE), lysophosphatidylcholine (LPC), and phosphatidylcholine (PC) species with the diet intervention (p < 0.05). Network analysis demonstrated significantly lower levels of palmitate-enriched TG species post-intervention, mirroring the previously shown reduction in DNL in response to the LFSD. Targeted oxylipins analysis revealed a decrease in the abundance of 8-isoprostane and 14,15-DiHET and an increase in 8,9-DiHET (p < 0.05). Overall, we observed reductions in TGs, DGs, ChE, PC, and LPC species among participants in the LFSD group. These same lipids have been associated with MASLD progression; therefore, our findings may indicate normalization of key biological processes, including lipid metabolism, insulin resistance, and lipotoxicity. Additionally, our targeted oxylipins assay revealed novel changes in eicosanoids, suggesting improvements in oxidative stress. Future studies are needed to elucidate the mechanisms of these findings and prospects of these lipids as biomarkers of MASLD regression.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Mathematical Modeling of Alpha-Tocopherol Early Degradation Kinetics to Predict the Shelf-Life of Bulk Oils

The kinetics of lipid oxidation includes a lag phase followed by an exponential increase in oxidation products, which cause rancidity. Current models focus on the slope of this exponential curve for shelf-life estimation, which still requires the measurement of full oxidation kinetics. In this paper, we analyzed the formation of lipid oxidation products in stripped soybean oil containing different levels of α-tocopherol. The lag phases of lipid hydroperoxides and headspace hexanal formation were found to have a strong positive correlation with the α-tocopherol depletion time. We propose that the kinetics of antioxidant (α-tocopherol) depletion occur during the lag phase and could serve as an early shelf-life indicator. Our results showed that α-tocopherol degradation can be described by Weibull kinetics over a wide range of initial concentrations. Furthermore, we conducted in silico investigations using Monte Carlo simulations to critically evaluate the feasibility and sensitivity of the shelf-life prediction using early antioxidant degradation kinetics. Our results revealed that the shelf life of soybean oil may be accurately predicted as early as 20% of the overall shelf life. This innovative approach provides a more efficient and faster assessment of shelf life, ultimately reducing waste and enhancing product quality.

Lipid droplets, autophagy, and ER stress as key (survival) pathways during ischemia-reperfusion of transplanted grafts

Ischemia-reperfusion injury is an event concerning any organ under a procedure of transplantation. The early result of ischemia is hypoxia, which causes malfunction of mitochondria and decrease in cellular ATP. This leads to disruption of cellular metabolism. Reperfusion also results in cell damage due to reoxygenation and increased production of reactive oxygen species, and later by induced inflammation. In damaged and hypoxic cells, the endoplasmic reticulum (ER) stress pathway is activated by increased amount of damaged or misfolded proteins, accumulation of free fatty acids and other lipids due to inability of their oxidation (lipotoxicity). ER stress is an adaptive response and a survival pathway, however, its prolonged activity eventually lead to induction of apoptosis. Sustaining cell functionality in stress conditions is a great challenge for transplant surgeons as it is crucial for maintaining a desired level of graft vitality. Pathways counteracting negative consequences of ischemia-reperfusion are autophagy and lipid droplets (LD) metabolism. Autophagy remove damaged organelles and molecules driving them to lysosomes, digested simpler compounds are energy source for the cell. Mitophagy and ER-phagy results in improvement of cell energetic balance and alleviation of ER stress. This is important in sustaining metabolic homeostasis and thus cell survival. LD metabolism is connected with autophagy as LD are degraded by lipophagy, a source of free fatty acids and glycerol-thus autophagy and LD can readily remove lipotoxic compounds in the cell. In conclusion, monitoring and pharmaceutic regulation of those pathways during transplantation procedure might result in increased/improved vitality of transplanted organ.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

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.

Metabolomics and lipidomics signature in celiac disease: a narrative review

Celiac disease (CD) is a chronic immune-mediated inflammatory disease of the small intestine caused by aberrant immune responses to consumed gluten proteins. CD is diagnosed by a combination of the patients reported symptoms, serologic and endoscopic biopsy evaluation of the small intestine; and adherence to a strict gluten-free diet (GFD) is considered the only available therapeutic approach for this disorder. Novel approaches need to be considered for finding new biomarkers to help this disorder diagnosis and finding a new alternative therapeutic method for this group of patients. Metabolomics and lipidomics are powerful tools to provide highly accurate and sensitive biomarkers. Previous studies indicated a metabolic fingerprint for CD deriving from alterations in gut microflora or intestinal permeability, malabsorption, and energy metabolism. Moreover, since CD is characterized by increased intestinal permeability and due to the importance of membrane lipid components in controlling barrier integrity, conducting lipidomics studies in this disorder is of great importance. In the current study, we tried to provide a critical overview of metabolomic and lipidomic changes in CD.

LC-ESI-HRMS - lipidomics of phospholipids : Characterization of extraction, chromatography and detection parameters

Lipids are a diverse class of molecules involved in many biological functions including cell signaling or cell membrane assembly. Owing to this relevance, LC-MS/MS-based lipidomics emerged as a major field in modern analytical chemistry. Here, we thoroughly characterized the influence of MS and LC settings - of a Q Exactive HF operated in Full MS/data-dependent MS2 TOP N acquisition mode - in order to optimize the semi-quantification of polar lipids. Optimization of MS-source settings improved the signal intensity by factor 3 compared to default settings. Polar lipids were separated on an ACQUITY Premier CSH C18 reversed-phase column (100 × 2.1 mm, 1.7 µm, 130 Å) during an elution window of 28 min, leading to a sufficient number of both data points across the chromatographic peaks, as well as MS2 spectra. Analysis was carried out in positive and negative ionization mode enabling the detection of a broader spectrum of lipids and to support the structural characterization of lipids. Optimal sample preparation of biological samples was achieved by liquid-liquid extraction using MeOH/MTBE resulting in an excellent extraction recovery > 85% with an intra-day and inter-day variability < 15%. The optimized method was applied on the investigation of changes in the phospholipid pattern in plasma from human subjects supplemented with n3-PUFA (20:5 and 22:6). The strongest increase was observed for lipids bearing 20:5, while 22:4 bearing lipids were lowered. Specifically, LPC 20:5_0:0 and PC 16:0_20:5 were found to be strongest elevated, while PE 18:0_22:4 and PC 18:2_18:2 were decreased by n3-PUFA supplementation. These results were confirmed by targeted LC-MS/MS using commercially available phospholipids as standards.

Sub-5-min RP-UHPLC-TIMS for high-throughput untargeted lipidomics and its application to multiple matrices

Untargeted lipidomics, with its ability to take a snapshot of the lipidome landscape, is an important tool to highlight lipid changes in pathology or drug treatment models. One of the shortcomings of most untargeted lipidomics based on UHPLC-HRMS is the low throughput, which is not compatible with large-scale screening. In this contribution, we evaluate the application of a sub-5-min high-throughput four-dimensional trapped ion mobility mass spectrometry (HT-4D-TIMS) platform for the fast profiling of multiple complex biological matrices. Human AC-16 cells and mouse brain, liver, sclera, and feces were used as samples. By using a fast 4-min RP gradient, the implementation of TIMS allows us to differentiate coeluting isomeric and isobaric lipids, with correct precursor ion isolation, avoiding co-fragmentation and chimeric MS/MS spectra. Globally, the HT-4D-TIMS allowed us to annotate 1910 different lipid species, 1308 at the molecular level and 602 at the sum composition level, covering 58 lipid subclasses, together with quantitation capability covering more than three orders of magnitude. Notably, TIMS values were highly comparable with respect to longer LC gradients (CV% = 0.39%). These results highlight how HT-4D-TIMS-based untargeted lipidomics possess high coverage and accuracy, halving the analysis time with respect to conventional UHPLC methods, and can be used for fast and accurate untargeted analysis of complex matrices to rapidly evaluate changes of lipid metabolism in disease models or drug discovery campaigns.

HILIC/MS quantitation of low-abundant phospholipids and sphingolipids in human plasma and serum: Dysregulation in pancreatic cancer

A new hydrophilic interaction liquid chromatography - mass spectrometry method is developed for low-abundant phospholipids and sphingolipids in human plasma and serum. The optimized method involves the Cogent Silica type C hydride column, the simple sample preparation by protein precipitation, and the removal of highly abundant lipid classes using the postcolumn valve directed to waste during two elution windows. The method allows a highly confident and sensitive identification of low-abundant lipid classes in human plasma (246 lipid species from 24 lipid subclasses) based on mass accuracy and retention dependencies in both polarity modes. The method is validated for quantitation using two internal standards (if available) for each lipid class and applied to human plasma and serum samples obtained from patients with pancreatic ductal adenocarcinoma (PDAC), healthy controls, and NIST SRM 1950. Multivariate data analysis followed by various statistical projection methods is used to determine the most dysregulated lipids. Significant downregulation is observed for lysophospholipids with fatty acyl composition 16:0, 18:0, 18:1, and 18:2. Distinct trends are observed for phosphatidylethanolamines (PE) in relation to the bonding type of fatty acyls, where most PE with acyl bonds are upregulated, while ether/plasmenyl PE are downregulated. For the sphingolipid category, sphingolipids with very long N-acyl chains are downregulated, while sphingolipids with shorter N-acyl chains were upregulated in PDAC. These changes are consistently observed for various classes of sphingolipids, ranging from ceramides to glycosphingolipids, indicating a possible metabolic disorder in ceramide biosynthesis caused by PDAC.

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods

BACKGROUND

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities.

OBJECTIVE

The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters.

METHOD

The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Expanding Lipidomic Coverage in Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry via a Convenient and Quantitative Methylation Strategy

Orthogonal separation techniques coupled to high-resolution mass spectrometry are required for characterizing the human lipidome, given its inherent chemical and structural complexity. However, electrophoretic separations remain largely unrecognized in contemporary lipidomics research compared to established chromatographic and ion mobility methods. Herein, we introduce a novel derivatization protocol based on 3-methyl-1-p-tolyltriazene (MTT) as a safer alternative to diazomethane for quantitative phospholipid (PL) methylation (∼90%), which enables their rapid analysis by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS). Isobaric interferences and ion suppression effects were minimized by performing an initial reaction using 9-fluorenylmethyoxycarbonyl chloride prior to MTT and a subsequent back extraction in hexane. This charge-switch derivatization strategy expands lipidome coverage when using MSI-NACE-MS under positive ion mode with improved resolution, greater sensitivity, and higher throughput (∼3.5 min/sample), notably for zwitterionic PLs that are analyzed as their cationic phosphate methyl esters. Our method was validated by analyzing methyl-tert-butyl ether extracts of reference human plasma, which enabled a direct comparison of 48 phosphatidylcholine and 27 sphingomyelin species previously reported in an interlaboratory lipidomics harmonization study. The potential for plasma PL quantification by MSI-NACE-MS via a serial dilution of NIST SRM-1950 was also demonstrated based on estimation of relative response factors using their reported consensus concentrations. Moreover, lipid identification was supported by modeling predictable changes in the electrophoretic mobility for cationic PLs in conjunction with MS/MS. Overall, this work offers a practical derivatization protocol to expand lipidome coverage in CE-MS beyond the analysis of hydrophilic/polar metabolites under aqueous buffer conditions.

Revealing the dynamic changes of lipids in coffee beans during roasting based on UHPLC-QE-HR-AM/MS/MS

Coffee is popular worldwide and its consumption is increasing in recent years. Although mass spectrometry-based lipidomics approaches have been prevalent, their application in studies related to detailed information and dynamic changes in lipid composition during coffee bean roasting is still limited. The aim of this study was to investigate the dynamic changes in coffee bean lipids during the roasting process. The lipid classes and lipid molecular species in coffee beans were characterized by lipidomic analysis combined with chemometrics. A total of 12 lipid classes and 105 lipid molecular species were identified and quantified. Triacylglycerols (TAG) was the most abundant lipid class in both green beans and roasted beans. The content of phosphatidylethanolamine (PE) and lysophosphatidylethanolamine (LPE) in green beans was obviously higher than that in roasted beans. Other phospholipids, such as phosphatidylinositol (PI), lysophosphatidylinositol (LPI), phosphatidylcholine (PC), lysophophatidylcholine (LPC) and phosphatidic acid (PA), showed a tendency to increase at the beginning of roasting, then decreased gradually. Several differential lipid molecule species, for instance, PE (16:0_18:2), PC (18:2_18:2) were significantly down-regulated, and PI (18:1_18:2) was significantly up-regulated. This study provided a scientific basis for the change of coffee bean lipids during the roasting process.

Host-pathogen interactions from a metabolic perspective: methods of investigation

Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.

Lipidomics Characterization of the Microbiome in People with Diabetic Foot Infection Using MALDI-TOF MS

Lipidomic profiling has emerged as a powerful tool for the comprehensive characterization of bacterial species, particularly in the context of clinical diagnostics. Utilizing matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), this study aims to elucidate the lipidomic landscapes of bacterial strains isolated from diabetic foot infections (DFI). Our analysis successfully identified a diverse array of lipids in the cellular membranes of both Gram-positive and Gram-negative bacteria, revealing a total of 108 unique fatty acid combinations. Specifically, we identified 26 LPG, 33 LPE, 43 PE, 114 PG, 89 TAG, and 120 CLP in Gram-positive bacteria and 10 LPG, 14 LPE, 124 PE, 37 PG, 13 TAG, and 22 CLP in Gram-negative strains. Key fatty acids, such as palmitic acid, palmitoleic acid, stearic acid, and oleic acid, were prominently featured. Univariate analysis further highlighted distinct lipidomic signatures among the bacterial strains, revealing elevated levels of phosphatidylethanolamine (PE) and phosphatidylglycerol (PG) in Gram-negative bacteria associated with DFI. In contrast, Gram-positive strains demonstrated increased or uniquely fluctuating levels of triglyceride (TAG) and cardiolipin (CLP). These findings not only underscore the utility of MALDI-TOF MS in bacterial lipidomics but also provide valuable insights into the lipidomic adaptations of bacteria in diabetic foot infections, thereby laying the groundwork for future studies aimed at constructing microbial lipid libraries for enhanced bacterial identification.

Lipidomic studies reveal two specific circulating phosphatidylcholines as surrogate biomarkers of the omega-3 index

Optimal dietary intake of omega-3 long-chain polyunsaturated fatty acids (n3-LCPUFAs) is critical to human health across the lifespan. However, omega-3 index (O3I) determination is not routinely assessed due to complicated procedures for n3-LCPUFA analysis from the phospholipid (PL) fraction of erythrocytes. Herein, a high-throughput method for lipidomics based on multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry was applied to identify circulating PLs as surrogate biomarkers of O3I in two randomized placebo-controlled trials. An untargeted lipidomic data workflow using a subgroup analysis of serum extracts from sunflower oil versus high-dose fish oil (FO)-supplemented participants revealed that ingested n3-LCPUFAs were primarily distributed as their phosphatidylcholines (PCs) relative to other PL classes. In both high-dose FO (5.0 g/day) and EPA-only trials (3.0 g/day), PC (16:0_20:5) was the most responsive PL, whereas PC (16:0_22:6) was selective to DHA-only supplementation. We also demonstrated that the sum concentration of both these PCs in fasting serum or plasma samples was positively correlated to the O3I following FO (r = 0.708, P = 1.02 × 10-11, n = 69) and EPA- or DHA-only supplementation (r = 0.768, P = 1.01 × 10-33, n = 167). Overall, DHA was more effective in improving the O3I (ΔO3I = 4.90 ± 1.33%) compared to EPA (ΔO3I = 2.99 ± 1.19%) in young Canadian adults who had a poor nutritional status with an O3I (3.50 ± 0.68%) at baseline. Our method enables the rapid assessment of the O3I by directly measuring two circulating PC species in small volumes of blood, which may facilitate screening applications for population and precision health.

Metabolomic and Lipidomic Characterization of Meningioma Grades Using LC-HRMS and Machine Learning

Meningiomas are among the most common brain tumors that arise from the leptomeningeal cover of the brain and spinal cord and account for around 37% of all central nervous system tumors. According to the World Health Organization, meningiomas are classified into three histological subtypes: benign, atypical, and anaplastic. Sometimes, meningiomas with a histological diagnosis of benign tumors show clinical characteristics and behavior of aggressive tumors. In this study, we examined the metabolomic and lipidomic profiles of meningioma tumors, focusing on comparing low-grade and high-grade tumors and identifying potential markers that can discriminate between benign and malignant tumors. High-resolution mass spectrometry coupled to liquid chromatography was used for untargeted metabolomics and lipidomics analyses of 85 tumor biopsy samples with different meningioma grades. We then applied feature selection and machine learning techniques to find the features with the highest information to aid in the diagnosis of meningioma grades. Three biomarkers were identified to differentiate low- and high-grade meningioma brain tumors. The use of mass-spectrometry-based metabolomics and lipidomics combined with machine learning analyses to prospect and characterize biomarkers associated with meningioma grades may pave the way for elucidating potential therapeutic and prognostic targets.

Mass Spectrometry Based on Chemical Derivatization Has Brought Novel Discoveries to Lipidomics: A Comprehensive Review

Lipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the "gold standard" analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.

Evaluation of Lipid Extraction Protocols for Untargeted Analysis of Mouse Tissue Lipidome

Lipidomics refers to the full characterization of lipids present within a cell, tissue, organism, or biological system. One of the bottlenecks affecting reliable lipidomic analysis is the extraction of lipids from biological samples. An ideal extraction method should have a maximum lipid recovery and the ability to extract a broad range of lipid classes with acceptable reproducibility. The most common lipid extraction relies on either protein precipitation (monophasic methods) or liquid-liquid partitioning (bi- or triphasic methods). In this study, three monophasic extraction systems, isopropanol (IPA), MeOH/MTBE/CHCl3 (MMC), and EtOAc/EtOH (EE), alongside three biphasic extraction methods, Folch, butanol/MeOH/heptane/EtOAc (BUME), and MeOH/MTBE (MTBE), were evaluated for their performance in characterization of the mouse lipidome of six different tissue types, including pancreas, spleen, liver, brain, small intestine, and plasma. Sixteen lipid classes were investigated in this study using reversed-phase liquid chromatography/mass spectrometry. Results showed that all extraction methods had comparable recoveries for all tested lipid classes except lysophosphatidylcholines, lysophosphatidylethanolamines, acyl carnitines, sphingomyelines, and sphingosines. The recoveries of these classes were significantly lower with the MTBE method, which could be compensated by the addition of stable isotope-labeled internal standards prior to lipid extraction. Moreover, IPA and EE methods showed poor reproducibility in extracting lipids from most tested tissues. In general, Folch is the optimum method in terms of efficacy and reproducibility for extracting mouse pancreas, spleen, brain, and plasma. However, MMC and BUME methods are more favored when extracting mouse liver or intestine.

Using MetaboAnalyst to introduce undergraduates to lipidomic analysis and lipid remodeling in barley roots

Lipidomics is a discipline that focuses on the identification and quantification of lipids. Although a part of the larger omics field, lipidomics requires specific approaches for the analysis and biological interpretation of datasets. This article presents a series of activities for introducing undergraduate microbiology students to lipidomic analysis through tools from the web-based platform MetaboAnalyst. The students perform a complete lipidomic workflow, which includes experiment design, data processing, data normalization, and statistical analysis of molecular phospholipid species obtained from barley roots exposed to Fusarium macroconidia. The input data are provided by the teacher, but students also learn about the methods through which they were originally obtained (untargeted liquid chromatography coupled with mass spectrometry). The ultimate aim is for students to understand the biological significance of phosphatidylcholine acyl editing. The chosen methodology allows users who are not proficient in statistics to make a comprehensive analysis of quantitative lipidomic datasets. We strongly believe that virtual activities based on the analysis of such datasets should be incorporated more often into undergraduate courses, in order to improve students' data-handling skills for omics sciences.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

Omics approaches for the assessment of biological responses to nanoparticles

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. While conventional methods have limitations in characterizing responses to NPs, omics approaches can analyze complete sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and analytical methods used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

UPLC-QTOF-MS-based lipidomic study of wedelolactone in acute colitis mice induced by dextran sulfate sodium

Inflammatory bowel disease is a relapsing inflammatory disease seriously endanger human health. Wedelolactone (WED) is a major active ingredient from Eclipta prostrata (L.) L. and has shown anti-inflammatory effects. However, the mechanism of WED in treating inflammatory colitis remains unknown. We aimed to investigate the mechanisms of WED in treating ulcerative colitis through lipidomic study. Sixty male C57BL/6 mice were exposed to DSS to induce acute colitis. Disease progression was judged by the disease activity index (DAI) and pathological changes of colon tissue. An ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) method was performed for colon and plasma lipidomics analyses. Differential metabolites in the three groups were distinguished by univariate and multivariate analysis. WED exerted anti-inflammatory effects representing by body weight and DAI score. Three metabolites were identified in plasma and 20 in colon. According to pathway analysis, the effects of WED on colitis were associated with seven pathways. The glycerophospholipid metabolism and ether lipid metabolism were the primary pathways. The findings provide important insight of the mechanism of WED in treating DSS induced colitis through lipidomic perspective.

The expanding organelle lipidomes: current knowledge and challenges

Lipids in cell membranes and subcellular compartments play essential roles in numerous cellular processes, such as energy production, cell signaling and inflammation. A specific organelle lipidome is characterized by lipid synthesis and metabolism, intracellular trafficking, and lipid homeostasis in the organelle. Over the years, considerable effort has been directed to the identification of the lipid fingerprints of cellular organelles. However, these fingerprints are not fully characterized due to the large variety and structural complexity of lipids and the great variability in the abundance of different lipid species. The process becomes even more challenging when considering that the lipidome differs in health and disease contexts. This review summarizes the information available on the lipid composition of mammalian cell organelles, particularly the lipidome of the nucleus, mitochondrion, endoplasmic reticulum, Golgi apparatus, plasma membrane and organelles in the endocytic pathway. The lipid compositions of extracellular vesicles and lamellar bodies are also described. In addition, several examples of subcellular lipidome dynamics under physiological and pathological conditions are presented. Finally, challenges in mapping organelle lipidomes are discussed.

The Potential of Salivary Lipid-Based Cannabis-Responsive Biomarkers to Evaluate Medical Cannabis Treatment in Children with Autism Spectrum Disorder

Introduction: Autism spectrum disorder (ASD) is a group of heterogeneous neurodevelopmental conditions affecting social communication and social interaction. Medical cannabis (MC) treatment shows promising results as an approach to reduce behavioral difficulties, as determined mainly by subjective observations. We have recently shown the potential of cannabis-responsive biomarkers detected in saliva of children with ASD to objectively quantify the impact of successful MC treatment using a metabolomics approach. Since the pathology of ASD is associated with abnormal lipid metabolism, we used lipidomics on the same samples to (1) expand the repertoire of cannabis-responsive biomarkers and (2) provide preliminary insight into the role of MC on lipid metabolism. Materials and Methods: Saliva samples collected from children with ASD (n=15) treated with MC (both before and at the time of maximal impact of treatment) and an age-matched group of typically developing (TD) children (n=9) were subjected to untargeted lipidomics. The study was observational. Each child from the ASD group was receiving a unique individualized MC treatment regimen using off-the-shelf products as permitted by California law under physician supervision for at least 1 year. Doses of tetrahydrocannabinol (THC) ranged from 0.05 to 50 mg and cannabidiol (CBD) from 7.5 to 200 mg per treatment. The ASD group was evaluated for signs of improvement using parental brief Likert scale surveys. Results: Twenty-two potential lipid-based cannabis-responsive biomarkers exhibiting a shift toward the TD physiological levels in children with ASD after MC treatment were identified. Members from all five lipid subclasses known to be present in saliva were characterized. Preliminary lipid association network analysis suggests involvement of two subnetworks previously linked to (1) inflammation and/or redox regulation and (2) oxidative stress. The significant changes in sphingomyelin in this study and in N-acetyl-aspartate (NAA) previously detected in the metabolomics analysis of the same saliva samples may indicate a role of MC in neuron function. Conclusions: Our findings suggest that lipid metabolites in saliva can potentially serve as cannabis-responsive biomarkers and objectively quantify the impact of MC treatment, and indicate a possible mechanism of action for MC. This preliminary study requires further investigation with a larger population and appropriate clinical trial monitoring.

Determination of Polar Lipids in Wheat and Oat by a Complementary Approach of Hydrophilic Interaction Liquid Chromatography and Reversed-Phase High-Performance Liquid Chromatography Hyphenated with High-Resolution Mass Spectrometry

Cereals contain lipids that fulfill important physiological roles and are associated with stress in the plant. However, many of the specific biological roles of lipids are yet unknown. Comprehensive analysis of these polar lipid categories in whole grain wheat and oat, cereals highly relevant also in nutrition, was performed. Hydrophilic interaction liquid chromatography (HILIC) and reversed-phase high-performance liquid chromatography (RP-HPLC) coupled with high-resolution mass spectrometry using electrospray ionization in both positive and negative ionization mode was used. Exploiting the different separation mechanisms, HILIC was used as a screening method for straightforward lipid class assignment and enabled differentiation of isomeric lipid classes, like phosphatidylethanolamine and lyso-N-acylphosphatidylethanolamine, while RP-HPLC facilitated separation of constitutional isomers. In combination with data-dependent MS/MS experiments, 67 lipid species belonging to nine polar lipid classes could be identified. Furthermore, with both ionization modes, fatty acyl chains directly connected to the lipid headgroups could be assigned. This work focused on the four lipid classes N-acylphosphatidylethanolamines, acyl-monogalactosyldiacylglycerols, digalactosyldiacylglycerols, and monogalactosyldiacylglycerols as they were less studied in detail in the past. Applying the complementary approach, the relative lipid species compositions in these lipid classes was investigated in detail.

Autologous hematopoietic stem cell transplantation significantly alters circulating ceramides in peripheral blood of relapsing-remitting multiple sclerosis patients

BACKGROUND

The common inflammatory disease multiple sclerosis (MS) is a disease of the central nervous system. For more than 25 years autologous hematopoietic stem cell transplantation (AHSCT) has been used to treat MS. It has been shown to be highly effective in suppressing inflammatory activity in relapsing-remitting MS (RRMS) patients. This treatment is thought to lead to an immune system reset, inducing a new, more tolerant system; however, the precise mechanism behind the treatment effect in MS patients is unknown. In this study, the effect of AHSCT on the metabolome and lipidome in peripheral blood from RRMS patients was investigated.

METHODS

Peripheral blood samples were collected from 16 patients with RRMS at ten-time points over the five months course of AHSCT and 16 MS patients not treated with AHSCT. Metabolomics and lipidomics analysis were performed using liquid-chromatography high-resolution mass spectrometry. Mixed linear models, differential expression analysis, and cluster analysis were used to identify differentially expressed features and groups of features that could be of interest. Finally, in-house and in-silico libraries were used for feature identification, and enrichment analysis was performed.

RESULTS

Differential expression analysis found 657 features in the lipidomics dataset and 34 in the metabolomics dataset to be differentially expressed throughout AHSCT. The administration of cyclophosphamide during mobilization and conditioning was associated with decreased concentrations in glycerophosphoinositol species. Thymoglobuline administration was associated with an increase in ceramide and glycerophosphoethanolamine species. After the conditioning regimen, a decrease in glycerosphingoidlipids concentration was observed, and following hematopoietic stem cell reinfusion glycerophosphocholine concentrations decreased for a short period of time. Ceramide concentrations were strongly associated with leukocyte levels during the procedure. The ceramides Cer(d19:1/14:0) and Cer(d20:1/12:0) were found to be increased (P < .05) in concentration at the three-month follow-up compared to baseline. C16 ceramide, Cer(D18:2/16:0), and CerPE(d16:2(4E,6E)/22:0) were found to be significantly increased in concentration after AHSCT compared to prior to treatment as well as compared to newly diagnosed RRMS patients.

CONCLUSION

AHSCT had a larger impact on the lipids in peripheral blood compared to metabolites. The variation in lipid concentration reflects the transient changes in the peripheral blood milieu during the treatment, rather than the changes in the immune system that are assumed to be the cause of clinical improvement within RRMS patients treated with AHSCT. Ceramide concentrations were affected by AHSCT and associated with leukocyte counts and were altered three months after treatment, suggesting a long-lasting effect.

Formation and Tandem Mass Spectrometry of Doubly Charged Lipid-Metal Ion Complexes

Phospholipids are major components of most eukaryotic cell membranes. Changes in metabolic states are often accompanied by phospholipid structure variations. The structural changes of phospholipids are the hallmark of disease states, or specific lipid structures have been associated with distinct organisms. Prime examples are microorganisms that synthesize phospholipids with, for example, different branched chain fatty acids. Assignment and relative quantitation of structural isomers of phospholipids that arise from attachment of different fatty acids to the glycerophospholipid backbone are difficult with routine tandem mass spectrometry or with liquid chromatography without authentic standards. In this work, we report on the observation that all investigated phospholipid classes form doubly charged lipid-metal ion complexes during electrospray ionization (ESI) and show that these complexes can be used to assign lipid classes and fatty acid moieties, distinguish isomers of branched chain fatty acids, and relatively quantify these isomers in positive-ion mode. Use of water free methanol and addition of divalent metal salts (100 mol %) to ESI spray solutions afford highly abundant doubly charged lipid-metal ion complexes (up to 70 times of protonated compounds). Higher-energy collisional dissociation and collision-induced dissociation of doubly charged complexes yield a diverse set of lipid class-dependent fragment ions. In common for all lipid classes is the liberation of fatty acid-metal adducts that yield fragment ions from the fatty acid hydrocarbon chain upon activation. This ability is used to pinpoint sites of branching in saturated fatty acids and is showcased for free fatty acids as well as glycerophospholipids. The analytical utility of doubly charged phospholipid-metal ion complexes is demonstrated by distinguishing fatty acid branching-site isomers in phospholipid mixtures and relatively quantifying the corresponding isomeric compounds.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Effects of Different Storage Conditions on Lipid Stability in Mice Tissue Homogenates

Lipids are biomolecules involved in numerous (patho-)physiological processes and their elucidation in tissue samples is of particular interest. However, tissue analysis goes hand in hand with many challenges and the influence of pre-analytical factors can intensively change lipid concentrations ex vivo, compromising the results of the whole research project. Here, we study the influence of pre-analytical factors on lipid profiles during the processing of homogenized tissues. Homogenates from four different mice tissues (liver, kidney, heart, spleen) were stored at room temperature as well as in ice water for up to 120 min and analyzed via ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). Lipid class ratios were calculated since their suitability as indicators for sample stability has been previously illustrated. Only approx. 40% of lipid class ratios were unchanged after 35 min, which was further reduced to 25% after 120 min during storage at room temperature. In contrast, lipids in tissue homogenates were generally stable when samples were kept in ice water, as more than 90% of investigated lipid class ratios remained unchanged after 35 min. Ultimately, swift processing of tissue homogenates under cooled conditions represents a viable option for lipid analysis and pre-analytical factors require more attention to achieve reliable results.

Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers

It is increasingly evident that a more detailed molecular structure analysis of isomeric lipids is critical to better understand their roles in biological processes. The occurrence of isomeric interference complicates conventional tandem mass spectrometry (MS/MS)-based determination, necessitating the development of more specialised methodologies to separate lipid isomers. The present review examines and discusses recent lipidomic studies based on ion mobility spectrometry combined with mass spectrometry (IMS-MS). Selected examples of the separation and elucidation of structural and stereoisomers of lipids are described based on their ion mobility behaviour. These include fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids. Recent approaches for specific applications to improve isomeric lipid structural information using direct infusion, coupling imaging, or liquid chromatographic separation workflows prior to IMS-MS are also discussed, including: 1) strategies to improve ion mobility shifts; 2) advanced tandem MS methods based on activation of lipid ions with electrons or photons, or gas-phase ion-molecule reactions; and 3) the use of chemical derivatisation techniques for lipid characterisation.

Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

Lipidomics analysis in drug discovery and development

Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers. In this review we present recent advances of lipid analysis in drug discovery and development. We cover current state of the art technologies which are constantly evolving to meet demands in terms of sensitivity and selectivity. A careful selection of important examples is then provided, illustrating the versatility of lipidomics analysis in the drug discovery and development process. Integration of lipidomics with other omics', stem-cell technologies, and metabolic flux analysis will open new avenues for deciphering pathophysiological mechanisms and the discovery of novel targets and biomarkers.

Comparison between Sickle Cell Disease Patients and Healthy Donors: Untargeted Lipidomic Study of Erythrocytes

Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on the multiple genetic and clinical profiles of SCD. However, the lipid composition of sickle cells has received little attention in the literature. According to recent studies, changes in the lipid profile are strongly linked to several disorders. Therefore, the aim of this study is to dig deeper into lipidomic analysis of erythrocytes in order to highlight any variations between healthy and patient subjects. 241 lipid molecular species divided into 17 classes have been annotated and quantified. Lipidomic profiling of SCD patients showed that over 24% of total lipids were altered most of which are phospholipids. In-depth study of significant changes in lipid metabolism can give an indication of the enzymes and genes involved. In a systems biology scenario, these variations can be useful to improve the understanding of the biochemical basis of SCD and to try to make a score system that could be predictive for the severity of clinical manifestations.

High-Resolution Liquid Chromatography-Mass Spectrometry for Lipidomics

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is a powerful tool for identification and classification of lipids. Ultra-high performance liquid chromatography (UHPLC) allows for robust separations of complex mixtures, while high-resolution mass spectrometry (HRMS) identifies compounds with efficiency and accuracy (Zullig T and Kofeler HC, Mass Spectrom Rev 40:162-176, 2021). The high specificity and sensitivity of mass spectrometry makes it the method of choice when analyzing lipids (Kofeler HC, J Lipid Res 62:100138, 2021). Untargeted mass spectrometry identifies all lipids within a sample and is useful for identification and further discovery. This chapter describes the use of a Q Exactive mass spectrometer to perform an untargeted LC-MS/MS lipidomics analysis.

Lipidomics Analysis with Triple Quadrupole Mass Spectrometry

Lipids serve an essential role in multiple cellular functions including signaling, metabolism, energy storage, and membrane constitution. Lipidomics, the study of lipids using analytical chemistry, allows for the study of disease states and cellular metabolism. Shotgun lipidomics is a technique that involves direct-infusion electrospray ionization (ESI) and analysis with a triple quadrupole mass spectrometer. Triple quadrupole mass spectrometry is ideally suited for lipidomics analysis because it allows for class-specific identification of lipids. Individual lipid class can be identified by the adjustment of three parameters-collision energy, ion mode, and scan type. This chapter describes the use of a triple quadrupole mass spectrometer, the TSQ Quantum Access MAX, to perform lipidomics analysis with high sensitivity, accuracy, and precision.