Versatile lipid profiling by liquid chromatography–high resolution mass spectrometry using all ion fragmentation and polarity switching. Preliminary application for serum samples phenotyping related to canine mammary cancer

Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population

BACKGROUND

The intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined.

OBJECTIVES

This study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n-3 polyunsaturated fatty acid (n-3 PUFA) biomarkers.

METHODS

Lipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers.

RESULTS

Stepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n-3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91.

CONCLUSIONS

Both fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n-3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.

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.

Characterization of lipoproteins and associated lipidome in very preterm infants: a pilot study

BACKGROUND

Preterm birth is associated with higher risks of suboptimal neurodevelopment and cardiometabolic disease later in life. Altered maternal-fetal lipid supply could play a role in such risks. Our hypothesis was that very preterm infants born with very low birth weight (VLBW) have altered lipidome and apolipoprotein profiles, compared with term infants.

METHODS

Seven mothers of VLBW infants born at <32 GA and 8 full-term mother-infant dyads were included. Cholesterol and triglycerides in lipoproteins were determined in maternal plasma and in the two blood vessels of the umbilical cord (vein (UV) and artery (UA)) following FPLC isolation. Apolipoprotein concentrations in lipoproteins and plasma lipidomic analysis were performed by LC-MS/MS.

RESULTS

We found higher cholesterol and VLDL-cholesterol in UV and UA and lower apolipoprotein A-I in HDL2 in UV in preterm neonates. Phosphatidylcholine (PC) containing saturated and monounsaturated fatty acids and specific sphingomyelin species were increased in UV and UA, whereas PC containing docosahexaenoic acid (DHA) was reduced in UV of VLBW neonates.

CONCLUSIONS

Lower DHA-PC suggests a lower DHA bioavailability and may contribute to the impaired neurodevelopment. Altered HDL-2, VLDL, and sphingomyelin profile reflect an atherogenic risk and increased metabolic risk at adulthood in infants born prematurely.

IMPACT

Lower ApoA-I in HDL2, and increased specific sphingomyelin and phosphatidylcholine containing saturated and monounsaturated fatty acid could explain the accumulation of cholesterol in umbilical vein in VLBW preterm neonates. Decreased phosphatidylcholine containing DHA suggest a reduced DHA availability for brain development in VLBW preterm infants. Characterization of alterations in fetal lipid plasma and lipoprotein profiles may help to explain at least in part the causes of the elevated cardiovascular risk known in people born prematurely and may suggest that a targeted nutritional strategy based on the composition of fatty acids carried by phosphatidylcholine may be promising in infants born very early.

Optimization of Mobile Phase Modifiers for Fast LC-MS-Based Untargeted Metabolomics and Lipidomics

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for the untargeted profiling of biological samples. A multiplatform LC-MS-based approach is needed to screen polar metabolites and lipids comprehensively. Different mobile phase modifiers were tested to improve the electrospray ionization process during metabolomic and lipidomic profiling. For polar metabolites, hydrophilic interaction LC using a mobile phase with 10 mM ammonium formate/0.125% formic acid provided the best performance for amino acids, biogenic amines, sugars, nucleotides, acylcarnitines, and sugar phosphate, while reversed-phase LC (RPLC) with 0.1% formic acid outperformed for organic acids. For lipids, RPLC using a mobile phase with 10 mM ammonium formate or 10 mM ammonium formate with 0.1% formic acid permitted the high signal intensity of various lipid classes ionized in ESI(+) and robust retention times. For ESI(-), the mobile phase with 10 mM ammonium acetate with 0.1% acetic acid represented a reasonable compromise regarding the signal intensity of the detected lipids and the stability of retention times compared to 10 mM ammonium acetate alone or 0.02% acetic acid. Collectively, we show that untargeted methods should be evaluated not only on the total number of features but also based on common metabolites detected by a specific platform along with the long-term stability of retention times.

Multi-dimensional characterization and identification of sterols in untargeted LC-MS analysis using all ion fragmentation technology

Sterols are an important type of lipids, and play many important roles in physiological and pathological processes. However, comprehensive analysis of sterols especially identification of unknown sterols is challenging. In this work, LC-MS with all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. AIF technology provided holistic and multi-dimensional characterization for both knowns and unknowns sterols, including accurate m/z, isotope pattern, retention time (RT), and co-eluted peak profiles between MS1 and MS2 ions in one analysis. We further developed an analysis strategy by integrating the multi-dimensional properties to support unambiguous identification of sterols, including distinguishing sterol isomers. The developed strategy enabled to identify a total of 23 sterols in mouse samples, and quantified 19 sterols in mouse liver tissues. More importantly, we demonstrated that AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures in biological samples. In summary, we employed the LC-MS based AIF technology to develop multi-dimensional characterization and identification of both known and unknown sterols in complex biological samples. The comprehensive analysis of sterols facilitates to provide molecular insights to many physiological and pathological activities in biology.

HILIC-ESI-FTMS with All Ion Fragmentation (AIF) Scans as a Tool for Fast Lipidome Investigations

Lipidomics suffers from the lack of fast and reproducible tools to obtain both structural information on intact phospholipids (PL) and fatty acyl chain composition. Hydrophilic interaction liquid chromatography with electrospray ionization coupled to an orbital-trap Fourier-transform analyzer operating using all ion fragmentation mode (HILIC-ESI-FTMS-AIF MS) is seemingly a valuable resource in this respect. Here, accurate m/z values, HILIC retention times and AIF MS scan data were combined for PL assignment in standard mixtures or real lipid extracts. AIF scans in both positive and negative ESI mode, achieved using collisional induced dissociation for fragmentation, were applied to identify both the head-group of each PL class and the fatty acyl chains, respectively. An advantage of the AIF approach was the concurrent collection of tandem MS-like data, enabling the identification of linked fatty acyl chains of precursor phospholipids through the corresponding carboxylate anions. To illustrate the ability of AIF in the field of lipidomics, two different types of real samples, i.e., the lipid extracts obtained from human plasma and dermal fibroblasts, were examined. Using AIF scans, a total of 253 intact lipid species and 18 fatty acids across 4 lipid classes were recognized in plasma samples, while FA C20:3 was confirmed as the fatty acyl chain belonging to phosphatidylinositol, PI 38:3, which was found to be down-regulated in fibroblast samples of Parkinson's disease patients.

Comparative Evaluation of Data Dependent and Data Independent Acquisition Workflows Implemented on an Orbitrap Fusion for Untargeted Metabolomics

Constant improvements to the Orbitrap mass analyzer, such as acquisition speed, resolution, dynamic range and sensitivity have strengthened its value for the large-scale identification and quantification of metabolites in complex biological matrices. Here, we report the development and optimization of Data Dependent Acquisition (DDA) and Sequential Window Acquisition of all THeoretical fragment ions (SWATH-type) Data Independent Acquisition (DIA) workflows on a high-field Orbitrap Fusion^TM Tribrid^TM instrument for the robust identification and quantification of metabolites in human plasma. By using a set of 47 exogenous and 72 endogenous molecules, we compared the efficiency and complementarity of both approaches. We exploited the versatility of this mass spectrometer to collect meaningful MS/MS spectra at both high- and low-mass resolution and various low-energy collision-induced dissociation conditions under optimized DDA conditions. We also observed that complex and composite DIA-MS/MS spectra can be efficiently exploited to identify metabolites in plasma thanks to a reference tandem spectral library made from authentic standards while also providing a valuable data resource for further identification of unknown metabolites. Finally, we found that adding multi-event MS/MS acquisition did not degrade the ability to use survey MS scans from DDA and DIA workflows for the reliable absolute quantification of metabolites down to 0.05 ng/mL in human plasma.

Dual Polarity Ion Confinement and Mobility Separations

Here, we present simulations and describe the initial implementation of a device capable of performing simultaneous ion mobility (IM) separations of positive and negative ions based upon the structures for lossless ion manipulations (SLIM). To achieve dual polarity ion confinement, the DC fields used for lateral confinement in previous SLIM were replaced with RF fields. Concurrent ion transport and mobility separation in the SLIM device are shown possible due to the nature of the traveling wave (TW) voltage profile which has potential minima at opposite sides of the wave for each ion polarity. We explored the potential for performing simultaneous IM separations of cations and anions over the same SLIM path and the impacts on the achievable IM resolution and resolving power. Initial results suggest comparable IM performance with previous single-polarity SLIM separations can be achieved. We also used ion trajectory simulations to investigate the capability to manipulate the spatial distributions of ion populations based on their polarities by biasing the RF fields and TW potentials on each SLIM surface so as to limit the interactions between opposite polarity ions. Graphical Abstract.

Comprehensive Preterm Breast Milk Metabotype Associated with Optimal Infant Early Growth Pattern

Early nutrition impacts preterm infant early growth rate and brain development but can have long lasting effects as well. Although human milk is the gold standard for feeding new born full-term and preterm infants, little is known about the effects of its bioactive compounds on breastfed preterm infants' growth outcomes. This study aims to determine whether breast milk metabolome, glycome, lipidome, and free-amino acids profiles analyzed by liquid chromatography-mass spectrometry had any impact on the early growth pattern of preterm infants. The study population consisted of the top tercile-Z score change in their weight between birth and hospital discharge ("faster grow", n = 11) and lowest tercile ("slower grow", n = 15) from a cohort of 138 premature infants (27⁻34 weeks gestation). This holistic approach combined with stringent clustering or classification statistical methods aims to discriminate groups of milks phenotype and identify specific metabolites associated with early growth of preterm infants. Their predictive reliability as biomarkers of infant growth was assessed using multiple linear regression and taking into account confounding clinical factors. Breast-milk associated with fast growth contained more branched-chain and insulino-trophic amino acid, lacto-N-fucopentaose, choline, and hydroxybutyrate, pointing to the critical role of energy utilization, protein synthesis, oxidative status, and gut epithelial cell maturity in prematurity.

Lipidomics and Biomarker Discovery in Kidney Disease

Technological advances in mass spectrometry-based lipidomic platforms have provided the opportunity for comprehensive profiling of lipids in biological samples and shown alterations in the lipidome that occur in metabolic disorders. A lipidomic approach serves as a powerful tool for biomarker discovery and gaining insight to molecular mechanisms of disease, especially when integrated with other -omics platforms (ie, transcriptomics, proteomics, and metabolomics) in the context of systems biology. In this review, we describe the workflow commonly applied to the conduct of lipidomic studies including important aspects of study design, sample preparation, biomarker identification and quantification, and data processing and analysis, as well as crucial considerations in clinical applications. We also review some recent studies of the application of lipidomic platforms that highlight the potential of lipid biomarkers and add to our understanding of the molecular basis of kidney disease.

Maternal obesity leads to long-term altered levels of plasma ceramides in the offspring as revealed by a longitudinal lipidomic study in children

BACKGROUND/OBJECTIVES

Maternal obesity is associated with increased risk of obesity and other symptoms of the metabolic syndrome in the offspring. Nevertheless, the molecular mechanisms and cellular factors underlying this enhanced disease susceptibility remain to be determined. Here, we aimed at identifying changes in plasma lipids in offspring of obese mothers that might underpin, and serve as early biomarkers of, their enhanced metabolic disease risk.

SUBJECTS/METHODS

We performed a longitudinal lipidomic profiling in plasma samples from normal weight, overweight, and obese pregnant women and their children that participated in the Prenatal Omega-3 Fatty Acid Supplementation, Growth, and Development trial conducted in Mexico. At recruitment women were aged between 18 and 35 years and in week 18-22 of pregnancy. Blood samples were collected at term delivery by venipuncture from mothers and from the umbilical cord of their newborns and from the same infants at 4 years old under non-fasting conditions. Lipidomic profiling was done using ultra-performance liquid chromatography high-resolution mass spectrometry.

RESULTS

Analysis of the lipidomic data showed that overweight and obese mothers exhibited a significant reduction in the total abundance of ceramides (Cer) in plasma, mainly of Cer (d18:1/20:0), Cer (d18:1/22:0), Cer (d18:1/23:0), and Cer (d18:1/24:0), compared with mothers of normal body weight. This reduction was confirmed by the direct quantification of these and other ceramide species. Similar quantitative differences in the plasma concentration of Cer (d18:1/22:0), Cer (d18:1/23:0), and Cer (d18:1/24:0), were also found between 4-year-old children of overweight and obese mothers compared with children of mothers of normal body weight. Noteworthy, children exhibited equal daily amounts of energy and food intake independently of the BMI of their mothers.

CONCLUSIONS

Maternal obesity results in long-lasting changes in plasma ceramides in the offspring suggesting that these lipids might be used as early predictors of metabolic disease risk due to maternal obesity.

Breast Milk Lipidome Is Associated with Early Growth Trajectory in Preterm Infants

Human milk is recommended for feeding preterm infants. The current pilot study aims to determine whether breast-milk lipidome had any impact on the early growth-pattern of preterm infants fed their own mother's milk. A prospective-monocentric-observational birth-cohort was established, enrolling 138 preterm infants, who received their own mother's breast-milk throughout hospital stay. All infants were ranked according to the change in weight Z-score between birth and hospital discharge. Then, we selected infants who experienced "slower" (n = 15, -1.54 ± 0.42 Z-score) or "faster" (n = 11, -0.48 ± 0.19 Z-score) growth; as expected, although groups did not differ regarding gestational age, birth weight Z-score was lower in the "faster-growth" group (0.56 ± 0.72 vs. -1.59 ± 0.96). Liquid chromatography-mass spectrometry lipidomic signatures combined with multivariate analyses made it possible to identify breast-milk lipid species that allowed clear-cut discrimination between groups. Validation of the selected biomarkers was performed using multidimensional statistical, false-discovery-rate and ROC (Receiver Operating Characteristic) tools. Breast-milk associated with faster growth contained more medium-chain saturated fatty acid and sphingomyelin, dihomo-γ-linolenic acid (DGLA)-containing phosphethanolamine, and less oleic acid-containing triglyceride and DGLA-oxylipin. The ability of such biomarkers to predict early-growth was validated in presence of confounding clinical factors but remains to be ascertained in larger cohort studies.

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.

The potential of Ion Mobility Mass Spectrometry for high-throughput and high-resolution lipidomics

Lipids are a large and highly diverse family of biomolecules, which play essential structural, storage and signalling roles in cells and tissues. Although traditional mass spectrometry (MS) approaches used in lipidomics are highly sensitive and selective, lipid analysis remains challenging due to the chemical diversity of lipid structures, multiple isobaric species and incomplete separation using many forms of chromatography. Ion mobility (IM) separates ions in the gas phase based on their physicochemical properties. Addition of IM to the traditional lipidomic workflow both enhances separation of complex lipid mixtures, beneficial for lipid identification, and improves isomer resolution. Herein, we discuss the recent developments in IM-MS for lipidomics.

Data acquisition workflows in liquid chromatography coupled to high resolution mass spectrometry-based metabolomics: Where do we stand?

Typical mass spectrometry (MS) based untargeted metabolomics protocols are tedious as well as time- and sample-consuming. In particular, they often rely on "full-scan-only" analyses using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) from which metabolites of interest are first highlighted, and then tentatively identified by using targeted MS/MS experiments. However, this situation is evolving with the emergence of integrated HRMS based-data acquisition protocols able to perform multi-event acquisitions. Most of these protocols, referring to as data dependent and data independent acquisition (DDA and DIA, respectively), have been initially developed for proteomic applications and have recently demonstrated their applicability to biomedical studies. In this context, the aim of this article is to take stock of the progress made in the field of DDA- and DIA-based protocols, and evaluate their ability to change conventional metabolomic and lipidomic data acquisition workflows, through a review of HRMS instrumentation, DDA and DIA workflows, and also associated informatics tools.

Lipidomics Insights in Health and Nutritional Intervention Studies

Lipids are among the major components of food and constitute the principal structural biomolecules of human body together with proteins and carbohydrates. Lipidomics encompasses the investigation of the lipidome, defined as the entire spectrum of lipids in a biological system at a given time. Among metabolomics technologies, lipidomics has evolved due to the relevance of lipids in nutrition and their well-recognized roles in health. Mass spectrometry advances have greatly facilitated lipidomics, but owing to the complexity and diversity of the lipids, lipidome purification and analysis are still challenging. This review focuses on lipidomics strategies, applications, and achievements of studies related to nutrition and health research.

Development of a Liquid Chromatography-High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition

High-resolution mass spectrometry (HRMS)-based metabolomics approaches have made significant advances. However, metabolite identification is still a major challenge with significant bottleneck in translating metabolomics data into biological context. In the current study, a liquid chromatography (LC)-HRMS metabolomics method was developed using an all ion fragmentation (AIF) acquisition approach. To increase the specificity in metabolite annotation, four criteria were considered: (i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum, and (iv) product/precursor ion intensity ratios. We constructed an in-house mass spectral library of 408 metabolites containing AMRT and MS/MS spectra information at four collision energies. The percent relative standard deviations between ion ratios of a metabolite in an analytical standard vs sample matrix were used as an additional metric for establishing metabolite identity. A data processing method for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information for each of the 413 metabolites. In the data processing method, the precursor ion and product ion were considered as the quantifier and qualifier ion, respectively. We also included a scheme to distinguish coeluting isobaric compounds by selecting a specific product ion as the quantifier ion instead of the precursor ion. An advantage of the current AIF approach is the concurrent collection of full scan data, enabling identification of metabolites not included in the database. Our data acquisition strategy enables a simultaneous mixture of database-dependent targeted and nontargeted metabolomics in combination with improved accuracy in metabolite identification, increasing the quality of the biological information acquired in a metabolomics experiment.

Preliminary evaluation of serum total cholesterol concentrations in dogs with osteosarcoma

OBJECTIVES

To determine if total serum cholesterol concentrations were altered in dogs with osteosarcoma. To evaluate association of total serum cholesterol concentration with clinical outcomes in dogs with appendicular osteosarcoma.

MATERIALS AND METHODS

Retrospective, multi-institutional study on 64 dogs with osteosarcoma. Control population consisted of dogs with traumatic bone fractures (n=30) and healthy patients of similar age and weight as those of the osteosarcoma cases (n=31). Survival analysis was done on 35 appendicular osteosarcoma patients that received the current standard of care. Statistical associations were assessed by univariable and multi-variable analysis. Information about age, sex, primary tumour location, total cholesterol concentration, monocytes and lymphocyte counts and alkaline phosphatase were also included.

RESULTS

Total cholesterol was elevated above the reference interval (3·89 to 7·12 mmol/L) (150 to 275 mg/dL) in 29 of 64 (45·3%) osteosarcoma-bearing dogs, whereas similar elevations were found in only 3 of 30 (10%) fracture controls (P<0·0001) and 2 of 31 (6·5%) similar age/weight controls (P=0·0002). Elevated total cholesterol was significantly associated with a reduced hazard ratio (0·27, P=0·008) for overall mortality in dogs with osteosarcoma.

CLINICAL SIGNIFICANCE

These results suggest that elevated total cholesterol is associated with canine osteosarcoma and may have prognostic significance.

Simultaneous metabolomics and lipidomics analysis based on novel heart-cutting two-dimensional liquid chromatography-mass spectrometry

Increasing metabolite coverage by combining data from different platforms or methods can improve understanding of related metabolic mechanisms and the identification of biomarkers. However, no one method can obtain metabolomic and lipidomic information in a single analysis. In this work, aiming at collecting comprehensive information on metabolome and lipidome in a single analytical run, we developed an on-line heart-cutting two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) method. Complex metabolites from biological samples are divided into two fractions by using a precolumn. The first fraction is directly transferred and subjected to metabolomics analysis. Most lipids are retained on the precolumn until the mobile phases for lipidomics flow through; then they are subjected to lipidomics analysis. Up to 447 and 289 metabolites in plasma, including amino acids, carnitines, bile acids, free fatty acids, lyso-phospholipids, phospholipids, sphingomyelins etc. were identified within 30 min in the positive mode and negative mode, respectively. A comparison of the newly developed method with the conventional metabolomic and lipidomic approaches showed that approximately 99% features obtained by the two conventional methods can be covered with this 2D-LC method. Analytical characteristics evaluation showed the method had a wide linearity range, high sensitivity, satisfactory recovery and repeatability. These results demonstrate that this method is reliable, stable and well qualified in metabolomics analysis, particularly for large-scale metabolomics studies with small amount of samples.

A Strategy Combining Higher Energy C-Trap Dissociation with Neutral Loss- and Product Ion-Based MSn Acquisition for Global Profiling and Structure Annotation of Fatty Acids Conjugates

Fatty acids conjugates (FACs) are ubiquitous but found in trace amounts in the natural world. They are composed of multiple unknown substructures and side chains. Thus, FACs are difficult to be analyzed by traditional mass spectrometric methods. In this study, an integrated strategy was developed to global profiling and targeted structure annotation of FACs in complex matrix by LTQ Orbitrap. Dicarboxylic acid conjugated bufotoxins (DACBs) in Venenum bufonis (VB) were used as model compounds. The new strategy (abbreviated as HPNA) combined higher-energy C-trap dissociation (HCD) with product ion- (PI), neutral loss- (NL) based MSⁿ (n ≥ 3) acquisition in both positive-ion mode and negative-ion mode. Several advantages are presented. First, various side chains were found under HCD in negative-ion mode, which included both known and unknown side chains. Second, DACBs with multiple side chains were simultaneously detected in one run. Compared with traditional quadrupole-based mass method, it greatly increased analysis throughput. Third, the fragment ions of side chain and steroids substructure could be obtained by PI- and NL-based MSⁿ acquisition, respectively, which greatly increased the accuracy of the structure annotation of DACBs. In all, 78 DACBs have been discovered, of which 68 were new compounds; 25 types of substructure formulas and seven dicarboxylic acid side chains were found, especially five new side chains, including two saturated dicarboxylic acids [(azelaic acid (C₉) and sebacic acid (C₁₀)] and three unsaturated dicarboxylic acids (u-C₈, u-C₉, and u-C₁₀). All these results greatly enriched the structures of DACBs in VB. Graphical Abstract ᅟ.

Impact of storage conditions on the urinary metabolomics fingerprint

Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions.

Investigation of signaling molecules and metabolites found in crustacean hemolymph via in vivo microdialysis using a multifaceted mass spectrometric platform

Neurotransmitters (NTs) are endogenous signaling molecules that play an important role in regulating various physiological processes in animals. Detection of these chemical messengers is often challenging due to their low concentration levels and fast degradation rate in vitro. In order to address these challenges, herein we employed in vivo microdialysis (MD) sampling to study NTs in the crustacean model Cancer borealis. Multifaceted separation tools, such as CE and ion mobility mass spectrometry (MS) were utilized in this work. Small molecules were separated by different mechanisms and detected by MALDI mass spectrometric imaging (MALDI-MSI). Performance of this separation-based MSI platform was also compared to LC-ESI-MS. By utilizing both MALDI and ESI-MS, a total of 208 small molecule NTs and metabolites were identified, of which 39 were identified as signaling molecules secreted in vivo. In addition, the inherent property of sub microscale sample consumption using CE enables shorter time of MD sample collection. Temporal resolution of MD was improved by approximately tenfold compared to LC-ESI-MS, indicating the significant advantage of applying separation-assisted MALDI-MS imaging platform.

Comprehensive untargeted lipidomic analysis using core-shell C30 particle column and high field orbitrap mass spectrometer

The goal of untargeted lipidomics is to have high throughput, yet comprehensive and unambiguous identification and quantification of lipids. Novel stationary phases in LC separation and new mass spectrometric instruments capable of high mass resolving power and faster scanning rate are essential to achieving this goal. In this work, 4 reversed phase LC columns coupled with a high field quadrupole orbitrap mass spectrometer (Q Exactive HF) were thoroughly compared using complex lipid standard mixture and rat plasma and liver samples. A good separation of all lipids was achieved in 24min of gradient. The columns compared include C30 and C18 functionalization on either core-shell or totally porous silica particles, with size ranging from 1.7 to 2.6μm. Accucore C30 column showed the narrowest peaks and highest theoretical plate number, and excellent peak capacity and retention time reproducibility (<1% standard deviation). As a result, it resulted in 430 lipid species identified from rat plasma and rat liver samples with highest confidence. The high resolution offered by the up-front RPLC allowed discrimination of cis/trans isomeric lipid species, and the high field orbitrap mass spectrometer afforded the clear distinction of isobaric lipid species in full scan MS and the unambiguous assignment of sn-positional isomers for lysophospholipids in MS/MS. Taken together, the high efficiency LC separation and high mass resolving MS analysis are very promising tools for untargeted lipidomics analysis.

Selective Identification of Organic Iodine Compounds Using Liquid Chromatography-High Resolution Mass Spectrometry

A method to selectively and sensitively detect organic iodine compounds and identify their structures has been developed using liquid chromatography-high resolution mass spectrometry (LC-HRMS). Using extracted ion chromatograms of product ions (iodine ion) collected on a rapid scanning quadrupole orbitrap mass spectrometer, the retention times of the unknown organic iodine compounds were determined, and the structural information were acquired according to the MS/MS experiments and the matching with reference standards. We have demonstrated the application of this method by identifying unknown organic iodine compounds in seaweed. A total of 28 possible organic iodine peaks were discovered, among them, the accurate mass and element composition of the corresponding precursor ions were identified for 12 peaks, and molecular structures were confirmed for 4 peaks, which were 3-iodo-L-tyrosine, 3,5-diiodo-L-tyrosine, 4-iodophenol, and 2-iodobenzoic acid. This method is expected to lead to the future discovery of new organic iodine compounds via LC-HRMS in different environmental samples, which is crucial for understanding the iodine biogeochemical cycling.

Molecular Characterization of the Elaeis guineensis Medium-Chain Fatty Acid Diacylglycerol Acyltransferase DGAT1-1 by Heterologous Expression in Yarrowia lipolytica

Diacylglycerol acyltransferases (DGAT) are involved in the acylation of sn-1,2-diacylglycerol. Palm kernel oil, extracted from Elaeis guineensis (oil palm) seeds, has a high content of medium-chain fatty acids mainly lauric acid (C12:0). A putative E. guineensis diacylglycerol acyltransferase gene (EgDGAT1-1) is expressed at the onset of lauric acid accumulation in the seed endosperm suggesting that it is a determinant of medium-chain triacylglycerol storage. To test this hypothesis, we thoroughly characterized EgDGAT1-1 activity through functional complementation of a Yarrowia lipolytica mutant strain devoid of neutral lipids. EgDGAT1-1 expression is sufficient to restore triacylglycerol accumulation in neosynthesized lipid droplets. A comparative functional study with Arabidopsis thaliana DGAT1 highlighted contrasting substrate specificities when the recombinant yeast was cultured in lauric acid supplemented medium. The EgDGAT1-1 expressing strain preferentially accumulated medium-chain triacylglycerols whereas AtDGAT1 expression induced long-chain triacylglycerol storage in Y. lipolytica. EgDGAT1-1 localized to the endoplasmic reticulum where TAG biosynthesis takes place. Reestablishing neutral lipid accumulation in the Y. lipolytica mutant strain did not induce major reorganization of the yeast microsomal proteome. Overall, our findings demonstrate that EgDGAT1-1 is an endoplasmic reticulum DGAT with preference for medium-chain fatty acid substrates, in line with its physiological role in palm kernel. The characterized EgDGAT1-1 could be used to promote medium-chain triacylglycerol accumulation in microbial-produced oil for industrial chemicals and cosmetics.

Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics has been a subject of dramatic developments over the past decade. This review focuses on state of the art in LC-MS-based lipidomics, covering all the steps of global lipidomic profiling. On the basis of review of 185 original papers and application notes, we can conclude that typical LC-MS-based lipidomics methods involve: (1) extraction using chloroform/MeOH or MTBE/MeOH protocols, both with addition of internal standards covering each lipid class; (2) separation of lipids using short microbore columns with sub-2-μm or 2.6-2.8-μm (fused-core) particle size with C18 or C8 sorbent with analysis time <30 min; (3) electrospray ionization in positive- and negative-ion modes with full spectra acquisition using high-resolution MS with capability to MS/MS. Phospholipids (phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, phosphatidylserines, phosphatidylglycerols) followed by sphingomyelins, di- and tri-acylglycerols, and ceramides were the most frequently targeted lipid species.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

Ultra-performance liquid chromatography-mass spectrometry as a sensitive and powerful technology in lipidomic applications

Lipidomics, the comprehensive illumination of lipid-based information in biology systems, involves in identifying lipids and profiling lipids and lipid-derived mediators. The development of lipidomics enables the characterization of lipid species and detailed lipid profiling in body fluid, tissue or cell, and allows for a wider understanding of the biological roles of lipid networks. Lipidomic research has been greatly facilitated by recent advances in ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and involved in lipid extraction, lipid identification and data analysis supporting applications from qualitative and quantitative assessment of multiple lipid species. UPLC technique, different mass spectrometry technique, lipid extraction and data analysis in lipidomics are reviewed. Afterwards, examples are provided on the use of UPLC-MS for finding lipid biomarkers in disease, drug, food, nutrition and plant fields. We also discuss the UPLC-MS-based lipidomics for the future perspectives and their potential problems.

Mass Spectrometry-based Lipidomics and Its Application to Biomedical Research

Lipidomics, a branch of metabolomics, is the large-scale study of pathways and networks of all cellular lipids in biological systems such as cells, tissues or organisms. The recent advance in mass spectrometry technologies have enabled more comprehensive lipid profiling in the biological samples. In this review, we compared four representative lipid profiling technoligies including GC-MS, LC-MS, direct infusion-MS and imaging-MS. We also summarized representative lipid database, and further discussed the applications of lipidomics to the diagnostics of various diseases such as diabetes, obesity, hypertension, and Alzheimer diseases.