Systematic Evaluation of HILIC Stationary Phases for Global Metabolomics of Human Plasma

Comprehensive untargeted polar metabolite analysis using solvent switching liquid chromatography tandem mass spectrometry

Metabolomics analyses enable the examination and identification of endogenous biochemical reaction products, revealing information on the metabolic pathways and processes active within a living cell or organism. Determination of metabolic shifts can provide important information on a treatment or disease. Unlike other omics fields that typically have analytes of the same chemical class with common building blocks, those that fall under the nomenclature of metabolites encompass a wide array of different compounds with very diverse physiochemical properties. Development of a comprehensive metabolomic pipeline therefore can be a troublesome and complicated process for the analyst. Often single liquid chromatography-mass spectrometry methods on unfractionated samples are carried out in order to be time-efficient, however this could potentially produce data with a low number of identifiable metabolites. In the present studies, we developed a comprehensive polar metabolomics pipeline for cell-based metabolomics. SH-SY5Y neuroblastoma cells were selected as the sample matrix for method development since they are one of the most widely used cell lines for human neurotoxicity studies. This was accomplished by investigating and optimising different mass spectrometry source and chromatographic conditions to enhance the signal of polar metabolites. Optimised hydrophilic interaction liquid chromatography (HILIC) based metabolomic methods at different pH values were examined in positive, negative, and polarity switching modes to determine which combination yielded the highest number of confidently identified metabolites. Additionally, the use of sequentially running two methods was also compared to determine the degree of overlap and whether there is merit in running two separate methods on one sample. It was determined that solvent switching between two optimised methods, acidic chromatographic conditions in positive mode and basic chromatographic conditions in negative mode, yielded the highest number of unique identifiable metabolites. This could be run in a single analytical batch due to the large pH range of the column. A quick switch method in-between each method allowed both conditioning the column and preparation of the MS source conditions for the sequential method.

Evaluation of ion source parameters and liquid chromatography methods for plasma untargeted metabolomics using orbitrap mass spectrometer

Although untargeted metabolomics holds promise for study of metabolites in human health and disease, robust method development and optimization are needed to reduce potential analytical biases and to ensure comprehensive, high-throughput results. In this study, the effect of mass spectrometer (MS) ion source parameters on the signal reproducibility and number of metabolite annotations during untargeted metabolomics is shown. Furthermore, different mobile phase gradients and columns (five reversed phase (RP)-C18 and two hydrophilic interaction liquid chromatography (HILIC) columns) were evaluated for untargeted metabolomics of blood plasma extracts. Positioning the electrospray needle at the farthest on the Z-direction and the closest tested position on the Y-direction with respect to the mass spectrometry inlet produced the best signal reproducibility and the greatest number of metabolite annotations. Moreover, optimal ion source conditions included a positive spray voltage between 2.5 and 3.5 kV, a negative spray voltage between 2.5 and 3.0 kV, vaporization and ion transfer tube (ITT) temperature between 250 and 350 °C, 30 to 50 arbitrary units of sheath gas, and at least 10 auxiliary gas units. Despite the differences in chromatographic characteristics, the different RP columns assessed showed comparable performance in terms of number of metabolites annotated. For HILIC columns, a zwitterionic column demonstrated better performance than an amide column. Finally, as compared with use of a RP column alone, use of both the optimal RP and HILIC approaches expanded metabolome coverage: the number of metabolites annotated increased by 60 %. This study highlights the significance of fine-tuning the MS ion source parameters and optimizing chromatographic conditions on metabolome coverage during untargeted metabolomics of plasma samples.

Decoding Sugars: Mass Spectrometric Advances in the Analysis of the Sugar Alphabet

Monosaccharides play a central role in metabolic networks and in the biosynthesis of glycomolecules, which perform essential functions across all domains of life. Thus, identifying and quantifying these building blocks is crucial in both research and industry. Routine methods have been established to facilitate the analysis of common monosaccharides. However, despite the presence of common metabolites, most organisms utilize distinct sets of monosaccharides and derivatives. These molecules therefore display a large diversity, potentially numbering in the hundreds or thousands, with many still unknown. This complexity presents significant challenges in the study of glycomolecules, particularly in microbes, including pathogens and those with the potential to serve as novel model organisms. This review discusses mass spectrometric techniques for the isomer-sensitive analysis of monosaccharides, their derivatives, and activated forms. Although mass spectrometry allows for untargeted analysis and sensitive detection in complex matrices, the presence of stereoisomers and extensive modifications necessitates the integration of advanced chromatographic, electrophoretic, ion mobility, or ion spectroscopic methods. Furthermore, stable-isotope incorporation studies are critical in elucidating biosynthetic routes in novel organisms.

Matrix effect evaluation using multi-component post-column infusion in untargeted hydrophilic interaction liquid chromatography-mass spectrometry plasma metabolomics

Metabolomics based on hydrophilic interaction liquid chromatography (HILIC) coupled with mass spectrometry (MS) is a powerful tool for polar metabolite identification and quantification to further contribute to biomarker discovery and disease mechanism elucidation. However, matrix effect (ME), which may lead to altered ionization efficiency due to co-eluting compounds, is a significant challenge during biological analysis. Therefore, ME evaluation plays a crucial role during method development. Two approaches to evaluate ME are using stable isotope labelled-internal standards (SIL-IS) and post-column infusion (PCI) of standards. In this study, we developed an untargeted HILIC-MS method by applying four PCI standards for ME evaluation. We found PCI is a compelling approach for ME assessment compared to SIL-IS method due to its advantage in untargeted analysis. Through the ME evaluation and chromatographic performance comparison of 18 SIL standards across three columns and three different mobile phase pH conditions, our findings revealed that the BEH-Z-HILIC column operated at pH 4 with 10 mM ammonium formate exhibited minimal ME and superior performance. The method showed exceptional linearity (R² > 0.98), reliable repeatability (RSD < 15 %), good inter-day precision (RSD < 30 %), and acceptable recovery (>75 %) for all SIL standards. Absolute matrix effect (AME) and relative matrix effect (RME) assessment in three plasma donors revealed a high consistency between PCI and SIL-IS approaches. Finally, this method coupled with the PCI approach was applied to 40 plasma samples. Fifty endogenous compounds were detected and their AME and RME were evaluated. Results showed that many compounds experienced severe ion suppression, though their ME variation between 40 samples is low. In conclusion, PCI method is a robust alternative for monitoring ME and evaluating ME of endogenous compounds during untargeted method optimization and biological analysis.

HILIC-MS/MS Multi-targeted Method for Metabolomics Applications

Metabolomics aims at identification and quantitation of key end point metabolites, basically polar, in order to study changes in biochemical activities in response to pathophysiological stimuli or genetic modifications. Targeted profiling assays enjoying a growing popularity over the last years with LC-MS/MS as a powerful tool for development of such (semi-)quantitative methods for a large number of metabolites. Here we describe a method for absolute quantitation of ca. 100 metabolites belonging to key metabolite classes such as sugars, amino acids, nucleotides, organic acids, and amines with a hydrophilic interaction liquid chromatography (HILIC) system comprised with ultra (high) performance liquid chromatography (UHPLC) with detection on a triple quadrupole mass spectrometer operating in both positive and negative modes.

A simplified liquid chromatography-mass spectrometry methodology to probe the shikimate and aromatic amino acid biosynthetic pathways in plants

Plants direct substantial amounts of carbon toward the biosynthesis of aromatic amino acids (AAAs), particularly phenylalanine to produce lignin and other phenylpropanoids. Yet, we have a limited understanding of how plants regulate AAA metabolism, partially because of a scarcity of robust analytical methods. Here, we established a simplified workflow for simultaneous quantification of AAAs and their pathway intermediates from plant tissues, based on extraction at two alternative pH and analysis by Zwitterionic hydrophilic interaction liquid chromatography coupled to mass spectrometry. This workflow was then used to analyze metabolic responses to elevated or reduced carbon flow through the shikimate pathway in plants. Increased flow upon expression of a feedback-insensitive isoform of the first shikimate pathway enzyme elevated all AAAs and pathway intermediates, especially arogenate, the last common precursor within the post-chorismate pathway of tyrosine and phenylalanine biosynthesis. Additional overexpression of an arogenate dehydrogenase enzyme increased tyrosine levels and depleted phenylalanine and arogenate pools; however, the upstream shikimate pathway intermediates remained accumulated at high levels. Glyphosate treatment, which restricts carbon flow through the shikimate pathway by inhibiting its penultimate step, led to a predictable accumulation of shikimate and other precursors upstream of its target enzyme but also caused an unexpected accumulation of downstream metabolites, including arogenate. These findings highlight that the shikimate pathway and the downstream post-chorismate AAA pathways function as independently regulated modules in plants. The method developed here paves the way for a deeper understanding of the shikimate and AAA biosynthetic pathways in plants.

The TRIM-NHL RNA-binding protein Brain Tumor coordinately regulates expression of the glycolytic pathway and vacuolar ATPase complex

The essential Drosophila RNA-binding protein Brain Tumor (Brat) represses specific genes to control embryogenesis and differentiation of stem cells. In the brain, Brat functions as a tumor suppressor that diminishes neural stem cell proliferation while promoting differentiation. Though important Brat-regulated target mRNAs have been identified in these contexts, the full impact of Brat on gene expression remains to be discovered. Here, we identify the network of Brat-regulated mRNAs by performing RNA sequencing (RNA-seq) following depletion of Brat from cultured cells. We identify 158 mRNAs, with high confidence, that are repressed by Brat. De novo motif analysis identified a functionally enriched RNA motif in the 3' untranslated regions (UTRs) of Brat-repressed mRNAs that matches the biochemically defined Brat binding site. Integrative data analysis revealed a high-confidence list of Brat-repressed and Brat-bound mRNAs containing 3'UTR Brat binding motifs. Our RNA-seq and reporter assays show that multiple 3'UTR motifs promote the strength of Brat repression, whereas motifs in the 5'UTR are not functional. Strikingly, we find that Brat regulates expression of glycolytic enzymes and the vacuolar ATPase complex, providing new insight into its role as a tumor suppressor and the coordination of metabolism and intracellular pH.

The Impact of Milk on Gut Permeability, Fecal 16S rRNA Gene Microbiota Profiling, and Fecal Metabolomics in Children with Moderate Malnutrition in Sierra Leone: A Double-Blind, Randomized Controlled Trial

BACKGROUND

Bovine milk is a beneficial ingredient in teh treatment of malnutrition.

OBJECTIVES

Our objectives were to determine the effect of dietary milk protein and milk carbohydrate on the intestinal permeability, fecal 16S rRNA gene configuration, and fecal metabolomics of children with moderate malnutrition.

METHODS

This was a randomized, double-blind, controlled trial among 413 children with wasting in rural Sierra Leone who received 1 of the following 4 supplementary foods, which differed in sources of protein and carbohydrate: milk protein and milk carbohydrate (MPMC), milk protein and vegetable carbohydrate (MPVC), vegetable protein and milk carbohydrate (VPMC), or a control group consuming entirely vegetable-based food (VPVC). After 4 wk, urine and stool were collected from participants enrolled with mid-upper arm circumference of <12.1 cm. Urine was analyzed for lactulose excretion (%L). Stool samples were subjected to both 16S rRNA gene analysis to assess β-diversity and untargeted metabolomic abundance.

RESULTS

Among the 386 children who completed permeability testing, the mean difference (95% CI) in %L excretion as compared with VPVC was 0.01 (-0.05, 0.07) for MPMC, 0.05 (-0.01, 0.11) for MPVC, and 0.01 (-0.05, 0.07) for VPMC. Of the 374 children who provided a stool sample that was analyzed, the β-diversity among bacterial taxa was similar between dietary groups (P > 0.05 for all comparisons). No significant differences between dietary groups were seen among the 20 most abundant bacterial taxa. Among the 5769 unique metabolomic features identified, greater flavonoid levels in VPVC were seen.

CONCLUSIONS

Abnormal intestinal permeability do not improve with 4 wk of supplementary feeding. Fecal rRNA do not differ with consumption of different diets. This trial was registered at clinicaltrials.gov as NCT04216043.

Oxygen-Dependent Interactions between the Ruthenium Cage and the Photoreleased Inhibitor in NAMPT-Targeted Photoactivated Chemotherapy

Photoactivated chemotherapy agents form a new branch of physically targeted anticancer agents with potentially lower systemic side effects for patients. On the other hand, limited information exists on the intracellular interactions between the photoreleased metal cage and the photoreleased anticancer inhibitor. In this work, we report a new biological study of the known photoactivated compound Ru-STF31 in the glioblastoma cancer cell line, U87MG. Ru-STF31 targets nicotinamide phosphoribosyltransferase (NAMPT), an enzyme overexpressed in U87MG. Ru-STF31 is activated by red light irradiation and releases two photoproducts: the ruthenium cage and the cytotoxic inhibitor STF31. This study shows that Ru-STF31 can significantly decrease intracellular NAD+ levels in both normoxic (21% O2) and hypoxic (1% O2) U87MG cells. Strikingly, NAD+ depletion by light activation of Ru-STF31 in hypoxic U87MG cells could not be rescued by the addition of extracellular NAD+. Our data suggest an oxygen-dependent active role of the ruthenium photocage released by light activation.

Metabolomic analysis of dietary-restriction-induced attenuation of sarcopenia in prematurely aging DNA repair-deficient mice

BACKGROUND

Sarcopenia is characterized by loss of skeletal muscle mass and function, and is a major risk factor for disability and independence in the elderly. Effective medication is not available. Dietary restriction (DR) has been found to attenuate aging and aging-related diseases, including sarcopenia, but the mechanism of both DR and sarcopenia are incompletely understood.

METHODS

In this study, mice body weight, fore and all limb grip strength, and motor learning and coordination performance were first analysed to evaluate the DR effects on muscle functioning. Liquid chromatography-mass spectrometry (LC-MS) was utilized for the metabolomics study of the DR effects on sarcopenia in progeroid DNA repair-deficient Ercc1∆/- and Xpg-/- mice, to identify potential biomarkers for attenuation of sarcopenia.

RESULTS

Muscle mass was significantly (P < 0.05) decreased (13-20%) by DR; however, the muscle quality was improved with retained fore limbs and all limbs grip strength in Ercc1∆/- and Xpg-/- mice. The LC-MS results revealed that metabolites and pathways related to oxidative-stress, that is, GSSG/GSH (P < 0.01); inflammation, that is, 9-HODE, 11-HETE (P < 0.05), PGE2, PGD2, and TXB2 (P < 0.01); and muscle growth (PGF2α) (P < 0.01) and regeneration stimulation (PGE2) (P < 0.05) are significantly downregulated by DR. On the other hand, anti-inflammatory indicator and several related metabolites, that is, β-hydroxybutyrate (P < 0.01), 14,15-DiHETE (P < 0.0001), 8,9-EET, 12,13-DiHODE, and PGF1 (P < 0.05); consumption of sources of energy (i.e., muscle and liver glycogen); and energy production pathways, that is, glycolysis (glucose, glucose-6-P, fructose-6-P) (P < 0.01), tricarboxylic acid cycle (succinyl-CoA, malate) (P < 0.001), and gluconeogenesis-related metabolite, alanine (P < 0.01), are significantly upregulated by DR. The notably (P < 0.01) down-modulated muscle growth (PGF2α) and regeneration (PGE2) stimulation metabolite and the increased consumption of glycogen in muscle and liver may be related to the significantly (P < 0.01) lower body weight and muscle mass by DR. The downregulated oxidative stress, pro-inflammatory mediators, and upregulated anti-inflammatory metabolites resulted in a lower energy expenditure, which contributed to enhanced muscle quality together with upregulated energy production pathways by DR. The improved muscle quality may explain why grip strength is maintained and motor coordination and learning performance are improved by DR in Ercc1∆/- and Xpg-/- mice.

CONCLUSIONS

This study provides fundamental supporting information on biomarkers and pathways related to the attenuation of sarcopenia, which might facilitate its diagnosis, prevention, and clinical therapy.

Olaris Global Panel (OGP): A Highly Accurate and Reproducible Triple Quadrupole Mass Spectrometry-Based Metabolomics Method for Clinical Biomarker Discovery

Mass spectrometry (MS)-based clinical metabolomics is very promising for the discovery of new biomarkers and diagnostics. However, poor data accuracy and reproducibility limit its true potential, especially when performing data analysis across multiple sample sets. While high-resolution mass spectrometry has gained considerable popularity for discovery metabolomics, triple quadrupole (QqQ) instruments offer several benefits for the measurement of known metabolites in clinical samples. These benefits include high sensitivity and a wide dynamic range. Here, we present the Olaris Global Panel (OGP), a HILIC LC-QqQ MS method for the comprehensive analysis of ~250 metabolites from all major metabolic pathways in clinical samples. For the development of this method, multiple HILIC columns and mobile phase conditions were compared, the robustness of the leading LC method assessed, and MS acquisition settings optimized for optimal data quality. Next, the effect of U-13C metabolite yeast extract spike-ins was assessed based on data accuracy and precision. The use of these U-13C-metabolites as internal standards improved the goodness of fit to a linear calibration curve from r2 < 0.75 for raw data to >0.90 for most metabolites across the entire clinical concentration range of urine samples. Median within-batch CVs for all metabolite ratios to internal standards were consistently lower than 7% and less than 10% across batches that were acquired over a six-month period. Finally, the robustness of the OGP method, and its ability to identify biomarkers, was confirmed using a large sample set.

Impact of conditioning runs on hydrophilic interaction chromatography repeatability and its application as a second dimension in online comprehensive two-dimensional liquid chromatography

A common separation approach for polar compounds involves coupling reversed-phase liquid chromatography (RPLC) with hydrophilic interaction chromatography (HILIC) in two-dimensional chromatography. The higher proportion of acetonitrile used in the HILIC mobile phase, which enhances mass spectrometry detection, encourages its use in the second dimension. Previous studies demonstrated that the HILIC column can be partially equilibrated within very short timeframes without compromising retention time stability, rendering it suitable in online comprehensive two-dimensional liquid chromatography (LC×LC) setups. In addition, a specific number of conditioning cycles seems necessary to establish stable retention times. Here, the repeatability of HILIC when employed as second dimension in LC×LC was investigated, with a focus on determining the required number of conditioning cycles to achieve repeatable retention times. Various parameters influenced by the LC×LC online modulation system were studied, such as steep gradient slopes up to 8%, and very short equilibration times, less than or equal to dead time, as well as injection volume and solvent, which depend on the first dimension. Finally, the use of HILIC as a second dimension with tailored conditioning runs was applied to the analysis of hyaluronic acid hydrogel digests. The application of an RPLC×HILIC method using five conditioning runs yielded exceptional stability in second-dimension retention times.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

Development of targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry method for acyl-Coenzyme A covering short- to long-chain species in a single analytical run

Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method using an LC-QTOF instrument for the identification of acyl-CoA species and optimizing their chromatography. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode using a QTRAP MS detector. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.

A comparison of hydrophilic interaction liquid chromatography and capillary electrophoresis for the metabolomics analysis of human serum

Cationic, anionic, zwitterionic and, partially polar metabolites are very important constituents of blood serum. Several of these metabolites underpin the core metabolism of cells (e.g., Krebs cycle, urea cycle, proteins synthesis, etc.), while others might be considered ancillary but still important to grasp the status of any organism through blood serum analysis. Due to its wide chemical diversity, modern metabolomics analysis of serum is still struggling to provide a complete and comprehensive picture of the polar metabolome, due to the limitations of each specific analytical method. In this study, two metabolomics-based analytical methods using the most successful techniques for polar compounds separation in human serum samples, namely hydrophilic interaction liquid chromatography (HILIC) and capillary electrophoresis (CE), are evaluated, both coupled to a high-resolution time-of-flight mass spectrometer via electrospray ionization (ESI-Q-TOF-MS). The performance of the two methods have been compared using five terms of comparison, three of which are specific to metabolomics, such as (1) compounds' detectability (2) Pezzatti score (Pezzatti et al. 2018), (3) intra-day precision (repeatability), (4) ease of automatic analysis of the data (through a common deconvolution alignment and extrapolation software, MS-DIAL, and (5) time & cost analysis. From this study, HILIC-MS proved to be a better tool for polar metabolome analysis, while CE-MS helped identify some interesting variables that gave it interest in completing metabolome coverage in metabolomics studies. Finally, in this framework, MS-DIAL demonstrates for the first time its ability to process CE data for metabolomics, although it is not designed for it.

Comparison between 5 extractions methods in either plasma or serum to determine the optimal extraction and matrix combination for human metabolomics

BACKGROUND

Although metabolomics continues to expand in many domains of research, methodological issues such as sample type, extraction and analytical protocols have not been standardized, impeding proper comparison between studies and future research.

METHODS

In the present study, five solvent-based and solid-phase extraction methods were investigated in both plasma and serum. All these extracts were analyzed using four liquid chromatography coupled with high resolution mass spectrometry (LC-MS) protocols, either in reversed or normal-phase and with both types of ionization. The performances of each method were compared according to putative metabolite coverage, method repeatability and also extraction parameters such as overlap, linearity and matrix effect; in both untargeted (global) and targeted approaches using fifty standard spiked analytes.

RESULTS

Our results verified the broad specificity and outstanding accuracy of solvent precipitation, namely methanol and methanol/acetonitrile. We also reveal high orthogonality between methanol-based methods and SPE, providing the possibility of increased metabolome coverage, however we highlight that such potential benefits must be weighed against time constrains, sample consumption and the risk of low reproducibility of SPE method. Furthermore, we highlighted the careful consideration about matrix choice. Plasma showed the most suitable in this metabolomics approach combined with methanol-based methods.

CONCLUSIONS

Our work proposes to facilitate rational design of protocols towards standardization of these approaches to improve the impact of metabolomics research.

Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS² fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRM^HR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS² fragmentation mode based on the measurement of ¹³C- or ¹⁵N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of ¹³C/¹⁵N atoms from D-¹³C₆-glucose/L-¹⁵N₂-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

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.

Methods on LDL particle isolation, characterization, and component fractionation for the development of novel specific oxidized LDL status markers for atherosclerotic disease risk assessment

The present study uses simple, innovative methods to isolate, characterize and fractionate LDL in its main components for the study of specific oxidations on them that characterize oxidized low-density lipoprotein (oxLDL) status, as it causatively relates to atherosclerosis-associated cardiovascular disease (CVD) risk assessment. These methods are: (a) A simple, relatively time-short, low cost protocol for LDL isolation, to avoid shortcomings of the currently employed ultracentrifugation and affinity chromatography methodologies. (b) LDL purity verification by apoB100 SDS-PAGE analysis and by LDL particle size determination; the latter and its serum concentration are determined in the present study by a simple method more clinically feasible as marker of CVD risk assessment than nuclear magnetic resonance. (c) A protocol for LDL fractionation, for the first time, into its main protein/lipid components (apoB100, phospholipids, triglycerides, free cholesterol, and cholesteryl esters), as well as into LDL carotenoid/tocopherol content. (d) Protocols for the measurement, for the first time, of indicative specific LDL component oxidative modifications (cholesteryl ester-OOH, triglyceride-OOH, free cholesterol-OOH, phospholipid-OOH, apoB100-MDA, and apoB100-DiTyr) out of the many (known/unknown/under development) that collectively define oxLDL status, which contrasts with the current non-specific oxLDL status evaluation methods. The indicative oxLDL status markers, selected in the present study on the basis of expressing early oxidative stress-induced oxidative effects on LDL, are studied for the first time on patients with end stage kidney disease on maintenance hemodialysis, selected as an indicative model for atherosclerosis associated diseases. Isolating LDL and fractionating its protein and main lipid components, as well as its antioxidant arsenal comprised of carotenoids and tocopherols, paves the way for future studies to investigate all possible oxidative modifications responsible for turning LDL to oxLDL in association to their possible escaping from LDL's internal antioxidant defense. This can lead to studies to identify those oxidative modifications of oxLDL (after their artificial generation on LDL), which are recognized by macrophages and convert them to foam cells, known to be responsible for the formation of atherosclerotic plaques that lead to the various CVDs.

13C Isotope Labeling and Mass Spectrometric Isotope Enrichment Analysis in Acute Brain Slices

Feeding of stable ¹³C-labeled compounds coupled to mass spectrometric analysis has enabled the characterization of dynamic metabolite partitioning in various experimental conditions. This information is particularly relevant for the study and functional understanding of brain metabolic heterogeneity. We here describe a protocol for the analysis of metabolic enrichment analysis upon feeding of murine acute cerebellar slices with ¹³C-labeled substrates.

HILIC-MS for Untargeted Profiling of the Free Glycation Product Diversity

Glycation products produced by the non-enzymatic reaction between reducing carbohydrates and amino compounds have received increasing attention in both food- and health-related research. Although liquid chromatography mass spectrometry (LC-MS) methods for analyzing glycation products already exist, only a few common advanced glycation end products (AGEs) are usually covered by quantitative methods. Untargeted methods for comprehensively analyzing glycation products are still lacking. The aim of this study was to establish a method for simultaneously characterizing a wide range of free glycation products using the untargeted metabolomics approach. In this study, Maillard model systems consisting of a multitude of heterogeneous free glycation products were chosen for systematic method optimization, rather than using a limited number of standard compounds. Three types of hydrophilic interaction liquid chromatography (HILIC) columns (zwitterionic, bare silica, and amide) were tested due to their good retention for polar compounds. The zwitterionic columns showed better performance than the other two types of columns in terms of the detected feature numbers and detected free glycation products. Two zwitterionic columns were selected for further mobile phase optimization. For both columns, the neutral mobile phase provided better peak separation, whereas the acidic condition provided a higher quality of chromatographic peak shapes. The ZIC-cHILIC column operating under acidic conditions offered the best potential to discover glycation products in terms of providing good peak shapes and maintaining comparable compound coverage. Finally, the optimized HILIC-MS method can detect 70% of free glycation product features despite interference from the complex endogenous metabolites from biological matrices, which showed great application potential for glycation research and can help discover new biologically important glycation products.