A Cardiovascular Disease-Linked Gut Microbial Metabolite Acts via Adrenergic Receptors.

Using untargeted metabolomics (n = 1,162 subjects), the plasma metabolite (m/z = 265.1188) phenylacetylglutamine (PAGln) was discovered and then shown in an independent cohort (n = 4,000 subjects) to be associated with cardiovascular disease (CVD) and incident major adverse cardiovascular events (myocardial infarction, stroke, or death). A gut microbiota-derived metabolite, PAGln, was shown to enhance platelet activation-related phenotypes and thrombosis potential in whole blood, isolated platelets, and animal models of arterial injury. Functional and genetic engineering studies with human commensals, coupled with microbial colonization of germ-free mice, showed the microbial porA gene facilitates dietary phenylalanine conversion into phenylacetic acid, with subsequent host generation of PAGln and phenylacetylglycine (PAGly) fostering platelet responsiveness and thrombosis potential. Both gain- and loss-of-function studies employing genetic and pharmacological tools reveal PAGln mediates cellular events through G-protein coupled receptors, including α2A, α2B, and ß2-adrenergic receptors. PAGln thus represents a new CVD-promoting gut microbiota-dependent metabolite that signals via adrenergic receptors.

Novel class of peptides disintegrating biological membranes to aid in the characterization of membrane proteins.

Styrene-maleic acid (SMA) and similar amphiphilic copolymers are known to cut biological membranes into lipid nanoparticles/nanodiscs containing membrane proteins apparently in their relatively native membrane lipid environment. Our previous work demonstrated that membrane raft microdomains resist such disintegration by SMA. The use of SMA in studying membrane proteins is limited by its heterogeneity and the inability to prepare defined derivatives. In the present paper, we demonstrate that some amphiphilic peptides structurally mimicking SMA also similarly disintegrate cell membranes. In contrast to the previously used copolymers, the simple peptides are structurally homogeneous. We found that their membrane-disintegrating activity increases with their length (reaching optimum at 24 amino acids) and requires a basic primary structure, that is, (XXD)n, where X represents a hydrophobic amino acid (optimally phenylalanine), D aspartic acid, and n is the number of repeats of these triplets. These peptides may provide opportunities for various well-defined potentially useful modifications in the study of membrane protein biochemistry. Our present results confirm a specific character of membrane raft microdomains.

Exploring contrast-enhancing staining agents for studying adipose tissue through contrast-enhanced computed tomography.

Contrast-enhanced computed tomography offers a nondestructive approach to studying adipose tissue in 3D. Several contrast-enhancing staining agents (CESAs) have been explored, whereof osmium tetroxide (OsO4) is the most popular nowadays. However, due to the toxicity and volatility of the conventional OsO4, alternative CESAs with similar staining properties were desired. Hf-WD 1:2 POM and Hexabrix have proven effective for structural analysis of adipocytes using contrast-enhanced computed tomography but fail to provide chemical information. This study introduces isotonic Lugol's iodine (IL) as an alternative CESA for adipose tissue analysis, comparing its staining potential with Hf-WD 1:2 POM and Hexabrix in murine caudal vertebrae and bovine muscle tissue strips. Single and sequential staining protocols were compared to assess the maximization of information extraction from each sample. The study investigated interactions, distribution, and reactivity of iodine species towards biomolecules using simplified model systems and assesses the potential of the CESA to provide chemical information. (Bio)chemical analyses on whole tissues revealed that differences in adipocyte gray values post-IL staining were associated with chemical distinctions between bovine muscle tissue and murine caudal vertebrae. More specific, a difference in the degree of unsaturation of fatty acids was identified as a likely contributor, though not the sole determinant of gray value differences. This research sheds light on the potential of IL as a CESA, offering both structural and chemical insights into adipose tissue composition.

Sodium-glucose cotransporter 2 inhibitors induce anti-inflammatory and anti-ferroptotic shift in epicardial adipose tissue of subjects with severe heart failure.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT-2i) are glucose-lowering agents used for the treatment of type 2 diabetes mellitus, which also improve heart failure and decrease the risk of cardiovascular complications. Epicardial adipose tissue (EAT) dysfunction was suggested to contribute to the development of heart failure. We aimed to elucidate a possible role of changes in EAT metabolic and inflammatory profile in the beneficial cardioprotective effects of SGLT-2i in subjects with severe heart failure. METHODS: 26 subjects with severe heart failure, with reduced ejection fraction, treated with SGLT-2i versus 26 subjects without treatment, matched for age (54.0 ± 2.1 vs. 55.3 ± 2.1 years, n.s.), body mass index (27.8 ± 0.9 vs. 28.8 ± 1.0 kg/m2, n.s.) and left ventricular ejection fraction (20.7 ± 0.5 vs. 23.2 ± 1.7%, n.s.), who were scheduled for heart transplantation or mechanical support implantation, were included in the study. A complex metabolomic and gene expression analysis of EAT obtained during surgery was performed. RESULTS: SGLT-2i ameliorated inflammation, as evidenced by the improved gene expression profile of pro-inflammatory genes in adipose tissue and decreased infiltration of immune cells into EAT. Enrichment of ether lipids with oleic acid noted on metabolomic analysis suggests a reduced disposition to ferroptosis, potentially further contributing to decreased oxidative stress in EAT of SGLT-2i treated subjects. CONCLUSIONS: Our results show decreased inflammation in EAT of patients with severe heart failure treated by SGLT-2i, as compared to patients with heart failure without this therapy. Modulation of EAT inflammatory and metabolic status could represent a novel mechanism behind SGLT-2i-associated cardioprotective effects in patients with heart failure.

Distinct roles of adipose triglyceride lipase and hormone-sensitive lipase in the catabolism of triacylglycerol estolides.

Branched esters of palmitic acid and hydroxy stearic acid are antiinflammatory and antidiabetic lipokines that belong to a family of fatty acid (FA) esters of hydroxy fatty acids (HFAs) called FAHFAs. FAHFAs themselves belong to oligomeric FA esters, known as estolides. Glycerol-bound FAHFAs in triacylglycerols (TAGs), named TAG estolides, serve as metabolite reservoir of FAHFAs mobilized by lipases upon demand. Here, we characterized the involvement of two major metabolic lipases, adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL), in TAG estolide and FAHFA degradation. We synthesized a library of 20 TAG estolide isomers with FAHFAs varying in branching position, chain length, saturation grade, and position on the glycerol backbone and developed an in silico mass spectra library of all predicted catabolic intermediates. We found that ATGL alone or coactivated by comparative gene identification-58 efficiently liberated FAHFAs from TAG estolides with a preference for more compact substrates where the estolide branching point is located near the glycerol ester bond. ATGL was further involved in transesterification and remodeling reactions leading to the formation of TAG estolides with alternative acyl compositions. HSL represented a much more potent estolide bond hydrolase for both TAG estolides and free FAHFAs. FAHFA and TAG estolide accumulation in white adipose tissue of mice lacking HSL argued for a functional role of HSL in estolide catabolism in vivo. Our data show that ATGL and HSL participate in the metabolism of estolides and TAG estolides in distinct manners and are likely to affect the lipokine function of FAHFAs.

Hydrophilic Interaction Liquid Chromatography-Hydrogen/Deuterium Exchange-Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics.

Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time-m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D2O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N1-acetylspermidine.

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.

Cyclooxygenase-derived proangiogenic metabolites of epoxyeicosatrienoic acids.

Arachidonic acid (ARA) is metabolized by cyclooxygenase (COX) and cytochrome P450 to produce proangiogenic metabolites. Specifically, epoxyeicosatrienoic acids (EETs) produced from the P450 pathway are angiogenic, inducing cancer tumor growth. A previous study showed that inhibiting soluble epoxide hydrolase (sEH) increased EET concentration and mildly promoted tumor growth. However, inhibiting both sEH and COX led to a dramatic decrease in tumor growth, suggesting that the contribution of EETs to angiogenesis and subsequent tumor growth may be attributed to downstream metabolites formed by COX. This study explores the fate of EETs with COX, the angiogenic activity of the primary metabolites formed, and their subsequent hydrolysis by sEH and microsomal EH. Three EET regioisomers were found to be substrates for COX, based on oxygen consumption and product formation. EET substrate preference for both COX-1 and COX-2 were estimated as 8,9-EET > 5,6-EET > 11,12-EET, whereas 14,15-EET was inactive. The structure of two major products formed from 8,9-EET in this COX pathway were confirmed by chemical synthesis: ct-8,9-epoxy-11-hydroxy-eicosatrienoic acid (ct-8,9-E-11-HET) and ct-8,9-epoxy-15-hydroxy-eicosatrienoic acid (ct-8,9-E-15-HET). ct-8,9-E-11-HET and ct-8,9-E-15-HET are further metabolized by sEH, with ct-8,9-E-11-HET being hydrolyzed much more slowly. Using an s.c. Matrigel assay, we showed that ct-8,9-E-11-HET is proangiogenic, whereas ct-8,9-E-15-HET is not active. This study identifies a functional link between EETs and COX and identifies ct-8,9-E-11-HET as an angiogenic lipid, suggesting a physiological role for COX metabolites of EETs.

Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data.

Large-scale untargeted lipidomics experiments involve the measurement of hundreds to thousands of samples. Such data sets are usually acquired on one instrument over days or weeks of analysis time. Such extensive data acquisition processes introduce a variety of systematic errors, including batch differences, longitudinal drifts, or even instrument-to-instrument variation. Technical data variance can obscure the true biological signal and hinder biological discoveries. To combat this issue, we present a novel normalization approach based on using quality control pool samples (QC). This method is called systematic error removal using random forest (SERRF) for eliminating the unwanted systematic variations in large sample sets. We compared SERRF with 15 other commonly used normalization methods using six lipidomics data sets from three large cohort studies (832, 1162, and 2696 samples). SERRF reduced the average technical errors for these data sets to 5% relative standard deviation. We conclude that SERRF outperforms other existing methods and can significantly reduce the unwanted systematic variation, revealing biological variance of interest.

Identification of small molecules using accurate mass MS/MS search.

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.

Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains.

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.

Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography-High-Resolution Mass Spectrometry Platforms.

Liquid chromatography-mass spectrometry (LC-MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted "best practice" documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC-MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.

Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography-Mass Spectroscopy (LC-MS) Data Processing.

Untargeted metabolomics by liquid chromatography-mass spectrometry generates data-rich chromatograms in the form of m/z-retention time features. Managing such datasets is a bottleneck. Many popular data processing tools, including XCMS-online and MZmine2, yield numerous false-positive peak detections. Flagging and removing such false peaks manually is a time-consuming task and prone to human error. We present a web application, Mass Spectral Feature List Optimizer (MS-FLO), to improve the quality of feature lists after initial processing to expedite the process of data curation. The tool utilizes retention time alignments, accurate mass tolerances, Pearson's correlation analysis, and peak height similarity to identify ion adducts, duplicate peak reports, and isotopic features of the main monoisotopic metabolites. Removing such erroneous peaks reduces the overall number of metabolites in data reports and improves the quality of subsequent statistical investigations. To demonstrate the effectiveness of MS-FLO, we processed 28 biological studies and uploaded raw and results data to the Metabolomics Workbench website ( www.metabolomicsworkbench.org ), encompassing 1481 chromatograms produced by two different data processing programs used in-house (MZmine2 and later MS-DIAL). Post-processing of datasets with MS-FLO yielded a 7.8% automated reduction of total peak features and flagged an additional 7.9% of features, per dataset, for review by the user. When manually curated, 87% of these additional flagged features were verified false positives. MS-FLO is an open source web application that is freely available for use at http://msflo.fiehnlab.ucdavis.edu .

Development of Tetramethylenedisulfotetramine (TETS) Hapten Library: Synthesis, Electrophysiological Studies, and Immune Response in Rabbits.

There is a need for fast detection methods for the banned rodenticide tetramethylenedisulfotetramine (TETS), a highly potent blocker of the γ-aminobutyric acid (GABAA ) receptors. General synthetic approach toward two groups of analogues was developed. Screening of the resulting library of compounds by FLIPR or whole-cell voltage-clamp revealed that, despite the structural differences, some of the TETS analogues retained GABAA receptor inhibition; however, their potency was an order of magnitude lower. Antibodies raised in rabbits against some of the TETS analogues conjugated to protein recognized free TETS and will be used for the development of an immunoassay for TETS.

Synthesis of cyclooxygenase metabolites of 8,9-epoxyeicosatrienoic acid (EET): 11- and 15-hydroxy 8,9-EETs.

COX metabolites of 8,9-EET, previously observed as potent mitogenic lipid mediators, were synthesized for the first time by using two synthetic approaches. These synthetic materials allow for structural confirmation of COX metabolites of 8,9-EET and further study of their biological roles.

Simultaneous production of intracellular triacylglycerols and extracellular polyol esters of fatty acids by Rhodotorula babjevae and Rhodotorula aff. paludigena.

Microbial oils have been analyzed as alternatives to petroleum. However, just a handful of microbes have been successfully adapted to produce chemicals that can compete with their petroleum counterparts. One of the reasons behind the low success rate is the overall economic inefficiency of valorizing a single product. This study presents a lab-scale analysis of two yeast species that simultaneously produce multiple high-value bioproducts: intracellular triacylglycerols (TG) and extracellular polyol esters of fatty acids (PEFA), two lipid classes with immediate applications in the biofuels and surfactant industries. At harvest, the yeast strain Rhodotorula aff. paludigena UCDFST 81-84 secreted 20.9 ± 0.2 g L-1 PEFA and produced 8.8 ± 1.0 g L-1 TG, while the yeast strain Rhodotorula babjevae UCDFST 04-877 secreted 11.2 ± 1.6 g L-1 PEFA and 18.5 ± 1.7 g L-1 TG. The overall glucose conversion was 0.24 and 0.22 g(total lipid) g (glucose)-1 , respectively. The results present a stable and scalable microbial growth platform yielding multiple co-products.

Discovery of synthesis and secretion of polyol esters of fatty acids by four basidiomycetous yeast species in the order Sporidiobolales.

Polyol esters of fatty acids (PEFA) are amphiphilic glycolipids produced by yeast that could play a role as natural, environmentally friendly biosurfactants. We recently reported discovery of a new PEFA-secreting yeast species, Rhodotorula babjevae, a basidiomycetous yeast to display this behavior, in addition to a few other Rhodotorula yeasts reported on the 1960s. Additional yeast species within the taxonomic order Sporidiobolales were screened for secreted glycolipid production. PEFA production equal or above 1 g L-1 were detected in 19 out of 65 strains of yeast screened, belonging to 6 out of 30 yeast species tested. Four of these species were not previously known to secrete glycolipids. These results significantly increase the number of yeast species known to secrete PEFA, holding promise for expanding knowledge of PEFA synthesis and secretion mechanisms, as well as setting the groundwork towards commercialization.

Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software.

Compound identification from accurate mass MS/MS spectra is a bottleneck for untargeted metabolomics. In this study, we propose nine rules of hydrogen rearrangement (HR) during bond cleavages in low-energy collision-induced dissociation (CID). These rules are based on the classic even-electron rule and cover heteroatoms and multistage fragmentation. We evaluated our HR rules by the statistics of MassBank MS/MS spectra in addition to enthalpy calculations, yielding three levels of computational MS/MS annotation: "resolved" (regular HR behavior following HR rules), "semiresolved" (irregular HR behavior), and "formula-assigned" (lacking structure assignment). With this nomenclature, 78.4% of a total of 18506 MS/MS fragment ions in the MassBank database and 84.8% of a total of 36370 MS/MS fragment ions in the GNPS database were (semi-) resolved by predicted bond cleavages. We also introduce the MS-FINDER software for structure elucidation. Molecular formulas of precursor ions are determined from accurate mass, isotope ratio, and product ion information. All isomer structures of the predicted formula are retrieved from metabolome databases, and MS/MS fragmentations are predicted in silico. The structures are ranked by a combined weighting score considering bond dissociation energies, mass accuracies, fragment linkages, and, most importantly, nine HR rules. The program was validated by its ability to correctly calculate molecular formulas with 98.0% accuracy for 5063 MassBank MS/MS records and to yield the correct structural isomer with 82.1% accuracy within the top-3 candidates. In a test with 936 manually identified spectra from an untargeted HILIC-QTOF MS data set of human plasma, formulas were correctly predicted in 90.4% of the cases, and the correct isomer structure was retrieved at 80.4% probability within the top-3 candidates, including for compounds that were absent in mass spectral libraries. The MS-FINDER software is freely available at http://prime.psc.riken.jp/ .

Multiplatform Mass Spectrometry-Based Approach Identifies Extracellular Glycolipids of the Yeast Rhodotorula babjevae UCDFST 04-877.

A multiplatform mass spectrometry-based approach was used for elucidating extracellular lipids with biosurfactant properties produced by the oleaginous yeast Rhodotorula babjevae UCDFST 04-877. This strain secreted 8.6 ± 0.1 g/L extracellular lipids when grown in a benchtop bioreactor fed with 100 g/L glucose in medium without addition of hydrophobic substrate, such as oleic acid. Untargeted reversed-phase liquid chromatography-quadrupole/time-of-flight mass spectrometry (QTOFMS) detected native glycolipid molecules with masses of 574-716 Da. After hydrolysis into the fatty acid and sugar components and hydrophilic interaction chromatography-QTOFMS analysis, the extracellular lipids were found to consist of hydroxy fatty acids and sugar alcohols. Derivatization and chiral separation gas chromatography-mass spectrometry (GC-MS) identified these components as d-arabitol, d-mannitol, (R)-3-hydroxymyristate, (R)-3-hydroxypalmitate, and (R)-3-hydroxystearate. In order to assemble these substructures back into intact glycolipids that were detected in the initial screen, potential structures were in-silico acetylated to match the observed molar masses and subsequently characterized by matching predicted and observed MS/MS fragmentation using the Mass Frontier software program. Eleven species of acetylated sugar alcohol esters of hydroxy fatty acids were characterized for this yeast strain.