Absolute Quantification Of Metabolites Research Articles

Low Nitrogen Input Mitigates Quantitative but Not Qualitative Reconfiguration of Leaf Primary Metabolism in Brassica napus L. Subjected to Drought and Rehydration.

In the context of climate change and the reduction of mineral nitrogen (N) inputs applied to the field, winter oilseed rape (WOSR) will have to cope with low-N conditions combined with water limitation periods. Since these stresses can significantly reduce seed yield and seed quality, maintaining WOSR productivity under a wide range of growth conditions represents a major goal for crop improvement. N metabolism plays a pivotal role during the metabolic acclimation to drought in Brassica species by supporting the accumulation of osmoprotective compounds and the source-to-sink remobilization of nutrients. Thus, N deficiency could have detrimental effects on the acclimation of WOSR to drought. Here, we took advantage of a previously established experiment to evaluate the metabolic acclimation of WOSR during 14 days of drought, followed by 8 days of rehydration under high- or low-N fertilization regimes. For this purpose, we selected three leaf ranks exhibiting contrasted sink/source status to perform absolute quantification of plant central metabolites. Besides the well-described accumulation of proline, we observed contrasted accumulations of some "respiratory" amino acids (branched-chain amino acids, lysineand tyrosine) in response to drought under high- and low-N conditions. Drought also induced an increase in sucrose content in sink leaves combined with a decrease in source leaves. N deficiency strongly decreased the levels of major amino acids and subsequently the metabolic response to drought. The drought-rehydration sequence identified proline, phenylalanine, and tryptophan as valuable metabolic indicators of WOSR water status for sink leaves. The results were discussed with respect to the metabolic origin of sucrose and some amino acids in sink leaves and the impact of drought on source-to-sink remobilization processes depending on N nutrition status. Overall, this study identified major metabolic signatures reflecting a similar response of oilseed rape to drought under low- and high-N conditions.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack.

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Uncertainty propagation in absolute metabolite quantification for in vivo MRS of the human brain.

Absolute spectral quantification is the standard method for deriving estimates of the concentration from metabolite signals measured using in vivo proton MRS (1 H-MRS). This method is often reported with minimum variance estimators, specifically the Cramér-Rao lower bound (CRLB) of the metabolite signal amplitude's scaling factor from linear combination modeling. This value serves as a proxy for SD and is commonly reported in MRS experiments. Characterizing the uncertainty of absolute quantification, however, depends on more than simply the CRLB. The uncertainties of metabolite-specific (T1m , T2m ), reference-specific (T1ref , T2ref ), and sequence-specific (TR , TE ) parameters are generally ignored, potentially leading to an overestimation of precision. In this study, the propagation of uncertainty is used to derive a comprehensive estimate of the overall precision of concentrations from an internal reference. The propagated uncertainty is calculated using analytical derivations and Monte Carlo simulations and subsequently analyzed across a set of commonly measured metabolites and macromolecules. The effect of measurement error from experimentally obtained quantification parameters is estimated using published uncertainties and CRLBs from in vivo 1 H-MRS literature. The additive effect of propagated measurement uncertainty from applied quantification correction factors can result in up to a fourfold increase in the concentration estimate's coefficient of variation compared to the CRLB alone. A case study analysis reveals similar multifold increases across both metabolites and macromolecules. The precision of absolute metabolite concentrations derived from 1 H-MRS experiments is systematically overestimated if the uncertainties of commonly applied corrections are neglected as sources of error.

Study on the effect of calibration standards prepared with different matrix on the accuracy of bile acid quantification using LC-MS/MS

The transition from relative to absolute quantification of metabolites is the future development trend of mass spectrometry-based metabolomics research, which could fundamentally solve the problem of comparability of data between different laboratories. However, absolute quantification of endogenous molecules is largely hampered by the lack of analyte-free matrix, leading to uncertainty and inconsistency in the preparation of calibration standards. Bile acids (BAs) are an important class of biomarkers that play a key role in disease progression. In this paper, the quantitative accuracy of calibration curves prepared in neat solvent (NSCCs), charcoal stripped matrix (SMCCs) and authentic matrix (AMCCs) were validated using quality control samples (QCs) prepared in authentic matrix. Results suggested that AMCCs could largely minimize the confidence interval (C.I.) and the deviation in accuracy compared with NSCCs and SMCCs when measured concentration is higher than 20% of the background level. In addition, experimental data demonstrated that two-step calibration strategy proposed here is a promising and reliable alternative strategy to quantify endogenous BAs in biological sample.

A large-scale, targeted metabolomics method for the analysis and quantification of metabolites in human plasma via liquid chromatography-mass spectrometry

Metabolomics is the study of small molecules, primarily metabolites, that are produced during metabolic processes. Analysis of the composition of an organism's metabolome can yield useful information about an individual's health status at any given time. In recent years, the development of large-scale, targeted metabolomic methods has allowed for the analysis of biological samples using analytical techniques such as LC-MS/MS. This paper presents a large-scale metabolomics method for analysis of biological samples, with a focus on quantification of metabolites found in blood plasma. The method comprises a 10-min chromatographic separation using HILIC and RP stationary phases combined with positive and negative electrospray ionization in order to maximize metabolome coverage. Complete analysis of a single sample can be achieved in as little as 40 min using the two columns and dual modes of ionization. With 540 metabolites and the inclusion of over 200 analytical standards, this method is comprehensive and quantitatively robust when compared to current targeted metabolomics methods. This study uses a large-scale evaluation of metabolite recovery from plasma that enables absolute quantification of metabolites by correcting for analyte loss throughout processes such as extraction, handling, or storage. In addition, the method was applied to plasma collected from adjuvant breast cancer patients to confirm the suitability of the method to clinical samples.

Plasma metabolic profiling of patients with tetralogy of fallot

BackgroundTetralogy of Fallot (TOF) is a common congenital heart disease with high mortality. However, the medical imageology and liquidbiopsy techniques present certain limitations. Thus, this study investigated the plasma metabolic profiles to distinguish key metabolites for early diagnosis of TOF. MethodsIn total, 69 patients with TOF and 43 normal controls were enrolled for targeted metabolomics based on liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Absolute quantification of metabolites was performed using our standard database. The differentially expressed metabolites (DEMs) were screened by fold change (FC), VIP value and pearson correlation coefficient of OPLS-DA model. Receiver operating characteristic curve (ROC) was used to evaluate predictive ability of DEMs. ResultsDifferent metabolic profiles were presented between TOF and Normal.The pathway analysis showed that significantly changed metabolites were enriched in nicotinamide and purine metabolism. Many intermediatesproductof purine and amido acid were higher in TOF than in Normal group, while energy substrates and electron carriers were lower in TOF than in Normal group. ROC analysis revealed a high diagnostic value of plasma FAD for differentiating TOF from Normal (AUC = 1). ConclusionOur study quantitatively characterized plasma metabolites in patients with TOF and may help to develop reliable biomarkers that contribute to the early TOF screening.

Comparative urine metabolomics of mice treated with non-toxic and toxic oral doses of (-)-epigallocatechin-3-gallate.

The green tea polyphenol, (-)-epigallocatechin-3-gallate (EGCG), has been studied for its potential positive health effects, but human and animal model studies have reported potential toxicity at high oral bolus doses. This study used liquid chromatography-mass spectrometry-based metabolomics to compare the urinary EGCG metabolite profile after administration of a single non-toxic (100 mg kg-1) or toxic (750 mg kg-1) oral bolus dose to male C57BL6/J mice to better understand how EGCG metabolism varies with dose. EGCG metabolites, including methyl, glucuronide, sulfate, and glucoside conjugates, were tentatively identified based on their mass to charge (m/z) ratio and fragment ion patterns. Partial least squares discriminant analysis (PLS-DA) results showed clear separation of the urine metabolite profiles between treatment groups. The most differentiating metabolites in the negative and positive ion modes were provisionally identified as di-glucuronidated EGCG quinone and di-glucuronidated EGCG, respectively. The presence of EGCG oxidation products at toxic dose is consistent with studies showing that EGCG toxicity is associated with oxidative stress. Relative amounts of methylated metabolites increased with dose to a lesser extent than glucuronide and sulfate metabolites, indicating that methylation is more prominent at low doses, whereas glucuronidation and sulfation may be more important at higher doses. One limitation of the current work is that the lack of commercially-available EGCG metabolite standards prevented absolute metabolite quantification and identification. Despite this limitation, these findings provide a basis for better understanding the dose-dependent changes in EGCG metabolism and advance studies on how these differences may contribute to the toxicity of high doses of EGCG.

Isotopic Tracer for Absolute Quantification of Metabolites of the Pentose Phosphate Pathway in Bacteria.

The pentose phosphate pathway (PPP) plays a key role in many metabolic functions, including the generation of NADPH, biosynthesis of nucleotides, and carbon homeostasis. In particular, the intermediates of PPP have been found to be significantly perturbed in bacterial metabolomic studies. Nonetheless, detailed analysis to gain mechanistic information of PPP metabolism remains limited as most studies are unable to report on the absolute levels of the metabolites. Absolute quantification of metabolites is a prerequisite to study the details of fluxes and its regulations. Isotope tracer or labeling studies are conducted in vivo and in vitro and have significantly improved the analysis and understanding of PPP. Due to the laborious procedure and limitations in the in vivo method, an in vitro approach known as Group Specific Internal Standard Technology (GSIST) has been successfully developed to measure the absolute levels of central carbon metabolism, including PPP. The technique adopts derivatization of an experimental sample and a corresponding internal standard with isotope-coded reagents to provide better precision for accurate identification and absolute quantification. In this review, we highlight bacterial studies that employed isotopic tracers as the tagging agents used for the absolute quantification analysis of PPP metabolites.

Simultaneous metabolomics analysis of atrial tissue, pericardial fluid and blood reveal novel metabolite signatures of the pathophysiology and biomarkers related to permanent atrial fibrillation

Abstract Introduction Atrial fibrillation (AF) is the most common, complex, and clinically relevant arrhythmia [1]. It is a growing medical condition associated with significant morbidity and mortality, but its pathophysiology has remained widely unknown [2]. Aims We aim to unravel the complex pathophysiological mechanisms of AF and identify clinically relevant AF-related metabolites. We aim to identify targets for therapeutical interventions and biomarkers for AF diagnostics. Our study material is unique as we can safely study human heart and pericardial fluid in addition to blood, that has been mainly examined in previous studies. Material and methods Patients recruited were undergoing cardiac surgery due to valve defects at the University Hospital. For our research, we collected preoperative blood samples and intraoperative right atrial appendage biopsy and pericardial fluid. For our metabolomics study on AF patients, we selected 16 patients with permanent AF and 17 age, gender and underlying disease matched control patients (Fig. 1). Liquid chromatography mass spectrometry (LC-MS) was used to identify molecules and metabolites related to AF. We integrated targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds and metabolites. Results Untargeted mass spectrometry (MS) metabolite analysis identified altogether 15751 molecular features and metabolites divided unequally between the sample types (Fig. 2). Altogether, we found 1041 (p<0.05) metabolites from the heart tissue, 774 from the pericardial fluid and 382 from the blood. There were 61 metabolites associated with permanent AF that were found in all three sample types. The approach and our research set-up also allowed us to distinguish metabolites that entered directly from heart tissue to blood and those that remained in heart tissue and pericardial fluid. According to the identified metabolites in the heart tissue, permanent AF was associated with a clear metabolite signature including signs of dysregulated energy -, histidine -, glutathione -, purine -, sugar -, and lipid metabolism and antioxidant defense. Altogether we identified altered, circulating AF-related biomarkers including novel carnitines and acylcarnitines, aminoacids, metabolites from immune response and lipid metabolism. Among the highest statistical significance with qualifiable difference (multivariate α-level 0.0007) we found two novel circulating molecules with known MS spectrum and molecular weight. Conclusions We identified totally new pathophysiological processes and novel potential metabolites related to permanent AF to be used as AF biomarkers. Permanent AF is associated with dysreculation of multiple biologically relevant metabolic pathways. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Academy of FinlandThe Finnish Foundation for Cardiovascular Research

In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC-RX Array Coil for Whole-Brain MR Spectroscopic Imaging.

Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies. To develop absolute quantification for whole-brain MRSI in glioma patients. Prospective. Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms. A 3 T; Adiabatic spin-echo spiral 3D MRSI with real-time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi-echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE). Absolute quantification was performed for five brain metabolites (total N-acetyl-aspartate [NAA]/creatine/choline, glutamine + glutamate, myo-inositol) and the oncometabolite 2-hydroxyglutarate using a custom-built 4x-ERETIC/8x-receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured. ERETIC and internal water methods for metabolite quantification were compared using Bland-Altman (BA) analysis and the nonparametric Mann-Whitney test. P < 0.05 was considered statistically significant. ERETIC could be integrated in receive arrays and inductive coupling dominated (5-886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification. Our results indicate that ERETIC integrated with receive arrays and whole-brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients. 2 TECHNICAL EFFICACY: Stage 1.

Absolute choline tissue concentration mapping for prostate cancer localization and characterization using 3D 1H MRSI without water‐signal suppression

PurposeUntil now, 1H MRSI of the prostate has been performed with suppression of the large water signal to avoid distortions of metabolite signals. However, this signal can be used for absolute quantification and spectral corrections. We investigated the feasibility of water‐unsuppressed MRSI in patients with prostate cancer for water signal–mediated spectral quality improvement and determination of absolute tissue levels of choline.MethodsEight prostate cancer patients scheduled for radical prostatectomy underwent multi‐parametric MRI at 3 T, including 3D water‐unsuppressed semi‐LASER MRSI. A postprocessing algorithm was developed to remove the water signal and its artifacts and use the extracted water signal as intravoxel reference for phase and frequency correction of metabolite signals and for absolute metabolite quantification.ResultsWater‐unsuppressed MRSI with dedicated postprocessing produced water signal and artifact‐free MR spectra throughout the prostate. In all patients, the absolute choline tissue concentration was significantly higher in tumorous than in benign tissue areas (mean ± SD: 7.2 ± 1.4 vs 3.8 ± 0.7 mM), facilitating tumor localization by choline mapping. Tumor tissue levels of choline correlated better with the commonly used (choline + spermine + creatine)/citrate ratio (r = 0.78 ± 0.1) than that of citrate (r = 0.21 ± 0.06). The highest maximum choline concentrations occurred in high‐risk cancer foci.ConclusionThis report presents the first successful water‐unsuppressed MRSI of the whole prostate. The water signal enabled amelioration of spectral quality and absolute metabolite quantification. In this way, choline tissue levels were identified as tumor biomarker. Choline mapping may serve as a tool in prostate cancer localization and risk scoring in multi‐parametric MRI for diagnosis and biopsy procedures.

Improved Automated Quantification Algorithm (AQuA) and Its Application to NMR-Based Metabolomics of EDTA-Containing Plasma.

We have recently presented an Automated Quantification Algorithm (AQuA) and demonstrated its utility for rapid and accurate absolute metabolite quantification in 1H NMR spectra in which positions and line widths of signals were predicted from a constant metabolite spectral library. The AQuA quantifies based on one preselected signal per metabolite and employs library spectra to model interferences from other metabolite signals. However, for some types of spectra, the interspectral deviations of signal positions and line widths can be pronounced; hence, interferences cannot be modeled using a constant spectral library. We here address this issue and present an improved AQuA that handles interspectral deviations. The improved AQuA monitors and characterizes the appearance of specific signals in each spectrum and automatically adjusts the spectral library to model interferences accordingly. The performance of the improved AQuA was tested on a large data set from plasma samples collected using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant (n = 772). These spectra provided a suitable test system for the improved AQuA since EDTA signals (i) vary in intensity, position, and line width between spectra and (ii) interfere with many signals from plasma metabolites targeted for quantification (n = 54). Without the improvement, ca. 20 out of the 54 metabolites would have been overestimated. This included acetylcarnitine and ornithine, which are considered particularly difficult to quantify with 1H NMR in EDTA-containing plasma. Furthermore, the improved AQuA performed rapidly (<10 s for all spectra). We believe that the improved AQuA provides a basis for automated quantification in other data sets where specific signals show interspectral deviations.

Dietary obesity in mice is associated with lipid deposition and metabolic shifts in the lungs sharing features with the liver

Obesity is associated with both chronic and acute respiratory illnesses, such as asthma, chronic obstructive pulmonary disease (COPD) or increased susceptibility to infectious diseases. Anatomical but also systemic and local metabolic alterations are proposed contributors to the pathophysiology of lung diseases in the context of obesity. To bring perspective to this discussion, we used NMR to compare the obesity-associated metabolomic profiles of the lung with those of the liver, heart, skeletal muscles, kidneys, brain and serum from male C57Bl/6J mice fed with a high-fat and high-sucrose (HFHSD) diet vs. standard (SD) chow for 14 weeks. Our results showed that the lung was the second most affected organ after the liver, and that the two organs shared reduced one-carbon (1C) metabolism and increased lipid accumulation. Altered 1C metabolism was found in all organs and in the serum, but serine levels were increased only in the lung of HFHSD compared to SD. Lastly, tricarboxylic acid (TCA)-derived metabolites were specifically and oppositely regulated in the serum and kidneys but not in other organs. Collectively, our data highlighted that HFHSD induced specific metabolic changes in all organs, the lung being the second most affected organ, the main alterations affecting metabolite concentrations of the 1C pathway and, to a minor extend, TCA. The absolute metabolite quantification performed in this study reveals some metabolic specificities affecting both the liver and the lung, that may reveal common metabolic determinants to the ongoing pathological process.

Deep mining of oxysterols and cholestenoic acids in human plasma and cerebrospinal fluid: Quantification using isotope dilution mass spectrometry

Both plasma and cerebrospinal fluid (CSF) are rich in cholesterol and its metabolites. Here we describe in detail a methodology for the identification and quantification of multiple sterols including oxysterols and sterol-acids found in these fluids. The method is translatable to any laboratory with access to liquid chromatography – tandem mass spectrometry. The method exploits isotope-dilution mass spectrometry for absolute quantification of target metabolites. The method is applicable for semi-quantification of other sterols for which isotope labelled surrogates are not available and approximate quantification of partially identified sterols. Values are reported for non-esterified sterols in the absence of saponification and total sterols following saponification. In this way absolute quantification data is reported for 17 sterols in the NIST SRM 1950 plasma along with semi-quantitative data for 8 additional sterols and approximate quantification for one further sterol. In a pooled (CSF) sample used for internal quality control, absolute quantification was performed on 10 sterols, semi-quantification on 9 sterols and approximate quantification on a further three partially identified sterols. The value of the method is illustrated by confirming the sterol phenotype of a patient suffering from ACOX2 deficiency, a rare disorder of bile acid biosynthesis, and in a plasma sample from a patient suffering from cerebrotendinous xanthomatosis, where cholesterol 27-hydroxylase is deficient.

Investigation of the effects of actinorhodin biosynthetic gene cluster expression and a rpoB point mutation on the metabolome of Streptomyces coelicolor M1146

The previously reported Streptomyces coelicolor M1146 is commonly used as a host strain for engineering of secondary metabolite production. In this study, absolute quantification of intracellular and extracellular metabolites of M1146 was performed in mid-log phase and stationary phase to observe major metabolites and the changes that occurred during growth. Decreased levels of central carbon metabolites (glycolysis, TCA cycle, and pentose phosphate pathway) and increased levels of amino acids were observed in stationary phase compared to mid-log phase. Furthermore, comparative metabolome analyses of M1146 upon expression of the actinorhodin biosynthetic gene cluster (M1146+ACT), a point mutation on the rpoB gene encoding RNA polymerase beta-subunit (M1152), and both expression of actinorhodin biosynthetic gene cluster and a rpoB point mutation (M1152+ACT) were performed. M1146+ACT showed higher levels of important cofactors, such as ATP, NADPH, and FMN while M1152 led to higher levels of intracellular S-adenosyl-methionine, acyl-CoAs, and extracellular nucleosides compared to M1146. M1152+ACT exhibited the highest levels of actinorhodin with elevated bases, nucleosides, and nucleotides, such as intracellular PRPP (phosphoribosyl phosphate), ATP, along with extracellular inosine, uridine, and guanine compared to the other three strains, which were considered to be combined effects of actinorhodin gene cluster expression and a rpoB point mutation. Metabolites analysis by means of absolute quantification demonstrated changes in precursors of secondary metabolites before and after phosphate depletion in M1146. Comparative metabolome analysis provided further insights into the effects of actinorhodin gene cluster expression along with a rpoB point mutation on the metabolome of S.coelicolor.

Longitudinal quantification of metabolites and macromolecules reveals age- and sex-related changes in the healthy Fischer 344 rat brain

Normal aging is associated with numerous biological changes, including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful noninvasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7 T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant defenses, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathologic aging trajectories.This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Plasma metabolomics are associated with metabolic syndrome: A targeted approach.

Advances in metabolomic tools have allowed us to gain a more comprehensive understanding of metabolic syndrome (MetS). The aim of this study was to evaluate the association between plasma metabolomic profiles and MetS. For this study, adults without diabetes, chronic kidney disease, stroke, heart disease, or cancer and with full metabolomics, biochemical, and dietetic data available, representing a subsample of the Health Survey of Sao Paulo study (ISA-Capital; N=130), were included. The joint interim statement consensus criteria were used for diagnosing MetS. Absolute quantification (µmol/L) of blood metabolites was achieved by targeted quantitative profiling of annotated metabolites by electrospray ionization tandem mass spectrometry in plasma samples. Mean differences in the compounds for MetS were evaluated by linear regression adjusted for confounding factors. Serine was inversely associated with MetS (β=-15.04; P=0.014). In glycerophospholipids with acyl-alkyl bonds, there was an inverse association with MetS, including phosphatidylcholine (PC) ae C42:5 (β=-0.15; P=0.040), PC ae C44:5 (β=-0.15; P=0.046), PC ae C40:4 (β=-0.21; P=0.014) and PC ae C44:4 (β=-0.04; P=0.032). Plasma metabolomic profiles were associated with MetS, especially the amino acid serine and some acyl-alkyl PCs.

MSphere of Influence: Tweaking Organellar Purification Approaches.

Diego Huet studies the organelles involved in the metabolic adaptations of the apicomplexan parasite Toxoplasma gondii In this mSphere of Influence article, he reflects on how the paper "Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism" by Chen et al. (W. W. Chen, E. Freinkman, T. Wang, K. Birsoy, and D. M. Sabatini, Cell 166:1324-1337.e11, 2016, https://doi.org/10.1016/j.cell.2016.07.040) shaped his research by providing an approach for rapidly and specifically isolating mitochondria to probe the metabolism of these organelles.

GC-MS-Based Metabolomics for the Smut Fungus Ustilago maydis: A Comprehensive Method Optimization to Quantify Intracellular Metabolites.

Ustilago maydis, a smut fungus, is an appealing model in fundamental research and an upcoming cell factory for industrial biotechnology. The genome of U. maydis has been sequenced and some synthesis pathways were biochemically described; however, the operation of the cellular metabolic network is not well-characterized. Thus, we conducted a comprehensive study to optimize the sample preparation procedure for metabolomics of U. maydis using GC-MS/MS. Due to the unique characteristics of U. maydis cell culture, two quenching solutions, different washing steps, eight extraction methods, and three derivatization conditions have been examined. The optimal method was then applied for stable isotope-assisted quantification of low molecular weight hydrophilic metabolites while U. maydis utilized different carbon sources including sucrose, glucose, and fructose. This study is the first report on a methodology for absolute quantification of intracellular metabolites in U. maydis central carbon metabolism such as sugars, sugar phosphates, organic acids, amino acids, and nucleotides. For biotechnological use, this method is crucial to exploit the full production potential of this fungus and can also be used to study other fungi of the family Ustilaginaceae.

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 FusionTM TribridTM 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.