Expanding coverage of the metabolome for global metabolite profiling

An optimized UPLC-MS/MS method for human plasma amyloid-β 42 and 40 measurement and application in Alzheimer's disease diagnosis

Critical events in Alzheimer's disease (AD) involve an imbalance between the production and clearance of amyloid-β (Aβ) peptides from the brain. The ratio of Aβ42 to Aβ40 in plasma was useful for evaluating AD, but quantification is limited by factors including preanalytical analyte loss and insufficient sensitivity. The availability of a targeted UPLC-MS/MS method with adequate analytical sensitivity and accurate values traceable to the SI units is essential for implementing a strategy for assay standardization. A targeted UPLC-MS/MS method for plasma Aβ42 and Aβ40 quantification was developed based on selected characteristic peptides spiked by 15N-labeled Aβ. The calibrator was assigned using an amino acid analysis reference method trace to SI units. UPLC-MS/MS conditions and sample preparation procedures were assessed. 59 plasma samples comparison were used to evaluate immunoassays. Additionally, two clinical cohorts were selected for diagnostic performance evaluation. The LOQ of Aβ42 and Aβ40 is 10 pg mL-1 and 20 pg mL-1, respectively. The linear range was 10-500 pg mL-1 for Aβ42 and 20-1000 pg mL-1 for Aβ40, recoveries between 95.3 % and 108.2 % for Aβ42, 93.2 % and 104.1 % for Aβ40, imprecisions were <7 %. The accuracy of method was validated by analysis of a certified reference material. Clinical cohorts for diagnostic performance evaluation shown that the area under the curve (AUC) for plasma Aβ42 and Aβ42/Aβ40 to differentiate between AD and CN were 0.767 and 0.799, respectively. A robust UPLC-MS/MS method was developed and demonstrated that suitable for a wide range of plasma Aβ42 and Aβ40. Applied to the investigation of clinically discrepant results, this method can act as an arbiter of the concentration of plasma Aβ42 and Aβ40 present.

High-Throughput Screening for Oligonucleotide Detection by ADE-OPI-MS

Oligonucleotides represent a class of shorter DNA or RNA nucleic acid polymers extensively applied in the biomedical field. Despite progress in detecting and analyzing oligonucleotides, high-throughput analysis of the samples remains challenging. In this work, a high-throughput analysis method for oligonucleotide analysis was developed based on acoustic droplet ejection-open port interface-mass spectrometry (ADE-OPI-MS) technology. This approach was applied to determine the enzymatic activity of terminal deoxynucleotide transferase (TdT) for DNA synthesis, with a rate of 3 s/sample, which enhanced single-sample analysis efficiency approximately 60-fold over the previous gel analysis. After testing approximately 10,000 TdT mutants, we obtained three new variants with higher catalytic activities. Finally, by integrating these mutants, the catalytic activity of TdT was improved about 4 times compared to the starting mutant. Our results successfully established a high-throughput screening method for oligonucleotide analysis, which not only provides a foundation to engineer highly efficient TdT for ab initio synthesis of DNA but also paves the way for the potential application of oligonucleotide analysis in biomedical fields.

A diverse proteome is present and enzymatically active in metabolite extracts

Metabolite extraction is the critical first-step in metabolomics experiments, where it is generally regarded to inactivate and remove proteins. Here, arising from efforts to improve extraction conditions for polar metabolomics, we discover a proteomic landscape of over 1000 proteins within metabolite extracts. This is a ubiquitous feature across several common extraction and sample types. By combining post-resuspension stable isotope addition and enzyme inhibitors, we demonstrate in-extract metabolite interconversions due to residual transaminase activity. We extend these findings with untargeted metabolomics where we observe extensive protein-mediated metabolite changes, including in-extract formation of glutamate dipeptide and depletion of total glutathione. Finally, we present a simple extraction workflow that integrates 3 kDa filtration for protein removal as a superior method for polar metabolomics. In this work, we uncover a previously unrecognized, protein-mediated source of observer effects in metabolomics experiments with broad-reaching implications across all research fields using metabolomics and molecular metabolism.

Targeted multi-analyte UHPLC-MS/MS methodology for emerging contaminants in septic tank wastewater, sludge and receiving surface water

Septic tanks treat wastewater of individual houses and small communities (up to 2000 people in Scotland) in rural and semi-urban areas and are understudied sources of surface water contamination. A multi-analyte methodology with solid phase extraction (SPE), ultra-sonic extraction, and direct injection sample preparation methods was developed to analyse a comprehensive range of emerging contaminants (ECs) including prescription and over-the-counter pharmaceuticals and related metabolites, natural and synthetic hormones, and other human wastewater marker compounds in septic tank influent and effluent, river water, suspended solids, and septic tank sludge by ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). The number of quantifiable compounds in each matrix varied from 68 in septic tank wastewater to 59 in sludge illustrating its applicability across a range of matrices. Method quantification limits were 2.9 × 10-5-1.2 μg L-1 in septic tank influent, effluent and river water, with ≤0.01 μg L-1 achieved for 60% of ECs in all three water matrices, and 0.080-49 μg kg-1 in sludge. The developed method was applied to a septic tank (292 population equivalents) and the receiving river in the North-East of Scotland. Across all samples analysed, 43 of 68 ECs were detected in at least one matrix, demonstrating the method's sensitivity. The effluent concentrations suggest limited removal of ECs in septic tanks and a potential impact to river water quality for some ECs. However, further monitoring is required to better appreciate this. The developed methodology for a wide variety of ECs in a range of liquid and solid phases will allow, for the first time, a comprehensive assessment of ECs fate and removal in septic tanks, and their impact to surface water quality.

Comparison between ammonium formate and ammonium fluoride in the analysis of stratum corneum lipids by reversed phase chromatography coupled with high resolution mass spectrometry

Lipids are key constituents of the barrier function in the human stratum corneum (SC), which is the outermost layer of the epidermis and amenable to non-invasive sampling by tape stripping. The three major lipid classes in the SC, i.e., ceramides, fatty acids, and cholesterol, present equimolar concentration. Liquid chromatography coupled with mass spectrometry (LCMS) is elective in profiling lipids in the SC in both positive and negative ion modes. Nevertheless, the latter one allows for the simultaneous detection of the three major epidermal components of the SC. Determination of ceramides in the SC poses analytical challenges due to their wide range of structures and concentrations especially in the case of limited sample amounts. Ammonium formate is a commonly used modifier added to the mobile phase to assist ionization. However, it introduces uncertainty in the identification of ceramides when operating in negative ion mode, even with high resolution MS. We tested the advantages of using fluoride in the lipid profiling of SC and unambiguous identification of ceramides subclasses. The use of fluoride enhanced the ionization of ceramides, regardless the specific substructure, solved misidentification issues, and was successfully applied to the simultaneous detection of all three lipid classes in the human SC.

Qualitative and quantitative determination of phenols and their metabolites in urine by in-syringe solid-phase extraction and LC-MS/MS analysis for evaluation of virgin olive oil metabolism

To know the bioavailability of virgin olive oil (VOO) phenols and its impact on health, it is necessary to determine the levels of phenols excreted in urine. We present here a novel strategy for in-syringe solid-phase extraction and analysis of the extract by liquid chromatography-tandem mass spectrometry (LC-MS/MS), using ammonium fluoride as ionization agent to enhance sensitivity. This approach allows avoiding additional steps such as solvent evaporation or analytes derivatization. The method can be used with a previous acid hydrolysis for quantitative determination of tyrosol and hydroxytyrosol to estimate metabolized phenols. We tested this application by analysis of a cohort of volunteers (n = 20) after a standardized intake of VOO. Additionally, the method can be used as such for metabolite profiling of phenolic derivatives in urine using LC-MS/MS in high-resolution data-independent acquisition (DIA). Information about the phenolic profile of the consumed VOO and the human metabolism is thus obtained. The proposed approach represents a simple and versatile tool for qualitative and quantitative characterization of VOO phenolic metabolism.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

Metabolomics Study Revealing Purines as Potential Diagnostic Biomarkers of Acute Respiratory Distress Syndrome in Patients with Community─Acquired Pneumonia

Community-acquired pneumonia (CAP) is a significant threat to human health and the leading cause of acute respiratory distress syndrome (ARDS). We aimed to reveal the metabolic profiling whether can be used for assessing CAP with or without ARDS (nARDS) and therapeutic effects on CAP patients after treatment. Urine samples were collected at the onset and recovery periods, and metabolomics was employed to identify robust biomarkers. 19 metabolites were significantly changed in the ARDS relative to nARDS, mainly involving purines and fatty acids. After treatment, 7 metabolites in the nARDS and 14 in the ARDS were found to be significantly dysregulated, including fatty acids and amino acids. In the validation cohort, we observed that the biomarker panel consisted of N2,N2-dimethylguanosine, 1-methyladenosine, 3-methylguanine, 1-methyladenosine, and uric acid exhibited better AUCs of 0.900 than pneumonia severity index and acute physiology and chronic health evaluation II (APACHE II) scores between the ARDS and nARDS. Combining L-phenylalanine, phytosphingosine, and N-acetylaspartylglutamate as biomarkers for discriminating the nARDS and ARDS patients after treatment exhibited good AUCs of 0.811 and 0.821, respectively. The metabolic pathway and defined biomarkers may serve as crucial indicators for predicting the development of ARDS in CAP patients and for assessing therapeutic effects.

Enhancement of Lipid Signals in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry with Ammonium Fluoride as a Matrix Additive

Lipids are essential macromolecules that play a crucial role in numerous biological events. Lipids are structurally diverse which allows them to fulfill multiple functional roles. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a powerful tool to understand the spatial localization of lipids within biological systems. Herein, we report the use of ammonium fluoride (NH4F) as a comatrix additive to enhance lipid detection in biological samples, with a signal increase of up to 200%. Emphasis was placed on anionic lipid enhancement with negative polarity measurements, with some preliminary work on cationic lipids detailed. We observed lipid signal enhancement of [M-H]- ions with the addition of NH4F additive attributed to a proton transfer reaction in several different lipid classes. Overall, our study demonstrates that the use of the NH4F comatrix additive substantially improves sensitivity for lipid detection in a MALDI system and is capable of being applied to a variety of different applications.

Higher Plasma Creatinine Is Associated with an Increased Risk of Death in Patients with Non-Metastatic Rectal but Not Colon Cancer: Results from an International Cohort Consortium

Colorectal cancer (CRC) is increasingly recognized as a heterogeneous disease. No studies have prospectively examined associations of blood metabolite concentrations with all-cause mortality in patients with colon and rectal cancer separately. Targeted metabolomics (Biocrates AbsoluteIDQ p180) and pathway analyses (MetaboAnalyst 4.0) were performed on pre-surgery collected plasma from 674 patients with non-metastasized (stage I-III) colon (n = 394) or rectal cancer (n = 283). Metabolomics data and covariate information were received from the international cohort consortium MetaboCCC. Cox proportional hazards models were computed to investigate associations of 148 metabolite levels with all-cause mortality adjusted for age, sex, tumor stage, tumor site (whenever applicable), and cohort; the false discovery rate (FDR) was used to account for multiple testing. A total of 93 patients (14%) were deceased after an average follow-up time of 4.4 years (60 patients with colon cancer and 33 patients with rectal cancer). After FDR adjustment, higher plasma creatinine was associated with a 39% increase in all-cause mortality in patients with rectal cancer. HR: 1.39, 95% CI 1.23-1.72, pFDR = 0.03; but not colon cancer: pFDR = 0.96. Creatinine is a breakdown product of creatine phosphate in muscle and may reflect changes in skeletal muscle mass. The starch and sucrose metabolisms were associated with increased all-cause mortality in colon cancer but not in rectal cancer. Genes in the starch and sucrose metabolism pathways were previously linked to worse clinical outcomes in CRC. In summary, our findings support the hypothesis that colon and rectal cancer have different etiological and clinical outcomes that need to be considered for targeted treatments.

Metabolomic Profiling in Children with Celiac Disease: Beyond the Gluten-Free Diet

Celiac disease (CD) is included in the group of complex or multifactorial diseases, i.e., those caused by the interaction of genetic and environmental factors. Despite a growing understanding of the pathophysiological mechanisms of the disease, diagnosis is still often delayed and there are no effective biomarkers for early diagnosis. The only current treatment, a gluten-free diet (GFD), can alleviate symptoms and restore intestinal villi, but its cellular effects remain poorly understood. To gain a comprehensive understanding of CD's progression, it is crucial to advance knowledge across various scientific disciplines and explore what transpires after disease onset. Metabolomics studies hold particular significance in unravelling the complexities of multifactorial and multisystemic disorders, where environmental factors play a significant role in disease manifestation and progression. By analyzing metabolites, we can gain insights into the reasons behind CD's occurrence, as well as better comprehend the impact of treatment initiation on patients. In this review, we present a collection of articles that showcase the latest breakthroughs in the field of metabolomics in pediatric CD, with the aim of trying to identify CD biomarkers for both early diagnosis and treatment monitoring. These advancements shed light on the potential of metabolomic analysis in enhancing our understanding of the disease and improving diagnostic and therapeutic strategies. More studies need to be designed to cover metabolic profiles in subjects at risk of developing the disease, as well as those analyzing biomarkers for follow-up treatment with a GFD.

Rapid Derivatization of Phenolic and Oxime Hydroxyl with Isonicotinoyl Chloride under Aqueous Conditions and Its Application in LC-MS/MS Profiling Multiclass Steroids

Quantification of steroids possesses a crucial clinical value in early diagnosis and prognosis evaluation of various endocrine diseases. However, it is still challenging to realize feasible analysis of estrogens, androgens, progestogens, and corticoids within one single workflow. In this study, two derivatization reactions were newly designed for improvement: (1) acylation of phenolic hydroxyl on estrogens with isonicotinoyl chloride (INC) under the catalysis of 4-dimethylaminopyridine and (2) post-modification of oxime hydroxyl on hydroxylamine-pretreated ketosteroids with INC. Both reactions could conduct instantaneously at room temperature under aqueous conditions. Moreover, the resulting phenolic-INC and oxime-INC esters exhibited favorable MS responses. Through integrating these derivatization strategies with cold-induced phase separation technology, a feasible LC-MS/MS method was developed for simultaneous quantification of 15 multiclass steroids with proper sample consumption (50 μL serum), satisfying sensitivity (lower limit of quantitation at 0.01-5.00 ng/mL) and high throughput (40 min for sample-preparation). The practical applicability was tested by detecting 30 real samples from pregnant and non-pregnant women. The obtained results showed a good agreement with a previous validated methodology.

Unified-Hydrophilic-Interaction/Anion-Exchange Liquid Chromatography Mass Spectrometry (Unified-HILIC/AEX/MS): A Single-Run Method for Comprehensive and Simultaneous Analysis of Polar Metabolome

One of the technical challenges in the field of metabolomics is the development of a single-run method to detect the full complement of polar metabolites in biological samples. However, an ideal method to meet this demand has not yet been developed. Herein, we proposed a simple methodology that enables the comprehensive and simultaneous analysis of polar metabolites using unified-hydrophilic-interaction/anion-exchange liquid chromatography mass spectrometry (unified-HILIC/AEX/MS) with a polymer-based mixed amines column composed of methacrylate-based polymer particles with primary, secondary, tertiary, and quaternary amines as functional groups. The optimized unified-HILIC/AEX/MS method is composed of two consecutive chromatographic separations, HILIC-dominant separation for cationic, uncharged, and zwitterionic polar metabolites [retention times (RTs) = 0-12.8 min] and AEX-dominant separation for polar anionic metabolites (RTs = 12.8-26.5 min), by varying the ratio of acetonitrile to 40 mM ammonium bicarbonate solution (pH 9.8). A total of 400 polar metabolites were analyzed simultaneously through a combination of highly efficient separation using unified-HILIC/AEX and remarkably sensitive detection using multiple reaction monitoring-based triple quadrupole mass spectrometry (unified-HILIC/AEX/MS/MS). A nontargeted metabolomic approach using unified-HILIC/AEX high-resolution mass spectrometry (unified-HILIC/AEX/HRMS) also provided more comprehensive information on polar metabolites (3242 metabolic features) in HeLa cell extracts than the conventional HILIC/HRMS method (2068 metabolic features). Our established unified-HILIC/AEX/MS/MS and unified-HILIC/AEX/HRMS methods have several advantages over conventional techniques, including polar metabolome coverage, throughput, and accurate quantitative performance, and represent potentially useful tools for in-depth studies on metabolism and biomarker discovery.

Engineering of global transcription factor FruR to redirect the carbon flow in Escherichia coli for enhancing L-phenylalanine biosynthesis

BACKGROUND

The catabolite repressor/activator protein (FruR) is a global regulatory protein known to control the expression of several genes concerned with carbon utilization and energy metabolism. This study aimed to illustrate effects of the FruR mutant on the _L-phenylalanine (_L-PHE) producing strain PHE01.

RESULTS

Random mutagenesis libraries of fruR generated in vitro were first integrated into the chromosome of PHE01 by CRISPR/Cas9 technique, and then the best mutant PHE07 (FruR^E173K) was obtained. With this mutant, a final _L-PHE concentration of 70.50 ± 1.02 g/L was achieved, which was 23.34% higher than that of PHE01. To better understand the mechanism, both transcriptomes and metabolomes of PHE07 were carried out and compared to that of PHE01. Specifically, the transcript levels of genes involved in gluconeogenesis pathway, pentose phosphate pathway, Krebs cycle, and glyoxylate shunt were up-regulated in the FruR^E173K mutant, whereas genes aceEF, acnB, and icd were down-regulated. From the metabolite level, the FruR^E173K mutation led to an accumulation of pentose phosphate pathway and Krebs cycle products, whereas the products of pyruvate metabolism pathway: acetyl-CoA and cis-aconic acid, were down-regulated. As a result of the altered metabolic flows, the utilization of carbon sources was improved and the supply of precursors (phosphoenolpyruvate and erythrose 4-phosphate) for _L-PHE biosynthesis was increased, which together led to the enhanced production of _L-PHE.

CONCLUSION

A novel strategy for _L-PHE overproduction by modification of the global transcription factor FruR in E. coli was reported. Especially, these findings expand the scope of pathways affected by the fruR regulon and illustrate its importance as a global regulator in _L-PHE production.

Liquid chromatography coupled to high-resolution mass spectrometry metabolomics: A useful tool for investigating tumor secretome based on a three-dimensional co-culture model

Three-dimensional (3D) cell culture technologies, which more closely mimic the complex microenvironment of tissue, are being increasingly evaluated as a tool for the preclinical screening of clinically promising new molecules, and studying of tissue metabolism. Studies of metabolites released into the extracellular space (secretome) allow understanding the metabolic dynamics of tissues and changes caused by therapeutic interventions. Although quite advanced in the field of proteomics, studies on the secretome of low molecular weight metabolites (< 1500 Da) are still very scarce. We present an untargeted metabolomic protocol based on the hybrid technique of liquid chromatography coupled with high-resolution mass spectrometry for the analysis of low-molecular-weight metabolites released into the culture medium by 3D cultures and co-culture (secretome model). For that we analyzed HT-29 human colon carcinoma cells and 3T3-L1 preadipocytes in 3D-monoculture and 3D-co-culture. The putative identification of the metabolites indicated a sort of metabolites, among them arachidonic acid, glyceric acid, docosapentaenoic acid and beta-Alanine which are related to cancer and obesity. This protocol represents a possibility to list metabolites released in the extracellular environment in a comprehensive and untargeted manner, opening the way for the generation of metabolic hypotheses that will certainly contribute to the understanding of tissue metabolism, tissue-tissue interactions, and metabolic responses to the most varied interventions. Moreover, it brings the potential to determine novel pathways and accurately identify biomarkers in cancer and other diseases. The metabolites indicated in our study have a close relationship with the tumor microenvironment in accordance with the literature review.

NMR and Metabolomics-A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Optimized integration of metabolomics and lipidomics reveals brain region-specific changes of oxidative stress and neuroinflammation in type 1 diabetic mice with cognitive decline

INTRODUCTION

Type 1 diabetes (T1D) causes cognitive decline and has been associated with brain metabolic disorders, but its potential molecular mechanisms remain unclear.

OBJECTIVES

The purpose of this study was to explore the molecular mechanisms underlying T1D-induced cognitive impairment using metabolomics and lipidomics.

METHODS

We developed an optimized integration approach of metabolomics and lipidomics for brain tissue based on UPLC-Q-TOF-MS and analyzed a comprehensive characterization of metabolite and lipid profiles in the hippocampus and frontal cortex of T1D male mice with cognitive decline (T1DCD) and age-matched control (CONT) mice.

RESULTS

The results show that T1DCD mice had brain metabolic disorders in a region-specific manner relative to CONT mice, and the frontal cortex exhibited a higher lipid peroxidation than the hippocampus in T1DCD mice. Based on metabolic changes, we found that microglia was activated under diabetic condition and thereby promoted oxidative stress and neuroinflammation, leading to neuronal injury, and this event was more pronounced in the frontal cortex than the hippocampus.

CONCLUSION

Our results suggest that brain region-specific shifts in oxidative stress and neuroinflammation may contribute to diabetic cognitive decline, and the frontal cortex could be the more vulnerable brain region than the hippocampus.

Synthetic surfactants in Swiss sewage sludges: Analytical challenges, concentrations and per capita loads

Surfactants are high-production-volume chemicals that are among the most abundant organic pollutants in municipal wastewater. In this study, sewage sludge samples of 36 Swiss wastewater treatment plants (WWTPs), serving 32% of the country's population, were analyzed for major surfactant classes by liquid chromatography mass spectrometry (LC-MS). The analyses required a variety of complementary approaches due to different analytical challenges, including matrix effects (which can affect adduct ion formation) and the lack of reference standards. The most abundant contaminants were linear alkylbenzene sulfonates (LAS; weighted mean [WM] concentration of 3700 μg g^-1 dry weight), followed by secondary alkane sulfonates (SAS; 190 μg g^-1). Alcohol polyethoxylates (AEO; 8.3 μg g^-1), nonylphenol polyethoxylates (NPEO; 16 μg g^-1), nonylphenol (NP; 3.1 μg g^-1), nonylphenol ethoxy carboxylates (NPEC; 0.35 μg g^-1) and tert-octylphenol (tert-OP, 1.8 μg g^-1) were present at much lower concentrations. This concentration pattern agrees with the production volumes of the surfactants and their fates in WWTPs. Branched AEO homologues dominated over linear homologues, probably due to higher persistence. Sludge concentrations of LAS, SAS, and NP were positively correlated with the residence time in the anaerobic digester. Derivation of the per capita loads successfully revealed potential industrial/commercial emission sources. Comparison of recent versus historic data showed a decrease in NPEO and NP levels by one or two orders of magnitude since their ban in the 1980s. By contrast, LAS still exhibit similar concentrations compared to 30 years ago.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

A Robust Method for Sample Preparation of Gastrointestinal Stromal Tumour for LC/MS Untargeted Metabolomics

Gastrointestinal stromal tumour has already been well explored at the genome level; however, little is known about metabolic processes occurring in the sarcoma. Sample preparation is a crucial step in untargeted metabolomics workflow, highly affecting the metabolome coverage and the quality of the results. In this study, four liquid-liquid extraction methods for the isolation of endogenous compounds from gastrointestinal stromal tumours were compared and evaluated. The protocols covered two-step or stepwise extraction with methyl-tert-butyl ether (MTBE) or dichloromethane. The extracts were subjected to LC-MS analysis by the application of reversed-phase and hydrophilic interaction liquid chromatography to enable the separation and detection of both polar and nonpolar analytes. The extraction methods were compared in terms of efficiency (total number of detected metabolites) and reproducibility. The method was based on the stepwise extraction with MTBE, methanol, and water proved to be the most reproducible, and thus, its robustness to fluctuations in experimental conditions was assessed employing Plackett–Burman design and hierarchical modelling. While most studied factors had no effect on the metabolite abundance, the highest coefficient value was observed for the volume of MTBE added during extraction. Herein, we demonstrate the application and the feasibility of the selected protocol for the analysis of gastrointestinal stromal tumour samples. The method selected could be considered as a reference for the best characterization of underlying molecular changes associated with complex tissue extracts of GIST.

Determination of specific urinary nonylphenol metabolites by online-SPE-LC-MS/MS as novel human exposure biomarkers

Nonylphenol (NP) is an endocrine disrupting and ecotoxic substance that has been detected in a variety of environmental matrices. It is utilized for the production of non-ionic nonylphenol ethoxylate (NPEO) detergents and other high production volume chemicals. Human biomonitoring data are scarce and mostly limited to the non-oxidized NP, which is ubiquitous in the (laboratory) environment and susceptible to external contamination. Here, we describe a sensitive, precise, accurate and rugged analytical method for the determination of OH-NP and oxo-NP, two potential alkyl-chain-oxidized metabolites of NP in human urine. We used single isomer standards, obtained by custom synthesis, for the quantification of the sum of the respective isomers. After enzymatic hydrolysis of potential urinary phase II conjugates, urine samples were analyzed by online turbulent flow chromatography for analyte enrichment and matrix depletion coupled to reversed phase liquid chromatography with negative electrospray-ionization triple quadrupole tandem mass spectrometry detection (online-SPE-LC-MS/MS). Quantification was performed by stable isotope dilution analysis. Limits of quantification in urinary matrix were 0.5 µg/L for OH-NP and 0.25 µg/L for oxo-NP. Mean relative recoveries were 101-105% (OH-NP) and 112-117% (oxo-NP) and the method imprecision (CV) in matrix was below 5%. In spite of extensive use restrictions in the EU since 2003, we could quantify OH-NP and oxo-NP in 94% and 47% of spot urine samples from the general German population (n = 32) collected in 2014. Thus, both metabolites seem suitable as sensitive and specific urinary biomarkers of NP exposure for future human biomonitoring population studies. Currently this method is used to quantitatively investigate human NP metabolism and to derive urinary metabolite excretion fractions that can be used to calculate external doses based on urinary biomarker concentrations.

Fluoride-assisted liquid chromatography-tandem mass spectrometry method for simultaneous analysis of propofol and its metabolites without derivatization in urine

The misuse of propofol for recreational purposes has become a serious social issue. Accordingly, practical and sensitive analytical methods to investigate the chronic abuse and toxicity of propofol are required. However, current propofol determination methods using liquid chromatography-mass spectrometry (LC-MS/MS) suffer from problems associated with loss in sample preparation due to its volatility and its poor ionization efficiency and collision-induced dissociation in mass spectrometry. Herein, we have developed a sensitive and accurate fluoride-assisted LC-MS/MS method combined with direct-injection for propofol determination. Ionization via fluoride-ion attachment/induced deprotonation, effected by ammonium fluoride in the mobile phase, was found to dramatically improve the sensitivity of propofol without derivatization. Furthermore, direct injection without derivatization enables the simultaneous analysis of propofol and its phase II metabolites without analyte loss. The optimal concentration of ammonium fluoride in the mobile phase was found to be 1 mM under methanol conditions. The linearity is good (R² ≥ 0.999) and the intra- and inter-day precisions for propofol determination are between 1.9 and 8.7%. The accuracies range from 87.5% to 105.4% and the limits of detection and quantitation for propofol in urine are 0.15 and 0.44 ng mL^-1, respectively. The present method was successfully applied to human urine and showed a sufficient sensitivity to determine propofol and five phase II metabolites over 48 h in human urine after administration. Consequently, the fluoride-assisted LC-MS/MS method was demonstrated to be sensitive, accurate, and practical for the determination of propofol and its metabolites.

The evolving landscape of untargeted metabolomics

AIMS

Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics.

DATA SYNTHESIS

Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available.

CONCLUSIONS

Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.

A systematic approach to development of analytical scale and microflow-based liquid chromatography coupled to mass spectrometry metabolomics methods to support drug discovery and development

As the reliance on metabolic biomarkers within drug discovery and development increases, there is also an increased demand for global metabolomics methods to provide broad metabolome coverage and sensitivity towards differences in metabolite expression and reproducibility. A systematic approach is necessary for the development, and evaluation, of metabolomics methods using either conventional techniques or when establishing new methods that allow for additional gains in sensitivity and a reduction in requirements for amounts of a biological sample, such as those seen with methods based on microseparations. We developed a novel standard mixture and used a systematic approach for the development and optimization of optimal, ion-pair free, liquid chromatography-mass spectrometry (LC-MS) global profiling methods. These methods were scaled-down to microflow-based LC separations and compared with analytical flow ion-pairing reagent containing methods. Average peak volume improvements of 7- and 22-fold were observed in the positive and negative ionization mode microflow methods as compared to the ion-pairing reagent analytical flow methods, respectively. The linear range of the newly developed microflow methods showed up to a 10-fold increase in the lower limit of detection in the negative ionization mode. The developed microflow LC-MS methods were further evaluated using wild-type mouse plasma where up to a 9-fold increase in peak volume was observed.

Dengue and metabolomics in humans

BACKGROUND

Dengue virus causes dengue fever (DF)disease, transmitted by the mosquito Aedes aegypti. The symptoms could be severe and disable the affected individuals for weeks. The severe form, dengue hemorrhagic fever (DHF), can lead to death if not adequately attended to. Due to global warming, the vector mosquito will advance over new areas and expose more people to this disease over the next decades. Despite the severity, there are no treatments nor efficient vaccines available. Metabolomic studies have shown a new perspective to understand this disease better at a new molecular level.

AIM OF REVIEW

Many published works rely on samples obtained from animal studies. This review will mainly focus on human samples and cell culture experiments to view how the dengue virus affects the metabolomic profile.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review compiles the sample sources, metabolomic techniques used, the detected compounds, and how they behave in different DF stages. This disease causes a significant change in many metabolites, but some results are still conflicting between studies. The results gathered here show that metabolomic approaches prove to be an excellent and viable way to expand knowledge about DF.

Urinary free metanephrines measurement in dogs with adrenal gland diseases using a new simple liquid chromatography tandem mass spectrometry method

Measurement of urinary metanephrines in spot samples is used for the diagnosis of canine pheochromocytoma (PC). We describe a simple analytical method based on liquid chromatography tandem mass spectrometry (LC-MS/MS) for measuring free metanephrine (MN) and normetanephrine (NMN) in spot urine samples. Using the developed method, we evaluated the stability of urinary free-MN and free-NMN at various storing conditions. In addition, we assessed the feasibility of urinary free-MN and -NMN measurement for diagnosing PC. Urine samples were mixed with stable isotope internal standards and thereafter purified by ultrafiltration. The purified samples were analyzed by LC-MS/MS in the multiple reaction monitoring mode after separation on a multimode octa decyl silyl column. The coefficient of variation of free-MN and -NMN measurement was 7.6% and 5.5%, respectively. The linearity range was 0.5–10 µg/l for both analytes. Degradation was less than 10% for both analytes under any of the storage conditions. The median free-NMN ratio to creatinine of 9 PC dogs (595, range 144–47,961) was significantly higher (P<0.05) than that of 13 dogs with hypercortisolism (125, range 52–224) or 15 healthy dogs (85, range 50–117). The developed method is simple and may not require acidification of spot urine. The results of this preliminary retrospective study suggest that the measurement of urinary free metanephrines is a promising tool for diagnosing canine PC.

Generic multicriteria approach to determine the best precipitation agent for removal of biomacromolecules prior to non-targeted metabolic analysis

The removal of biomacromolecules from biofluids decreases the sample complexity and lower electrospray suppression effects. Furthermore, it can increase the analysis sensitivity, precision, and selectivity. Often removal approaches evaluate the model based on a single criterion, like protein removed or response of one of few specific metabolites. In this study, we used a multicriteria approach to test the effect of using the solvents methanol and acetonitrile (organic solvent precipitation), trichloroacetic acid (acidic precipitation) and ammonium sulphate (salting out) to remove biomacromolecules from a downstream recovery process from a bacillus fermentation. The downstream recovery process intermediates were analysed using reversed-phase ultra-high-pressure liquid chromatography with electrospray ionisation and high-resolution time-of-flight mass spectrometry detection. To evaluate the pre-treatment agents the following multicriteria was applied i) practical considerations, ii) total amino acid in the precipitated pellet, iii) putative identification of the molecules removed or created by the different treatments, iv) coherence between high quality extracted ion chromatograms (repeatability of DW-CODA) and v) replicate consistency from principal component analysis score values obtained by using the CHEMometric analysis of sections of Selected Ion Chromatograms (CHEMSIC) method. This study presents a generic workflow to find the best pre-treatment for removing bio-macromolecules from biofluids with a multicriteria approach. In our case, the best protein removal strategy for downstream recovery intermediates was acetonitrile precipitation. This method showed high precision, created few artefact peaks compared to simple sample dilution, and mainly removed small peptides.

From a single steroid to the steroidome: Trends and analytical challenges

For several decades now, the analysis of steroids has been a key tool in the diagnosis and monitoring of numerous endocrine pathologies. Thus, the available methods used to analyze steroids in biological samples have dramatically evolved over time following the rapid pace of technology and scientific knowledge. This review aims to synthetize the advances in steroids' analysis, from classical approaches considering only a few steroids or a limited number of steroid ratios, up to the new steroid profiling strategies (steroidomics) monitoring large sets of steroids in biological matrices. In this context, the use of liquid chromatography coupled to mass spectrometry has emerged as the technique of choice for the simultaneous determination of a high number of steroids, including phase II metabolites, due to its sensitivity and robustness. However, the large dynamic range to be covered, the low natural abundance of some key steroids, the selectivity of the analytical methods, the extraction protocols, and the steroid ionization remain some of the current challenges in steroid analysis. This review provides an overview of the different analytical workflows available depending on the number of steroids under study. Special emphasis is given to sample treatment, acquisition strategy, data processing, steroid identification and quantification using LC-MS approaches. This work also outlines how the availability of steroid standards, the need for complementary analytical strategies and the improvement of calibration approaches are crucial for achieving complete steroidome quantification.

Enhancing Coverage of Phosphatidylinositol Species in Canola Through Specialised Liquid Chromatography-Mass Spectrometry Buffer Conditions

Phosphatidylinositols (PIs) constitute a minor class of phospholipid with wide-spread influence throughout various cellular functions. Monitoring the distribution of these lipids can therefore provide insight as to the state of cellular processes or reveal the development of various pathologies. The speciation of these compounds is often performed either as part of a comprehensive characterisation of lipids, or specifically targeted using the same methods, however, such methods were intended to maximise coverage of lipid classes rather than provide an in-depth analysis of any single class. In the particular case of PIs, the majority of reported molecular diversity is limited to a small proportion of the already minor class, as such the cursory glance enabled by such methods is insufficient. Therefore, this work compared the suitability of both established and novel LC-MS buffers with the aim of maximising the ionisation efficiency of PIs, in an attempt to enhance coverage of the class. Through experimentation, it was determined that a 0.25 mM ammonium fluoride buffer provided up to a 6-fold increase in signal intensity, and on average a 38-fold increase in the signal-to-noise ratio. Using these new conditions, 14 PI species, and 12 PI candidates were identified within a dilute lipid extract sourced from canola seed, compared to 0 species identified using the generalised method. As a result, it is suggested that this procedure has yielded the highest number of PI species identifications for a sample of this concentration. Methods which therefore intend to characterise PI species in dilute quantities, such as those extracted from mammalian cells, are henceforth provided with the means to conduct more comprehensive characterisations.

Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics

Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

An exploratory approach for an oriented development of an untargeted hydrophilic interaction liquid chromatography-mass spectrometry platform for polar metabolites in biological matrices

The analysis of polar metabolites based on liquid chromatography-mass spectrometry (LC-MS) methods should take into consideration the complexity of interactions in LC columns to be able to cover a broad range of metabolites of key biological pathways. Therefore, in this study, different chromatographic columns were tested for polar metabolites including reversed-phase and hydrophilic interaction liquid chromatography (HILIC) columns. Based on a column screening, two new generations of zwitterionic HILIC columns were selected for further evaluation. A tree-based method optimization was applied to investigate the chromatographic factors affecting the retention mechanisms of polar metabolites with zwitterionic stationary phases. The results were evaluated based on a scoring system which was applied for more than 80 polar metabolites with a high coverage of key human metabolic pathways. The final optimized methods showed high complementarity to analyze a wide range of metabolic classes including amino acids, small peptides, sugars, amino sugars, phosphorylated sugars, organic acids, nucleobases, nucleosides, nucleotides and acylcarnitines. Optimized methods were applied to analyze different biological matrices, including human urine, plasma and liver cell extracts using an untargeted approach. The number of high-quality features (< 30% median relative standard deviation) ranged from 3,755 for urine to 5,402 for the intracellular metabolome of liver cells, showing the potential of the methods for untargeted purposes.

Rapid Simultaneous Determination of Cascade Metabolites of Acrylamide in Urine for Toxicokinetics Profiles and Short-Term Dietary Internal Exposure

The current study developed an ultrahigh-performance liquid chromatography tandem mass spectrometry method to simultaneously analyze cascade metabolites of acrylamide in urine of rats and humans, including acrylamide, glycidamide, N-acetyl-S-(2-carbamoylethyl)-l-cysteine (AAMA), N-acetyl-S-(2-carbamoylethyl)-l-cysteine-sulfoxide, N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine, and N-acetyl-S-(1-carbamoyl-2-hydroxyethyl)-l-cysteine. A tandem solid-phase extraction procedure was novelly used to purify all metabolites at once from human urine. The rapid analysis showed high sensitivity with LOD and LOQ ranges of 0.1-0.8 and 0.4-5.8 ng/mL, respectively, and achieved acceptable within-laboratory reproducibility (RSD < 12.0%) and spiking recovery (92.2%-117.3%) within 8 min per sample. Approximately 70.7 and 63.0% of ingested acrylamide were recovered during the toxicokinetics analysis from urine of male and female rats, respectively. For nonsmoking participants, the urinary levels of acrylamide and glycidamide were higher in men than women, whereas the urinary concentration of AAMA showed the opposite behavior. The current analysis provides methodological support of cascade metabolites of acrylamide for the dietary short-term internal exposure assessment of acrylamide.

Staring into the void: demystifying microbial metabolomics

Metabolites give us a window into the chemistry of microbes and are split into two subclasses: primary and secondary. Primary metabolites are required for life whereas secondary metabolites have historically been classified as those appearing after exponential growth and are not necessarily needed for survival. Many microbial species are estimated to produce hundreds of metabolites and can be affected by differing nutrients. Using various analytical techniques, metabolites can be directly detected in order to elucidate their biological significance. Currently, a single experiment can produce anywhere from megabytes to terabytes of data. This big data has motivated scientists to develop informatics tools to help target specific metabolites or sets of metabolites. Broadly, it is imperative to identify clear biological questions before embarking on a study of metabolites (metabolomics). For instance, studying the effect of a transposon insertion on phenazine biosynthesis in Pseudomonas is a very different from asking what molecules are present in a specific banana-derived strain of Pseudomonas. This review is meant to serve as a primer for a 'choose your own adventure' approach for microbiologists with limited mass spectrometry expertise, with a strong focus on liquid chromatography mass spectrometry based workflows developed or optimized within the past five years.

Chemical Discovery in the Era of Metabolomics

Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely recognized as the rate-limiting step of the experimental workflow. In spite of exponential increases in the size of metabolomic databases, which now contain experimental MS/MS spectra for over a half a million reference compounds, chemical structures still cannot be confidently assigned to many signals in a typical LC/MS dataset. The purpose of this Perspective is to consider why identification rates continue to be low in untargeted metabolomics. One rationalization is that many naturally occurring metabolites detected by LC/MS are true "novel" compounds that have yet to be incorporated into metabolomic databases. An alternative possibility, however, is that research data do not provide database matches because of informatic artifacts, chemical contaminants, and signal redundancies. Increasing evidence suggests that, for at least some sample types, many unidentifiable signals in untargeted metabolomics result from the latter rather than new compounds originating from the specimen being measured. The implications of these observations on chemical discovery in untargeted metabolomics are discussed.

MS2 and LC libraries for untargeted metabolomics: Enhancing method development and identification confidence

As part of the "omics" technologies in the life sciences, metabolomics is becoming increasingly important. In untargeted metabolomics, unambiguous metabolite identification and the inevitable coverage bias that comes with the selection of analytical conditions present major challenges. Reliable compound annotation is essential for translating metabolomics data into meaningful biological information. Here, we developed a fast and transferable method for generating in-house MS² libraries to improve metabolite identification. Using the new method we established an in-house MS² library that includes over 4,000 fragmentation spectra of 506 standard compounds for 6 different normalized collision energies (NCEs). Additionally, we generated a comprehensive liquid chromatography (LC) library by testing 57 different LC-MS conditions for 294 compounds. We used the library information to develop an untargeted metabolomics screen with maximum coverage of the metabolome that was successfully tested in a study of 360 human serum samples. The current work demonstrates a workflow for LC-MS/MS-based metabolomics, with enhanced metabolite identification confidence and the possibility to select suitable analysis conditions according to the specific research interest.

Identification of novel biomarkers of hepatocellular carcinoma by high-definition mass spectrometry: Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry and desorption electrospray ionization mass spectrometry imaging

RATIONALE

Hepatocellular carcinoma (HCC) is a highly malignant disease for which the development of prospective or prognostic biomarkers is urgently required. Although metabolomics is widely used for biomarker discovery, there are some bottlenecks regarding the comprehensiveness of detected features, reproducibility of methods, and identification of metabolites. In addition, information on localization of metabolites in tumor tissue is needed for functional analysis. Here, we developed a wide-polarity global metabolomics (G-Met) method, identified HCC biomarkers in human liver samples by high-definition mass spectrometry (HDMS), and demonstrated localization in cryosections using desorption electrospray ionization MS imaging (DESI-MSI) analysis.

METHODS

Metabolic profiling of tumor (n = 38) and nontumor (n = 72) regions in human livers of HCC was performed by an ultrahigh-performance liquid chromatography quadrupole time-of-flight MS (UHPLC/QTOFMS) instrument equipped with a mixed-mode column. The HCC biomarker candidates were extracted by multivariate analyses and identified by matching values of the collision cross section and their fragment ions on the mass spectra obtained by HDMS. Cryosections of HCC livers, which included both tumor and nontumor regions, were analyzed by DESI-MSI.

RESULTS

From the multivariate analysis, m/z 904.83 and m/z 874.79 were significantly high and low, respectively, in tumor samples and were identified as triglyceride (TG) 16:0/18:1(9Z)/20:1(11Z) and TG 16:0/18:1(9Z)/18:2(9Z,12Z) using the synthetic compounds. The TGs were clearly localized in the tumor or nontumor areas of the cryosection.

CONCLUSIONS

Novel biomarkers for HCC were identified by a comprehensive and reproducible G-Met method with HDMS using a mixed-mode column. The combination analysis of UHPLC/QTOFMS and DESI-MSI revealed that the different molecular species of TGs were associated with tumor distribution and were useful for characterizing the progression of tumor cells and discovering prospective biomarkers.

Metabolic profiling by reversed-phase/ion-exchange mass spectrometry

Metabolic profiling is commonly achieved by mass spectrometry (MS) following reversed-phase (RP) and hydrophilic interaction chromatography (HILIC) either performed independently, leading to overlapping datasets, or in a coupled configuration, requiring multiple liquid chromatography (LC) systems. To overcome these limitations, we developed a single, 20-minute chromatographic method using an in-line RP-ion-exchange (IEX) column arrangement and a single LC system. This configuration separates clinically significant polar and non-polar compounds without derivatization or ion-pairing reagents, allowing ionization in both polarities. An in-house library was created with 397 authentic standards, including acylcarnitines, amino acids, bile acids, nucleosides, organic acids, steroid hormones, and vitamins. Analysis of pooled plasma and urine samples revealed 5445 and 4111 ion features, leading to 88 and 82 confirmed metabolite identifications, respectively. Metabolites were detected at clinically relevant concentrations with good precision, and good chromatographic separation was demonstrated for clinically significant isomers including methylmalonic acid and succinic acid, as well as alloisoleucine and isoleucine/leucine. Evaluation of the samples by unsupervised principal component analysis showed excellent analytical quality.

A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non-targeted liquid chromatography with high-resolution mass spectrometry

RATIONALE

For the characterization of the chemical composition of complex matrices such as tobacco smoke, containing more than 6000 constituents, several analytical approaches have to be combined to increase compound coverage across the chemical space. Furthermore, the identification of unknown molecules requiring the implementation of additional confirmatory tools in the absence of reference standards, such as tandem mass spectrometry spectra comparisons and in silico prediction of mass spectra, is a major bottleneck.

METHODS

We applied a combination of four chromatographic/ionization techniques (reversed-phase (RP) - heated electrospray ionization (HESI) in both positive (+) and negative (-) modes, RP - atmospheric pressure chemical ionization (APCI) in positive mode, and hydrophilic interaction liquid chromatography (HILIC) - HESI positive) using a Thermo Q Exactive™ liquid chromatography/high-resolution accurate mass spectrometry (LC/HRAM-MS) platform for the analysis of 3R4F-derived smoke. Compound identification was performed by using mass spectral libraries and in silico predicted fragments from multiple integrated databases.

RESULTS

A total of 331 compounds with semi-quantitative estimates ≥100 ng per cigarette were identified, which were distributed within the known chemical space of tobacco smoke. The integration of multiple LC/HRAM-MS-based chromatographic/ionization approaches combined with complementary compound identification strategies was key for maximizing the number of amenable compounds and for strengthening the level of identification confidence. A total of 50 novel compounds were identified as being present in tobacco smoke. In the absence of reference MS2 spectra, in silico MS2 spectra prediction gave a good indication for compound class and was used as an additional confirmatory tool for our integrated non-targeted screening (NTS) approach.

CONCLUSIONS

This study presents a powerful chemical characterization approach that has been successfully applied for the identification of novel compounds in cigarette smoke. We believe that this innovative approach has general applicability and a huge potential benefit for the analysis of any complex matrices.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.

n-Butylamine for Improving the Efficiency of Untargeted Mass Spectrometry Analysis of Plasma Metabolite Composition

A comparative study of the impact of n-butylamine and traditionally used additives (ammonium hydroxide and formic acid) on the efficiency of the electrospray ionization (ESI) process for the enhancement of metabolite coverage was performed by direct injection mass spectrometry (MS) analysis in negative mode. Evaluation of obtained MS data showed that n-butylamine is one of the most effective additives for the analysis of metabolite composition in ESI in negative ion mode (ESI(-)) The limitations of the use of n-butylamine and other alkylamines in the analysis of metabolic composition and a decontamination procedure that can reduce MS device contamination after their application are discussed. The proposed procedure allows the performance of high-sensitivity analysis of low-molecular-weight compounds on the same MS device in both polarities.

Ammonium Fluoride as Suitable Additive for HILIC-Based LC-HRMS Metabolomics

Hydrophilic Interaction Liquid Chromatography (HILIC) chromatography is widely applied in metabolomics as a complementary strategy to reverse phase chromatography. Nevertheless, it still faces several issues in terms of peak shape and compounds ionization, limiting the automatic de-convolution and data semi-quantification performed through dedicated software. A way to improve the chromatographic and ionization performance of a HILIC method is to modify the electrostatic interactions of the analytes with both mobile and stationary phases. In this study, using a ZIC-HILIC chromatographic phase, we evaluated the performance of ammonium fluoride (AF) as additive salt, comparing its performance to ammonium acetate (AA). Three comparative criteria were selected: (1) identification and peak quality of 34 standards following a metabolomics-specific evaluation approach, (2) an intraday repeatability test with real samples and (3) performing two real metabolomics fingerprints with the AF method to evaluate its inter-day repeatability. The AF method showed not only higher ionization efficiency and signal-to-noise ratio but also better repeatability and robustness than the AA approach. A tips and tricks section is then added, aiming at improving method replicability for further users. In conclusion, ammonium fluoride as additive salt presents several advantages and might be considered as a step forward in the application of robust HILIC methods in metabolomics.

Essentiality of fatty acid synthase in the 2D to anchorage-independent growth transition in transforming cells

Upregulation of fatty acid synthase (FASN) is a common event in cancer, although its mechanistic and potential therapeutic roles are not completely understood. In this study, we establish a key role of FASN during transformation. FASN is required for eliciting the anaplerotic shift of the Krebs cycle observed in cancer cells. However, its main role is to consume acetyl-CoA, which unlocks isocitrate dehydrogenase (IDH)-dependent reductive carboxylation, producing the reductive power necessary to quench reactive oxygen species (ROS) originated during the switch from two-dimensional (2D) to three-dimensional (3D) growth (a necessary hallmark of cancer). Upregulation of FASN elicits the 2D-to-3D switch; however, FASN's synthetic product palmitate is dispensable for this process since cells satisfy their fatty acid requirements from the media. In vivo, genetic deletion or pharmacologic inhibition of FASN before oncogenic activation prevents tumor development and invasive growth. These results render FASN as a potential target for cancer prevention studies.

Bioavailability, metabolism, and excretion of a complex Alternaria culture extract versus altertoxin II: a comparative study in rats

Despite the frequent infection of agricultural crops by Alternaria spp., their toxic secondary metabolites and potential food contaminants lack comprehensive metabolic characterization. In this study, we investigated their bioavailability, metabolism, and excretion in vivo. A complex Alternaria culture extract (50 mg/kg body weight) containing 11 known toxins and the isolated lead toxin altertoxin II (0.7 mg/kg body weight) were administered per gavage to groups of 14 Sprague Dawley rats each. After 3 h and 24 h, plasma, urine and feces were collected to determine toxin recoveries. For reliable quantitation, an LC–MS/MS method for the simultaneous detection of 20 Alternaria toxins and metabolites was developed and optimized for either biological matrix. The obtained results demonstrated efficient excretion of alternariol (AOH) and its monomethyl ether (AME) via feces (> 89%) and urine (> 2.6%) after 24 h, while the majority of tenuazonic acid was recovered in urine (20 and 87% after 3 and 24 h, respectively). Moreover, modified forms of AOH and AME were identified in urine and fecal samples confirming both, mammalian phase-I (4-hydroxy-AOH) and phase-II (sulfates) biotransformation in vivo. Despite the comparably high doses, perylene quinones were recovered only at very low levels (altertoxin I, alterperylenol, < 0.06% in urine and plasma, < 5% in feces) or not at all (highly genotoxic, epoxide-holding altertoxin II, stemphyltoxin III). Interestingly, altertoxin I was detected in all matrices of rats receiving altertoxin II and suggests enzymatic de-epoxidation in vivo. In conclusion, the present study contributes valuable information to advance our understanding of the emerging Alternaria mycotoxins and their relevance on food safety.

Botanical metabolite ions extraction from full electrospray ionization mass spectrometry using high-dimensional penalized regression

INTRODUCTION

Mass spectrometric data analysis of complex biological mixtures can be a challenge due to its vast datasets. There is lack of data treatment pipelines to analyze chemical signals versus noise. These tasks, so far, have been up to the discretion of the analysts.

OBJECTIVES

The aim of this work is to demonstrate an analytical workflow that would enhance the confidence in metabolomics before answering biological questions by serial dilution of botanical complex mixture and high-dimensional data analysis. Furthermore, we would like to provide an alternative approach to a univariate p-value cutoff from t-test for blank subtraction procedure between negative control and biological samples.

METHODS

A serial dilution of complex mixture analysis under electrospray ionization was proposed to study firsthand chemical complexity of metabolomics. Advanced statistical models using high-dimensional penalized regression were employed to study both the concentration and ion intensity relationship and the ion-ion relationship per second of retention time sub dataset. The multivariate analysis was carried out with a tool built in-house, so called metabolite ions extraction and visualization, which was implemented in R environment.

RESULTS

A test case of the medicinal plant goldenseal (Hydrastis canandensis L.), showed an increase in metabolome coverage of features deemed as "important" by a multivariate analysis compared to features deemed as "significant" by a univariate t-test. For an illustration, the data analysis workflow suggested an unexpected putative compound, 20-hydroxyecdysone. This suggestion was confirmed with MS/MS acquisition and literature search.

CONCLUSION

The multivariate analytical workflow selects "true" metabolite ions signals and provides an alternative approach to a univariate p-value cutoff from t-test, thus enhancing the data analysis process of metabolomics.