Metabonomics and Biomarker Discovery: LC−MS Metabolic Profiling and Constant Neutral Loss Scanning Combined with Multivariate Data Analysis for Mercapturic Acid Analysis

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

Comparison of urinary mercapturic acid excretions in users of various tobacco/nicotine products

Urinary mercapturic acids (MAs) are detoxification products for electrophiles occurring in the human body. They are suitable biomarkers of exposure to directly acting electrophilic chemicals or to chemicals which generate the electrophile during its metabolism. We determined the urinary excretion of 19 MAs in habitual users of combustible cigarettes (CCs), electronic cigarettes (ECs), heated tobacco products (HTPs), oral tobacco (OT), and nicotine replacement therapy (NRT) products, and nonusers (NUs) of any tobacco/nicotine products. The 19 MAs are assumed to be physiologically formed primarily from 15 toxicants with three of them belonging to IARC Group 1 (human carcinogen), seven to Group 2A (probable human carcinogen), four to Group 2B (possible human carcinogen), and one to Group 3 (not classifiable as carcinogen). Smoking (CC) was found to be associated with significantly elevated exposure to ethylene oxide (or ethylene), 1,3-butadiene, benzene, dimethylformamide, acrolein, acrylamide, styrene, propylene oxide, acrylonitrile, crotonaldehyde, and isoprene compared with the other user groups and NU. Users of HTPs revealed slight elevation in the MAs related to acrolein, acrylamide, and crotonaldehyde compared with the other non-CC groups. Vaping (EC) was not found to be associated with any of the MAs studied. In conclusion, the determination of urinary MAs is a useful tool for assessing the exposure to toxicants (mainly potential carcinogens) in users of various tobacco/nicotine products. Our data also give cause to clarify the role of vaping (EC) in urinary excretion of DHPMA (precursor: glycidol).

Global Profiling of Urinary Mercapturic Acids Using Integrated Library-Guided Analysis

Urinary mercapturic acids (MAs) are often used as biomarkers for monitoring human exposures to occupational and environmental xenobiotics. In this study, we developed an integrated library-guided analysis workflow using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. This method includes expanded assignment criteria and a curated library of 220 MAs and addresses the shortcomings of previous untargeted approaches. We employed this workflow to profile MAs in the urine of 70 participants─40 nonsmokers and 30 smokers. We found approximately 500 MA candidates in each urine sample, and 116 MAs from 63 precursors were putatively annotated. These include 25 previously unreported MAs derived mostly from alkenals and hydroxyalkenals. Levels of 68 MAs were comparable in nonsmokers and smokers, 2 MAs were higher in nonsmokers, and 46 MAs were elevated in smokers. These included MAs of polycyclic aromatic hydrocarbons and hydroxyalkenals and those derived from toxicants present in cigarette smoke (e.g., acrolein, 1,3-butadiene, isoprene, acrylamide, benzene, and toluene). Our workflow allowed profiling of known and unreported MAs from endogenous and environmental sources, and the levels of several MAs were increased in smokers. Our method can also be expanded and applied to other exposure-wide association studies.

Performance comparison of three scaling algorithms in NMR-based metabolomics analysis

Unit variance (UV) scaling, mean centering (CTR) scaling, and Pareto (Par) scaling are three commonly used algorithms in the preprocessing of metabolomics data. Based on our NMR-based metabolomics studies, we found that the clustering identification performances of these three scaling methods were dramatically different as tested by the spectra data of 48 young athletes’ urine samples, spleen tissue (from mice), serum (from mice), and cell (from Staphylococcus aureus) samples. Our data suggested that for the extraction of clustering information, UV scaling could serve as a robust approach for NMR metabolomics data for the identification of clustering analysis even with the existence of technical errors. However, for the purpose of discriminative metabolite identification, UV scaling, CTR scaling, and Par scaling could equally extract discriminative metabolites efficiently based on the coefficient values. Based on the data presented in this study, we propose an optimal working pipeline for the selection of scaling algorithms in NMR-based metabolomics analysis, which has the potential to serve as guidance for junior researchers working in the NMR-based metabolomics research field.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats

SCOPE

High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated.

METHODS AND RESULTS

Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet.

CONCLUSION

Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Quo vadis blood protein adductomics?

Chemicals are measured regularly in air, food, the environment, and the workplace. Biomonitoring of chemicals in biological fluids is a tool to determine the individual exposure. Blood protein adducts of xenobiotics are a marker of both exposure and the biologically effective dose. Urinary metabolites and blood metabolites are short term exposure markers. Stable hemoglobin adducts are exposure markers of up to 120 days. Blood protein adducts are formed with many xenobiotics at different sites of the blood proteins. Newer methods apply the techniques developed in the field of proteomics. Larger adducted peptides with 20 amino acids are used for quantitation. Unfortunately, at present the methods do not reach the limits of detection obtained with the methods looking at single amino acid adducts or at chemically cleaved adducts. Therefore, to progress in the field new approaches are needed.

Complementary Analytical Platforms of NMR Spectroscopy and LCMS Analysis in the Metabolite Profiling of Isochrysis galbana

This study was designed to profile the metabolites of Isochrysis galbana, an indigenous and less explored microalgae species. ¹H Nuclear Magnetic Resonance (NMR) spectroscopy and Liquid Chromatography-Mass Spectrometry (LCMS) were used to establish the metabolite profiles of five different extracts of this microalga, which are hexane (Hex), ethyl acetate (EtOAc), absolute ethanol (EtOH), EtOH:water 1:1 (AqE), and 100% water (Aq). Partial least square discriminant analysis (PLS–DA) of the generated profiles revealed that EtOAc and Aq extracts contain a diverse range of metabolites as compared to the other extracts with a total of twenty-one metabolites, comprising carotenoids, polyunsaturated fatty acids, and amino acids, that were putatively identified from the NMR spectra. Meanwhile, thirty-two metabolites were successfully annotated from the LCMS/MS data, ten of which (palmitic acid, oleic acid, α-linolenic acid, arachidic acid, cholesterol, DHA, DPA, fucoxanthin, astaxanthin, and pheophytin) were similar to those present in the NMR profile. Another eleven glycerophospholipids were discovered using MS/MS-based molecular network (MN) platform. The results of this study, besides providing a better understanding of I.galbana’s chemical make-up, will be of importance in exploring this species potential as a feed ingredient in the aquaculture industry.

A Urine Metabonomics Study of Rat Bladder Cancer by Combining Gas Chromatography-Mass Spectrometry with Random Forest Algorithm

A urine metabolomics study based on gas chromatography-mass spectrometry (GC-MS) and multivariate statistical analysis was applied to distinguish rat bladder cancer. Urine samples with different stages were collected from animal models, i.e., the early stage, medium stage, and advanced stage of the bladder cancer model group and healthy group. After resolving urea with urease, the urine samples were extracted with methanol and, then, derived with N, O-Bis(trimethylsilyl) trifluoroacetamide and trimethylchlorosilane (BSTFA + TMCS, 99 : 1, v/v), before analyzed by GC-MS. Three classification models, i.e., healthy control vs. early- and middle-stage groups, healthy control vs. advanced-stage group, and early- and middle-stage groups vs. advanced-stage group, were established to analyze these experimental data by using Random Forests (RF) algorithm, respectively. The classification results showed that combining random forest algorithm with metabolites characters, the differences caused by the progress of disease could be effectively exhibited. Our results showed that glyceric acid, 2, 3-dihydroxybutanoic acid, N-(oxohexyl)-glycine, and D-turanose had higher contributions in classification of different groups. The pathway analysis results showed that these metabolites had relationships with starch and sucrose, glycine, serine, threonine, and galactose metabolism. Our study results suggested that urine metabolomics was an effective approach for disease diagnosis.

The mercapturic acid pathway

The mercapturic acid pathway is a major route for the biotransformation of xenobiotic and endobiotic electrophilic compounds and their metabolites. Mercapturic acids (N-acetyl-l-cysteine S-conjugates) are formed by the sequential action of the glutathione transferases, γ-glutamyltransferases, dipeptidases, and cysteine S-conjugate N-acetyltransferase to yield glutathione S-conjugates, l-cysteinylglycine S-conjugates, l-cysteine S-conjugates, and mercapturic acids; these metabolites constitute a "mercapturomic" profile. Aminoacylases catalyze the hydrolysis of mercapturic acids to form cysteine S-conjugates. Several renal transport systems facilitate the urinary elimination of mercapturic acids; urinary mercapturic acids may serve as biomarkers for exposure to chemicals. Although mercapturic acid formation and elimination is a detoxication reaction, l-cysteine S-conjugates may undergo bioactivation by cysteine S-conjugate β-lyase. Moreover, some l-cysteine S-conjugates, particularly l-cysteinyl-leukotrienes, exert significant pathophysiological effects. Finally, some enzymes of the mercapturic acid pathway are described as the so-called "moonlighting proteins," catalytic proteins that exert multiple biochemical or biophysical functions apart from catalysis.

Global Profiling of Toxicologically Relevant Metabolites in Urine: Case Study of Reactive Aldehydes

Among the numerous unknown metabolites representative of our exposure, focusing on toxic compounds should provide more relevant data to link exposure and health. For that purpose, we developed and applied a global method using data independent acquisition (DIA) in mass spectrometry to profile specifically electrophilic compounds originating metabolites. These compounds are most of the time toxic, due to their chemical reactivity toward nucleophilic sites present in biomacromolecules. The main line of cellular defense against these electrophilic molecules is conjugation to glutathione, then metabolization into mercapturic acid conjugates (MACs). Interestingly, MACs display a characteristic neutral loss in MS/MS experiments that makes it possible to detect all the metabolites displaying this characteristic loss, thanks to the DIA mode, and therefore to highlight the corresponding reactive metabolites. As a proof of concept, our workflow was applied to the toxicological issue of the oxidation of dietary polyunsaturated fatty acids, leading in particular to the formation of toxic alkenals, which lead to MACs upon glutathione conjugation and metabolization. By this way, dozens of MACs were detected and identified. Interestingly, multivariate statistical analyses carried out only on extracted HRMS signals of MACs yield a better characterization of the studied groups compared to results obtained from a classic untargeted metabolomics approach.

Comprehensive transcriptomics, proteomics, and metabolomics analyses of the mechanisms regulating tiller production in low-tillering wheat

Tiller development in low-tillering wheat is related to several differentially expressed genes, proteins, and metabolites, as determined by an integrated omics approach combining transcriptome analysis, iTRAQ, and HPLC-MS on multiple NILs. Tillering is an important aspect of plant morphology that affects spike number, thereby contributing to the final crop yield. However, the mechanisms inhibiting tiller production in low-tillering wheat are poorly characterized. To investigate this aspect of wheat biology, two pairs of near-isogenic lines were developed, and an integrated omics approach combining transcriptome analysis, isobaric tags for relative and absolute quantification, and high-performance liquid chromatography-mass spectrometry were used to compare the free-tillering and low-tillering caused by an allele at Qltn.sicau-2D in wheat samples. Overall, 474 genes, 166 proteins, and 28 metabolites were identified as tillering-associated differentially expressed genes, proteins, and metabolites (DEGs, DEPs, and DEMs, respectively). Functional analysis indicated that the abundance of DEGs/DEPs/DEMs was related to lignin and cellulose metabolism, cell division, cell cycle processes, and glycerophospholipid metabolism; three transcription factor families, GRAS, GRF, and REV, might be related to the decrease in tillering in low-tillering wheat. These findings contribute to improve our understanding of the mechanisms responsible for the inhibition of tiller development in low-tillering wheat cultivars.

Protein Adductomics: Analytical Developments and Applications in Human Biomonitoring

Proteins contain many sites that are subject to modification by electrophiles. Detection and characterisation of these modifications can give insights into environmental agents and endogenous processes that may be contributing factors to chronic human diseases. An untargeted approach, utilising mass spectrometry to detect modified amino acids or peptides, has been applied to blood proteins haemoglobin and albumin, focusing in particular on the N-terminal valine residue of haemoglobin and the cysteine-34 residue in albumin. Technical developments to firstly detect simultaneously multiple adducts at these sites and then subsequently to identify them are reviewed here. Recent studies in which the methods have been applied to biomonitoring human exposure to environmental toxicants are described. With advances in sensitivity, high-throughput handling of samples and robust quality control, these methods have considerable potential for identifying causes of human chronic disease and of identifying individuals at risk.

A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops

In the last decade, the consumption trend of organic food has increased dramatically worldwide. However, the lack of reliable chemical markers to discriminate between organic and conventional products makes this market susceptible to food fraud in products labeled as "organic". Metabolomic fingerprinting approach has been demonstrated as the best option for a full characterization of metabolome occurring in plants, since their pattern may reflect the impact of both endogenous and exogenous factors. In the present study, advanced technologies based on high performance liquid chromatography-high-resolution accurate mass spectrometry (HPLC-HRAMS) has been used for marker search in organic and conventional tomatoes grown in greenhouse under controlled agronomic conditions. The screening of unknown compounds comprised the retrospective analysis of all tomato samples throughout the studied period and data processing using databases (mzCloud, ChemSpider and PubChem). In addition, stable nitrogen isotope analysis (δ¹⁵N) was assessed as a possible indicator to support discrimination between both production systems using crop/fertilizer correlations. Pesticide residue analyses were also applied as a well-established way to evaluate the organic production. Finally, the evaluation by combined chemometric analysis of high-resolution accurate mass spectrometry (HRAMS) and δ¹⁵N data provided a robust classification model in accordance with the agricultural practices. Principal component analysis (PCA) showed a sample clustering according to farming systems and significant differences in the sample profile was observed for six bioactive components (L-tyrosyl-L-isoleucyl-L-threonyl-L-threonine, trilobatin, phloridzin, tomatine, phloretin and echinenone).

Biomarkers of exposure to new and emerging tobacco delivery products

Accurate and reliable measurements of exposure to tobacco products are essential for identifying and confirming patterns of tobacco product use and for assessing their potential biological effects in both human populations and experimental systems. Due to the introduction of new tobacco-derived products and the development of novel ways to modify and use conventional tobacco products, precise and specific assessments of exposure to tobacco are now more important than ever. Biomarkers that were developed and validated to measure exposure to cigarettes are being evaluated to assess their use for measuring exposure to these new products. Here, we review current methods for measuring exposure to new and emerging tobacco products, such as electronic cigarettes, little cigars, water pipes, and cigarillos. Rigorously validated biomarkers specific to these new products have not yet been identified. Here, we discuss the strengths and limitations of current approaches, including whether they provide reliable exposure estimates for new and emerging products. We provide specific guidance for choosing practical and economical biomarkers for different study designs and experimental conditions. Our goal is to help both new and experienced investigators measure exposure to tobacco products accurately and avoid common experimental errors. With the identification of the capacity gaps in biomarker research on new and emerging tobacco products, we hope to provide researchers, policymakers, and funding agencies with a clear action plan for conducting and promoting research on the patterns of use and health effects of these products.

Metabonomics screening of serum identifies pyroglutamate as a diagnostic biomarker for nonalcoholic steatohepatitis

OBJECTIVE

A key step in managing non-alcoholic fatty liver disease (NAFLD) is to differentiate nonalcoholic steatohepatitis (NASH) from simple steatosis (SS).

METHOD

Serum samples were collected from three groups: NASH patients (N=21), SS patients (N=38) and healthy controls (N=31). High performance liquid chromatography-mass spectrometry (HPLC-MS) was used to analyse the metabolic profile of the serum samples. The acquired data were processed by multivariate principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) to identify novel metabolites. The potential biomarkers were quantitatively determined and their diagnostic power was further validated.

RESULTS

A total of 56 metabolites were capable of distinguishing NASH from SS samples based on the OPLS-DA model. Pyroglutamate was found to be the most promising factor in distinguishing the NASH from SS groups. With an optimal cut-off value of 4.82mmol/L, the sensitivity and specificity of the diagnosis of NASH were 72% and 85%, respectively. The area under the receiver operating characteristic (AUROC) of the pyroglutamate levels of NASH versus SS patients was more than those of tumor necrosis factor-α, adiponectin and interleukin-8.

CONCLUSION

These data suggest that pyroglutamate may be a new and useful biomarker for the diagnosis of NASH.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017.

Metabolomics Toward Biomarker Discovery

Metabolomics has been used as practical tool in the discovery of novel biomarkers in a broad area in the clinic. The analytical platforms including nuclear magnetic resonance (NMR) and mass spectrometry (MS) can cover thousands of metabolites. With the help of multivariate data analysis, many potential biomarkers can be defined in the studies. Since metabolites stand at the end point of metabolism, it remains difficult to find novel biomarkers with good diagnostic or prognostic performance. In this chapter, we will introduce a general protocol for biomarker discovery within the scope of metabolomics using MS.

Metabolism and bioactivation of the tricyclic antidepressant amitriptyline in human liver microsomes and human urine

Aim: Amitriptyline is a widely used tricyclic antidepressant, but the metabolic studies were conducted almost 20 years ago using high-performance liquid chromatography coupled with ultraviolet detector or radiolabeled methods. Results: First, multiple ion monitoring (MIM)- enhanced product ion (EPI) scan was used to obtain the diagnostic ions or neutral losses in human liver microsome incubations with amitriptyline. Subsequently, predicted multiple reaction monitoring (MRM)-EPI scan was used to identify the metabolites in human urine with the diagnostic ions or neutral losses. Finally, product ion filtering and neutral loss filtering were used as the data mining tools to screen metabolites. Consequently, a total of 28 metabolites were identified in human urine after an oral administration using LC–MS/MS. Conclusion: An integrated workflow using LC–MS/MS was developed to comprehensively profile the metabolites of amitriptyline in human urine, in which five N-acetyl-l-cysteine conjugates were characterized as tentative biomarkers for idiosyncratic toxicity.

Growth and metabolism of Beauveria bassiana spores and mycelia

Background

Fungi are ubiquitous in nature and have evolved over time to colonize a wide range of ecosystems including pest control. To date, most research has focused on the hypocrealean genera Beauveria bassiana, which is a typical filamentous fungus with a high potential for insect control. The morphology and components of fungi are important during the spores germination and outgrow to mycelia. However, to the best of our knowledge, there is no report on the morphology and components of B. bassiana spores and mycelia. In the work, the growth and metabolism of Beauveria bassiana spores and mycelia were studied. High performance liquid chromatography-mass spectrometry (HPLC-MS) was employed to study the metabolism of B. bassiana spores and mycelia. Principal component analysis (PCA) based on HPLC-MS was conducted to study the different components of the spores and mycelia of the fungus. Metabolic network was established based on HPLC-MS and KEGG database.

Results

Through Gompertz model based on macroscopic and microscopic techniques, spore elongation length was found to increase exponentially until approximately 23.1 h after cultivation, and then growth became linear. In the metabolic network, the decrease of glyoxylate, pyruvate, fumarate, alanine, succinate, oxaloacetate, dihydrothymine, ribulose, acetylcarnitine, fructose-1, 6-bisphosphate, mycosporin glutamicol, and the increase of betaine, carnitine, ergothioneine, sphingosine, dimethyl guanosine, glycerophospholipids, and in spores indicated that the change of the metabolin can keep spores in inactive conditions, protect spores against harmful effects and survive longer.

Conclusions

Analysis of the metabolic pathway in which these components participate can reveal the metabolic difference between spores and mycelia, which provide the tools for understand and control the process of of spores germination and outgrow to mycelia.

Growth and metabolism of Beauveria bassiana spores and mycelia

BACKGROUND

Fungi are ubiquitous in nature and have evolved over time to colonize a wide range of ecosystems including pest control. To date, most research has focused on the hypocrealean genera Beauveria bassiana, which is a typical filamentous fungus with a high potential for insect control. The morphology and components of fungi are important during the spores germination and outgrow to mycelia. However, to the best of our knowledge, there is no report on the morphology and components of B. bassiana spores and mycelia. In the work, the growth and metabolism of Beauveria bassiana spores and mycelia were studied. High performance liquid chromatography-mass spectrometry (HPLC-MS) was employed to study the metabolism of B. bassiana spores and mycelia. Principal component analysis (PCA) based on HPLC-MS was conducted to study the different components of the spores and mycelia of the fungus. Metabolic network was established based on HPLC-MS and KEGG database.

RESULTS

Through Gompertz model based on macroscopic and microscopic techniques, spore elongation length was found to increase exponentially until approximately 23.1 h after cultivation, and then growth became linear. In the metabolic network, the decrease of glyoxylate, pyruvate, fumarate, alanine, succinate, oxaloacetate, dihydrothymine, ribulose, acetylcarnitine, fructose-1, 6-bisphosphate, mycosporin glutamicol, and the increase of betaine, carnitine, ergothioneine, sphingosine, dimethyl guanosine, glycerophospholipids, and in spores indicated that the change of the metabolin can keep spores in inactive conditions, protect spores against harmful effects and survive longer.

CONCLUSIONS

Analysis of the metabolic pathway in which these components participate can reveal the metabolic difference between spores and mycelia, which provide the tools for understand and control the process of of spores germination and outgrow to mycelia.

The application of targeted mass spectrometry-based strategies to the detection and localization of post-translational modifications

This review describes some of the more interesting and imaginative ways in which mass spectrometry has been utilized to study a number of important post-translational modifications over the past two decades; from circa 1990 to 2013. A diverse range of modifications is covered, including citrullination, sulfation, hydroxylation and sumoylation. A summary of the biological role of each modification described, along with some brief mechanistic detail, is also included. Emphasis has been placed on strategies specifically aimed at detecting target modifications, as opposed to more serendipitous modification discovery approaches, which rely upon straightforward product ion scanning methods. The authors have intentionally excluded from this review both phosphorylation and glycosylation since these major modifications have been extensively reviewed elsewhere.

Human metabolic responses to chronic environmental polycyclic aromatic hydrocarbon exposure by a metabolomic approach

The toxicities of polycyclic aromatic hydrocarbons (PAHs) have been extensively explored due to their carcinogenic and mutagenic potency; however, little is known about the metabolic responses to chronic environmental PAH exposure among the general population. In the present study, 566 healthy volunteers were dichotomized into exposed and control groups to investigate PAH-induced perturbations in the metabolic profiles. Nine urine PAH metabolites were measured by a sensitive LC-MS/MS method to comprehensively evaluate the PAH exposure level of each individual, and the metabolic profiles were characterized via a LC-MS-based metabolomic approach. PAH exposure was correlated to its metabolic outcomes by linear and logistic regression analyses. Metabolites related to amino acid, purine, lipid, and glucuronic acid metabolism were significantly changed in the exposed group. 1-Hydroxyphenanthrene and dodecadienylcarnitine have potential as sensitive and reliable biomarkers for PAH exposure and its metabolic outcomes, respectively, in the general population. These findings generally support the hypothesis that environmental PAH exposure causes oxidative stress-related effects in humans. The current study provides new insight into the early molecular events induced by PAH exposure in the actual environment.

Effect of pre- and postnatal growth and post-weaning activity on glucose metabolism in the offspring

Maternal caloric restriction during late gestation reduces birth weight, but whether long-term adverse metabolic outcomes of intra-uterine growth retardation (IUGR) are dependent on either accelerated postnatal growth or exposure to an obesogenic environment after weaning is not established. We induced IUGR in twin-pregnant sheep using a 40% maternal caloric restriction commencing from 110 days of gestation until term (∼147 days), compared with mothers fed to 100% of requirements. Offspring were reared either as singletons to accelerate postnatal growth or as twins to achieve standard growth. To promote an adverse phenotype in young adulthood, after weaning, offspring were reared under a low-activity obesogenic environment with the exception of a subgroup of IUGR offspring, reared as twins, maintained in a standard activity environment. We assessed glucose tolerance together with leptin and cortisol responses to feeding in young adulthood when the hypothalamus was sampled for assessment of genes regulating appetite control, energy and endocrine sensitivity. Caloric restriction reduced maternal plasma glucose, raised non-esterified fatty acids, and changed the metabolomic profile, but had no effect on insulin, leptin, or cortisol. IUGR offspring whose postnatal growth was enhanced and were obese showed insulin and leptin resistance plus raised cortisol. This was accompanied by increased hypothalamic gene expression for energy and glucocorticoid sensitivity. These long-term adaptations were reduced but not normalized in IUGR offspring whose postnatal growth was not accelerated and remained lean in a standard post-weaning environment. IUGR results in an adverse metabolic phenotype, especially when postnatal growth is enhanced and offspring progress to juvenile-onset obesity.

Toxicity of Glutathione-Binding Metals: A Review of Targets and Mechanisms

Mercury, cadmium, arsenic and lead are among priority metals for toxicological studies due to the frequent human exposure and to the significant burden of disease following acute and chronic intoxication. Among their common characteristics is chemical affinity to proteins and non-protein thiols and their ability to generate cellular oxidative stress by the best-known Fenton mechanism. Their health effects are however diverse: kidney and liver damage, cancer at specific sites, irreversible neurological damages with metal-specific features. Mechanisms for the induction of oxidative stress by interaction with the cell thiolome will be presented, based on literature evidence and of experimental findings.

Validation of a two-step quality control approach for a large-scale human urine metabolomic study conducted in seven experimental batches with LC/QTOF-MS

After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets.

Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC–MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.

Basics of mass spectrometry based metabolomics

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

Identifying early urinary metabolic changes with long-term environmental exposure to cadmium by mass-spectrometry-based metabolomics

Cadmium (Cd) is a common environmental pollutant, and urinary Cd (UCd) is generally used as a marker of exposure; however, our understanding on the related urinary metabolic changes caused by Cd exposure is still not clear. In this study, we applied a mass-spectrometry-based metabolomic approach to assess the urinary metabolic changes in human with long-term environmental Cd exposure, aimed to identify early biomarkers to assess Cd nephrotoxicity. Urine samples from 94 female never smokers aged 44-70 with UCd in the range of 0.20-68.67 μg/L were analyzed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-ToF-MS) and gas chromatography-mass spectrometry (GC-MS). It was found that metabolites related to amino acid metabolism (L-glutamine, L-cystine, L-tyrosine, N-methyl-L-histidine, L-histidinol, taurine, phenylacetylglutamine, hippurate, and pyroglutamic acid), galactose metabolism (D-galactose and myo-inositol), purine metabolism (xanthine, urea, and deoxyadenosine monophosphate), creatine pathway (creatine and creatinine), and steroid hormone biosynthesis (17-α-hydroxyprogesterone, tetrahydrocortisone, estrone, and corticosterone) were significantly higher among those with a UCd level higher than 5 μg/L. Moreover, we noticed that the level of N-methyl-L-histidine had already started to elevate among individuals with a UCd concentration of ≥2 μg/L. The overall findings illustrate that metabolomics offer a useful approach for revealing metabolic changes as a result of Cd exposure.

Ion fusion of high-resolution LC-MS-based metabolomics data to discover more reliable biomarkers

A systematic approach for the fusion of associated ions from a common molecule was developed to generate "one feature for one peak" metabolomics data. This approach guarantees that each molecule is equally selected as a potential biomarker and may largely enhance the chance to obtain reliable findings without employing redundant ion information. The ion fusion is based on low mass variation in contrast to the theoretical calculation measured by a high-resolution mass spectrometer, such as LTQ orbitrap, and a high correlation of ion pairs from the same molecule. The mass characteristics of isotopic distribution, neutral loss, and adduct ions were simultaneously applied to inspect each extracted ion in the range of a predefined retention time window. The correlation coefficient was computed with the corresponding intensities of each ion pair among all experimental samples. Serum metabolomics data for the investigation of hepatocellular carcinoma (HCC) and healthy controls were utilized as an example to demonstrate this strategy. In total, 609 and 1084 ion pairs were respectively found meeting one or more criteria for fusion, and therefore fused to 106 and 169 metabolite features of the datasets in the positive and negative modes, respectively. The important metabolite features were separately discovered and compared to distinguish the HCC from the healthy controls using the two datasets with and without ion fusion. The results show that the developed method can be an effective tool to process high-resolution mass spectrometry data in "omics" studies.

A metabolomics investigation into the effects of HIV protease inhibitors on HPV16 E6 expressing cervical carcinoma cells

Recently, it has been reported that anti-viral drugs, such as indinavir and lopinavir (originally targeted for HIV), also inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells. In order to understand more about the mode-of-action(s) of these drugs the metabolome of HPV16 E6 expressing cervical carcinoma cell lines was investigated using mass spectrometry (MS)-based metabolic profiling. The metabolite profiling of C33A parent and E6-transfected cells exposed to these two anti-viral drugs was performed by ultra performance liquid chromatography (UPLC)-MS and gas chromatography (GC)-time of flight (TOF)-MS. Using a combination of univariate and multivariate analyses, these metabolic profiles were investigated for analytical and biological reproducibility and to discover key metabolite differences elicited during anti-viral drug challenge. This approach revealed both distinct and common effects of these two drugs on the metabolome of two different cell lines. Finally, intracellular drug levels were quantified, which suggested in the case of lopinavir that increased activity of membrane transporters may contribute to the drug sensitivity of HPV infected cells.

Isotope labelling – paired homologous double neutral loss scan-mass spectrometry for profiling of metabolites with a carboxyl group

The development of a method for non-targeted screening of metabolites with a carboxyl group by high performance liquid chromatography-mass spectrometry with paired homologous double neutral loss scan mode afterin vitroisotope labelling was reported.

Assessment of peeling of Astragalus roots using 1H NMR- and UPLC-MS-based metabolite profiling

A metabolomic analysis was performed to examine the postharvest processing of Astragalus membranaceus roots with a focus on the peeling procedure using (1)H NMR and UPLC-MS analyses. Principal component analysis (PCA) score plots from the (1)H NMR and UPLC-MS data showed clear separation between peeled and unpeeled Astragalus roots. Peeled roots exhibited significant losses of several primary metabolites, including acetate, alanine, arginine, caprate, fumarate, glutamate, histidine, N-acetylaspartate, malate, proline, sucrose, trigonelline, and valine. In contrast, the peeled roots contained higher levels of asparagine, aspartate, and xylose, which are xylem-related compounds, and formate, which is produced in response to wound stress incurred during postharvest processing. In addition, the levels of isoflavonoids and astragalosides were significantly reduced in peeled Astragalus root. These results demonstrate that metabolite profiling based on a combination of (1)H NMR and UPLC-MS analyses can be used to evaluate peeling procedures used in the postharvest processing of herbal medicines.

A novel approach to transforming a non-targeted metabolic profiling method to a pseudo-targeted method using the retention time locking gas chromatography/mass spectrometry-selected ions monitoring

Non-targeted metabolic profiling is the most widely used method for metabolomics. In this paper, a novel approach was established to transform a non-targeted metabolic profiling method to a pseudo-targeted method using the retention time locking gas chromatography/mass spectrometry-selected ion monitoring (RTL-GC/MS-SIM). To achieve this transformation, an algorithm based on the automated mass spectral deconvolution and identification system (AMDIS), GC/MS raw data and a bi-Gaussian chromatographic peak model was developed. The established GC/MS-SIM method was compared with GC/MS-full scan (the total ion current and extracted ion current, TIC and EIC) methods, it was found that for a typical tobacco leaf extract, 93% components had their relative standard deviations (RSDs) of relative peak areas less than 20% by the SIM method, while 88% by the EIC method and 81% by the TIC method. 47.3% components had their linear correlation coefficient higher than 0.99, compared with 5.0% by the EIC and 6.2% by TIC methods. Multivariate analysis showed the pooled quality control samples clustered more tightly using the developed method than using GC/MS-full scan methods, indicating a better data quality. With the analysis of the variance of the tobacco samples from three different planting regions, 167 differential components (p<0.05) were screened out using the RTL-GC/MS-SIM method, but 151 and 131 by the EIC and TIC methods, respectively. The results show that the developed method not only has a higher sensitivity, better linearity and data quality, but also does not need complicated peak alignment among different samples. It is especially suitable for the screening of differential components in the metabolic profiling investigation.

Metabolomics techniques in nanotoxicology studies

The rapid growth in the development of nanoparticles for uses in a variety of applications including targeted drug delivery, cancer therapy, imaging, and as biological sensors has led to questions about potential toxicity of such particles to humans. High-throughput methods are necessary to evaluate the potential toxicity of nanoparticles. The omics technologies are particularly well suited to evaluate toxicity in both in vitro and in vivo systems. Metabolomics, specifically, can rapidly screen for biomarkers related to predefined pathways or processes in biofluids and tissues. Specifically, oxidative stress has been implicated as a potential mechanism of toxicity in nanoparticles and is generally difficult to measure by conventional methods. Furthermore, metabolomics can provide mechanistic insight into nanotoxicity. This chapter focuses on the application of both LC/MS and NMR-based metabolomics approaches to study the potential toxicity of nanoparticles.