Evaluation of Matrix Effects in Metabolite Profiling Based on Capillary Liquid Chromatography Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Profiling of 1-aminocyclopropane-1-carboxylic acid and selected phytohormones in Arabidopsis using liquid chromatography-tandem mass spectrometry

BACKGROUND

Gaseous phytohormone ethylene levels are directly influenced by the production of its immediate non-volatile precursor 1-aminocyclopropane-1-carboxylic acid (ACC). Owing to the strongly acidic character of the ACC molecule, its quantification has been difficult to perform. Here, we present a simple and straightforward validated method for accurate quantification of not only ACC levels, but also major members of other important phytohormonal classes - auxins, cytokinins, jasmonic acid, abscisic acid and salicylic acid from the same biological sample.

RESULTS

The presented technique facilitates the analysis of 15 compounds by liquid chromatography coupled with tandem mass spectrometry. It was optimized and validated for 10 mg of fresh weight plant material. The extraction procedure is composed of a minimal amount of necessary steps. Accuracy and precision were the basis for evaluating the method, together with process efficiency, recovery and matrix effects as validation parameters. The examined compounds comprise important groups of phytohormones, their active forms and some of their metabolites, including six cytokinins, four auxins, two jasmonates, abscisic acid, salicylic acid and 1-aminocyclopropane-1-carboxylic acid. The resulting method was used to examine their contents in selected Arabidopsis thaliana mutant lines.

CONCLUSION

This profiling method enables a very straightforward approach for indirect ethylene study and explores how it interacts, based on content levels, with other phytohormonal groups in plants.

Determination of Phosphoethanolamine in Urine with HPLC-ICPMS/MS Using 1,2-Hexanediol as a Chromatographic Eluent

The importance of element-selective detection with inductively coupled plasma mass spectrometry (ICPMS) has been significantly increased in recent years following the introduction of tandem ICPMS (ICPMS/MS), which unlocked access to nonmetal speciation analysis. However, nonmetals are ubiquitous, and the feasibility of nonmetal speciation analysis in matrices with complex metabolomes is yet to be demonstrated. Herein, we report the first phosphorous speciation study by HPLC-ICPMS/MS in a human sample, namely, urine, involving the determination of the natural metabolite and biomarker phosphoethanolamine. A simple one-step derivatization procedure was employed to enable the separation of the target compound from the hydrophilic phosphorous metabolome in urine. The challenge of eluting the hydrophobic derivative under ICPMS-compatible chromatographic conditions was addressed by employing hexanediol, a novel chromatographic eluent recently described in our previous work but has not yet been exploited in a real-world application. The developed method features fast chromatographic separation (<5 min), no need for an isotopically labeled internal standard, and an instrumental LOD of 0.5 μg P L^-1. The method was evaluated for recovery (90-110%), repeatability (RSD ±5%), and linearity (r² = 0.9998). The method accuracy was thoroughly examined by comparing with an independently developed method based on HPLC-ESIMS/MS without derivatization, where agreement was found within ±5-20%. An application is presented to gain first insight into the variability in the human excretion of phosphoethanolamine, which is key for the interpretation of its levels as a biomarker, by repeated urine collection from a group of volunteers over 4 weeks.

The effect of root hairs on exudate composition: a comparative non-targeted metabolomics approach

Root exudation is a major pathway of organic carbon input into soils. It affects soil physical properties, element solubility as well as speciation, and impacts the microbial community in the rhizosphere. Root exudates contain a large number of primary and secondary plant metabolites, and the amount and composition are highly variable depending on plant species and developmental stage. Detailed information about exudate composition will allow for a better understanding of exudate-driven rhizosphere processes and their feedback loops. Although non-targeted metabolomics by high-resolution mass spectrometry is an established tool to characterize root exudate composition, the extent and depth of the information obtained depends strongly on the analytical approach applied. Here, two genotypes of Zea mays L., differing in root hair development, were used to compare six mass spectrometric approaches for the analysis of root exudates. Reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography combined with time-of-flight mass spectrometry (LC-TOF-MS), as well as direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS), were applied with positive and negative ionization mode. By using the same statistical workflow, the six approaches resulted in different numbers of detected molecular features, ranging from 176 to 889, with a fraction of 48 to 69% of significant features (fold change between the two genotypes of > 2 and p-value < 0.05). All approaches revealed the same trend between genotypes, namely up-regulation of most metabolites in the root hair defective mutant (rth3). These results were in agreement with the higher total carbon and nitrogen exudation rate of the rth3-mutant as compared to the corresponding wild-type maize (WT). However, only a small fraction of features were commonly found across the different analytical approaches (20-79 features, 13-31% of the rth3-mutant up-regulated molecular formulas), highlighting the need for different mass spectrometric approaches to obtain a more comprehensive view into the composition of root exudates. In summary, 111 rth3-mutant up-regulated compounds (92 different molecular formulas) were detected with at least two different analytical approaches, while no WT up-regulated compound was found by both, LC-TOF-MS and DI-FT-ICR-MS. Zea mays L. exudate features obtained with multiple analytical approaches in our study were matched against the metabolome database of Zea mays L. (KEGG) and revealed 49 putative metabolites based on their molecular formula.

To Analyze the Influencing Factors of Senile Coronary Heart Disease Patients Complicated with Frailty Syndrome

To analyze the influencing factors of senile coronary heart disease patients complicated with frailty syndrome. A total of 80 elderly patients with coronary heart disease admitted to our hospital from March 2020 to March 2021 were selected as the research subjects. The Fried Frailty Symptom Scale was used to evaluate whether the 80 patients were complicated with frailty syndrome. According to the evaluation results, the patients were divided into a nonfrailty syndrome group (52 cases in total) and frailty syndrome group (28 cases in total). Clinical data of two groups of patients were collected, and multivariate logistic regression was used to analyze the influencing factors of senile coronary heart disease patients complicated with frailty syndrome. Among 80 patients, the incidence of frailty syndrome was 35.00% (28/80), including 18 cases in early frailty and 10 cases in frailty stage. Univariate analysis showed that age, body mass (BMI), diabetes mellitus, congestive heart failure, chronic renal insufficiency, chronic obstructive pulmonary disease (COPD), tumor, high uric acid hematic disease, arrhythmia, interleukin-6 (IL-6), c-reactive protein (CRP), fibrinogen (FIB), brain natriuretic peptide (BNP), uric acid (UA), serum creatinine (Scr), serum protein (ALB), white blood cell count (WBC), and neutrophil count were the possible risk factors for senile coronary heart disease complicated with frailty syndrome (P < 0.05). Multivariate logistic regression analysis showed that combined COPD, combined tumor, IL-6, BNP, UA, SCR, ALB, and neutrophil count were independent risk factors for senile CHD complicated with frailty syndrome (P < 0.05). Combined with COPD, combined with tumor, IL-6, BNP, UA, SCR, ALB, and neutron cell count are the influencing factors for senile coronary heart disease patients complicated with frailty syndrome. These factors can be used as the basis for the diagnosis of frailty syndrome and guide the clinical development of targeted diagnosis and treatment plan.

Parallel and Comparative Non-Targeted Metabolomic Speciation Analysis of Metalloids and Their Non-Metal Analogues by HPLC-ICPMS/MS in Mushrooms

With the introduction of tandem mass spectrometry to inductively coupled plasma mass spectrometry (ICPMS/MS), the potential for non-targeted elemental metabolomic analysis has been expanded to many non-metals of pivotal biological importance. Arsenic and selenium are trace elements that share chemical similarity with the non-metals phosphorus and sulfur, respectively, and this similarity can be exploited to gain more insight into the incompletely understood biological significance of these metalloids and the evolution of their biochemical pathways. As a proof of concept, we show the applicability of HPLC-ICPMS/MS for non-targeted and parallel speciation analysis of arsenic, selenium, phosphorus, and sulfur in mushrooms-metabolically diverse organisms. Incredibly contrasting levels of diversity were found in the metabolomic profiles of the four investigated elements among the various species along with sharp discrepancies among related elements (e.g. phosphorous vs. arsenic) in certain mushroom species. The present work shows that ICPMS/MS offers a new dimension in non-targeted metabolomic analysis and enables a unique comparative approach in investigating and tracking the biochemistry of related elements in moderately complex organisms.

A classification of liquid chromatography mass spectrometry techniques for evaluation of chemical composition and quality control of traditional medicines

Natural products (NPs) and traditional medicines (TMs) are used for treatment of various diseases and also to develop new drugs. However, identification of drug leads within the immense biodiversity of living organisms is a challenging task that requires considerable time, labor, and computational resources as well as the application of modern analytical instruments. LC-MS platforms are widely used for both drug discovery and quality control of TMs and food supplements. Moreover, a large dataset generated during LC-MS analysis contains valuable information that could be extracted and handled by means of various data mining and statistical tools. Novel sophisticated LC-MS based approaches are being introduced every year. Therefore, this review is prepared for the scientists specialized in pharmacognosy and analytical chemistry of NPs as well as working in related areas, in order to navigate them in the world of diverse LC-MS based techniques and strategies currently employed for NP discovery and dereplication, quality control, pattern recognition and sample comparison, and also in targeted and untargeted metabolomic studies. The suggested classification system includes the following LC-MS based procedures: elemental composition determination, isotopic fine structure analysis, mass defect filtering, de novo identification, clustering of the compounds in Molecular Networking (MN), diagnostic fragment ion (or neutral loss) filtering, manual dereplication using MS/MS data, database-assisted peak annotation, annotation of spectral trees, MS fingerprinting, feature extraction, bucketing of LC-MS data, peak profiling, predicted metabolite screening, targeted quantification of biomarkers, quantitative analysis of multi-component system, construction of chemical fingerprints, multi-targeted and untargeted metabolite profiling.

Rapid simultaneous determination of 160 drugs in urine and blood of livestock and poultry by ultra-high-performance liquid chromatography-tandem mass spectrometry

In order to address the specific question of food safety in livestock and poultry, it is imperative to monitor veterinary drugs at every moment in the process of livestock and poultry breeding. Thus, multi-residue analysis of a wide variety of drugs using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) has become a tool of critical significance, especially for veterinary drug monitoring programs. A total of 160 compounds, belonging to 17 different families of veterinary drugs, were investigated in the urine and blood of livestock and poultry. Drug samples were extracted using a slightly acidic acetonitrile solution. The QuEChERS (quick, easy, cheap, effective, rugged, and safe) preparation method, combined with dispersive solid phase extraction (d-SPE) was compared with the approach of solid phase extraction (SPE). In the end, the QuEChERS extraction procedure was selected to reduce matrix effects and efficiently extract target veterinary drugs, and d-SPE was applied as a cleanup step. Electrospray ionization coupled with positive dynamic multiple reaction monitoring (dMRM) was utilized for the analysis of 160 different drugs in a single chromatographic run of 24 min. The efficiency of this method was evaluated using 7 matrices (pig blood, cattle blood, sheep blood, chicken blood, pig urine, cattle urine, and sheep urine). Good linearity was obtained for the analytes in a concentration range of 1-100 ng/mL, with correlation coefficients higher than 0.990. Most of the 160 drugs studied gave estimated limits of detection (LOQs) of 1 ng/mL, with some LOQs reaching as much as 5 ng/mL. The mean recoveries at four spike-in levels of 1, 5, 10, and 50 ng/mL, ranged from 60% to 120%. The intra-day precision measurements had coefficients of variation (n = 6) <15%, and the inter-day precision measurements were below 25%. Our method was applied in real samples and proved to be adequate for routine analysis. The proposed method proved to be simple, rapid and reliable for monitoring 160 drugs in the urine and blood of livestock and poultry, and can also be used for food safety monitoring.

Analysis of Chemically Labile Glycation Adducts in Seed Proteins: Case Study of Methylglyoxal-Derived Hydroimidazolone 1 (MG-H1)

Seeds represent the major source of food protein, impacting on both human nutrition and animal feeding. Therefore, seed quality needs to be appropriately addressed in the context of viability and food safety. Indeed, long-term and inappropriate storage of seeds might result in enhancement of protein glycation, which might affect their quality and longevity. Glycation of seed proteins can be probed by exhaustive acid hydrolysis and quantification of the glycation adduct N^ɛ-(carboxymethyl)lysine (CML) by liquid chromatography-mass spectrometry (LC-MS). This approach, however, does not allow analysis of thermally and chemically labile glycation adducts, like glyoxal-, methylglyoxal- and 3-deoxyglucosone-derived hydroimidazolones. Although enzymatic hydrolysis might be a good solution in this context, it requires aqueous conditions, which cannot ensure reconstitution of seed protein isolates. Because of this, the complete profiles of seed advanced glycation end products (AGEs) are not characterized so far. Therefore, here we propose the approach, giving access to quantitative solubilization of seed proteins in presence of sodium dodecyl sulfate (SDS) and their quantitative enzymatic hydrolysis prior to removal of SDS by reversed phase solid phase extraction (RP-SPE). Using methylglyoxal-derived hydroimidazolone 1 (MG-H1) as a case example, we demonstrate the applicability of this method for reliable and sensitive LC-MS-based quantification of chemically labile AGEs and its compatibility with bioassays.

Atmo-ecometabolomics: a novel atmospheric particle chemical characterization methodology for ecological research

Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biological-activity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles. We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmo-ecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry.

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Terroir refers to the combination of environmental factors that affect the characteristics of crops such as grapevine (Vitis vinifera) according to particular habitats and management practices. This article shows how certain terroir signatures can be detected in the berry metabolome and transcriptome of the grapevine cultivar Corvina using multivariate statistical analysis. The method first requires an appropriate sampling plan. In this case study, a specific clone of the Corvina cultivar was selected to minimize genetic differences, and samples were collected from seven vineyards representing three different macro-zones during three different growing seasons. An untargeted LC-MS metabolomics approach is recommended due to its high sensitivity, accompanied by efficient data processing using MZmine software and a metabolite identification strategy based on fragmentation tree analysis. Comprehensive transcriptome analysis can be achieved using microarrays containing probes covering ~99% of all predicted grapevine genes, allowing the simultaneous analysis of all differentially expressed genes in the context of different terroirs. Finally, multivariate data analysis based on projection methods can be used to overcome the strong vintage-specific effect, allowing the metabolomics and transcriptomics data to be integrated and analyzed in detail to identify informative correlations.

A novel stable isotope labelling assisted workflow for improved untargeted LC-HRMS based metabolomics research

Many untargeted LC-ESI-HRMS based metabolomics studies are still hampered by the large proportion of non-biological sample derived signals included in the generated raw data. Here, a novel, powerful stable isotope labelling (SIL)-based metabolomics workflow is presented, which facilitates global metabolome extraction, improved metabolite annotation and metabolome wide internal standardisation (IS). The general concept is exemplified with two different cultivation variants, (1) co-cultivation of the plant pathogenic fungi Fusarium graminearum on non-labelled and highly ¹³C enriched culture medium and (2) experimental cultivation under native conditions and use of globally U-¹³C labelled biological reference samples as exemplified with maize and wheat. Subsequent to LC-HRMS analysis of mixtures of labelled and non-labelled samples, two-dimensional data filtering of SIL specific isotopic patterns is performed to better extract truly biological derived signals together with the corresponding number of carbon atoms of each metabolite ion. Finally, feature pairs are convoluted to feature groups each representing a single metabolite. Moreover, the correction of unequal matrix effects in different sample types and the improvement of relative metabolite quantification with metabolome wide IS are demonstrated for the F. graminearum experiment. Data processing employing the presented workflow revealed about 300 SIL derived feature pairs corresponding to 87-135 metabolites in F. graminearum samples and around 800 feature pairs corresponding to roughly 350 metabolites in wheat samples. SIL assisted IS, by the use of globally U-¹³C labelled biological samples, reduced the median CV value from 7.1 to 3.6 % for technical replicates and from 15.1 to 10.8 % for biological replicates in the respective F. graminearum samples.

Two birds with one stone: doing metabolomics with your proteomics kit

Proteomic research facilities and laboratories are facing increasing demands for the integration of biological data from multiple ‘-OMICS’ approaches. The aim to fully understand biological processes requires the integrated study of genomes, proteomes and metabolomes. While genomic and proteomic workflows are different, the study of the metabolome overlaps significantly with the latter, both in instrumentation and methodology. However, chemical diversity complicates an easy and direct access to the metabolome by mass spectrometry (MS). The present review provides an introduction into metabolomics workflows from the viewpoint of proteomic researchers. We compare the physicochemical properties of proteins and peptides with metabolites/small molecules to establish principle differences between these analyte classes based on human data. We highlight the implications this may have on sample preparation, separation, ionisation, detection and data analysis. We argue that a typical proteomic workflow (nLC-MS) can be exploited for the detection of a number of aliphatic and aromatic metabolites, including fatty acids, lipids, prostaglandins, di/tripeptides, steroids and vitamins, thereby providing a straightforward entry point for metabolomics-based studies. Limitations and requirements are discussed as well as extensions to the LC-MS workflow to expand the range of detectable molecular classes without investing in dedicated instrumentation such as GC-MS, CE-MS or NMR.

Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity

Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR) and HPLC/MS (high-performance liquid chromatography with mass spectrometry). Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR) is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF) treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA), LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

Exploring matrix effects and quantification performance in metabolomics experiments using artificial biological gradients

Metabolomics has become an integral part of many life-science applications but is technically still very challenging. Numerous analytical approaches are needed as metabolites have very broad concentration ranges and extremely diverse chemical properties. Configuring a metabolomics pipeline and exploring its merits is a complex task that depends on effective and transparent evaluation procedures. Unfortunately, there are no widely applicable methods to evaluate how well acquired data can approximate actual concentration differences. Here, we introduce a powerful approach that provides semiquantitative calibration curves over a biologically defined concentration range for all detected compounds. By performing metabolomics on a stepwise gradient between two biological specimens, we obtain a data set where each peak would ideally show a linear dependency on the mixture ratio. An example gradient between extracts of tomato leaf and fruit demonstrates good calibration statistics for a large proportion of the peaks but also highlights cases with strong background-dependent signal interference. Analysis of artificial biological gradients is a general and inexpensive tool for calibration that greatly facilitates data interpretation, quality control and method comparisons.

Ultra-pressure liquid chromatography/tandem mass spectrometry targeted profiling of arachidonic acid and eicosanoids in human colorectal cancer

Cumulative evidence shows that eicosanoids such as prostaglandins, leukotrienes, thromboxanes and hydroxy eicosatetraenoic acids play an important role in associating inflammation with human colorectal cancer (CRC). In this study an ultra-pressure liquid chromatography/tandem mass spectrometry (UPLC/MS/MS) method was developed and validated for the targeted profiling of eight relevant eicosanoids and the major metabolic precursor, arachidonic acid (AA), in human colon. Multiple reaction monitoring (MRM) experiments were performed in negative electrospray ionization mode. The metabolites were separated using a C(18) column consisting of 1.7 µm ethylene-bridged hybrid particles (100 × 2.1 mm i.d.) and gradient elution (50 to 95% of solvent B) with a mobile phase comprising water (0.1% formic acid) [solvent A] and acetonitrile (0.1% formic acid) [solvent B] at a flow rate of 0.4 mL/min. The analysis time for each sample was 5.5 min. Our UPLC/MS/MS method demonstrated satisfactory validation results in terms of selectivity, sensitivity, matrix effect, linearity, extraction efficiency, intra- and inter-day precision, accuracy and autosampler stability. The method was applied for the clinical profiling of matched pairs of cancerous and normal colon mucosae obtained from eight colorectal cancer patients. Endogenous levels of AA and selected eicosanoids such as prostaglandin E(2) (PGE(2)), prostacyclin (PGI(2)) [assayed as its stable hydrolytic product 6-keto-prostaglandin(1α) (6-k PGF(1α))] and 12-hydroxy-5Z,8Z,10E,14Z-eicosatetraenoic acid (12-HETE) were found to be significantly different (p <0.05; paired t-test) between cancerous and normal mucosae.

Capillary separations in metabolomics

Capillary-based separations offer increased resolution, low mass LOD and, in the case of MS, higher sensitivity. The chemical diversity and wide dynamic range of the metabolome requires systems that offer breadth and depth of analysis. In this review, we will highlight novel chemical innovations, technological advancements and various applications of capillary separations in the field of metabolomics.

Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity

A novel framework for automated elucidation of metabolite structures in liquid chromatography-mass spectrometer metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals. The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method.

Streamlined pentafluorophenylpropyl column liquid chromatography-tandem quadrupole mass spectrometry and global (13)C-labeled internal standards improve performance for quantitative metabolomics in bacteria

Streamlined quantitative metabolomics in central metabolism of bacteria would be greatly facilitated by a high-efficiency liquid chromatography (LC) method in conjunction with accurate quantitation. To achieve this goal, a methodology for LC-tandem quadrupole mass spectrometry (LC-MS/MS) involving a pentafluorophenylpropyl (PFPP) column and culture-derived global (13)C-labeled internal standards (I.Ss.) has been developed and compared to hydrophilic interaction liquid chromatography (HILIC)-MS/MS and published combined two-dimensional gas chromatography and LC methods. All 50 tested metabolite standards from 5 classes (amino acids, carboxylic acids, nucleotides, acyl-CoAs and sugar phosphates) displayed good chromatographic separation and sensitivity on the PFPP column. In addition, many important critical pairs such as isomers/isobars (e.g. isoleucine/leucine, methylsuccinic acid/ethylmalonic acid and malonyl-CoA/3-hydroxybutyryl-CoA) and metabolites of similar structure (e.g. malate/fumarate) were resolved better on the PFPP than on the HILIC column. Compared to only one (13)C-labeled I.S., the addition of global (13)C-labeled I.Ss. improved quantitative linearity and accuracy. PFPP-MS/MS with global (13)C-labeled I.Ss. allowed the absolute quantitation of 42 metabolite pool sizes in Methylobacterium extorquens AM1. A comparison of metabolite level changes published previously for ethylamine (C2) versus succinate (C4) cultures of M. extorquens AM1 indicated a good consistency with the data obtained by PFPP-MS/MS, suggesting this single approach has the capability of providing comprehensive metabolite profiling similar to the combination of methods. The more accurate quantification obtained by this method forms a fundamental basis for flux measurements and can be used for metabolism modeling in bacteria in future studies.

Recent and potential developments in the analysis of urine: a review

Analysis of urine is a widely used diagnostic tool that traditionally measured one or, at most, a few metabolites. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to urine for disease diagnostics. This review looks at various aspects of urinalysis including sampling and traditional approaches before reviewing recent developments using metabolomics. Spectrometric approaches are covered briefly since there are already a number of very good reviews on NMR spectroscopy and mass spectrometry and other spectrometries are not as highly developed in their applications to metabolomics. On the other hand, there has been a recent surge in chromatographic applications dedicated to characterising the human urinary metabolome. While developments in the analysis of urine encompassing both classical approaches of urinalysis and metabolomics are covered, it must be emphasized that these approaches are not orthogonal - they both have their uses and are complementary. Regardless, the need to normalise analytical data remains an important impediment.

Common and divergent physiological, hormonal and metabolic responses of Arabidopsis thaliana and Thellungiella halophila to water and salt stress

To explain the higher tolerance of Thellungiella to abiotic stress in comparison to Arabidopsis, several studies have focused on differences in ion absorption and gene expression. However, little is known about hormone regulation and metabolic responses. In this work, plants of both species were subjected to desiccation and salt stress to compare common and divergent responses. In control conditions, the number of significantly upregulated mass features as well as proline levels was higher in Tellungiella than in Arabidopsis. When subjected to desiccation, both species exhibited similar rates of water loss but proline over accumulation only occurred in Thellungiella; both species accumulated ABA and JA with a similar trend although Arabidopsis showed higher concentrations of both hormones which indicated a stronger impact of desiccation on Arabidopsis. However, Arabidopsis showed a higher number of significantly altered mass features than Thellungiella. Under salt stress, Thellungiella plants accumulated lower amounts of Cl(-) ions than Arabidopsis but exhibited a similar proline response. Under these conditions, ABA and JA levels increased in Arabidopsis whereas minimal changes in both hormone concentrations were recorded in Thellungiella. Contrastingly, the impact of salt stress on metabolite profiles was higher in Thellungiella than in Arabidopsis. Overall, data indicated that physiological responses in Arabidopsis are induced after stress imposition through hormonal regulation whereas Thellungiella has a basal metabolic configuration, better prepared to endure environmental cues.

Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis

Comparative metabolomics of Leishmania species requires the simultaneous identification and quantification of a large number of intracellular metabolites. Here, we describe the optimisation of a comprehensive metabolite extraction protocol for Leishmania parasites and the subsequent optimisation of the analytical approach, consisting of hydrophilic interaction liquid chromatography coupled to LTQ-orbitrap mass spectrometry. The final optimised protocol starts with a rapid quenching of parasite cells to 0 °C, followed by a triplicate washing step in phosphate-buffered saline. The intracellular metabolome of 4 × 10(7) parasites is then extracted in cold chloroform/methanol/water 20/60/20 (v/v/v) for 1 h at 4 °C, resulting in both cell disruption and comprehensive metabolite dissolution. Our developed metabolomics platform can detect approximately 20% of the predicted Leishmania metabolome in a single experiment in positive and negative ionisation mode.

Multitarget quantitative metabolic profiling of hydrophilic metabolites in fermentation broths of β-lactam antibiotics production by HILIC-ESI-MS/MS

The presented work deals with the development and comprehensive validation of a quantitative LC-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) method using a triple quadrupole instrument in the MRM mode for the metabolic profiling of amino acids, organic acids, vitamins, some biogenic amines, secondary metabolites of β-lactam antibiotics biosynthesis as well as their intermediates, and degradation products in fermentation broths of β-lactam antibiotics production (in total 57 hydrophilic compounds). A great number of chromatographic systems (22 different stationary phase/mobile phase conditions) were screened for their adequate chromatographic selectivity to cope with isobaric compounds and other critical analyte pairs. Finally, a hydrophilic interaction liquid chromatography (HILIC) method employing a zwitterionic ZIC-HILIC column was selected as best compromise. Particular focus was given on the elucidation of absolute and relative matrix effects via comparison of slopes of calibration functions of spiked matrix and standard solutions. These data as well as precision and accuracy data confirm suitability of the HILIC-ESI-MS/MS assay for metabolic profiling studies in fermentation samples. Detailed comprehensive data sets are presented which should illustrate critical issues, problems, and challenges of multitarget quantitative metabolic profiling and should outline possible strategies to circumvent pitfalls and overcome common problems.

MS-based Plant Metabolomic Approaches for Biomarker Discovery

Metabolomics, which aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples, is playing an increasingly important role in plant science. Various biological issues have been successfully studied by this holistic approach that includes global metabolite composition assessment, mutant characterization, taxonomy, developmental processes, stress response, interaction with environment, quality control assessment and mode of action of herbal medicine. This review summarizes the main mass spectrometry methods used for performing these studies and discusses the potential, but also the current limitations of the various approaches. The intention is not to cover exhaustively the field, which has considerably grown over about one decade, but to give a brief insight into the methods commonly employed and discuss some applications that reveal the potential of metabolomics in phytochemistry and systems biology.

Plant phenotype demarcation using nontargeted LC-MS and GC-MS metabolite profiling

The characterization of the metabolome is a critical aspect in basic research and plant breeding. In this work, the putative application of metabolomics for phenotyping closely related genotypes has been tested. Crude extracts were profiled by LC-MS and GC-MS, and mass data extraction was performed with XCMS software. Result validation was achieved with principal component analysis (PCA). The ability of the profiling methodologies to discriminate plant genotypes was assessed after hierarchical clustering analysis (HCA). Cluster robustness was assessed by a multiscale bootstrap resampling method. A better performance of LC-MS profiling over GC-MS was evidenced in terms of phenotype demarcation after PCA and HCA. Citrus demarcation was similarly achieved independently of the environmental conditions used to grow plants. In addition, when all different locations were pooled in a single experimental design, it was still possible to differentiate the three closely related genotypes. The presented methodology provides a fast and nontargeted workflow as a powerful tool to discriminate related plant phenotypes. The novelty of the technique relies on the use of mass signals as markers for phenotype demarcation independent of putative metabolite identities and the relatively simple analytical strategy that can be applicable to a wide range of plant matrices with no previous optimization.

Singlet oxygen-dependent translational control in the tigrina-d.12 mutant of barley

The tigrina (tig)-d.12 mutant of barley is impaired in the negative control limiting excess protochlorophyllide (Pchlide) accumulation in the dark. Upon illumination, Pchlide operates as photosensitizer and triggers singlet oxygen production and cell death. Here, we show that both Pchlide and singlet oxygen operate as signals that control gene expression and metabolite accumulation in tig-d.12 plants. In vivo labeling, Northern blotting, polysome profiling, and protein gel blot analyses revealed a selective suppression of synthesis of the small and large subunits of ribulose-1,5-bisphosphate carboxylase/oxygenase (RBCSs and RBCLs), the major light-harvesting chlorophyll a/b-binding protein of photosystem II (LHCB2), as well as other chlorophyll-binding proteins, in response to singlet oxygen. In part, these effects were caused by an arrest in translation initiation of photosynthetic transcripts at 80S cytoplasmic ribosomes. The observed changes in translation correlated with a decline in the phosphorylation level of ribosomal protein S6. At later stages, ribosome dissociation occurred. Together, our results identify translation as a major target of singlet oxygen-dependent growth control and cell death in higher plants.

High-resolution spatial and temporal analysis of phytoalexin production in oats

The production of oat (Avena sativa L.) phytoalexins, avenanthramides, occurs in response to elicitor treatment with oligo-N-acetylchitooligosaccharides. In this study, avenanthramides production was investigated by techniques that provide high spatial and temporal resolution in order to clarify the process of phytoalexin production at the cellular level. The amount of avenanthramides accumulation in a single mesophyll cell was quantified by a combination of laser micro-sampling and low-diffuse nanoflow liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) techniques. Avenanthramides, NAD(P)H and chlorophyll were also visualized in elicitor-treated mesophyll cells using line-scanning fluorescence microscopy. We found that elicitor-treated mesophyll cells could be categorized into three characteristic cell phases, which occurred serially over time. Phase 0 indicated the normal cell state before metabolic or morphological change in response to elicitor, in which the cells contained abundant NAD(P)H. In phase 1, rapid NAD(P)H oxidation and marked movement of chloroplasts occurred, and this phase was the early stage of avenanthramides biosynthesis. In phase 2, avenanthramides accumulation was maximized, and chloroplasts were degraded. Avenanthramides appear to be synthesized in the chloroplast, because a fluorescence signal originating from avenanthramides was localized to the chloroplasts. Moreover, our results indicated that avenanthramides biosynthesis and the hypersensitive response (HR) occurred in identical cells. Thus, the avenanthramides production may be one of sequential events programmed in HR leading to cell death. Furthermore, the phase of the defense response was different among mesophyll cells simultaneously treated with elicitor. These results suggest that individual cells may have different susceptibility to the elicitor.

A method for monitoring and controlling reproducibility of intensity data in complex electrospray mass spectra: a thermometer ion-based strategy

Reproducibility in mass spectral data is important in both biomarker discovery and spectral database searching. We report a strategy, employing a series of substituted benzylpyridinium thermometer ions that can be used to monitor changes in performance of multiple aspects of an electrospray ionization source that impact the intensity axis of a spectrum. Performance attributes, which could confound even isotope-based quantification strategies, are readily assessed using a mixture of thermometer ions. Based on the observed behavior of the ions, a procedure is proposed for monitoring instrument performance and compensating for factors that affect reproducibility across both time and instruments.

Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis

Metabolomics is facing a major challenge: the lack of knowledge about metabolites present in a given biological system. Thus, large-scale discovery of metabolites is considered an essential step toward a better understanding of plant metabolism. We show here that the application of a metabolomics approach generating structural information for the analysis of Arabidopsis (Arabidopsis thaliana) mutants allows the efficient cataloging of metabolites. Fifty-six percent of the features that showed significant differences in abundance between seeds of wild-type, transparent testa4, and transparent testa5 plants could be annotated. Seventy-five compounds were structurally characterized, 21 of which could be identified. About 40 compounds had not been known from Arabidopsis before. Also, the high-resolution analysis revealed an unanticipated expansion of metabolic conversions upstream of biosynthetic blocks. Deficiency in chalcone synthase results in the increased seed-specific biosynthesis of a range of phenolic choline esters. Similarly, a lack of chalcone isomerase activity leads to the accumulation of various naringenin chalcone derivatives. Furthermore, our data provide insight into the connection between p-coumaroyl-coenzyme A-dependent pathways. Lack of flavonoid biosynthesis results in elevated synthesis not only of p-coumarate-derived choline esters but also of sinapate-derived metabolites. However, sinapoylcholine is not the only accumulating end product. Instead, we observed specific and sophisticated changes in the complex pattern of sinapate derivatives.

Instrumental and experimental effects in LC-MS-based metabolomics

The experimental complexity of a metabolomics study can cause uncontrolled variance that is not related to the biological effect being studied and may distort or obscure the data analysis. While some sources can be controlled with good experimental techniques and careful sample handling, others are inherent in the analytical technique used and cannot easily be avoided. We discuss the sources and appearance of some of these artifacts and show ways in which they can be detected using visualization and statistical tools, allowing appropriate treatment prior to multivariate analysis (MVA).