Urine profiling using capillary electrophoresis-mass spectrometry and multivariate data analysis

Two chromatographic methods for analyzing paracetamol in spiked human plasma with its toxic metabolite, N-acetyl parabenzoquinone imine and its antidote, N-acetyl-L-cysteine

Acetaminophen, also known as paracetamol (APAP), is a highly utilized pharmaceutical agent on a global scale, particularly in the field of pediatrics. Regrettably, an overdose of APAP, resulting from the predominant oxidation, has the potential to trigger acute liver injury. The study's goal was to find an easy, accurate, and selective way to measure APAP, N-acetyl para benzoquinone imine (NAPQI) (an APAP metabolite that is harmful), and N-acetyl-L-cysteine (NAC) (an antidote). Two different chromatographic methods were used. The HPTLC method, which used silica gel 60 F254 as a stationary phase and a developing liquid made up of methanol, ethyl acetate, and glacial acetic acid (8:2:0.2, v/v/v) and a UV detection at 254 nm. The HPLC method was developed using a mobile phase consisting of water, methanol, and formic acid in a proportion of (70:30:0.15, v/v/v). The stationary phase used in the approach was a C18 column. Analytes quantification was established utilizing a UV detector operating at a wavelength of 254 nm. The present methods make it possible to measure the amount of APAP in plasma samples. When it comes to pharmacokinetics or medication levels in children's plasma, for example, this may be also very helpful. The current methods can quantify NAPQI, which is helpful in figuring out drug concentrations in individuals with APAP intoxication diagnoses. Additionally, the current approaches can estimate NAC as an antidote; as a result, this study is a complete study because it can analyse drug, toxic metabolite, and antidote in one analytical run. Using the innovative blue applicability grade index software, which measures the practicality of procedures, both methodologies were compared with a reported methods. Additionally, the achievement of the eco-friendliness profile of the designed procedures was assessed. Both techniques passed the ICH validation tests.

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous algorithms, many of which were derived with the aid of artificial intelligence, were brought up in a strive for perfection in predicting the status of sepsis-related survival or exacerbation. This review aims to provide key insights on the contextual utilization of metabolomics. The aim of this the metabolomic approach set of methods can be used to investigate both bacterial and host metabolite sets from both the host and its microbes in several types of specimens - even in one's breath, mainly with use of two methods - Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR). Metabolomics, and has been used to elucidate the mechanisms underlying disease development and metabolic identification changes in a wide range of metabolite contents, leading to improved methods of diagnosis, treatment, and prognosis of meningitis. Mass spectrometry (MS) and Nuclear Magnetic Resonance (NMR) are the main analytical platforms used in metabolomics. Its high sensitivity accounts for the usefulness of metabolomics in studies into meningitis, its sequelae, and concomitant comorbidities. Metabolomics approaches are a double-edged sword, due to not only their flexibility, but also - high complexity, as even minor changes in the multi-step methods can have a massive impact on the results. Information on the differential diagnosis of meningitis act as a background in presenting the merits and drawbacks of the use of metabolomics in context of meningeal infections.

Strategies for capillary electrophoresis: Method development and validation for pharmaceutical and biological applications-Updated and completely revised edition

This review is in support of the development of selective, precise, fast, and validated capillary electrophoresis (CE) methods. It follows up a similar article from 1998, Wätzig H, Degenhardt M, Kunkel A. "Strategies for capillary electrophoresis: method development and validation for pharmaceutical and biological applications," pointing out which fundamentals are still valid and at the same time showing the enormous achievements in the last 25 years. The structures of both reviews are widely similar, in order to facilitate their simultaneous use. Focusing on pharmaceutical and biological applications, the successful use of CE is now demonstrated by more than 600 carefully selected references. Many of those are recent reviews; therefore, a significant overview about the field is provided. There are extra sections about sample pretreatment related to CE and microchip CE, and a completely revised section about method development for protein analytes and biomolecules in general. The general strategies for method development are summed up with regard to selectivity, efficiency, precision, analysis time, limit of detection, sample pretreatment requirements, and validation.

The effects of 2'-fucosyllactose and lacto-N-neotetraose, galacto-oligosaccharides, and maternal human milk oligosaccharide profile on iron absorption in Kenyan infants

BACKGROUND

Whether prebiotic human milk oligosaccharides (HMO), such as 2'-fucosyllactose (2'-FL) and lacto-N-neotetraose (LNnT), enhance iron absorption in infants is unknown. Moreover, whether maternal HMO profile affects absorption of iron fortificants or the effects of prebiotic galacto-oligosaccharides (GOS) and/or HMO on iron absorption is uncertain.

OBJECTIVES

The aim of this study was to test whether consumption of 3.0 g GOS or HMO enhances iron absorption from iron-fortified maize porridge in partially breastfed Kenyan infants and whether maternal HMO profile modulates these effects.

METHODS

In a randomized, prospective crossover study, 55 infants (aged 8-12 mo) were fed test meals fortified with 1 of the following: 1) 5.0 mg iron as ⁵⁴Fe-labeled ferrous fumarate (FeFum); 2) 5.0 mg iron as ⁵⁸FeFum and 3.0 g GOS (FeFum+GOS); and 3) 5.0 mg iron as ⁵⁷FeFum and 2.0 g 2'-FL and 1.0 g LNnT (FeFum+HMO). Fractional iron absorption (FIA) was assessed by erythrocyte incorporation of iron isotopes. HMO profiles were determined by capillary gel electrophoresis with laser-induced florescence detection. Data were analyzed with mixed-effect models, and iron dialyzability was measured in vitro.

RESULTS

Of the 55 infants included, 49 were fed as instructed. FIA from the FeFum+GOS group [median (IQR) 22.2% (16.5%-25.9%)] was higher than that from the FeFum group [12.5% (9.5%-20.9%)] (P = 0.005). FIA from the FeFum+HMO group was 13.3% (7.1%-24.4%) and did not differ from the FeFum group (P = 0.923). Maternal HMO profile did not predict FIA or modulate the effects of GOS or HMO on FIA. Iron dialyzability ratios at pH 2 of FeFum+GOS to FeFum and FeFum+HMO to FeFum were 2.1 and 0.9 (P = 0.001 and P = 0.322), respectively.

CONCLUSIONS

In Kenyan infants consuming FeFum-fortified maize porridge, co-provision of 3.0 g GOS increased FIA by 78%, whereas co-provision of 3.0 g HMO did not affect FIA. Variations in maternal HMO profile, including secretor and Lewis phenotype, did not predict FIA. These data argue against a physiologic role for 2'-FL and LNnT in facilitating iron absorption in infancy. The study was registered at clinicaltrials.gov as NCT04163406 (https://clinicaltrials.gov/ct2/show/NCT04163406).

Gut microbiome function and composition in infants from rural Kenya and association with human milk oligosaccharides

The gut microbiota evolves rapidly after birth, responding dynamically to environmental factors and playing a key role in short- and long-term health. Lifestyle and rurality have been shown to contribute to differences in the gut microbiome, including Bifidobacterium levels, between infants. We studied the composition, function and variability of the gut microbiomes of 6- to 11-month-old Kenyan infants (n = 105). Shotgun metagenomics showed Bifidobacterium longum to be the dominant species. A pangenomic analysis of B. longum in gut metagenomes revealed a high prevalence of B. longum subsp. infantis (B. infantis) in Kenyan infants (80%), and possible co-existence of this subspecies with B. longum subsp. longum. Stratification of the gut microbiome into community (GMC) types revealed differences in composition and functional features. GMC types with a higher prevalence of B. infantis and abundance of B. breve also had a lower pH and a lower abundance of genes encoding pathogenic features. An analysis of human milk oligosaccharides (HMOs) classified the human milk (HM) samples into four groups defined on the basis of secretor and Lewis polymorphisms revealed a higher prevalence of HM group III (Se+, Le-) (22%) than in most previously studied populations, with an enrichment in 2'-fucosyllactose. Our results show that the gut microbiome of partially breastfed Kenyan infants over the age of six months is enriched in bacteria from the Bifidobacterium community, including B. infantis, and that the high prevalence of a specific HM group may indicate a specific HMO-gut microbiome association. This study sheds light on gut microbiome variation in an understudied population with limited exposure to modern microbiome-altering factors.

Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review

Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).

Presence and Levels of Galactosyllactoses and Other Oligosaccharides in Human Milk and Their Variation during Lactation and According to Maternal Phenotype

Among the human milk oligosaccharides (HMOS), the galactosyllactoses (GLs) are only limitedly studied. This study aims to describe the presence and relative levels of HMOS, including GLs, in human milk (HM) according to maternal Secretor and Lewis (SeLe) phenotype and lactation stage. Relative levels of 19 HMOS were measured in 715 HM samples collected in the first 4 months postpartum from 371 donors participating in the PreventCD study. From a subset of 24 Dutch women (171 HM samples), samples were collected monthly up to 12 months postpartum and were additionally analyzed for relative and absolute levels of β6′-GL, β3′-GL and α3′-GL. Maternal SeLe phenotype or HM group was assigned based on the presence of specific fucosylated HMOS. Most HMOS, including β6′- and β3′-GL, were present in the vast majority (≥75%) of HM samples, whereas others (e.g., LNDFH II, 2′-F-LNH and α3′-GL) only occurred in a low number (<25%) of samples. Clear differences were observed between the presence and relative levels of the HMOS according to the maternal phenotype and lactation stage. Absolute concentrations of β6′-GL and β3′-GL were higher in HM group IV samples compared to samples of the other three HM groups. β3′-GL was also higher in HM group II samples compared to HM group I samples. β3′-GL and β6′-GL were stable over lactation stages. In conclusion, presence and levels of HMOS vary according to HM group and lactation stage. Not all HMOS behave similarly: some HMOS depend strongly on maternal phenotype and/or lactation stage, whereas others do not. β3′-GL and β6′-GL were present in low concentrations in over 75% of the analyzed HM samples and showed differences between HM groups, but not between the lactation stages.

Capillary electrophoresis mass spectrometry as a tool for untargeted metabolomics

Highly polar and ionic metabolites, such as sugars, most amino acids, organic acids or nucleotides are not retained by conventional reversed-phase LC columns and polar stationary phases and hydrophilic-interaction LC lacks of robustness, which is still limiting their applications for untargeted metabolomics where reproducibility is a must. Biological samples such as blood, urine or even tissues include many hydrophilic compounds secreted from cells, their analysis is essential for biomarker discovery, disease progression or treatment effects. This review focuses on CE coupled to MS as a mature technique for untargeted metabolomics including sample pretreatment, types of matrices, analytical methods, applications and data treatment strategies for polar compound analysis in biological matrices. The main applications and results of CE-MS in untargeted metabolomics are discussed and presented in a tabulated format.

Metabolomics study of metabolic variations in enterotoxigenic Escherichia coli-infected piglets

This study aimed to explore the metabolic profiling in the serum of enterotoxigenic Escherichia coli (ETEC) infected piglets.

TracMass 2--a modular suite of tools for processing chromatography-full scan mass spectrometry data

In untargeted proteomics and metabolomics, raw data obtained with an LC/MS instrument are processed into a format that can be used for statistical analysis. Full scan MS data from chromatographic separation of biological samples are complex and analyte concentrations need to be extracted and aligned so that they can be compared across the samples. Several computer programs and methods have been developed for this purpose. There is still a need to improve the ease of use and feedback to the user because of the advanced multiparametric algorithms used. Here, we present and make publicly available, TracMass 2, a suite of computer programs that gives immediate graphical feedback to the data analyst on parameter settings and processing results, as well as producing state-of-the-art results. The main advantage of TracMass 2 is that the feedback and transparency of the processing steps generate confidence in the end result, which is a table of peak intensities. The data analyst can easily validate every step of the processing pipeline. Because the user receives feedback on how all parameter values affect the result before starting a lengthy computation, the user's learning curve is enhanced and the total time used for data processing can be reduced. TracMass 2 has been released as open source and is included in the Supporting Information . We anticipate that TracMass 2 will set a new standard for how chemometrical algorithms are implemented in computer programs.

Metabonomics study on the hepatoprotective effect of polysaccharides from different preparations of Angelica sinensis

ETHNOPHARMACOLOGICAL RELEVANCE

Angelica sinensis (AS) has been used for thousands of years in Traditional Chinese Medicine (TCM). Processed products of AS mainly include charred Angelica, parching Angelica with oil, parching Angelica with wine, and parching Angelica with soil, which have been widely used in TCM prescriptions. Polysaccharides are important chemical substances of AS. These compounds effectively treat liver diseases, shows hepatoprotectivity, and contributes directly to the therapeutic effect of AS. However, the precise molecular mechanism of the effects of the different AS products polysaccharide has not been comprehensively explored. The present investigation was designed to assess the effects and possible mechanisms of polysaccharide in the different AS products against carbon tetrachloride-induced liver injury.

MATERIALS AND METHODS

Liver injury was induced by intraperitoneal injection with Carbon tetrachloride (CCl4) in the mice. Gas chromatography-mass spectrometry (GC-MS) combined with pattern recognition approaches, namely, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), were used to determine differentiating metabolites in plasma and liver tissue.

RESULTS

PCA and PLS-DA score plots of the liver injury group clustered separately from that of the control, while groups treated with polysaccharides from charred AS (ASTP), parching AS with soil (ASTUP), parching AS with wine (ASJP), parching AS with Sesame Oil (ASYP) clustered closely with the control. This result indicates that the metabolic profiles of the ASTP, ASTUP, ASJP, and ASYP groups are almost similar to those of the control. Potential metabolite biomarkers (six in the liver homogenates and seven in the plasma) were identified. These biomarkers include citric acid, succinic acid,glycine, palmitelaidic acid, arachidonic acid, fumaric acid, malic acid, valine, ananine, and hexadecanoic acid. Functional pathway analysis revealed that alterations in these metabolites are associated with lipid, amino acid, and energy metabolism. Notably, ASTP exhibited a potential pharmacological effect by regulating multiple perturbed pathways to the normal state.

CONCLUSION

It is likely that ASTP, ASTUP, ASJP, ASYP intervenes the metabolic process of liver injury mice by affecting the lipid and amino acid metabolism. Metabonomics is a robust and promising for the identification of biomarkers and elucidation of the mechanisms of a disease, thereby highlighting its importance in drug discovery.

Metabolite fingerprinting by capillary electrophoresis-mass spectrometry

Changes in metabolite concentrations in response to specific diseases, treatments, diets, or other factors can be used to understand the complex mechanisms that control and regulate the human body and potentially detect the onset of disease prior to the observation of symptoms in a patient. Different analytical and chemometric platforms are necessary to detect as many metabolites as possible in different biological fluids. Capillary electrophoresis (CE) coupled to mass spectrometry (MS) is a particularly attractive, although still not common, approach for metabolomics for the detection of mainly polar and ionic metabolites. Among its main features, CE provides the capability to separate complex mixtures with high resolution and minimum sample treatment. However, the routine, automated use of CE-MS is not without challenges. In this chapter we describe a well-tested method for fingerprinting serum and urine using CE-TOF-MS. We describe below a sensitive and quite robust method for metabolomics with CE-MS including sample treatment, separation conditions, instrumental setup, and identification of 76 metabolites in the profile. Useful advice for daily practice is also included for every step of the procedure.

Development of a CZE-ESI-MS assay with a sulfonated capillary for profiling picolinic acid and quinolinic acid formation in multienzyme system

This article describes the development of a reliable CZE-ESI-MS method to simultaneously separate and quantitate three specific metabolites (3-hydroxyanthranilic acid (3-HAA), quinolinic acid (QA), and picolinic acid (PA)) of the kynurenine pathway (KP) of tryptophan catabolism. Using a covalently bonded sulfonated capillary, the parameters such as pH, type of background electrolyte, type of organic solvent, nebulizer pressure as well as both negative and positive ESI-MS modes were optimized to achieve the best Rs and S/N of three KP metabolites. The developed CZE-ESI-MS assay provided high resolution of PA/QA, high specificity, a total analysis time of 10 min with satisfactory intraday and interday repeatability of migration time and peak areas. Under optimized CZE-ESI-MS conditions, the calibration curves over a concentration range of 19-300 μM for 3-HAA and QA, and 75-300 μM for PA were simultaneously generated. The method was successfully applied for the first time to profile the concentrations of initial substrate, 3-HAA, and its eventual products, PA and QA, formed in the complex multienzyme system. As the ratio of two enzymes, 3-hydroxyanthranilate 3,4-dioxygenase (HAO) and α-amino-β-carboxymuconate-ε-semialdehyde decarboxylase (ACMSD) decreases, the concentration of QA approaches essentially zero indicating that all ACMS formed by the action of HAO is consumed by ACMSD rather than its spontaneous decay to QA.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

CE-ESI-MS metabolic fingerprinting of Leishmania resistance to antimony treatment

Metabolomics has become an invaluable tool to unveil biology of pathogens, with immediate application to chemotherapy. It is currently accepted that there is not one single technique capable of obtaining the whole metabolic fingerprint of a biological system either due to their different physical-chemical properties or concentrations. In this work, we have explored the capability of capillary electrophoresis mass spectrometry with a sheathless interface with electrospray ionization (CE-ESI-TOF-MS) to separate metabolites in order to be used as a complementary technique to LC. As proof of concept, we have compared the metabolome of Leishmania infantum promastigotes BCN 150 (Sb (III) IC(50) = 20.9 μM) and its variation when treated with 120 μM of Sb(III) potassium tartrate for 12 h, as well as with its Sb(III) resistant counterpart obtained by growth of the parasites under increasing Sb(III) in a step-wise manner up to 180 μM. The number of metabolites compared were of 264 for BCN150 Sb(III) treated versus nontreated and of 195 for Sb(III) resistant versus susceptible parasites. After successive data filtering, differences in seven metabolites identified in databases for Leishmania pathways, showed the highest significant differences, corresponding mainly to amino acids or their metabolite surrogates. Most of them were assigned to sulfur containing amino acids and polyamine biosynthetic pathways, of special relevance considering the deterioration of the thiol-dependent redox metabolism in Leishmania by Sb(III). Given the low concentrations typical for most of these metabolites, the assay can be considered a success that should be explored for new biological questions.

Liquid chromatography-mass spectrometry based global metabolite profiling: a review

Untargeted, global metabolite profiling (often described as metabonomics or metabolomics) represents an expanding research topic and is, potentially, a major pillar for systems biology studies. To obtain holistic metabolic profiles from complex samples, such as biological fluids or tissue extracts, requires powerful, high resolution and information-rich analytical methods and for this spectroscopic technologies are generally used. Mass spectrometry, coupled to liquid chromatography (LC-MS), is increasingly being used for such investigations as a result of the significant advances in both technologies over the past decade. Here we try to critically review the topic of LC-MS-based global metabolic profiling and describe and compare the results offered by different analytical strategies and technologies. This review highlights the current challenges, limitations and opportunities of the current methodology.

Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies

Metabonomics and metabolomics represent one of the three major platforms in systems biology. To perform metabolomics it is necessary to generate comprehensive "global" metabolite profiles from complex samples, for example, biological fluids or tissue extracts. Analytical technologies based on mass spectrometry (MS), and in particular on liquid chromatography-MS (LC-MS), have become a major tool providing a significant source of global metabolite profiling data. In the present review we describe and compare the utility of the different analytical strategies and technologies used for MS-based metabolomics with a particular focus on LC-MS. Both the advantages offered by the technology and also the challenges and limitations that need to be addressed for the successful application of LC-MS in metabolite analysis are described. Data treatment and approaches resulting in the detection and identification of biomarkers are considered. Special emphasis is given to validation issues, instrument stability, and QA/quality control (QC) procedures.

A plasma metabonomic investigation into the intervention of volatile oil of Magnolia biondii Pamp on rat model of acute inflammation

ETHNOPHARMACOLOGICAL RELEVANCE

The dried flower buds of Magnolia biondii Pamp (Magnoliaceae) possesses significant anti-inflammatory activities.

AIM OF THE STUDY

Volatile oil in Magnolia biondii Pamp (VOMbP) is considered to be important pharmacologically active individuals against acute inflammation, but its exact anti-inflammatory mechanism remains elusive. In this study, we aimed to investigate the intervention of VOMbP on rats with acute inflammation and explore the possible anti-inflammatory mechanisms of VOMbP with metabonomic strategy.

MATERIALS AND METHODS

Acute inflammation was induced by subcutaneously injection of carrageenan in the rats. Plasma was analyzed using gas chromatography-mass spectrometry (GC-MS), based on which the principal component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) models were established for metabonomic analysis.

RESULTS

It was revealed that the pretreatment of VOMbP in acute inflammatory rats induces a substantial and characteristic change in their metabolic profiles. Some significantly changed metabolites, including hexadecanoic acid, linoleic acid, oleic acid, stearic acid, and cholesterol, were found to be reasonable in explaining the anti-inflammatory mechanism of VOMbP.

CONCLUSIONS

In all, it is likely that VOMbP intervenes the metabolic process of inflammatory rats by affecting the fatty acid and cholesterol metabolism. Our work also indicated that the metabonomics method is a promising tool for performing intervention and mechanism research of traditional Chinese medicines.

Capillary electrophoresis-mass spectrometry analysis of trehalose-6-phosphate in Arabidopsis thaliana seedlings

Trehalose-6-phosphate (T6P) is an intermediate in the plant metabolic pathway that results in trehalose production. T6P has been shown to inhibit the sucrose nonfermenting-1-related protein kinase 1, which is a major regulator of metabolism. The quantitation of T6P has proven difficult due to the complexity of the plant matrix and the low abundance of T6P in plant tissues. The aim of this work was to develop a quantitation method for T6P present in Arabidopsis tissues, with capillary electrophoresis (CE) coupled to electrospray ionization-mass spectrometry (MS) with a sheath liquid (SL) interface. The CE-MS method was first optimized with respect to T6P signal intensity and separation of isomers by studying the composition of the background electrolyte (BGE) and SL. The use of triethylamine (TEA) in the BGE was favorable, providing separation of T6P from sucrose-6-phosphate and minimizing ionization suppression. Replacing ammonium acetate with TEA enhanced T6P signal intensities more than four times. The optimized method allowed quantification of T6P in plant extracts with good linearity (r² > 0.99) within a biologically relevant concentration range. The limit of quantification was 80 nM in Arabidopsis extracts, corresponding to 33 pmol/g plant fresh weight. The CE-MS method was applied to the determination of T6P in seedlings from wild type (WT) Arabidopsis and mutants lacking the trehalase AtTRE1, tre1-1, challenged with trehalose or sorbitol. T6P accumulation in tre1-1 plants grown on sorbitol was about twice the level of T6P found in WT. CE-MS is shown to be a fast and reliable technique to analyze phosphodisaccharides for seedling extracts. The low sample volume requirement of CE and its direct MS coupling makes it an attractive alternative for anion-exchange liquid chromatography–MS.

Metabolomic applications of HILIC-LC-MS

Hydrophilic interaction liquid chromatography (HILIC), although not a new technique, has enjoyed a recent renaissance with the introduction of robust and reproducible stationary phases. It is consequently finding application in metabolomics studies, which have traditionally relied on the stability of reversed phases (RPs), since the biofluids analyzed are predominantly aqueous and thus contain many polar analytes. HILIC's retention of those polar compounds and use of solvents readily compatible with mass spectrometry have seen its increasing adoption in studies of complex aqueous metabolomes. This review describes the stationary phases and their features, surveys HILIC-LC-MS's role in metabolomics experiments, discusses approaches to data extraction and analysis including multivariate analysis, and reviews the literature on HILIC-MS applications in metabolomics.

Explorative analysis of urine by capillary electrophoresis-mass spectrometry in chronic patients with complex regional pain syndrome

Complex Regional Pain Syndrome (CRPS) is characterized by various combinations of sensory, autonomic and motor disturbances. Pain disproportionate to the severity and duration of the inciting event is the most devastating symptom. Diagnosis of CRPS is difficult as the underlying mechanisms remain unclear. To try to derive metabolic indicators potentially characteristic for CRPS, we applied capillary electrophoresis time-of-flight mass spectrometry (CE-ToF-MS) to the explorative analysis of urine. The CE-ToF-MS method provided fast and stable metabolic profiles of urine samples. The mean intraday and interday CVs were <2% and <9% for migration times and peak areas, respectively, demonstrating robustness of the method. With the use of multivariate chemometric analysis, discrimination between urine samples from CRPS patients and controls was obtained, emphasizing differences in metabolic signatures between CRPS-diseased patients and controls. Several compounds, such as 3-methylhistidine, were responsible for discriminating the samples. The biological relevance of these compounds with regard to CRPS is discussed. Thus, CE-ToF-MS-based metabolic profiling of urine from CRPS patients and controls revealed metabolites that differentiate between diseased and control, illustrating the usefulness of this approach to get more insight into the pathology underlying CRPS.

Different sample preparation and detection methods for normal and lung cancer urinary proteome analysis

The urinary proteome is known to be a valuable field of study related to human physiological functions because many components in urine provide an alternative to blood plasma as a potential source of disease biomarkers useful in clinical diagnosis and therapeutic application. Due to the variability and complexity of urine, sample preparation is very important for decreasing the dynamic range of components and isolating specific urinary proteins prior to analysis. We discuss many useful sample preparation methods in this chapter, including those of lung cancer urine samples. In addition, protein detection methods are also crucial in visualizing protein profiles and for quantification of protein content in urine samples from both normal donor and lung cancer patients. This chapter also provides alternative choices of urine sample preparation and detection methods for selective use in urinary proteome analysis and for identifying urinary protein markers in lung cancer and other diseases.

Spectroscopic and statistical methods in metabonomics

Metabonomics is rapidly evolving through advances in analytical technologies together with the development of new hyphenated approaches that are increasingly being applied to analyze complex biological systems. Improvements in analytical performance, such as increased sensitivity and selectivity, are providing greater resolution to analytical datasets and the rich potential of metabonomics as a systems biology tool of choice is becoming clear. However, such improvements are resulting in datasets becoming increasingly demanding in terms of data handling and interpretation, and the degree to which metabonomics continues to develop will be dependent on how chemometrics and data-handling approaches keep pace with continually improving analytical technologies. This review provides an overview of the field of metabonomics, with a particular focus on the analytical techniques that are chiefly employed and the chemometric methods that have found most use. However, in addition, we mention less widely used analytical methods and suggest that advanced statistical methods will play a larger role in the future.

Comparing capillary electrophoresis-mass spectrometry fingerprints of urine samples obtained after intake of coffee, tea, or water

Metabolomic fingerprinting is a growing strategy for characterizing complex biological samples without detailed prior knowledge about the metabolic system. A two-way analysis system with liquid separation and mass spectrometric detection provides detail-rich data suitable for such fingerprints. As a model study, human urine samples, obtained after intake of coffee, tea, or water, were analyzed with capillary electrophoresis electrospray ionization time-of-flight mass spectrometry (CE-ESI-TOF-MS). In-house-developed software (in Matlab) was utilized to manage and explore the large amount of data acquired (230 CE-MS runs, each with 50-100 million nonzero data points). After baseline and noise reduction, followed by suitable binning in time and m/z, the data sets comprised 9 and 14 million data points in negative and positive ESI mode, respectively. Finally, a signal threshold was applied, further reducing the number to about 100 000 data points per data set. A set of interactive exploratory tools, utilizing principal component analysis (PCA) and analysis of variance (ANOVA) results based on a general linear model, facilitated visual interpretation with score plots (for group assessment) and differential fingerprints (for "hot spot" detection). In the model study highly significant differences due to beverage intake were obtained among the 10 first principal components (p < 10(-6) for two of the components in both ESI modes). Especially, the contrasts between "coffee" and "tea or water" indicated several "hot spots" with highly elevated intensities (e.g., for uncharged masses 93, 94, 109, 119, 123, 132, 148, 169, 178, 187, 190, and 193) suitable for further analysis, for example, with tandem MS.

Advances in separation science applied to metabonomics

Metabonomics focuses on metabolite profile changes in diverse living systems caused by a biological perturbation. These metabolite signatures can be achieved with techniques such as gas chromatography, high-performance liquid chromatography (ultra-high-performance/pressure liquid chromatography and capHPLC), capillary electrophoresis, and capillary electrochromatography normally hyphenated with MS. In this review we present the latest developments of the abovementioned techniques applied in the field of metabonomics, with applications covering phytochemistry, toxicology and clinical research.

No-alignment-strategies for exploring a set of two-way data tables obtained from capillary electrophoresis-mass spectrometry

Hyphenated techniques such as capillary electrophoresis-mass spectrometry (CE-MS) or high-performance liquid chromatography with diode array detection (HPLC-DAD), etc., are known to produce a huge amount of data since each sample is characterized by a two-way data table. In this paper different ways of obtaining sample-related information from a set of such tables are discussed. Working with original data requires alignment techniques due to time shifts caused by unavoidable variations in separation conditions. Other pre-processing techniques have been suggested to facilitate comparison among samples without prior peak alignment, for example, 'binning' and/or 'blurring' the data along the time dimension. All these techniques, however, require optimization of some parameters, and in this paper an alternative parameter-free method is proposed. The individual data tables (X) are represented as Gram matrices (XXT), where the summation is taken over the time dimension. Hence the possible variations in time scale are eliminated, while the time information is at least partly preserved by the correlation structure between the detection channels. For comparison among samples, a similarity matrix is constructed and explored by principal component analysis and hierarchical clustering. The Gram matrix approach was tested and compared to some other methods using 'binned' and 'blurred' data for a data set with CE-MS runs on urine samples. In addition to data exploration by principal component analysis and hierarchical clustering, a discriminant partial least squares model was constructed to discriminate between the samples that were taken with and without the prior intake of a drug. The result showed that the proposed method is at least as good as the others with respect to cluster identification and class prediction. A distinct advantage is that there is no need for parameter optimization, while a potential drawback is the large size of the Gram matrices for data with high mass resolution.