High temperature-ultra performance liquid chromatography-mass spectrometry for the metabonomic analysis of Zucker rat urine

Gas explosion-induced acute blast lung injury assessment and biomarker identification by a LC-MS-based serum metabolomics analysis

The objective of this study was to evaluate the histopathological effect of gas explosion on rats, and to explore the metabolic alterations associated with gas explosion-induced acute blast lung injury (ABLI) in real roadway environment using metabolomics analyses. All rats were exposed to the gas explosion source at different distance points (160 m and 240 m) except the control group. Respiratory function indexes were monitored and lung tissue analysis was performed to correlate histopathological effect to serum metabolomics. Their sera samples were collected to measure the metabolic alterations by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). HE staining in lung showed that the gas explosion caused obvious inflammatory pulmonary injury, which was consistent with respiratory function monitoring results and the serum metabolomics analysis results. The metabolomics identified 9 significantly metabolites different between the control- and ABLI rats. 2-aminoadipic acid, L-methionine, L-alanine, L-lysine, L-threonine, cholic acid and L-histidine were significantly increased in the exposed groups. Citric acid and aconitic acid were significantly decreased after exposure. Pathway analyses identified 8 perturbed metabolic pathways, which provided novel potential mechanisms for the gas explosion-induced ABLI. Therefore, metabolomics analysis identified both known and unknown alterations in circulating biomarkers, adding an integral mechanistic insight into the gas explosion-induced ABLI in real roadway environment.

Application of High Resolution Mass Spectrometric methods coupled with chemometric techniques in olive oil authenticity studies - A review

Extra Virgin Olive Oil (EVOO), the emblematic food of the Mediterranean diet, is recognized for its nutritional value and beneficial health effects. The main authenticity issues associated with EVOO's quality involve the organoleptic properties (EVOO or defective), mislabeling of production type (organic or conventional), variety and geographical origin, and adulteration. Currently, there is an emerging need to characterize EVOOs and evaluate their genuineness. This can be achieved through the development of analytical methodologies applying advanced "omics" technologies and the investigation of EVOOs chemical fingerprints. The objective of this review is to demonstrate the analytical performance of High Resolution Mass Spectrometry (HRMS) in the field of food authenticity assessment, allowing the determination of a wide range of food constituents with exceptional identification capabilities. HRMS-based workflows used for the investigation of critical olive oil authenticity issues are presented and discussed, combined with advanced data processing, comprehensive data mining and chemometric tools. The use of unsupervised classification tools, such as Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA), as well as supervised classification techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Partial Least Square Discriminant Analysis (PLS-DA), Orthogonal Projection to Latent Structure-Discriminant Analysis (OPLS-DA), Counter Propagation Artificial Neural Networks (CP-ANNs), Self-Organizing Maps (SOMs) and Random Forest (RF) is summarized. The combination of HRMS methodologies with chemometrics improves the quality and reliability of the conclusions from experimental data (profile or fingerprints), provides valuable information suggesting potential authenticity markers and is widely applied in food authenticity studies.

Untargeted LC/MS-based metabolic phenotyping (metabonomics/metabolomics): The state of the art

Liquid chromatography (LC) hyphenated to mass spectrometry is currently the most widely used means of determining metabolic phenotypes via both untargeted and targeted analysis. At present a range of analytical separations, including reversed-phase, hydrophilic interaction and ion-pair LC are employed to maximise metabolome coverage with ultra (high) performance liquid chromatography (UHPLC) increasingly displacing conventional high performance liquid chromatography because of the need for short analysis times and high peak capacity in such applications. However, it is widely recognized that these methodologies do not entirely solve the problems facing researchers trying to perform comprehensive metabolic phenotyping and in addition to these "routine" approaches there are continuing investigations of alternative separation methods including 2-dimensional/multi column approaches. These involve either new stationary phases or multidimensional combinations of the more conventional materials currently used, as well as application of miniaturization or "new" approaches such as supercritical HP and UHP- chromatographic separations. There is also a considerable amount of interest in the combination of chromatographic and ion mobility separations, with the latter providing both an increase in resolution and the potential to provide additional structural information via the determination of molecular collision cross section data. However, key problems remain to be solved including ensuring quality, comparability across different laboratories and the ever present difficulty of identifying unknowns.

Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets.

Relative quantification of amine-containing metabolites using isobaric N,N-dimethyl leucine (DiLeu) reagents via LC-ESI-MS/MS and CE-ESI-MS/MS

Tandem mass spectrometry (MS/MS)-based relative quantification by isobaric labeling is a useful technique to compare different metabolic expression levels in biological systems. For the first time, we have labeled primary and secondary amine-containing small molecules using 4-plex isobaric N,N-dimethyl leucine (DiLeu) to perform relative quantification. Good labeling efficiency and quantification accuracy were demonstrated with a mixture of 12 metabolite standards including amino acids and small molecule neurotransmitters. Labeling amine-containing metabolites with DiLeu reagents also enabled the separation of polar metabolites by nanoRPLC and improved the detection sensitivity by CE-ESI-MS. The 4-plex DiLeu labeling technique combined with LC-MS/MS and CE-MS/MS platforms were applied to profile and quantify amine-containing metabolites in mouse urine. The variability of concentrations of identified metabolites in urine samples from different mouse individuals was illustrated by the ratios of reporter ion intensities acquired from online data-dependent analysis.

Plasma metabolomic profiling of patients with diabetes-associated cognitive decline

Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of DACD remain somewhat elusive. To understand the pathophysiological changes that underpin the development and progression of DACD, we carried out a global analysis of metabolic alterations in response to DACD. The metabolic alterations associated with DACD were first investigated in humans, using plasma metabonomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. The related pathway of each metabolite of interest was searched in database online. The network diagrams were established KEGGSOAP software package. Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic accuracy of metabolites. This is the first report of reliable biomarkers of DACD, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of DACD. The disorders of sphingolipids metabolism, bile acids metabolism, and uric acid metabolism pathway were found in T2DM and DACD. On the other hand, differentially expressed plasma metabolites offer unique metabolic signatures for T2DM and DACD patients. These are potential biomarkers for disease monitoring and personalized medication complementary to the existing clinical modalities.

Metabolomics in the developmental origins of obesity and its cardiometabolic consequences

In this review, we discuss the potential role of metabolomics to enhance understanding of obesity-related developmental origins of health and disease (DOHaD). We first provide an overview of common techniques and analytical approaches to help interested investigators dive into this relatively novel field. Next, we describe how metabolomics may capture exposures that are notoriously difficult to quantify, and help to further refine phenotypes associated with excess adiposity and related metabolic sequelae over the life course. Together, these data can ultimately help to elucidate mechanisms that underlie fetal metabolic programming. Finally, we review current gaps in knowledge and identify areas where the field of metabolomics is likely to provide insights into mechanisms linked to DOHaD in human populations.

WITHDRAWN: Recent advances in chemometric methods for plant metabolomics: A review

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Liquid Chromatographic Techniques in Metabolomics

In the past decade, LC‐MS‐based metabolomic/metabonomic profiling has become a major analytical focus for biomarker research. Chromatographic resolution is continually improving with the development of more advanced separation platforms based on smaller particle sizes, new types of stationary phase and miniaturized systems allowing the profiling of biological samples for metabolites in ways that were simply not possible before. Chromatographic advances, combined with increased mass resolution instruments that provide sub‐2 ppm mass accuracy and high sensitivity, have greatly facilitated the detection and identification of potential biomarkers. In this chapter, the most common LC(‐MS) methods utilized in metabolic analyses are presented, with emphasis on novel high‐efficiency and high‐throughput analyses and their suitability for metabolic analyses. Guidelines for the selection of the appropriate method for different applications are given, with emphasis on the use of LC‐MS.

Chemical profiles and identification of key compound caffeine in marine-derived traditional Chinese medicine Ostreae concha

To compare the chemical differences between the medicinal and cultured oyster shells, their chemical profiles were investigated. Using the ultra performance liquid chromatography-electron spraying ionization-mass spectrometry (UPLC-ESI-MS), combined with principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA), the discrimination of the chemical characteristics among the medicinal and cultured oyster shells was established. Moreover, the chemometric analysis revealed some potential key compounds. After a large-scale extraction and isolation, one target key compound was unambiguously identified as caffeine (1) based on extensive spectroscopic data analysis (1D and 2D NMR, MS, and UV) and comparison with literature data.

Metabolomic analysis of rat serum in streptozotocin-induced diabetes and after treatment with oral triethylenetetramine (TETA)

Background

The prevalence, and associated healthcare burden, of diabetes mellitus is increasing worldwide. Mortality and morbidity are associated with diabetic complications in multiple organs and tissues, including the eye, kidney and cardiovascular system, and new therapeutics to treat these complications are required urgently. Triethylenetetramine (TETA) is one such experimental therapeutic that acts to chelate excess copper (II) in diabetic tissues and reduce oxidative stress and cellular damage.

Methods

Here we have performed two independent metabolomic studies of serum to assess the suitability of the streptozotocin (STZ)-induced rat model for studying diabetes and to define metabolite-related changes associated with TETA treatment. Ultraperformance liquid chromatography-mass spectrometry studies of serum from non-diabetic/untreated, non-diabetic/TETA-treated, STZ-induced diabetic/untreated and STZ-induced diabetic/TETA-treated rats were performed followed by univariate and multivariate analysis of data.

Results

Multiple metabolic changes related to STZ-induced diabetes, some of which have been reported previously in other animal and human studies, were observed, including changes in amino acid, fatty acid, glycerophospholipid and bile acid metabolism. Correlation analysis suggested that treatment with TETA led to a reversal of diabetes-associated changes in bile acid, fatty acid, steroid, sphingolipid and glycerophospholipid metabolism and proteolysis.

Conclusions

Metabolomic studies have shown that the STZ-induced rat model of diabetes is an appropriate model system to undertake research into diabetes and potential therapies as several metabolic changes observed in humans and other animal models were also observed in this study. Metabolomics has also identified several biological processes and metabolic pathways implicated in diabetic complications and reversed following treatment with the experimental therapeutic TETA.

Applications of mass spectrometry to metabolomics and metabonomics: detection of biomarkers of aging and of age-related diseases

Every 5 years or so new technologies, or new combinations of old ones, seemingly burst onto the science scene and are then sought after until they reach the point of becoming commonplace. Advances in mass spectrometry instrumentation, coupled with the establishment of standardized chemical fragmentation libraries, increased computing power, novel data-analysis algorithms, new scientific applications, and commercial prospects have made mass spectrometry-based metabolomics the latest sought-after technology. This methodology affords the ability to dynamically catalogue and quantify, in parallel, femtomole quantities of cellular metabolites. The study of aging, and the diseases that accompany it, has accelerated significantly in the last decade. Mutant genes that alter the rate of aging have been found that increase lifespan by up to 10-fold in some model organisms, and substantial progress has been made in understanding fundamental alterations that occur at both the mRNA and protein level in tissues of aging organisms. The application of metabolomics to aging research is still relatively new, but has already added significant insight into the aging process. In this review we summarize these findings. We have targeted our manuscript to two audiences: mass spectrometrists interested in applying their technical knowledge to unanswered questions in the aging field, and gerontologists interested in expanding their knowledge of both mass spectrometry and the most recent advances in aging-related metabolomics.

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.

Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry

BACKGROUND

The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study.

METHODS

The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB.

RESULTS

Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on the chromatograms.

CONCLUSIONS

N-acetyl-L-leucine is an endogenous compound included in all biological specimens (plasma, hair, liver and kidney). Therefore, this metabolite appears to be a potential biomarker candidate related to diabetes. Although the structures of other biomarker candidates have still not yet determined, the present approach based upon a metabolite profiling study using UPLC-ESI-TOF-MS could be helpful for understanding the abnormal state of various diseases.

Practical analytical approach for the identification of biomarker candidates in prediabetic state based upon metabonomic study by ultraperformance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry

The number of diabetic patients has recently been increasing worldwide. Thus, the discovery of potential diabetic biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, is strongly required. The diagnosis of the prediabetic state in humans is a very difficult issue because of the lifestyle differences in each person and ethical consideration. Upon the basis of these considerations, animal experiments using ddY strain mice (ddY-H), which undergo naturally occurring diabetes along with age, were carried out in this study. Biomarker discovery based upon a metabonome study is now quite common, the same as that in the proteome analysis. Reversed-phase liquid chromatography-mass spectrometry (LC-MS) has mainly been used for the extensive analysis of low-molecular mass compounds including metabolites. The metabolites in the plasma of diabetic mice (ddY-H) and normal mice (ddY-L) were exhaustively separated and detected by ultraperformance liquid chromatography along with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS) using T3-C18 and HS-F5 columns. The biomarker candidates related to diabetes mellitus were extracted from the metabolite profiling of ddY-H and ddY-L at 5, 9 13, and 20 weeks old using a multivariate statistical analysis such as orthogonal partial least-squares-discriminant analysis (OPLS-DA). Various metabolites and unknown compounds were detected as biomarker candidates related to diabetic mellitus. Furthermore, the concentration of several metabolites on Lysine biosynthesis and Lysine degradation pathways were remarkably changed between the 9-week old ddY-H and ddY-L mice. Because a couple of biomarker candidates related to the prediabetic state were identified using the present approach, the metabolite profiling study could be helpful for understanding the abnormal state of various diseases.

Chromatography with higher pressure, smaller particles and higher temperature: a bioanalytical perspective

Recent years have seen widespread use of ultra-high-pressure liquid chromatography (UHPLC) in biological fluids. Most commonly the emphasis is on developing high throughput assay methods to reduce the analysis time and cost. Particle size and temperature are chromatographic parameters that can be changed to improve efficiency and obtain rapid separations. UHPLC and high-temperature liquid chromatography (HTLC) are two techniques that reduce the analysis time by decreasing the size of the column packing material and increasing the column temperature, respectively. Both of these techniques have advantages and limitations. In this article we have summarized the history, theoretical background of UHPLC and HTLC and the various advantages and limitations of sample preparation techniques and the detection systems (mass spectrometry and ultraviolet) used for the bioanalytical assays. In addition, selected bioanalytical applications of the two techniques have been reviewed and tabulated.

Global metabolic profiling procedures for urine using UPLC-MS

The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

Metabonomics study of urine and plasma in depression and excess fatigue rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry

A novel metabonomic method based on fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC/MS-IT-TOF) was applied to study the metabolic changes of plasma and urine in depression and excess fatigue rats. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied for classifying the depression, excess fatigue and the control rats. Metabolites which were important for the classification in the three groups of rats were selected as potential biomarkers and identified by MS(n) information achieved from UFLC/MS-IT-TOF analysis. Spermine, propionylcarnitine, butyrylcarnitine, phenylalanine, lysophosphatidylcholine (LPC) C14:0 and LPC C18:2 were down-regulated, methyl-hippuric acid and chenodeoxycholic acid (CDCA) were up-regulated significantly in plasma of the excess fatigue rats. Spermine, leucine, propionylcarnitine, and butyrylcarnitine decreased, hippuric acid, methyl-hippuric acid, cholic acid, CDCA and LPC C16:0 increased markedly in plasma of the depression rats. Ethyl N2-acetyl-L-argininate and N-methyl-2-pyridone-5-carboxamide (2-PY) (or N-methyl-4-pyridone-3-carboxamide (4-PY)) were down-regulated, leucylproline and pantothenic acid were up-regulated remarkably both in urine of depression and excess fatigue rats. The concentration of kynurenic acid and N2-succinyl-L-ornithine was low in urine of depression rats compared with control rats. Based on the data, correlation networks for depression and excess fatigue rats revealed the abnormality of nicotinate and nicotinamide metabolism, arginine metabolism, cholesterol metabolism, tryptophan metabolism and kynurenine metabolism in depression rats, and in excess fatigue rat alterations of energy metabolism, nicotinate and nicotinamide metabolism and lecithin metabolism. Our results provide novel insights in the complex metabolic mechanisms occurring in depression and excess fatigue rats.

An introduction to liquid chromatography-mass spectrometry instrumentation applied in plant metabolomic analyses

Over the past decade the application of non-targeted high-throughput metabolomic analysis within the plant sciences has gained ever increasing interest and has truly established itself as a valuable tool for plant functional genomics and studies of plant biochemical composition. Whilst proton nuclear magnetic resonance ((1)H-NMR) spectroscopy is particularly appropriate for the analysis of bulk metabolites and gas chromatography mass spectrometry (GC-MS) to the analysis of volatile organic compounds (VOC's) and derivatised primary metabolites, liquid chromatography (LC)-MS is highly applicable to the analysis of a wide range of semi-polar compounds including many secondary metabolites of interest to plant researchers and nutritionists. In view of the recent developments in the separation sciences, leading to the advent of ultra high performance liquid chromatography (UHPLC) and MS based technology showing the ever improving resolution of metabolite species and precision of mass measurements (sub-ppm accuracy now being achievable), this review sets out to introduce the background and update the reader upon LC, high performance (HP)LC and UHPLC, as well as the large range of MS instruments that are being applied in current plant metabolomic studies. As well as covering the theory behind modern day LC-MS, the review also discusses the most relevant metabolomics applications for the wide range of MS instruments that are currently being applied to LC.

The potential of mass spectrometry for the global profiling of parasite metabolomes

The strengths and limitations of existing mass spectrometry methods for metabolite detection and identification are discussed. A brief review is made of the methods available for quenching and extraction of cells or organisms prior to instrumental analysis. The techniques available for carrying out mass spectrometry-based profiling of metabolomes are discussed using the analysis of extracts from trypanosomes to illustrate various points regarding methods of separation and mass spectrometric analysis. The advantages of hydrophilic interaction chromatography (HILIC) for the analysis of polar metabolites are discussed. The challenges of data processing are outlined and illustrated using the example of ThermoFisher's Sieve software. The existing literature on applications of mass spectrometry to the profiling of parasite metabolomes is reviewed.

Application of ultra performance liquid chromatography-mass spectrometry to profiling rat and dog bile

Reversed-phase gradient UPLC-ESI-MS, in both positive and negative ionization modes, has been applied to the analysis of untreated bile obtained from bile-cannulated rats and dogs. The use of UPLC provided a high-resolution system that enabled global metabolite profiles of bile from the two species to be obtained that were suitable for metabolomic and metabonomic applications. When these metabolite profiles were analyzed using unsupervised multivariate statistical methods, based on principle components analysis (PCA), they were correctly classified by species of origin. Conventional approaches to characterizing sample components via, for example, mass and retention time compared to authentic standards resulted in the identification of a range of bile acids. In addition, the value of using an "MSE" approach to simplify the problem of classifying and identifying the metabolites present in the sample (as e.g., sulfates or taurine conjugates) was demonstrated.

Metabonomics research of diabetic nephropathy and type 2 diabetes mellitus based on UPLC-oaTOF-MS system

Ultra performance liquid chromatography (UPLC) coupled with orthogonal acceleration time-of-flight (oaTOF) mass spectrometry has showed great potential in diabetes research. In this paper, a UPLC-oaTOF-MS system was employed to distinguish the global serum profiles of 8 diabetic nephropathy (DN) patients, 33 type 2 diabetes mellitus (T2DM) patients and 25 healthy volunteers, and tried to find potential biomarkers. The UPLC system produced information-rich chromatograms with typical measured peak widths of 4 s, generating peak capacities of 225 in 15 min. Furthermore, principal component analysis (PCA) was used for group differentiation and marker selection. As shown in the scores plot, the distinct clustering between the patients and controls was observed, and DN and T2DM patients were also separated into two individual groups. Several compounds were tentatively identified based on accurate mass, isotopic pattern and MS/MS information. In addition, significant changes in the serum level of leucine, dihydrosphingosine and phytosphingosine were noted, indicating the perturbations of amino acid metabolism and phospholipid metabolism in diabetic diseases, which having implications in clinical diagnosis and treatment.

Metabonomic study of biochemical changes in the serum of type 2 diabetes mellitus patients after the treatment of metformin hydrochloride

A metabonomic study on biochemical changes in the serum of type 2 diabetes mellitus patients after the treatment of metformin hydrochloride was performed. (1)H NMR and UPLC/MS were used to generate metabolic fingerprints for the metabonomic analysis of serum samples obtained from 20 type 2 diabetes mellitus patients without any drugs treatment and 15 type 2 diabetes mellitus patients treated with metformin hydrochloride for 3 months. The resulting data were subjected to chemometric analysis (principal component analysis and partial least squares discriminant analysis) to investigate the effect of metformin hydrochloride on serum metabolite profiles of type 2 diabetes mellitus patients. (1)H NMR spectroscopic analysis revealed increased trimethylamine-N-oxide (TMAO), 3-hydroxybutyrate (3-HB) and decreased glucose, N-acetyl glycoprotein (NAC), lipoprotein, lactate, acetoacetate and unsaturated lipids in serum from metformin treated patients compared to untreated ones. UPLC/MS in positive electrospray ionization detected increased tryptophan and decreased lysophosphatidylcholines (C16:0 LPC, C18:0 LPC and C18:2 LPC) as well as phenylalanine in treated group. Both analytical techniques used in this study were able to detect biochemical changes in the serum of type 2 diabetes mellitus patients after the treatment of metformin hydrochloride, which may be helpful to the understanding of action mechanism of metformin hydrochloride.

Chromatography in industry

This review focuses on the chromatography research that has been carried out within industry or in close cooperation with industry and that has been reported in the scientific literature between 2006 and mid-2008. Companies in the health care sector, such as pharmaceutical and biotechnology companies, are the largest contributors. Industrial research seems to take place in an open environment in cooperation with academia, peer companies, and institutions. Industry appears ready to embrace new technologies as they emerge, but they focus strongly on making chromatography work robustly, reliably, rapidly, and automatically. "Hyphenated" systems that incorporate on-line sample-preparation techniques and mass-spectrometric detection are the rule rather than the exception. Various multidimensional separation methods are finding numerous applications. Strategies aimed at speeding up the development of new chromatographic methods remain the focus of attention. Also, there is a clear trend toward exploring chromatographic methods for parallel processing along with other strategies for high-throughput analysis.