Joint MS‐based platforms for comprehensive comparison of rat plasma and serum metabolic profiling

Metabolomics is a rapidly growing field in the comprehensive understanding of cellular and organism‐specific responses associated with perturbations induced by medicines, chemicals and environment. Blood matrices are frequently used in clinical and biological studies. In this study, we compared metabolic profiling between rat plasma and serum using complementary platforms of gas chromatography–mass spectrometry (GC‐MS) and liquid chromatography–quadruple time‐of‐flight–mass spectrometry (LC‐QTOF‐MS). The sample types that were tested included plasma prepared with K₂EDTA and serum collected using venous blood collection protocols. The results of peak area variation for each detected metabolite/feature in the quality control samples showed a good reproducibility in LC‐QTOF‐MS and better reproducibility in GC‐MS. In GC‐MS analysis: (a) 25.8% of the defined metabolites differed serum from plasma profiling (t‐test, p < 0.05); and (b) serum possessed higher sensitivity than plasma for its generally higher peak intensity in the metabolic profiling. In LC‐QTOF‐MS analysis, 13 (in positive ion mode) and seven (in negative ion mode) important metabolites were identified as mainly contributing to the separation between serum and plasma. Copyright © 2014 John Wiley & Sons, Ltd.     

Probing genetic algorithms for feature selection in comprehensive metabolic profiling approach

Six different clones of 1-year-old loblolly pine (Pinus taeda L.) seedlings grown under standardized conditions in a green house were used for sample preparation and further analysis. Three independent and complementary analytical techniques for metabolic profiling were applied in the present study: hydrophilic interaction chromatography (HILIC-LC/ESI-MS), reversed-phase liquid chromatography (RP-LC/ESI-MS), and gas chromatography all coupled to mass spectrometry (GC/TOF-MS). Unsupervised methods, such as principle component analysis (PCA) and clustering, and supervised methods, such as classification, were used for data mining. Genetic algorithms (GA), a multivariate approach, was probed for selection of the smallest subsets of potentially discriminative classifiers. From more than 2000 peaks found in total, small subsets were selected by GA as highly potential classifiers allowing discrimination among six investigated genotypes. Annotated GC/TOF-MS data allowed the generation of a small subset of identified metabolites. LC/ESI-MS data and small subsets require further annotation. The present study demonstrated that combination of comprehensive metabolic profiling and advanced data mining techniques provides a powerful metabolomic approach for biomarker discovery among small molecules. Utilizing GA for feature selection allowed the generation of small subsets of potent classifiers.     

Rapid and quantitative detection of the microbial spoilage in milk using Fourier transform infrared spectroscopy and chemometrics

Microbiological safety plays a very significant part in the quality control of milk and dairy products worldwide. Current methods used in the detection and enumeration of spoilage bacteria in pasteurized milk in the dairy industry, although accurate and sensitive, are time-consuming. FT-IR spectroscopy is a metabolic fingerprinting technique that can potentially be used to deliver results with the same accuracy and sensitivity, within minutes after minimal sample preparation. We tested this hypothesis using attenuated total reflectance (ATR), and high throughput (HT) FT-IR techniques. Three main types of pasteurized milk - whole, semi-skimmed and skimmed - were used and milk was allowed to spoil naturally by incubation at 15 degrees C. Samples for FT-IR were obtained at frequent, fixed time intervals and pH and total viable counts were also recorded. Multivariate statistical methods, including principal components-discriminant function analysis and partial least squares regression (PLSR), were then used to investigate the relationship between metabolic fingerprints and the total viable counts. FT-IR ATR data for all milks showed reasonable results for bacterial loads above 10(5) cfu ml(-1). By contrast, FT-IR HT provided more accurate results for lower viable bacterial counts down to 10(3) cfu ml(-1) for whole milk and, 4 x 10(2) cfu ml(-1) for semi-skimmed and skimmed milk. Using FT-IR with PLSR we were able to acquire a metabolic fingerprint rapidly and quantify the microbial load of milk samples accurately, with very little sample preparation. We believe that metabolic fingerprinting using FT-IR has very good potential for future use in the dairy industry as a rapid method of detection and enumeration.     

Multivariate calibration: What is in chemometrics for the analytical chemist?

Chemometrics has been used for some 30 years but there is still need for disseminating the potential benefits to a wider audience. In this paper, we claim that proper analytical chemistry (1) must in fact incorporate a chemometric approach and (2) that there are several significant advantages of doing so. In order to explain this, an indirect route will be taken, where the most important benefits of chemometric methods are discussed using small illustrative examples. Emphasis will be on multivariate data analysis (for example calibration), whereas other parts of chemometrics such as experimental design will not be treated here. Four distinct aspects are treated in detail: noise reduction; handling of interferents; the exploratory aspect and the possible outlier control. Additionally, some new developments in chemometrics are described.     

Pre-analytical method for NMR-based grape metabolic fingerprinting and chemometrics

Although metabolomics aims at profiling all the metabolites in organisms, data quality is quite dependent on the pre-analytical methods employed. In order to evaluate current methods, different pre-analytical methods were compared and used for the metabolic profiling of grapevine as a model plant. Five grape cultivars from Portugal in combination with chemometrics were analyzed in this study. A common extraction method with deuterated water and methanol was found effective in the case of amino acids, organic acids, and sugars. For secondary metabolites like phenolics, solid phase extraction with C-18 cartridges showed good results. Principal component analysis, in combination with NMR spectroscopy, was applied and showed clear distinction among the cultivars. Primary metabolites such as choline, sucrose, and leucine were found discriminating for ‘Alvarinho’, while elevated levels of alanine, valine, and acetate were found in ‘Arinto’ (white varieties). Among the red cultivars, higher signals for citrate and GABA in ‘Touriga Nacional’, succinate and fumarate in ‘Aragonês’, and malate, ascorbate, fructose and glucose in ‘Trincadeira’, were observed. Based on the phenolic profile, ‘Arinto’ was found with higher levels of phenolics as compared to ‘Alvarinho’. ‘Trincadeira’ showed lowest phenolics content while higher levels of flavonoids and phenylpropanoids were found in ‘Aragonês’ and ‘Touriga Nacional’, respectively. It is shown that the metabolite composition of the extract is highly affected by the extraction procedure and this consideration has to be taken in account for metabolomics studies.     

Biological nanostructures: platforms for analytical chemistry at the sub-zeptomolar level

The analysis and manipulation of molecules at the sub-zeptomolar level (i.e., from 1 to 600 molecules) remains the unconquered frontier of analytical chemistry. While some techniques offer sensitivity to single molecules, there are no established tools for the manipulation of such small quantities of material. Scanning probe lithography has begun to provide practicable means to manipulate biological organisation on length scales of 100 nm and less, and three promising approaches (dip-pen nanolithography, nanoshaving, and scanning near-field photolithography) are reviewed. Each offers extraordinary spatial resolution combined with the capability for use under ambient and, in some cases, fluid conditions. These techniques offer a multitude of strategies that may at last make the manipulation of handfuls of molecules--and perhaps single molecules--a practical possibility for the analytical chemist.     

Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling

Variable scaling alters the covariance structure of data, affecting the outcome of multivariate analysis and calibration. Here we present a new method, variable stability (VAST) scaling, which weights each variable according to a metric of its stability. The beneficial effect of VAST scaling is demonstrated for a data set of ¹H NMR spectra of urine acquired as part of a metabonomic study into the effects of unilateral nephrectomy in an animal model. The application of VAST scaling improved the class distinction and predictive power of partial least squares discriminant analysis (PLS-DA) models. The effects of other data scaling and pre-processing methods, such as orthogonal signal correction (OSC), were also tested. VAST scaling produced the most robust models in terms of class prediction, outperforming OSC in this aspect. As a result the subtle, but consistent, metabolic perturbation caused by unilateral nephrectomy could be accurately characterised despite the presence of much greater biological differences caused by normal physiological variation. VAST scaling presents itself as an interpretable, robust and easily implemented data treatment for the enhancement of multivariate data analysis.     

Metabolomics of colorectal cancer: past and current analytical platforms

Metabolomics is coming of age as an important area of investigation which may help reveal answers to questions left unanswered or only partially understood from proteomic or genomic approaches. Increased knowledge of the relationship of genes and proteins to smaller biomolecules (metabolites) will advance our ability to diagnose, treat, and perhaps prevent cancer and other diseases that have eluded scientists for generations. Colorectal tumors are the second leading cause of cancer mortality in the USA, and the incidence is rising. Many patients present late, after the onset of symptoms, when the tumor has spread from the primary site. Once metastases have occurred, the prognosis is significantly worse. Understanding alterations in metabolic profiles that occur with tumor onset and progression could lead to better diagnostic tests as well as uncover new approaches to treat or even prevent colorectal cancer (CRC). In this review, we explore the various analytical technologies that have been applied in CRC metabolomics research and summarize all metabolites measured in CRC and integrate them into metabolic pathways. Early studies with nuclear magnetic resonance and gas-chromatographic mass spectrometry suggest that tumor cells are characterized by aerobic glycolysis, increased purine metabolism for DNA synthesis, and protein synthesis. Liquid chromatography, capillary electrophoresis, and ion mobility, each coupled with mass spectrometry, promise to advance the field and provide new insight into metabolic pathways used by cancer cells. Studies with improved technology are needed to identify better biomarkers and targets for treatment or prevention of CRC.

CMMSE-17: general analytical laws for metabolic pathways

In this paper a general formulation for the kinetics of multi-step enzymatic reactions is presented. The optimal enzyme and metabolite concentrations are studied for the problem of minimizing the operation time in which the substrate is converted into the product. We give an analytic solution for three different kinetic models for both the unbranched and branched cases. Sufficient conditions for the optimality of the solution are studied. Several examples are presented.     

Coupling chemometrics and electrochemical-based sensor for detection of bacterial population

This work describes a home-made microelectrode array, based on reticulated vitreous carbon, which has been used to record the normal pulse voltammograms with the aim of obtaining the growth curves of Escherichia coli ATCC 13706 and Pseudomonas aeruginosa ATCC 27853 chosen as test microorganisms. The electrochemical signal data have been analysed with partial least squares (PLS) regression in order to highlight the useful analytical information and correlate with the data obtained from the aerobic plate counting. The obtained PLS models generally had a low root mean square error of cross-validation (RMSECV), a cross validated explained variance percentage near 90%.     

GC-MS detection of central nervous tissues as TSE risk material in meat products: analytical quality and strategy

The detection of central nervous system (CNS) tissue (i.e. brain and spinal cord) by the use of GC-MS and certain fatty acids (FAs) as their methyl esters (FAMEs) was previously shown to be a very promising approach towards identification of CNS tissue as a specified risk material (SRM) in meat products, contrasting available immunochemical methods. This GC-MS method promised to allow quantification of CNS material as low as 0.01%. Here, we show that the CNS-relevant FAMEs C22:6, C24:19, C24:17, C24:0 and C24-OH are present in pure muscle and adipose tissue samples in detectable amounts. Thus, limits of detection are not feasible as quality parameters in this analytical GC-MS approach. Instead, cut-off values have to be applied as calculated from the baseline content of the respective FAME in CNS-free samples and its variation for a given statistical security. Furthermore, the FAs used for quantification of the CNS showed distinct differences depending on species and age. This finding is in accordance with previous studies where it had been concluded that species and age differentiation of CNS might be possible with GC-MS. However, it was not taken into account that it also necessitates a strict analytical strategy for quantification of the CNS content: identification of the presence of CNS (step 1); identification of species and age (step 2); and quantification by use of a species- and age-specific CNS calibration (step 3). Differences between the FA content of the CNS used for calibrating and the CNS in the sample will cause up to fivefold deviation from the true CNS content. Our results show that the FA best suited for identification (step 1) and quantification (step 3) purposes is cerebronic acid C24-OH after silylation. Further in-depth studies are needed in order to elucidate variability of brain FA content and to determine analytical limits. However, the present GC-MS approach is already a highly promising supplement to existing immunochemical methods for the detection of traces of CNS material in meat products.     

Quantitative profiling of oxylipins through comprehensive LC-MS/MS analysis: application in cardiac surgery

Oxylipins, including eicosanoids, affect a broad range of biological processes, such as the initiation and resolution of inflammation. These compounds, also referred to as lipid mediators, are (non-) enzymatically generated by oxidation of polyunsaturated fatty acids such as arachidonic acid (AA). A plethora of lipid mediators exist which makes the development of generic analytical methods challenging. Here we developed a robust and sensitive targeted analysis platform for oxylipins and applied it in a biological setting, using high performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) operated in dynamic multiple reaction monitoring (dMRM). Besides the well-described AA metabolites, oxylipins derived from linoleic acid, dihomo-γ-linolenic acid, α-linolenic acid, eicosapentaenoic acid and docosahexaenoic acid were included. Our comprehensive platform allows the quantitative evaluation of approximately 100 oxylipins down to low nanomolar levels. Applicability of the analytical platform was demonstrated by analyzing plasma samples of patients undergoing cardiac surgery. Altered levels of some of the oxylipins, especially in certain monohydroxy fatty acids such as 12-HETE and 12-HEPE, were observed in samples collected before and 24 h after cardiac surgery. These findings indicate that this generic oxylipin profiling platform can be applied broadly to study these highly bioactive compounds in relation to human disease.     

Contactless conductivity detection for analytical techniques: Developments from 2016 to 2018

The publications concerning capacitively coupled contactless conductivity detection for the 2‐year period from mid‐2016 to mid‐2018 are covered in this update to the earlier reviews of the series. Relatively few reports on fundamental investigations or new designs have appeared in the literature in this time interval, but the development of new applications with the detection method has continued strongly. Most often, contactless conductivity measurements have been employed for the detection of inorganic or small organic ions in conventional capillary electrophoresis, less often in microchip electrophoresis. A number of other uses, such as detection in chromatography or the gauging of bubbles in streams have also been reported.     

Cyclodextrin-based nonaqueous electrokinetic chromatography with UV and mass spectrometric detection: application to the impurity profiling of amiodarone

The potential of nonaqueous electrokinetic chromatography (NAEKC) using cyclodextrins (CD) for the analysis of basic drugs and related compounds was evaluated. Both UV absorbance and mass spectrometric (MS) detection were employed. Addition of neutral CD to the NA background electrolyte did not significantly enhance the separation of a test mixture of basic drugs, and no change in selectivity was observed. In contrast, anionic single-isomer-sulfated CD strongly added to the selectivity of the NAEKC system inducing an improved resolution among the test compounds and increasing the migration time window. The applicability of the NAEKC system using anionic CD is demonstrated by the profiling of a sample of the drug amiodarone that had been stored for 1 year at room temperature. Amiodarone is poorly soluble in water. NAEKC-UV analysis indicated the presence of at least seven impurities in the amiodarone sample. In order to identify these compounds, the NAEKC system was coupled directly to electrospray ionization (ESI) ion-trap MS. The total of detected impurities increased to 12 due to the added sensitivity and selectivity of MS detection. Based on the acquired MS/MS data, three sample constituents could be identified as 'known' impurities (British Pharmacopoeia), whereas for three unknown impurities molecular structures could be proposed. Estimated limits of detection for amiodarone using the NAEKC method were 1 microg/mL with UV detection and 15 ng/mL with ESI-MS detection (full-scan). Based on relative responses, the impurity content of the stored drug substance was estimated to be 0.33 and 0.47% using NAEKC-UV and NAEKC-ESI-MS, respectively.     

Automated peak tracking for comprehensive impurity profiling in orthogonal liquid chromatographic separation using mass spectrometric detection

The presence and quantity of impurities in pharmaceutical drugs can have a significant impact on their quality and safety. With the continuous pressure for increased industry productivity, there is urgent need for a systematic and comprehensive drug impurity profiling strategy. We report here our development of the fully automated Comprehensive Orthogonal Method Evaluation Technology (COMET) system. The system includes five columns, seven orthogonal HPLC methods, and hyphenated UV-MS detections, which provides automated generic impurities screening for any drug sample. An automated MS peak tracking approach by program-based mass spectral interpretation is devised to unambiguously track impurities among all orthogonal HPLC methods. The program passes electro-spray ionization mass spectra (ESI-MS) through four sequential decision-making mass ion tests and determines molecular weights for every peak. The system reduces the time required to obtain impurity profile from weeks to days, while the automated MS peak tracking takes only minutes to interpret all MS spectral data of interest. Up-to-date, impurity contents of 56 in-development drug candidate samples have all been successfully illustrated by COMET, which contained more than 500 chemical entities. The program is able to track more than 80% of the compounds automatically with majority of the failure due to insufficient ionization for some impurities by ESI. This system is well suited for efficient drug development and ensuring the quality and safety of drug products.     

A fluorescence detection system for the analytical ultracentrifuge and its application to proteins,nucleic acids,and viruses

A fluorescence detection system was developed for the analytical ultracentrifuge Spinco model E. Fluorescence is excited by a laser beam which is focussed into the cell and illuminates an area with a dimension of 60 m in radial direction. For scanning the laser beam is moved in radial direction. After passing the cell, the laser beam is quenched by a carbon light trap and a set of optical filters. Fluorescence emission intensity is monitored by a photomultiplier located behind the light trap and the set of filters. The sensitivity of the detection system was tested by applying it to the sedimentation analysis of proteins and nucleic acids. Bovine serum albumin (BSA) was covalently labelled with the fluorescence-dye fluorescein-isothiocyanate (FITC), and its sedimentation coefficient could be determined even if BSA was analyzed in a concentration as low as 10^–10 M. Nucleic acids were labelled non-covalently by the intercalating dye ethidium bromide. Only 8 ng RNA were needed for the determination of the sedimentation coefficient. The particular advantages of the fluorescence detection system were exploited for the establishment of a new method for quantitative virus detection. To tobacco mosaic virus (TMV) a monoclonal anti-TMV antibody from mouse was bound, and to this a second, anti-mouse antibody that carried the fluorescence-label FITC was attached. Either by UV-irradiation or by incubation with glutaraldehyde, the first antibody was covalently crosslinked to TMV, and the second antibody to the first. In CsCl density centrifugation with fluorescence detection as little as 3.2 ng virus/80 l or 6×10⁸ virus particles/ml were recorded in a well expressed band at the corresponding buoyant density. Tenfold lower concentration would result still in a significant band. The sensitivity compares well with those of the most advanced techniques from immunology. Due to the specific labelling of viruses by antibodies it will be possible to carry out quantitative physical characterization of virus containing samples without purifying the virus. Future applications of the fluorescence detection system and of the virus detection technique are discussed.This paper was presented at the VI. Symposium on Analytical Ultracentrifugation, Marburg, FRG, February 16–17, 1989.     

High throughput physical organic chemistry: analytical constructs for monomer reactivity profiling

A polymer-supported analytical construct was used to quantify the reactivity of a range of monomers in the Ugi four-component condensation using positive electrospray ionization mass spectrometry (MS) as a quantitative analytical tool. The construct incorporated a bromo group to act as a peak splitter and a quaternary ammonium to act as a MS sensitizer and ionization leveler, thereby allowing direct quantitation of the cleaved adducts by MS. The relative reactivities of 10 carboxylic acids were quantified by the relative levels of product generated as determined by MS and 10 isonitriles, and 10 aldehydes were investigated in the same way. The effect of concentration variations on monomers reactivity and product profiles were rapidly determined using this approach, and the method opens up the way for studying, in a single pot, multiple reactions with a broad range of monomers under identical and self-consistent reaction conditions.     

Review: Microfluidic applications in metabolomics and metabolic profiling

Metabolomics is an emerging area of research focused on measuring small molecules in biological samples. There are a number of different types of metabolomics, ranging from global profiling of all metabolites in a single sample to measurement of a selected group of analytes. Microfluidics and related technologies have been used in this research area with good success. The aim of this review article is to summarize the use of microfluidics in metabolomics. Direct application of microfluidics to the determination of small molecules is covered first. Next, important sample preparation methods developed for microfluidics and applicable to metabolomics are covered. Finally, a summary of metabolomic work as it relates to analysis of cellular events using microfluidics is covered.