Hydrophilic interaction ultra performance liquid chromatography retention prediction under gradient elution

Peak shape enhancement using diethylamine in hydrophilic liquid interaction chromatography: Application in simultaneous determination of methionine and paracetamol

Methionine (MET) is combined with paracetamol (PAR) in a pain relief soft capsule in order to prevent the haematologic damage of paracetamol. A hydrophillic liquid chromatographic (HILIC) method was developed for simultaneous determination of PAR and MET in the combined formulation. Various analytical conditions were investigated, and the final method was chosen using silica column (150 × 4,6 mm; 5 μm), mobile phase of acetonitrile - aqueous solution of 10 mM formic acid 5 mM diethylamine (60:40, v/v), UV detection at 254 nm for PAR and 210 nm for MET. The method was validated according to ICH guidelines in terms of selectivity, linearity, accuracy, precision and robustness. The method was successfully applied for quantitation of both compounds in soft capsule preparations bought from the market. Notably, in this study, a novel approach was proposed to improve peak shape of amino acid - a problem often observed in HILIC. The addition of diethylamine to mobile phase shortened the retention time of MET and significantly improved peak shape on both silica and cyano columns, due to electrostatic interaction competition and silanol end-capping effect. The result of this research demonstrated the advantages of HILIC in simultaneous analysis of a polar compound amino acid, especially in combination with a less polar substance. The use of diethylamine as a mobile phase modifier to enhance peak shape is a new suggestion that can be used in further studies on amino acid analysis by HILIC.

FoodOmicsGR_RI. A Consortium for Comprehensive Molecular Characterisation of Food Products

The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of "omics" technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet's effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders.

Use of Untargeted Liquid Chromatography-Mass Spectrometry Metabolome To Discriminate Italian Monovarietal Red Wines, Produced in Their Different Terroirs

The aim of this project was to register, in a liquid chromatography-mass spectrometry-based untargeted single-batch analysis, the metabolome of 11 single-cultivar, single-vintage Italian red wines (Aglianico, Cannonau, Corvina, Montepulciano, Nebbiolo, Nerello, Primitivo, Raboso, Sagrantino, Sangiovese, and Teroldego) from 12 regions across Italy, each one produced in their terroirs under ad hoc legal frameworks to guarantee their quality and origin. The data provided indications regarding the similarity between the cultivars and highlighted a rich list of putative biomarkers of origin wines (pBOWs) characterizing each individual cultivar-terroir combination, where Primitivo, Teroldego, and Nebbiolo had the maximum number of unique pBOWs. The pBOWs included anthocyanins (Teroldego), flavanols (Aglianico, Sangiovese, Nerello, and Nebbiolo), amino acids and N-containing metabolites (Primitivo), hydroxycinnamates (Cannonau), and flavonols (Sangiovese). The raw data generated in this study are publicly available and, therefore, accessible and reusable as a baseline data set for future investigations.

Recent applications of chemometrics in one- and two-dimensional chromatography

The proliferation of increasingly more sophisticated analytical separation systems, often incorporating increasingly more powerful detection techniques, such as high-resolution mass spectrometry, causes an urgent need for highly efficient data-analysis and optimization strategies. This is especially true for comprehensive two-dimensional chromatography applied to the separation of very complex samples. In this contribution, the requirement for chemometric tools is explained and the latest developments in approaches for (pre-)processing and analyzing data arising from one- and two-dimensional chromatography systems are reviewed. The final part of this review focuses on the application of chemometrics for method development and optimization.

Mobile phase effects in reversed-phase and hydrophilic interaction liquid chromatography revisited

Correct adjustment of the mobile phase is equally important as the selection of the appropriate column for the separation of polar compounds in LC. Both solvophobic and selective polar interactions control the retention in the Reversed Phase and Hydrophilic Interaction modes. The retention models describing the effects of the volume fraction of the strong eluent component in binary mobile phases on the sample retention factors apply in a limited mobile phase composition range. We introduced a three-parameter retention model, which provides improved prediction of retention over a broad mobile phase range, under isocratic and gradient elution conditions. The model does not imply any assumptions concerning either adsorption or partition distribution mechanism, but allows estimating retention in pure strong and in pure weak mobile phase components. The experimental retention data for phenolic acids and flavones on several core-shell columns with different types of stationary phases agree with the theory. Many polar columns with important structural hydrophobic moieties show dual retention mechanism, (Reversed Phase in water rich mobile phases and Hydrophilic Interaction at high acetonitrile concentrations). It is possible to select the mobile phase compositions in each of the two modes for separations of samples containing compounds largely differing in polarity. The three-parameter model describes the retention in each mode, with separately determined best-fit parameters. We applied the two-mode model to the retention data of sulfonamides and benzoic acid related compounds on a new polymethacrylate zwitterionic monolithic micro-column.

Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles

Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase we used, column distortion is an important factor to take into account in retention projection in HILIC that is not usually important in RPLC.

A strategy for the targeted metabolomics analysis of 11 gut microbiota-host co-metabolites in rat serum, urine and feces by ultra high performance liquid chromatography-tandem mass spectrometry

Microbiota-host co-metabolites are well-known to play important physiological roles, and their dysregulation has been found to be closely related to various diseases, including but not limited to inflammatory disorders. We developed herein an original and feasible method using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The method developed enables rapid quantification of 11 key gut microbiota-host co-metabolites spanning the succinate, phenylacetylglutamine, hippurate and trimethylamine metabolic pathways within 10 min. With this method, we were able to simultaneously monitor inflammation-induced alterations of these metabolites in rat serum, urine and feces matrices. The measured levels for this panel of endogenous metabolites ranged from 0.001 to 172.8 μg m L(-1). The intra- and inter-day precision of three analytes was less than 13.1% and the accuracy was between -13.0 to 11.2% for all QC levels. The extraction recoveries in serum ranged from 85.4 to 103.2%, while the RSD was 9.0% or less for all recoveries. In addition, extraction recoveries of 11 analytes in urine and feces samples were between 85.7% and 102.0% and RSD was less than 9.5%. The method developed here has been successfully applied to the analysis of real samples from 2,4,6-trinitrobenzenesulfonic acid-induced Crohn's disease in rats. All of these results suggest that the presently developed method is sufficiently sensitive and robust to simultaneously monitor co-metabolites with diverse properties and a range of different concentrations. Therefore, this method will be expected to be useful for comprehensive studies of the pathophysiological roles and mechanisms of these key microbiota-host co-metabolites, which reflect the function of the intestine, consequently offering novel opportunities for evaluating the occurrence, development and therapeutic effects of diseases related to microbiota disturbances.

Recent progress in the fundamental understanding of hydrophilic interaction chromatography (HILIC)

With the exponential growth in the application of the HILIC technique, there has been a significant progress in understanding the fundamental aspects of hydrophilic interaction chromatography.

Quantification of γ-Aminobutyric Acid in Sri Lankan Tea by Means of Ultra Performance Tandem Mass Spectrometry

γ-Aminobutyric acid (GABA), an important bioactive component of tea, acts as a major inhibitory neurotransmitter and is considered to influence other physiological processes in human as well as in planta. In the hereby presented study, the content of this valuable metabolite was investigated in two novel types of Ceylon Tea, explicitly “Silver Tips” and “White Tea”, originating from minimally processed buds of the unique cultivar, “TRI 2043″. The samples were subjected to hot water infusion, equivalent to the traditional beverage preparation procedure, and analyzed by means of hydrophilic interaction ultra performance liquid chromatography coupled to tandem mass spectrometry (HILIC LC-MS/MS). The registered GABA levels were compared with those obtained for the classic “Black Tea” and “Green Tea” samples from Sri Lanka. A high variation of GABA content was observed among the different tea types, especially in the case of “Silver Tips” and “White Tea”, indicating the crucial influence of the manufacturing procedure (processing extent) on the final abundance of the bioactive component of interest. Furthermore, “White Tea” samples boasted the highest GABA concentration reported for this type of tea so far, reaching up to 50% of that characteristic of the high-priced “GABA Tea”. Therefore, “White Tea” and “Silver Tips” were proved to be high quality teas with amounts of γ-aminobutyric acid comparable with those described for similar types before. To our knowledge, this is the first report on HILIC LC-MS/MS application for the quantification of GABA and for in-depth characterization of teas from Sri Lanka.

LC-MS-based holistic metabolic profiling. Problems, limitations, advantages, and future perspectives

The present review aims to critically discuss some of the major problems and limitations of LC-MS based metabolomics as experienced from an analytical chemistry standpoint. Metabolomics offers distinct advantages to a variety of life sciences. Continuous development of the field has been realised due to intensive efforts from a great many scientists from widely divergent backgrounds and research interests as demonstrated by the contents of this special issue. The aim of this commentary is to describe current hindrances to field's progress, (some unique to metabolomics, some common with other omics fields or with conventional targeted bioanalysis) to propose some potential solutions to overcome these constraints and to provide a future perspective for likely developments in the field.

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

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

Mass spectrometric quantification of L-arginine and its pathway related substances in biofluids: the road to maturity

The amino acid L-arginine together with its metabolites and related substances is in the center of many biologically important pathways, especially the urea cycle and the nitric oxide (NO) synthesis. Therefore, the concentrations of these substances in various biological fluids are of great interest as predictive markers for health and disease. Yet, they provide major analytical difficulties as they are very polar in nature and therefore not easily to be separated on standard reversed phase HPLC stationary phases. Furthermore, as endogenous substances, no analyte-free matrix is available, a fact that results in complicated calibration procedures. This review evaluates the analytical literature for the determination of L-arginine, symmetric dimethylarginine, asymmetric dimethylarginine, monomethylarginine, L-citrulline, L-ornithine, L-homoarginine, agmatine and dimethylguanidinovaleric acid in biological fluids. Papers are discussed, which were published since 2007 and describe methods applying capillary electrophoresis (CE), gas chromatography (GC), reversed phase HPLC or polar phase HPLC, coupled to mass spectrometric quantification. Nowadays, many carefully developed and validated methods for L-arginine and its related substances are available to the scientific community. The use of stable isotope labeled internal standards enables high precision and accuracy in mass spectrometry-based quantitative analysis.