Comparison of different liquid chromatography stationary phases in LC-HRMS metabolomics for the detection of recombinant growth hormone doping control

Growth hormone (GH) is a polypeptide suspected of being used in horse racing to speed up physical performances. Despite scientific advances in the recent years, the control of its administration remains difficult. In order to improve it, a metabolomics study through LC-high resolution mass spectrometry measurements was recently initiated to assess the metabolic perturbations caused by recombinant equine growth hormone administration. Few tens of ions not identified structurally were highlighted as compounds responsible for the modification of metabolic profiling observed in treated animals. This previous work was based on the use of Uptisphere Strategy NEC as the chromatographic column. In parallel, more and more metabolomics studies showed the interest of the use of new chromatographic supports such as hydrophilic interaction chromatography for the analysis of polar compounds. It is in this context that an investigation was conducted on Uptisphere HDO and Luna hydrophilic interaction chromatography stationary phases to generate and process urinary metabolomics fingerprints, which could allow to establish a comparison with Uptisphere Strategy NEC. The chromatographic column the most adapted for the detection of new biomarkers of GH administration has been used to set up a relevant statistical model based on the analysis of more than hundred biological samples.     

Current status of retention time prediction in metabolite identification

Metabolite identification is a crucial step in nontargeted metabolomics, but also represents one of its current bottlenecks. Accurate identifications are required for correct biological interpretation. To date, annotation and identification are usually based on the use of accurate mass search or tandem mass spectrometry analysis, but neglect orthogonal information such as retention times obtained by chromatographic separation. While several tools are available for the analysis and prediction of tandem mass spectrometry data, prediction of retention times for metabolite identification are not widespread. Here, we review the current state of retention time prediction in liquid chromatography–mass spectrometry‐based metabolomics, with a focus on publications published after 2010.     

The Short and Long of it: Shorter Chromatographic Analysis Suffice for Sample Classification During UHPLC-MS-Based Metabolic Fingerprinting

Ultra high-performance liquid chromatography hyphenated to mass spectrometry (UHPLC-MS) technologies has been widely applied in metabolomics, and the high resolution and peak capacity thereof are only some of the key aspects that are exploited in such and related fields. In the current study, we investigated if low resolution chromatography, with the aid of multivariate data analyses, could be sufficient for a metabolic fingerprinting study that aims at discriminating between samples of different biological status or origin. UHPLC-MS data from chemically-treated Arabidopsis thaliana plants were used and chromatograms with different gradient lengths were compared. MarkerLynx? technology was employed for data mining, followed by principal component analysis (PCA) and orthogonal projections to latent structure discriminant analysis (OPLS-DA) as multivariate statistical interpretations. The results showed that, despite the congestion in low resolution chromatograms (of 5 and 10 min), samples could be classified based on their respective biological background in a similar manner as when using chromatograms with better resolution (of 20 and 40 min). This paper thus underlines that, in a metabolic fingerprinting study, low resolution chromatography together with multivariate data analyses suffice for biological classification of samples. The results also suggest that, depending on the initial objective of the undertaken study, optimisation in chromatographic resolution prior to full scale metabolomics studies is mandatory.     

CE‐MS for metabolomics: Developments and applications in the period 2016–2018

In the field of metabolomics, CE‐MS is now recognized as a strong analytical technique for the analysis of (highly) polar and charged metabolites in a wide range of biological samples. Over the past few years, significant attention has been paid to the design and improvement of CE‐MS approaches for (large‐scale) metabolic profiling studies and for establishing protocols in order to further expand the role of CE‐MS in metabolomics. In this paper, which is a follow‐up of a previous review paper covering the years 2014–2016 (Electrophoresis 2017, 38, 190–202), main advances in CE‐MS approaches for metabolomics studies are outlined covering the literature from July 2016 to June 2018. Aspects like developments in interfacing designs and data analysis tools for improving the performance of CE‐MS for metabolomics are discussed. Representative examples highlight the utility of CE‐MS in the fields of biomedical, clinical, microbial, and plant metabolomics. A complete overview of recent CE‐MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings and MS detection mode. Finally, some general conclusions and perspectives are given.     

Semi‐quantitative non‐target analysis of water with liquid chromatography/high‐resolution mass spectrometry: How far are we?

Combining high‐resolution mass spectrometry (HRMS) with liquid chromatography (LC) has considerably increased the capability of analytical chemistry. Among others, it has stimulated the growth of the non‐target analysis, which aims at identifying compounds without their preceding selection. This approach is already widely applied in various fields, such as metabolomics, proteomics, etc. The applicability of LC/HRMS‐based non‐target analysis in environmental analyses, such as water studies, would be beneficial for understanding the environmental fate of polar pollutants and evaluating the health risks exposed by the new emerging contaminants. During the last five to seven years the use of LC/HRMS‐based non‐target analysis has grown rapidly. However, routine non‐target analysis is still uncommon for most environmental monitoring agencies and environmental scientists. The main reasons are the complicated data processing and the inability to provide quantitative information about identified compounds. The latter shortcoming follows from the lack of standard substances, considered so far as the soul of each quantitative analysis for the newly discovered pollutants. To overcome this, non‐target analyses could be combined with semi‐quantitation. This Perspective aims at describing the current methods for non‐target analysis, the possibilities and challenges of standard substance‐free semi‐quantitative analysis, and proposes tools to join these two fields together.     

CE–MS for anionic metabolic profiling: An overview of methodological developments

The efficient profiling of highly polar and charged metabolites in biological samples remains a huge analytical challenge in metabolomics. Over the last decade, new analytical techniques have been developed for the selective and sensitive analysis of polar ionogenic compounds in various matrices. Still, the analysis of such compounds, notably for acidic ionogenic metabolites, remains a challenging endeavor, even more when the available sample size becomes an issue for the total analytical workflow. In this paper, we give an overview of the possibilities of capillary electrophoresis‐mass spectrometry (CE–MS) for anionic metabolic profiling by focusing on main methodological developments. Attention is paid to the development of improved separation conditions and new interfacing designs in CE–MS for anionic metabolic profiling. A complete overview of all CE–MS‐based methods developed for this purpose is provided in table format (Table 1) which includes information on sample type, separation conditions, mass analyzer and limits of detection (LODs). Selected applications are discussed to show the utility of CE–MS for anionic metabolic profiling, especially for small‐volume biological samples. On the basis of the examination of the reported literature in this specific field, we conclude that there is still room for the design of a highly sensitive and reliable CE–MS method for anionic metabolic profiling. A rigorous validation and the availability of standard operating procedures would be highly favorable in order to make CE–MS an alternative, viable analytical technique for metabolomics.     

Enrichment tags for enhanced-resolution profiling of the polar metabolome

The field of metabolomics aims to develop and apply methods to study the full complement of endogenous small molecules in biological systems. One of the major challenges in metabolomics is obtaining adequate resolution of compounds with similar physicochemical properties. The resolution of polar metabolites can be exceptionally problematic as these compounds are often poorly retained with reverse phase matrices. Here, we describe an advanced chemoselective tagging strategy to enrich and profile highly polar metabolites. Metabolite-reactive tags were appended with a hydrophobic p-Cl-phenylalanine residue, which conferred enhanced retention and resolution upon labeled small-molecules. Notably, the increased resolution afforded by hydrophobic tags minimized overlap in tandem mass spectrometry profiles for polar metabolites, thereby facilitating their structure determination in complex biological samples. Additionally, the chlorine atom of the tag permitted the discrimination of tagged metabolites from background peaks (i.e., false positives) and the discovery of metabolites that possess multiple copies of the same functional group. These studies designate chemoselective small-molecule tags as versatile tools for enriching and profiling challenging fractions of the metabolome.     

High‐performance liquid chromatographic and subcritical fluid chromatographic separation of α‐arylated ß‐carboline,N‐alkylated tetrahydroisoquinolines and their bioisosteres on polysaccharide‐based chiral stationary phases

New, pharmacologically interesting chiral amino compounds, namely, stereoisomers of α‐hydroxynaphthyl‐ß‐carboline, benz[d]azepine and benz[c]azepine analogs as well as N‐α‐hydroxynaphthylbenzyl‐substituted isoquinolines were enantioseparated by high‐performance liquid chromatographic and subcritical fluid chromatographic methods on polysaccharide‐based chiral stationary phases. Separation of the stereoisomers was optimized in both subcritical fluid chromatography and normal phase liquid chromatographic modes by investigating the effects of the composition of the bulk solvent, temperature, and the structures of the analytes and selectors. Both normal phase liquid chromatography and subcritical fluid chromatography exhibited satisfactory performance, albeit with somewhat different effectiveness in the separation of the stereoisomers studied. The optimized methods offer the possibility to apply preparative‐scale separations thereby enabling further pharmacological investigations of the enantiomers.     

NMR‐based metabolomics coupled with pattern recognition methods in biomarker discovery and disease diagnosis

Molecular biomarkers could detect biochemical changes associated with disease processes. The key metabolites have become an important part for improving the diagnosis, prognosis, and therapy of diseases. Because of the chemical diversity and dynamic concentration range, the analysis of metabolites remains a challenge. Assessment of fluctuations on the levels of endogenous metabolites by advanced NMR spectroscopy technique combined with multivariate statistics, the so‐called metabolomics approach, has proved to be exquisitely valuable in human disease diagnosis. Because of its ability to detect a large number of metabolites in intact biological samples with isotope labeling of metabolites using nuclei such as H, C, N, and P, NMR has emerged as one of the most powerful analytical techniques in metabolomics and has dramatically improved the ability to identify low concentration metabolites and trace important metabolic pathways. Multivariate statistical methods or pattern recognition programs have been developed to handle the acquired data and to search for the discriminating features from biosample sets. Furthermore, the combination of NMR with pattern recognition methods has proven highly effective at identifying unknown metabolites that correlate with changes in genotype or phenotype. The research and clinical results achieved through NMR investigations during the first 13 years of the 21st century illustrate areas where this technology can be best translated into clinical practice. In this review, we will present several special examples of a successful application of NMR for biomarker discovery, implications for disease diagnosis, prognosis, and therapy evaluation, and discuss possible future improvements. Copyright © 2013 John Wiley & Sons, Ltd.     

Differential mobility spectrometry (DMS) reveals the elevation of urinary acetylcarnitine in non‐human primates (NHPs) exposed to radiation

Acetylcarnitine has been identified as one of several urinary biomarkers indicative of radiation exposure in adult rhesus macaque monkeys (non‐human primates, NHPs). Previous work has demonstrated an up‐regulated dose‐response profile in a balanced male/female NHP cohort. 1 As a contribution toward the development of metabolomics‐based radiation biodosimetry in human populations and other applications of acetylcarnitine screening, we have developed a quantitative, high‐throughput method for the analysis of acetylcarnitine. We employed the Sciex SelexIon DMS‐MS/MS QTRAP 5500 platform coupled to flow injection analysis (FIA), thereby allowing for fast analysis times of less than 0.5 minutes per injection with no chromatographic separation. Ethyl acetate is used as a DMS modifier to reduce matrix chemical background. We have measured NHP urinary acetylcarnitine from the male cohorts that were exposed to the following radiation levels: control, 2, 4, 6, 7, and 10 Gy. Biological variability, along with calibration accuracy of the FIA‐DMS‐MS/MS method, indicates LOQ of 20 μM, with observed biological levels on the order of 600 μM and control levels near 10 μM. There is an apparent onset of intensified response in the transition from 6 to 10 Gy. The results demonstrate that FIA‐DMS‐MS/MS is a rapid, quantitative technique that can be utilized for the analysis of urinary biomarker levels for radiation biodosimetry.     

CRAFT (complete reduction to amplitude frequency table) – robust and time‐efficient Bayesian approach for quantitative mixture analysis by NMR

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR‐based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time‐domain Bayesian approaches have been reported to be better than conventional frequency‐domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time‐efficient fashion – thus converting the time‐domain FID to a frequency‐amplitude table. CRAFT uses a two‐step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.     

PLS‐DA for compositional data with application to metabolomics

When quantifying information in metabolomics, the results are often expressed as data carrying only relative information. Vectors of these data have positive components, and the only relevant information is contained in the ratios between their parts; such observations are called compositional data. The aim of the paper is to demonstrate how partial least squares discriminant analysis (PLS‐DA)—the most widely used method in chemometrics for multivariate classification—can be applied to compositional data. Theoretical arguments are provided, and data sets from metabolomics are investigated. The data are related to the diagnosis of inherited metabolic disorders (IMDs). The first example analyzes the significance of the corresponding regression parameters (metabolites) using a small data set resulting from targeted metabolomics, where just a subset of potential markers is selected. The second example—the approach of untargeted metabolomics—was used for the analysis detecting almost 500 metabolites. The significance of the metabolites is investigated by applying PLS‐DA, accommodated according to a compositional approach. The significance of important metabolites (markers of diseases) is more clearly visible with the compositional method in both examples. Also, cross‐validation methods lead to better results in case of using the compositional approach. Copyright © 2014 John Wiley & Sons, Ltd.     

High‐resolution extracted ion chromatography,a new tool for metabolomics and lipidomics using a second‐generation orbitrap mass spectrometer

Most analytical methods in metabolomics are based on one of two strategies. The first strategy is aimed at specifically analysing a limited number of known metabolites or compound classes. Alternatively, an unbiased approach can be used for profiling as many features as possible in a given metabolome without prior knowledge of the identity of these features. Using high‐resolution mass spectrometry with instruments capable of measuring m/z ratios with sufficiently low mass measurement uncertainties and simultaneous high scan speeds, it is possible to combine these two strategies, allowing unbiased profiling of biological samples and targeted analysis of specific compounds at the same time without compromises. Such high mass accuracy and mass resolving power reduces the number of candidate metabolites occupying the same retention time and m/z ratio space to a minimum. In this study, we demonstrate how targeted analysis of phospholipids as well as unbiased profiling is achievable using a benchtop orbitrap instrument after high‐speed reversed‐phase chromatography. The ability to apply both strategies in one experiment is an important step forward in comprehensive analysis of the metabolome. Copyright © 2009 John Wiley & Sons, Ltd.     

Effects of variation in modulator temperature during cryogenic modulation in comprehensive two‐dimensional gas chromatography

Many modulation systems in comprehensive 2D GC (GC×GC) are based on cryogenic methods. High trapping temperatures in these systems can result in ineffective trapping of the more volatile compounds, whilst temperatures that are too low can prevent efficient remobilisation of some compounds. To better understand the trapping and release of compounds over a wide range of volatilities, we have investigated a number of different constant temperature modulator settings, and have also examined a constant temperature differential between the cryo‐trap and the chromatographic oven. These investigations have led us to modify the temperature regulation capabilities of the longitudinally modulated cryogenic system (LMCS). In contrast to the current system, where the user sets a constant temperature for the cooling chamber, the user now sets the temperature difference between the cryo‐trap and the chromatographic oven. In this configuration, the cooling chamber temperature increases during the chromatographic run, tracking the oven temperature ramp. This produces more efficient, volatility‐dependent modulation, and increases the range of volatile compounds that can be analysed under optimal trap‐and‐release conditions within a single analytical run. This system also reduces cryogenic fluid consumption.     

Metabolomics‐based parallel discovery of xenobiotics and induced endogenous metabolic dysregulation in clinical toxicology

Intoxication by xenobiotics triggers the perturbation of metabolic fingerprints in biofluids, including the accumulation of xenobiotic compounds and the dysregulation of endogenous metabolites. In this work, an untargeted metabolomics workflow was developed to simultaneously profile both xenobiotic and endogenous metabolites for the identification of the xenobiotic origin and an in‐depth understanding of the intoxication mechanism. This workflow was demonstrated in a real‐world clinical case. Plasma samples were collected from four intoxicated children and another three healthy children. Untargeted metabolomics analysis was performed using ultraperformance liquid chromatography (UPLC) coupled to a high‐resolution mass spectrometer (HRMS) with data‐independent MS^E acquisition. LC–MS^E data was processed using an untargeted metabolomics data interpretation workflow, in which the identities of xenobiotics and altered endogenous metabolic features were determined via database searching. Five xenobiotic chemicals and 19 endogenous metabolites were found to be dysregulated. Combined with the clinical evidence, penfluridol was confirmed as the xenobiotic toxin. Furthermore, a mechanistic hypothesis was developed to explain the dysregulation of the four endogenous acyl‐carnitines. This workflow can be readily applied to a wide range of clinical toxicology cases, offering a powerful and convenient means of simultaneous discovery of intoxication source and the understanding of intoxication mechanisms.     

MASSyPup — an ‘Out of the Box’ solution for the analysis of mass spectrometry data

Mass spectrometry has evolved to a key technology in the areas of metabolomics and proteomics. Centralized facilities generate vast amount of data, which frequently need to be processed off‐site. Therefore, the distribution of data and software, as well as the training of personnel in the analysis of mass spectrometry data, becomes increasingly important. Thus, we created a comprehensive collection of mass spectrometry software which can be run directly from different media such as DVD or USB without local installation. MASSyPup is based on a Linux Live distribution and was complemented with programs for conversion, visualization and analysis of mass spectrometry (MS) data. A special emphasis was put on protein analysis and proteomics, encompassing the measurement of complete proteins, the identification of proteins based on Peptide Mass Fingerprints (PMF) or LC‐MS/MS data, and de novo sequencing. Another focus was directed to the study of metabolites and metabolomics, covering the detection, identification and quantification of compounds, as well as subsequent statistical analyses. Additionally, we added software for Mass Spectrometry Imaging (MSI), including hardware support for self‐made MSI devices. MASSyPup represents a ‘ready to work’ system for teaching or MS data analysis, but also represents an ideal platform for the distribution of MS data and the development of related software. The current Live DVD version can be downloaded free of charge from http://www.bioprocess.org/massypup . Copyright © 2014 John Wiley & Sons, Ltd.     

Real-time 2D separation by LC × differential ion mobility hyphenated to mass spectrometry

The liquid chromatography–mass spectrometry (LC-MS) analysis of complex samples such as biological fluid extracts is widespread when searching for new biomarkers as in metabolomics. The success of this hyphenation resides in the orthogonality of both separation techniques. However, there are frequent cases where compounds are co-eluting and the resolving power of mass spectrometry (MS) is not sufficient (e.g., isobaric compounds and interfering isotopic clusters). Different strategies are discussed to solve these cases and a mixture of eight compounds (i.e., bromazepam, chlorprothixene, clonapzepam, fendiline, flusilazol, oxfendazole, oxycodone, and pamaquine) with identical nominal mass (i.e., m/z 316) is taken to illustrate them. Among the different approaches, high-resolution mass spectrometry or liquid chromatography (i.e., UHPLC) can easily separate these compounds. Another technique, mostly used with low resolving power MS analyzers, is differential ion mobility spectrometry (DMS), where analytes are gas-phase separated according to their size-to-charge ratio. Detailed investigations of the addition of different polar modifiers (i.e., methanol, ethanol, and isopropanol) into the transport gas (nitrogen) to enhance the peak capacity of the technique were carried out. Finally, a complex urine sample fortified with 36 compounds of various chemical properties was analyzed by real-time 2D separation LC×DMS-MS(/MS). The addition of this orthogonal gas-phase separation technique in the LC-MS(/MS) hyphenation greatly improved data quality by resolving composite MS/MS spectra, which is mandatory in metabolomics when performing database generation and search.     

Gas chromatographic determination of some glycol ethers and glycol ether acetates by FID,O-FID,and MS detection. Preliminary applications in simultaneous monitoring of these chemicals in biological matrices

Twelve compounds, commonly used as industrial solvents and belonging to the chemical class of glycol ethers and glycol ether acetates, were investigated. Several analytical conditions, applied to single or connected capillary columns of different length and polarity coating and connected to FID, O-FID and MS detection systems, were assayed. Tests on heptafluorobutyryl derivatives were also attempted to improve the analytical sensitivity. The aims were to establish gas chromatographic methods suitable for analysis of reference standard compounds and to verify their applicability to biological matrix analysis for pharmacokinetic and toxicological studies, since these chemicals have been shown to be hazardous in laboratory animals and are presumed to be dangerous in man.