Recent advances in liquid-phase separations for clinical metabolomics

A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research

Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Metabolite discovery: Biochemistry's scientific driver

Metabolite identification represents a major challenge, and opportunity, for biochemistry. The collective characterization and quantification of metabolites in living organisms, with its many successes, represents a major biochemical knowledgebase and the foundation of metabolism's rebirth in the 21^st century; yet, characterizing newly observed metabolites has been an enduring obstacle. Crystallography and NMR spectroscopy have been of extraordinary importance, although their applicability in resolving metabolism's fine structure has been restricted by their intrinsic requirement of sufficient and sufficiently pure materials. Mass spectrometry has been a key technology, especially when coupled with high-performance separation technologies and emerging informatic and database solutions. Even more so, the collective of artificial intelligence technologies are rapidly evolving to help solve the metabolite characterization conundrum. This perspective describes this challenge, how it was historically addressed, and how metabolomics is evolving to address it today and in the future.

Analytical Platforms for Mass Spectrometry-Based Metabolomics of Polar and Ionizable Metabolites

Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.

Understanding the Gastrointestinal Protective Effects of Polyphenols using Foodomics-Based Approaches

Plant polyphenols are rich sources of natural anti-oxidants and prebiotics. After ingestion, most polyphenols are absorbed in the intestine and interact with the gut microbiota and modulated metabolites produced by bacterial fermentation, such as short-chain fatty acids (SCFAs). Dietary polyphenols immunomodulatory role by regulating intestinal microorganisms, inhibiting the etiology and pathogenesis of various diseases including colon cancer, colorectal cancer, inflammatory bowel disease (IBD) and colitis. Foodomics is a novel high-throughput analysis approach widely applied in food and nutrition studies, incorporating genomics, transcriptomics, proteomics, metabolomics, and integrating multi-omics technologies. In this review, we present an overview of foodomics technologies for identifying active polyphenol components from natural foods, as well as a summary of the gastrointestinal protective effects of polyphenols based on foodomics approaches. Furthermore, we critically assess the limitations in applying foodomics technologies to investigate the protective effect of polyphenols on the gastrointestinal (GI) system. Finally, we outline future directions of foodomics techniques to investigate GI protective effects of polyphenols. Foodomics based on the combination of several analytical platforms and data processing for genomics, transcriptomics, proteomics and metabolomics studies, provides abundant data and a more comprehensive understanding of the interactions between polyphenols and the GI tract at the molecular level. This contribution provides a basis for further exploring the protective mechanisms of polyphenols on the GI system.

Collective Solvation and Transport at Tetrahydrofuran-Silica Interfaces for Separation of Aromatic Compounds: Insight from Molecular Dynamics Simulations

We have performed umbrella sampling molecular dynamics simulations to study the separation mechanism of aromatic compounds at the tetrahydrofuran (THF)-methanol-silica interface by liquid chromatography. Solute molecules with different polarities (naphthol and naphthalene) are selected as representative aromatic compounds. For the polar solute (naphthol), the free energy profile shows a deep minimum near the THF-silica interface, suggesting strong interactions with the polar surface. When methanol is added to the interface, there is a sharp increase in naphthol's free energy minimum, and the corresponding diffusion dynamics also undergoes a dramatic change. These findings explain the fast separation mechanism in recent experiments of separating fused ring compounds in asphaltenes with liquid chromatography. Further solvation structure and orientation analysis suggest that apolar and polar solutes may find their own comfort zones several angstroms away from the interface, and their phenyl ring's orientations would undergo a parallel-to-perpendicular transition as the solute molecule moves away from the surface. Extending our simulation studies to systems with different solute concentrations reveals that there is a decrease in the adsorption free energy accompanied by enhanced surface diffusion as the solute concentration increases, which is related to the crowding in the interfacial layers. Our simulation analysis gives a detailed microscopic description of solute solvation and transport at the THF-silica chromatography interface and will be helpful for improving separation protocols in future applications.

Capillary Electrophoresis-Mass Spectrometry for Metabolomics: Possibilities and Perspectives

Capillary electrophoresis-mass spectrometry (CE-MS) is a very useful analytical technique for the selective and highly efficient profiling of polar and charged metabolites in a wide range of biological samples. Compared to other analytical techniques, the use of CE-MS in metabolomics is relatively low as the approach is still regarded as technically challenging and not reproducible. In this chapter, the possibilities of CE-MS for metabolomics are highlighted with special emphasis on the use of recently developed interfacing designs. The utility of CE-MS for targeted and untargeted metabolomics studies is demonstrated by discussing representative and recent examples in the biomedical and clinical fields. The potential of CE-MS for large-scale and quantitative metabolomics studies is also addressed. Finally, some general conclusions and perspectives are given on this strong analytical separation technique for probing the polar metabolome.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

Comparison of microcapillary column length and inner diameter investigated with gradient analysis of lipids by ultrahigh-pressure liquid chromatography-mass spectrometry

Biological samples in lipidomic studies can consist of extremely complex mixtures due to the diverse range of species and isomerism. Herein, highly efficient, in-house packed microcapillary columns introduce the potential to better separate these complex mixtures. We compared the effects of changing column length (15, 30, and 60 cm) and inner diameter (75 and 100 μm) on lipid separation efficiency by reversed-phase gradient analysis using ultrahigh-pressure liquid chromatography coupled to mass spectrometry with operating pressures ranging from 450 to 2200 bar. Seven lipid standards composed of phosphatidylcholine and triacylglycerol species were analyzed at four different gradient rates to calculate conditional peak capacity. The longest column, 60 cm, at the shallowest gradient of 2% gave the highest peak capacity of 359 with a separation window of 2 h. The intermediate column length of 30 cm with 75 μm inner diameter provided a peak capacity of 287 with a separation window of 1 h. There was no significant difference in peak capacity between 75 and 100 μm inner diameter columns. This study showed that using highly efficient microcapillary columns increased peak capacity and resolution of lipids, and thus, this technique seems promising for enhancing lipid coverage and enabling better discovery of lipid biomarkers.

Analytical techniques for metabolomic studies: a review

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

Rapid Solution-Phase Hydrogen/Deuterium Exchange for Metabolite Compound Identification

Rapid, solution-phase hydrogen/deuterium exchange (HDX) coupled with mass spectrometry (MS) is demonstrated as a means for distinguishing small-molecule metabolites. HDX is achieved using capillary vibrating sharp-edge spray ionization (cVSSI) to allow sufficient time for reagent mixing and exchange in micrometer-sized droplets. Different compounds are observed to incorporate deuterium with varying efficiencies resulting in unique isotopic patterns as revealed in the MS spectra. Using linear regression techniques, parameters representing contribution to exchange by different hydrogen types can be computed. In this proof-of-concept study, the exchange parameters are shown to be useful in the retrodiction of the amount of deuterium incorporated within different compounds. On average, the exchange parameters retrodict the exchange level with ~ 2.2-fold greater accuracy than treating all exchangeable hydrogens equally. The parameters can be used to produce hypothetical isotopic distributions that agree (± 16% RMSD) with experimental measurements. These initial studies are discussed in light of their potential value for identifying challenging metabolite species.

Evaluating the Adsorbed Water Layer on Polar Stationary Phases for Hydrophilic Interaction Chromatography (HILIC)

The water-rich liquid layer immobilized on the surface of the polar stationary phases is critical to the retention of polar compounds in hydrophilic interaction chromatography (HILIC). Although the presence of the adsorbed water layer has been investigated and confirmed by multiple techniques, there is a lack of quantitative measures that can be easily determined and linked to chromatographic parameters. This study proposes a simple measure termed volume ratio (the ratio of the adsorbed water layer volume and the mobile phase volume) that can be easily determined using toluene elution volume. The volume ratio values measured using the proposed method indicate that the volume of the adsorbed water layer varies in a wide range in the stationary phases commonly used in HILIC separation. It was observed that the volume ratio increases with the acetonitrile content and ammonium acetate concentration in the mobile phase. In addition, increasing the column temperature had the effect of reducing the volume ratio and diminishing the adsorbed water layer.

Recent applications of on-line supercritical fluid extraction coupled to advanced analytical techniques for compounds extraction and identification

In a previous review (Sánchez-Camargo et al., J. Sep. Sci. 40 (2017) 213-227), we discussed the application of on-line supercritical fluid extraction coupled to chromatographic techniques. This review includes an update of the most recent publications (from January 2016 till June 2018) on this topic, which employs advanced analytical techniques for extracting and identifying valuable analytes. Supercritical fluid extraction has been widely recognized as a green sample preparation technique, because it is efficient, environmentally friendly, powerful, and faster, offering the possibility of direct coupling to analytical instrumental techniques. Among those techniques, supercritical fluid chromatography has experienced an innovative progression in the last 10 years, and the most recent applications of supercritical fluid extraction are coupled to this advanced analytical tool. The general principles, both methodological and instrumental of on-line supercritical fluid extraction coupled to supercritical fluid chromatography are described here. Besides, applications of the mentioned coupling for analysing biological fluids, food, soil, and botanical samples are also presented and discussed. Finally, a brief description about the very recent on-line coupling of supercritical fluid extraction to ion mobility spectrometry is presented, as well as concluding remarks about the importance of using these coupled techniques in the near future.

Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

Applicability of supercritical fluid chromatography - mass spectrometry to metabolomics. I - Optimization of separation conditions for the simultaneous analysis of hydrophilic and lipophilic substances

The aim of this study was to evaluate the suitability of SFC-MS for the analysis of a wide range of compounds including lipophilic and highly hydrophilic substances (log P values comprised between -6 and 11), for its potential application toward human metabolomics. For this purpose, a generic unified chromatography gradient from 2 to 100% organic modifier in CO₂ was systematically applied. In terms of chemistry, the best stationary phases for this application were found to be the Agilent Poroshell HILIC (bare silica) and Macherey-Nagel Nucleoshell HILIC (silica bonded with a zwitterionic ligand). To avoid system overpressure at very high organic modifier proportion, columns of 100 × 3 mm I.D. packed with sub-3 μm superficially porous particles were selected. In terms of organic modifier, a mixture of 95% MeOH and 5% water was selected, with 50 mM ammonium formate and 1 mM ammonium fluoride, to afford good solubility of analytes in the mobile phase, limited retention for the most hydrophilic metabolites and suitable peak shapes of ionizable species. A sample diluent containing 50%ACN/50% water was employed as injection solvent. These conditions were applied to a representative set of metabolites belonging to nucleosides, nucleotides, small organic acids, small bases, sulfated/sulfonated metabolites, poly-alcohols, lipid related substances, quaternary ammonium metabolites, phosphate-based substances, carbohydrates and amino acids. Among all these metabolites, 65% of the compounds were adequately analyzed with excellent peak shape, 23% provided distorted peak shapes, while only 12% were not detected (mostly metabolites having several phosphate or several carboxylic acid groups).

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min.

Overcoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry

Blood is widely used for discovery metabolomics to search for disease biomarkers. However, blood sample matrix can have a profound effect on metabolome analysis, which can impose an undesirable restriction on the type of blood collection tubes that can be used for blood metabolomics. We investigated the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. We used ¹²C-/¹³C-dansylation LC-MS to perform relative quantification of the amine/phenol submetabolomes of four types of samples (i.e., serum, EDTA plasma, heparin plasma, and citrate plasma) collected from healthy individuals and compare their metabolomic results. From the analysis of 80 plasma and serum samples in experimental triplicate, we detected a total of 3651 metabolites with an average of 1818 metabolites per run (n = 240). The number of metabolites detected and the precision and accuracy of relative quantification were found to be independent of the sample type. Within each sample type, the metabolome data set could reveal biological variation (e.g., sex separation). Although the relative concentrations of some individual metabolites might be different in the four types of samples, for sex separation, all 66 significant metabolites with larger fold-changes (FC ≥ 2 and p < 0.05) found in at least one sample type could be found in the other types of samples with similar or somewhat reduced, but still significant, fold-changes. Our results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics; any blood samples properly collected in routine clinical settings, including those in biobanks originally used for other purposes, can potentially be used for discovery metabolomics.

Comprehensive metabonomic analysis of heart tissue from isoproterenol-induced myocardial infarction rat based on reversed-phase and hydrophilic interaction chromatography coupled to mass spectrometry

We aim to describe the metabonomic characteristics of myocardial infarction rats. High-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was utilized to develop a metabonomic method of the heart homogenates of myocardial infarction rats. Hydrophilic interaction chromatography allows the analysis of high polar metabolites, providing complementary information to reversed-phase liquid chromatography. We combined reversed phase and hydrophilic interaction chromatographic separations to analyze 18 samples, ten from myocardial infarction rat hearts and eight from normal rat hearts. A total of 16 potential biomarkers in rat heart tissue were screened out, primarily related to oxidative stress, nitric oxide damage, taurine, and hypotaurine metabolism and sphingolipid metabolism. This research showed that a comprehensive metabonomic study is a useful tool to reveal the underlying mechanism of myocardial infarction.