Phosphorus NMR and Its Application to Metabolomics

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Quantitative Analysis of the Human Semen Phosphorometabolome by 31P-NMR

Phosphorus-containing metabolites occupy a prominent position in cell pathways. The phosphorometabolomic approach in human sperm samples will deliver valuable information as new male fertility biomarkers could emerge. This study analyzed, by 31P-NMR, seminal plasma and whole semen from asthenozoospermic and normozoospermic samples (71% vs. 27% and 45% vs. 17%, total and progressive sperm motility, respectively), and also ejaculates from healthy donors. At least 16 phosphorus-containing metabolites involved in central energy metabolism and phospholipid, nucleotide, and nicotinamide metabolic pathways were assigned and different abundances between the samples with distinct sperm quality was detected. Specifically, higher levels of phosphocholine, glucose-1-phosphate, and to a lesser degree, acetyl phosphate were found in the asthenozoospermic seminal plasma. Notably, the phosphorometabolites implicated in lipid metabolism were highlighted in the seminal plasma, while those associated with carbohydrate metabolism were more abundant in the spermatozoa. Higher levels of phosphocholine, glucose-1-phosphate, and acetyl phosphate in the seminal plasma with poor quality suggest their crucial role in supporting sperm motility through energy metabolic pathways. In the seminal plasma, phosphorometabolites related to lipid metabolism were prominent; however, spermatozoa metabolism is more dependent on carbohydrate-related energy pathways. Understanding the presence and function of sperm phosphorylated metabolites will enhance our knowledge of the metabolic profile of healthy human sperm, improving assessment and differential diagnosis.

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Fingerprinting and profiling in metabolomics of biosamples

This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.

Labile Metabolite Profiling in Human Blood Using Phosphorus NMR Spectroscopy

Phosphorus metabolites occupy a unique place in cellular function as critical intermediates and products of cellular metabolism. Human blood is the most widely used biospecimen in the clinic and in the metabolomics field, and hence an ability to profile phosphorus metabolites in blood, quantitatively, would benefit a wide variety of investigations of cellular functions in health and diseases. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the two premier analytical platforms used in the metabolomics field. However, detection and quantitation of phosphorus metabolites by MS can be challenging due to their lability, high polarity, structural isomerism, and interaction with chromatographic columns. The conventionally used 1H NMR, on the other hand, suffers from poor resolution of these compounds. As a remedy, 31P NMR promises an important alternative to both MS and 1H NMR. However, numerous challenges including the instability of phosphorus metabolites, their chemical shift sensitivity to solvent composition, pH, salt, and temperature, and the lack of identified metabolites have so far restricted the scope of 31P NMR. In the current study, we describe a method to analyze nearly 25 phosphorus metabolites in blood using a simple one-dimensional (1D) NMR spectrum. Establishment of the identity of unknown metabolites involved a combination of (a) comprehensively analyzing an array of 1D and two-dimensional (2D) 1H/31P homonuclear and heteronuclear NMR spectra of blood; (b) mapping the central carbon metabolic pathway; (c) developing and using 1H and 31P spectral and chemical shift databases; and finally (d) confirming the putative metabolite peaks with spiking using authentic compounds. The resulting simple 1D 31P NMR-based method offers an ability to visualize and quantify the levels of intermediates and products of multiple metabolic pathways, including central carbon metabolism, in one step. Overall, the findings represent a new dimension for blood metabolite analysis and are anticipated to greatly impact the blood metabolomics field.

Exploring the potential application of alternative nuclei in NMR based metabolomics

INTRODUCTION

Nuclear magnetic resonance (NMR) is widely used in metabolomics but it focusses on ¹H over other NMR-active nuclei.

OBJECTIVES

To evaluate the potential of alternative NMR-sensitive nuclei to generate useful metabolomic data.

METHOD

Proton, carbon, phosphorus, and nitrogen-based NMR metabolomics was undertaken on extracts from mint and European honey bee tissue.

RESULTS

Carbon NMR provided useful information but required larger sample sizes. Phosphorus produced overlapping peaks in one dimensional (1D) analysis but showed potential in 2D experiments. ¹⁵N NMR was found to not be sensitive enough for general metabolomic work.

CONCLUSIONS

Alternative NMR active nuclei are useful for metabolomics.

Advances in the Synthesis and Analysis of Biologically Active Phosphometabolites

Phosphorus-containing metabolites cover a large molecular diversity and represent an important domain of small molecules which are highly relevant for life and represent essential interfaces between biology and chemistry, between the biological and abiotic world. The large but not unlimited amount of phosphate minerals on our planet is a key resource for living organisms on our planet, while the accumulation of phosphorus-containing waste is associated with negative effects on ecosystems. Therefore, resource-efficient and circular processes receive increasing attention from different perspectives, from local and regional levels to national and global levels. The molecular and sustainability aspects of a global phosphorus cycle have become of much interest for addressing the phosphorus biochemical flow as a high-risk planetary boundary. Knowledge of balancing the natural phosphorus cycle and the further elucidation of metabolic pathways involving phosphorus is crucial. This requires not only the development of effective new methods for practical discovery, identification, and high-information content analysis, but also for practical synthesis of phosphorus-containing metabolites, for example as standards, as substrates or products of enzymatic reactions, or for discovering novel biological functions. The purpose of this article is to review the advances which have been achieved in the synthesis and analysis of phosphorus-containing metabolites which are biologically active.

Large 31P-NMR enhancements in liquid state dynamic nuclear polarization through radical/target molecule non-covalent interaction

Dynamic nuclear polarization (DNP) is a method to enhance the low sensitivity of nuclear magnetic resonance (NMR) via spin polarization transfer from electron spins to nuclear spins. In the liquid state, this process is mediated by fast modulations of the electron-nuclear hyperfine coupling and its efficiency depends strongly on the applied magnetic field. A peculiar case study is triphenylphosphine (PPh₃) dissolved in benzene and doped with BDPA radical because it gives ³¹P-NMR signal enhancements of two orders of magnitude up to a magnetic field of 14.1 T. Here we show that the large ³¹P enhancements of BDPA/PPh₃ in benzene at 1.2 T (i) decrease when the moieties are dissolved in other organic solvents, (ii) are strongly reduced when using a nitroxide radical, and (iii) vanish with pentavalent ³¹P triphenylphosphine oxide. Those experimental observations are rationalized with numerical calculations based on density functional theory that show the tendency of BDPA and PPh₃ to form a weak complex via non-covalent interaction that leads to large hyperfine couplings to ³¹P (ΔA_iso ≥ 13 MHz). This mechanism is hampered in other investigated systems. The case study of ³¹P-DNP in PPh₃ is an important example that extends the current understanding of DNP in the liquids state: non-covalent interactions between radical and target can be particularly effective to obtain large NMR signal enhancements.

Chemical shift variations in common metabolites

The reliability and robustness of metabolite assignments in 1H NMR is complicated by numerous factors including variations in temperature, pH, buffer choice, ionic strength, and mixture composition that led to peak overlap and spectral crowding. As sample conditions fluctuate, peak drift and line broadening further complicate peak deconvolution and subsequent chemical assignment. We present a collection of 1D 1H NMR spectra of 54 common metabolites at varied pH (6.0 to 8.0 in 0.5 step increments) and temperature (290 K to 308 K) to quantify chemical shift variability to facilitate automated metabolite assignments. Our results illustrate the fundamental challenges with accurately assigning NMR peaks under varied environmental conditions prevalent in complex mixtures. Phosphorylated metabolites showed a larger variation in chemical shifts due to pH, whereas; amino acids showed a higher variation due to temperature. Mixtures of phosphorous compounds showed a consistently poor reliability in achieving an accurate assignment. Phosphorylated cholines, amino acids, and glycerols yielded a 40 % false negative rate for 7 out of 9 mixture conditions. Amino acids had a false negative rate of 57 % at 298 K and pH 8. Our results demonstrate that the automated assignments of complex biofluid mixtures require an expert to intervene to confirm the accuracy of metabolite assignments. Our analysis also indicates the need for reference databases to include spectra under a variety of conditions that includes mixtures and a range of pH and temperature to improve the accuracy and reproducibility of metabolite assignments.

Electron Correlation or Basis Set Quality: How to Obtain Converged and Accurate NMR Shieldings for the Third-Row Elements?

The quality of theoretical NMR shieldings calculated at the quantum-chemical level depends on various theoretical aspects, of which the basis set type and size are among the most important factors. Nevertheless, not much information is available on the basis set effect on theoretical shieldings of the NMR-active nuclei of the third row. Here, we report on the importance of proper basis set selection to obtain accurate and reliable NMR shielding parameters for nuclei from the third row of the periodic table. All calculations were performed on a set of eleven compounds containing the elements Na, Mg, Al, Si, P, S, or Cl. NMR shielding tensors were calculated using the SCF-HF, DFT-B3LYP, and CCSD(T) methods, combined with the Dunning valence aug-cc-pVXZ, core-valence aug-cc-pCVXZ, Jensen polarized-convergent aug-pcSseg-n and Karlsruhe x2c-Def2 basis set families. We also estimated the complete basis set limit (CBS) values of the NMR parameters. Widely scattered nuclear shieldings were observed for the Dunning polarized-valence basis set, which provides irregular convergence. We show that the use of Dunning core-valence or Jensen basis sets effectively reduces the scatter of theoretical NMR results and leads to their exponential-like convergence to CBS. We also assessed the effect of vibrational, temperature, and relativistic corrections on the predicted shieldings. For systems with single bonds, all corrections are relatively small, amounting to less than 4% of the CCSD(T)/CBS value. Vibrational and temperature corrections were less reliable for H₃PO and HSiCH due to the high anharmonicity of the molecules. An abnormally high relativistic correction was observed for phosphorus in PN, reaching ~20% of the CCSD(T)/CBS value, while the correction was less than 7% for other tested molecules.

NMR-based isotope editing, chemoselection and isotopomer distribution analysis in stable isotope resolved metabolomics

NMR is a very powerful tool for identifying and quantifying compounds within complex mixtures without the need for individual standards or chromatographic separation. Stable Isotope Resolved Metabolomics (or SIRM) is an approach to following the fate of individual atoms from precursors through metabolic transformation, producing an atom-resolved metabolic fate map. However, extracts of cells or tissue give rise to very complex NMR spectra. While multidimensional NMR experiments may partially overcome the spectral overlap problem, additional tools may be needed to determine site-specific isotopomer distributions. NMR is especially powerful by virtue of its isotope editing capabilities using NMR active nuclei such as 13C, 15N, 19F and 31P to select molecules containing just these atoms in a complex mixture, and provide direct information about which atoms are present in identified compounds and their relative abundances. The isotope-editing capability of NMR can also be employed to select for those compounds that have been selectively derivatized with an NMR-active stable isotope at particular functional groups, leading to considerable spectral simplification. Here we review isotope analysis by NMR, and methods of chemoselection both for spectral simplification, and for enhanced isotopomer analysis.

Studying Metabolism by NMR-Based Metabolomics

During the past few decades, the direct analysis of metabolic intermediates in biological samples has greatly improved the understanding of metabolic processes. The most used technologies for these advances have been mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. NMR is traditionally used to elucidate molecular structures and has now been extended to the analysis of complex mixtures, as biological samples: NMR-based metabolomics. There are however other areas of small molecule biochemistry for which NMR is equally powerful. These include the quantification of metabolites (qNMR); the use of stable isotope tracers to determine the metabolic fate of drugs or nutrients, unravelling of new metabolic pathways, and flux through pathways; and metabolite-protein interactions for understanding metabolic regulation and pharmacological effects. Computational tools and resources for automating analysis of spectra and extracting meaningful biochemical information has developed in tandem and contributes to a more detailed understanding of systems biochemistry. In this review, we highlight the contribution of NMR in small molecule biochemistry, specifically in metabolic studies by reviewing the state-of-the-art methodologies of NMR spectroscopy and future directions.

Research Progress of NMR in Natural Product Quantification

In the fields of medicine and health, traditional high-performance liquid chromatography or UV-visible spectrophotometry is generally used for substance quantification. However, over time, nuclear magnetic resonance spectroscopy (NMR) has gradually become more mature. Nuclear magnetic resonance spectroscopy has certain advantages in the quantitative analysis of substances, such as being nondestructive, having a high flux and short analysis time. Nuclear magnetic resonance spectroscopy has been included in the pharmacopoeiae of various countries. In this paper, the principle of nuclear magnetic resonance spectroscopy and the recent progress in the quantitative study of natural products by NMR are reviewed, and its application in the quantitative study of natural products is proposed. At the same time, the problems of using NMR alone to quantify natural products are summarized and corresponding suggestions are put forward.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies

Detailed molecular analysis is of increasing importance in research into the regulation of biochemical pathways, organismal growth and disease. Lipidomics in particular is increasingly sought after as it provides insight into molecular species involved in energy storage, signalling and fundamental cellular structures. This has led to the use of a range of tools and techniques to acquire lipidomics data. 31P NMR for lipidomics offers well-resolved head group/lipid class analysis, structural data that can be used to inform and strengthen interpretation of mass spectrometry data and part of a priori structural determination. In the present study, we codify the use of 31P NMR for lipidomics studies to make the technique more accessible to new users and more useful for a wider range of questions. The technique can be used in isolation (phospholipidomics) or as a part of determining lipid composition (lipidomics). We describe the process from sample extraction to data processing and analysis. This pipeline is important because it allows greater thoroughness in lipidomics studies and increases scope for answering scientific questions about lipid-containing systems.

Metabolic Landscape of the Mouse Liver by Quantitative 31 P Nuclear Magnetic Resonance Analysis of the Phosphorome

BACKGROUND AND AIMS

The liver plays a central role in all metabolic processes in the body. However, precise characterization of liver metabolism is often obscured by its inherent complexity. Phosphorylated metabolites occupy a prominent position in all anabolic and catabolic pathways. Here, we develop a ³¹ P nuclear magnetic resonance (NMR)-based method to study the liver "phosphorome" through the simultaneous identification and quantification of multiple hydrophilic and hydrophobic phosphorylated metabolites.

APPROACH AND RESULTS

We applied this technique to define the metabolic landscape in livers from a mouse model of the rare disease disorder congenital erythropoietic porphyria (CEP) as well as two well-known murine models of nonalcoholic steatohepatitis: one genetic, methionine adenosyltransferase 1A knockout mice, and the other dietary, mice fed a high-fat choline-deficient diet. We report alterations in the concentrations of phosphorylated metabolites that are readouts of the balance between glycolysis, gluconeogenesis, the pentose phosphate pathway, the tricarboxylic acid cycle, and oxidative phosphorylation and of phospholipid metabolism and apoptosis. Moreover, these changes correlate with the main histological features: steatosis, apoptosis, iron deposits, and fibrosis. Strikingly, treatment with the repurposed drug ciclopirox improves the phosphoromic profile of CEP mice, an effect that was mirrored by the normalization of liver histology.

CONCLUSIONS

In conclusion, these findings indicate that NMR-based phosphoromics may be used to unravel metabolic phenotypes of liver injury and to identify the mechanism of drug action.

New software tools, databases, and resources in metabolomics: updates from 2020

BACKGROUND

Precision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success.

AIM OF THE REVIEW

In this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.

Improved NMR Detection of Phospho-Metabolites in a Complex Mixture

Phosphorylated metabolites are omnipresent in cells, but their analytical characterization faces several technical hurdles. Here, we detail an improved NMR workflow aimed at assigning the high-resolution subspectrum of the phospho-metabolites in a complex mixture. Combining a pure absorption J-resolved spectrum (Pell, A. J.; J. Magn. Reson. 2007, 189 (2), 293-299) with alternate on- and off-switching of the ³¹P coupling interaction during the t₁ evolution with a pure in-phase (PIP) HSQMBC experiment (Castañar, L.; Angew. Chem., Int. Ed. 2014, 53 (32), 8379-8382) without or with total correlation spectroscopy (TOCSY) transfer during the insensitive nuclei enhancement by polarization transfer (INEPT) gives access to selective identification of the individual subspectra of the phosphorylated metabolites. Returning to the initial J-res spectra, we can extract with optimal resolution the full trace for the individual phospho-metabolites, which can then be transposed on the high-resolution quantitative one dimensional spectrum.

Quantitative NMR as a Versatile Tool for the Reference Material Preparation

The assessment of primary calibrator purity is critical for establishing traceability to the International System of Units (SI). Recently, quantitative nuclear magnetic resonance (qNMR) has been used as a purity determination method for reference material development, and many related measurement techniques have been designed to acquire accurate and reliable results. This review introduces the recent advances in these techniques (including multidimensional methods), focusing on the application of qNMR to reference material preparation.

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

Nuclear Magnetic Resonance (NMR) spectroscopy is a quantitative analytical tool commonly utilized for metabolomics analysis. Quantitative NMR (qNMR) is a field of NMR spectroscopy dedicated to the measurement of analytes through signal intensity and its linear relationship with analyte concentration. Metabolomics-based NMR exploits this quantitative relationship to identify and measure biomarkers within complex biological samples such as serum, plasma, and urine. In this review of quantitative NMR-based metabolomics, the advancements and limitations of current techniques for metabolite quantification will be evaluated as well as the applications of qNMR in biomedical metabolomics. While qNMR is limited by sensitivity and dynamic range, the simple method development, minimal sample derivatization, and the simultaneous qualitative and quantitative information provide a unique landscape for biomedical metabolomics, which is not available to other techniques. Furthermore, the non-destructive nature of NMR-based metabolomics allows for multidimensional analysis of biomarkers that facilitates unambiguous assignment and quantification of metabolites in complex biofluids.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.