Metabolomics analysis II. Preparation of biological samples prior to detection

Extraction and untargeted analysis of metabolome from undemineralised cortical bone matrix

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) untargeted metabolomics has become the gold standard for the profiling of low-molecular-weight compounds. Recently, this discipline has raised great interest in forensic sciences, especially in the field of toxicology and for post-mortem interval estimation. The current study aims at evaluating three extraction protocols and two LC-MS/MS assays run in both positive and negative modes, to identify the most suitable method to conduct post-mortem metabolomic profiling of bone tissue. A fragment of the anterior tibia of a 82 years-old male sampled from a human taphonomy facility was powdered via freeze-milling. The powdered sub-samples were extracted in five replicates per protocol. Methods tested were (I) a biphasic chloroform-methanol-water protocol, (II) a single phase methanol-water protocol, and (III) a single phase methanol-acetonitrile-water protocol. LC-MS/MS analyses were carried out via high performance liquid chromatography, either on hydrophilic interaction (HILIC) or on reversed-phase (C18) columns in both positive and negative ionisation modes, coupled with a Q-TOF mass spectrometer. Results suggest that the highest consistency between replicates and quality control samples was obtained with the single phase extractions (i.e., methanol-acetonitrile-water), whilst the ideal combination of instrumental set up HILIC chromatography in positive ionisation mode and of C18 chromatography in negative ionisation mode. For the purpose of forensic investigations, a combination of a single phase extraction and the two aforementioned chromatographic and mass spectrometry modes could represent an ideal set up for obtaining bone metabolomic profiles from taphonomically altered bones.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Miniaturization and Automation Protocol of a Urinary Organic Acid Liquid-Liquid Extraction Method on GC-MS

The aim of this study was to improve the extraction method for urinary organic acids by miniaturizing and automating the process. Currently, manual extraction methods are commonly used, which can be time-consuming and lead to variations in test results. To address these issues, we reassessed and miniaturized the in-house extraction method, reducing the number of steps and the sample-to-solvent volumes required. The evaluated miniaturized method was translated into an automated extraction procedure on a MicroLab (ML) Star (Hamilton Technologies) liquid handler. This was then validated using samples obtained from the ERNDIM External Quality Assurance program. The organic acid extraction method was successfully miniaturized and automated using the Autosampler robot. The linear range for most of the thirteen standard analytes fell between 0 to 300 mg/L in spiked synthetic urine, with low (50 mg/L), medium (100 mg/L), and high (500 mg/L) levels. The correlation coefficient (r) for most analytes was >0.99, indicating a strong relationship between the measured values. Furthermore, the automated extraction method demonstrated acceptable precision, as most organic acids had coefficients of variation (CVs) below 20%. In conclusion, the automated extraction method provided comparable or even superior results compared to the current in-house method. It has the potential to reduce solvent volumes used during extraction, increase sample throughput, and minimize variability and random errors in routine diagnostic settings.

Behavioral metabolomics: how behavioral data can guide metabolomics research on neuropsychiatric disorders

INTRODUCTION

Metabolomics produces vast quantities of data but determining which metabolites are the most relevant to the disease or disorder of interest can be challenging.

OBJECTIVES

This study sought to demonstrate how behavioral models of psychiatric disorders can be combined with metabolomics research to overcome this limitation.

METHODS

We designed a preclinical, untargeted metabolomics procedure, that focuses on the determination of central metabolites relevant to substance use disorders that are (a) associated with changes in behavior produced by acute drug exposure and (b) impacted by repeated drug exposure. Untargeted metabolomics analysis was carried out on liquid chromatography-mass spectrometry data obtained from 336 microdialysis samples. Samples were collected from the medial striatum of male Sprague-Dawley (N = 21) rats whilst behavioral data were simultaneously collected as part of a (±)-3,4-methylenedioxymethamphetamine (MDMA)-induced behavioral sensitization experiment. Analysis was conducted by orthogonal partial least squares, where the Y variable was the behavioral data, and the X variables were the relative concentrations of the 737 detected features.

RESULTS

MDMA and its derivatives, serotonin, and several dopamine/norepinephrine metabolites were the greatest predictors of acute MDMA-produced behavior. Subsequent univariate analyses showed that repeated MDMA exposure produced significant changes in MDMA metabolism, which may contribute to the increased abuse liability of the drug as a function of repeated exposure.

CONCLUSION

These findings highlight how the inclusion of behavioral data can guide metabolomics data analysis and increase the relevance of the results to the phenotype of interest.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

Simultaneous Quantification of Opioids in Blood and Urine by Gas Chromatography-Mass Spectrometer with Modified Dispersive Solid-Phase Extraction Technique

Common methodologies such as liquid-liquid extraction and solid-phase extraction are applied for the extraction of opioids from biological specimens i.e., blood and urine. Techniques including LC-MS/LC-MSMS, GC-MS, etc. are used for qualitative or quantitative determination of opioids. The goal of the present work is to design a green, economic, rugged, and simple extraction technique for famous opioids in human blood and urine and their simultaneous quantification by GC-MS equipped with an inert plus electron impact (EI) ionization source at SIM mode to produce reproducible and efficient results. Morphine, codeine, 6-acetylmorphine, nalbuphine, tramadol and dextromethorphan were selected as target opioids. Anhydrous Epsom salt was applied for dSPE of opioids from blood and urine into acetonitrile extraction solvent with the addition of sodium phosphate buffer (pH 6) and n-hexane was added to remove non-polar interfering species from samples. BSTFA was used as a derivatizing agent for GC-MS. Following method validation, the LOD/LLOQ and ULOQ were determined for morphine, codeine, nal-buphine, tramadol, and dextromethorphan at 10 ng/mL and 1500 ng/mL, respectively, while the LOD/LLOQ and ULOQ were determined for 6-acetylmorphine at 5 ng/mL and 150 ng/mL, respectively. This method was applied to real blood and urine samples of opioid abusers and the results were found to be reproducible with true quantification.

Stability of Metabolomic Content during Sample Preparation: Blood and Brain Tissues

Thermal and enzymatic reactions can significantly change the tissue metabolomic content during the sample preparation. In this work, we evaluated the stability of metabolites in human whole blood, serum, and rat brain, as well as in metabolomic extracts from these tissues. We measured the concentrations of 63 metabolites in brain and 52 metabolites in blood. We have shown that metabolites in the extracts from biological tissues are stable within 24 h at 4 °C. Serum and whole blood metabolomes are also rather stable, changes in metabolomic content of the whole blood homogenate become apparent only after 1–2 h of incubation at 4 °C, and become strong after 24 h. The most significant changes correspond to energy metabolites: the concentrations of ATP and ADP decrease fivefold, and the concentrations of NAD, NADH, and NADPH decrease below the detectable level. A statistically significant increase was observed for AMP, IMP, hypoxanthine, and nicotinamide. The brain tissue is much more metabolically active than human blood, and significant metabolomic changes occur already within the first several minutes during the brain harvest and sample homogenization. At a longer timescale (hours), noticeable changes were observed for all classes of compounds, including amino acids, organic acids, alcohols, amines, sugars, nitrogenous bases, nucleotides, and nucleosides.

Bias caused by incomplete metabolite extraction and matrix effect: Evaluation of critical factors for plasma sample preparation prior to metabolomics

Metabolomics is an omics strategy to study the metabolite alteration in the biological system. Unbiased observation of the metabolite level is essential for targeted metabolite quantification and untargeted metabolic profiling. State-of-the-art instruments and versatile tools have been developed for accurate observation of metabolic alterations in various studies. Several analytical pitfalls, such as sample overloading and signal-saturation-induced bias, have been revealed and addressed. In this study, we proposed incomplete-metabolite-extraction-caused bias is also an important issue that results in biased observation when performing metabolomics. In the demonstration example, numerous metabolites exhibited no significant difference between extracted plasma samples with different plasma contents, which is attributed to incomplete-metabolite-extraction-caused bias and matrix effect. Matrix effect is a well-known factor that result in biased observation, it can be reduced by sample dilution and compensated by using stable isotope labelled internal standards. The detection of metabolite signals in the following consecutive extractions provided further evidence of incomplete metabolite extraction. The completeness of metabolite extraction is crucial for unbiased observation of metabolic profile changes. To address this issue, we optimized the extraction time and methanol volume to reduce the incomplete-metabolite-extraction-caused bias and evaluated the metabolite signals in consecutive extractions. Methanol extraction performed with a plasma-to-methanol ratio of 1:14 resulted in metabolite responses of less than 18.1 % in the second extractions observed by metabolomic profiling. Finally, the optimized sample preparation procedure and untargeted profiling platform were applied to detect metabolite alterations associated with patients with cerebrovascular diseases and several features with significant difference were successfully identified. This study revealed and evaluated the bias caused by incomplete metabolite extraction and matrix effect in the commonly used methanol extraction method for human plasma sample preparation for metabolomics. We anticipate the proposed metabolite extraction evaluation method could benefit more clinical and biological metabolomics studies.

Phytochemicals as Regulators of Tumor Glycolysis and Hypoxia Signaling Pathways: Evidence from In Vitro Studies

The full understanding of the complex nature of cancer still faces many challenges, as cancers arise not as a result of a single target disruption but rather involving successive genetic and epigenetic alterations leading to multiple altered metabolic pathways. In this light, the need for a multitargeted, safe and effective therapy becomes essential. Substantial experimental evidence upholds the potential of plant-derived compounds to interfere in several important pathways, such as tumor glycolysis and the upstream regulating mechanisms of hypoxia. Herein, we present a comprehensive overview of the natural compounds which demonstrated, in vitro studies, an effective anticancer activity by affecting key regulators of the glycolytic pathway such as glucose transporters, hexokinases, phosphofructokinase, pyruvate kinase or lactate dehydrogenase. Moreover, we assessed how phytochemicals could interfere in HIF-1 synthesis, stabilization, accumulation, and transactivation, emphasizing PI3K/Akt/mTOR and MAPK/ERK pathways as important signaling cascades in HIF-1 activation. Special consideration was given to cell culture-based metabolomics as one of the most sensitive, accurate, and comprising approaches for understanding the response of cancer cell metabolome to phytochemicals.

Decorated magnetic nanoparticles with polyvinyl alcohol brushes modified with metal chelate affinity groups for purification of proteins

Refining is a serious challenge in the production of recombinant proteins, and this study proposes a new and easy strategy for the synthesis of magnetic affinity nanoparticles. First, the nanoparticles attached to polyvinyl alcohol brushes were synthesized, and then the hydroxyl groups of this polymer were converted to chelate groups. The nanoparticles were examined by (SEM) scanning electron microscopy, (TEM) transmission electron microscopy, (DLS) dynamic light scattering, (FT-IR) Fourier transform infrared, (XRD) X-ray powder diffraction, (VSM) vibrating sample magnetometry, and (TGA) thermal gravimetric analysis. The results confirm that uniform and spherical magnetic polymer nanoparticles with high magnetization and superparamagnetic properties were successfully synthesized. The S100A9 protein, a His-tagged recombinant protein, was expressed and purified using the synthesized nanoparticles. According to the (SDS-PAGE) sulfate-polyacrylamide gel electrophoresis results, there is a high degree of resolution in protein separation. The synthesized nanoparticles have a high protein binding capacity of about 208 mg of protein per gram of nanoparticles.

Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis

The metabolomics approach represents the last downstream phenotype and is widely used in clinical studies and drug discovery. In this paper, we outline recent advances in the metabolomics research of autoimmune diseases (ADs) such as rheumatoid arthritis (RA), multiple sclerosis (MuS), and systemic lupus erythematosus (SLE). The newly discovered biomarkers and the metabolic mechanism studies for these ADs are described here. In addition, studies elucidating the metabolic mechanisms underlying these ADs are presented. Metabolomics has the potential to contribute to pharmacotherapy personalization; thus, we summarize the biomarker studies performed to predict the personalization of medicine and drug response.

Identification of Effector Metabolites Using Exometabolite Profiling of Diverse Microalgae

Dissolved exometabolites mediate algal interactions in aquatic ecosystems, but microalgal exometabolomes remain understudied. We conducted an untargeted metabolomic analysis of nonpolar exometabolites exuded from four phylogenetically and ecologically diverse eukaryotic microalgal strains grown in the laboratory, freshwater Chlamydomonas reinhardtii, brackish Desmodesmus sp., marine Phaeodactylum tricornutum, and marine Microchloropsis salina, to identify released metabolites based on relative enrichment in the exometabolomes compared to cell pellet metabolomes. Exudates from the different taxa were distinct, but we did not observe clear phylogenetic patterns. We used feature-based molecular networking to explore the identities of these metabolites, revealing several distinct di- and tripeptides secreted by each of the algae, lumichrome, a compound that is known to be involved in plant growth and bacterial quorum sensing, and novel prostaglandin-like compounds. We further investigated the impacts of exogenous additions of eight compounds selected based on exometabolome enrichment on algal growth. Of these compounds, five (lumichrome, 5′-S-methyl-5′-thioadenosine, 17-phenyl trinor prostaglandin A2, dodecanedioic acid, and aleuritic acid) impacted growth in at least one of the algal cultures. Two of these compounds (dodecanedioic acid and aleuritic acid) produced contrasting results, increasing growth in some algae and decreasing growth in others. Together, our results reveal new groups of microalgal exometabolites, some of which could alter algal growth when provided exogenously, suggesting potential roles in allelopathy and algal interactions.

IMPORTANCE Microalgae are responsible for nearly half of primary production on earth and play an important role in global biogeochemical cycling as well as in a range of industrial applications. Algal exometabolites are important mediators of algal-algal and algal-bacterial interactions that ultimately affect algal growth and physiology. In this study, we characterize exometabolomes across marine and freshwater algae to gain insights into the diverse metabolites they release into their environments (“exudates”). We observe that while phylogeny can play a role in exometabolome content, environmental conditions or habitat origin (freshwater versus marine) are also important. We also find that several of these compounds can influence algal growth (as measured by chlorophyll production) when provided exogenously, highlighting the importance of characterization of these novel compounds and their role in microalgal ecophysiology.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Untargeted Metabolomics in Forensic Toxicology: A New Approach for the Detection of Fentanyl Intake in Urine Samples

The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time frame allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive "fingerprint" of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together with 81 urine samples including negative controls and positive samples obtained from recent users of either fentanyl or "traditional" drugs, were subjected to untargeted analysis using both UHPLC reverse phase and HILIC chromatography combined with QTOF mass spectrometry. Data independent acquisition was performed by SWATH in order to obtain a comprehensive profile of the urinary metabolome. After extensive processing, the resulting datasets were initially subjected to unsupervised exploration by principal component analysis (PCA), yielding clear separation of the fentanyl positive samples with respect to both controls and samples positive to other drugs. The urine datasets were then systematically investigated by supervised classification models based on soft independent modeling by class analogy (SIMCA) algorithms, with the end goal of identifying fentanyl users. A final single-class SIMCA model based on an RP dataset and five PCs yielded 96% sensitivity and 74% specificity. The distinguishable metabolic patterns produced by fentanyl in comparison to other opioids opens up new perspectives in the interpretation of the biological activity of fentanyl.

Lipidomic analysis using hydrophilic interaction liquid chromatography microgradient fractionation of total lipid extracts

Lipidomic samples are complex mixtures of structurally different species of a wide range of concentrations providing challenges in their characterization. In this work, we present a proof of concept for the application of a simple microgradient liquid chromatography device on the detailed analysis of lipid classes. Our lipidomic analysis is based on a lipid class microgradient fractionation of a total lipid extract using an in-house-prepared hydrophilic interaction liquid chromatography microcolumn followed by RP-LC/MS of the collected lipid class fractions. The final fractionation method uses a 40-mm-long microcolumn of 500 μm ID with silica stationary phase obtained from a commercially available chromatographic column and the microgradient of the mobile phase prepared in a microsyringe using methyl tert-butyl ether (MTBE) - methanol - water - ammonium acetate mixtures of various elution strengths. MTBE total lipid extract is directly separated by microgradient elution into lipid classes according to their polarity, which enables the collection of isolated fractions of most lipid classes. The method has been applied to the fractionation of porcine brain extract into nonpolar lipids, hexosylceramides, phosphoethanolamines, phosphocholines, sphingomyelins, and lysophosphocholines classes. Achieved repeatability, recovery, and advanced lipid coverage prove the applicability of the microgradient fractionation of total lipid extract for the comprehensive lipidomic analysis.

Generic multicriteria approach to determine the best precipitation agent for removal of biomacromolecules prior to non-targeted metabolic analysis

The removal of biomacromolecules from biofluids decreases the sample complexity and lower electrospray suppression effects. Furthermore, it can increase the analysis sensitivity, precision, and selectivity. Often removal approaches evaluate the model based on a single criterion, like protein removed or response of one of few specific metabolites. In this study, we used a multicriteria approach to test the effect of using the solvents methanol and acetonitrile (organic solvent precipitation), trichloroacetic acid (acidic precipitation) and ammonium sulphate (salting out) to remove biomacromolecules from a downstream recovery process from a bacillus fermentation. The downstream recovery process intermediates were analysed using reversed-phase ultra-high-pressure liquid chromatography with electrospray ionisation and high-resolution time-of-flight mass spectrometry detection. To evaluate the pre-treatment agents the following multicriteria was applied i) practical considerations, ii) total amino acid in the precipitated pellet, iii) putative identification of the molecules removed or created by the different treatments, iv) coherence between high quality extracted ion chromatograms (repeatability of DW-CODA) and v) replicate consistency from principal component analysis score values obtained by using the CHEMometric analysis of sections of Selected Ion Chromatograms (CHEMSIC) method. This study presents a generic workflow to find the best pre-treatment for removing bio-macromolecules from biofluids with a multicriteria approach. In our case, the best protein removal strategy for downstream recovery intermediates was acetonitrile precipitation. This method showed high precision, created few artefact peaks compared to simple sample dilution, and mainly removed small peptides.

Assessment of solid phase microextraction as a sample preparation tool for untargeted analysis of brain tissue using liquid chromatography-mass spectrometry

This work presents an evaluation of solid-phase microextraction (SPME) SPME in combination with liquid chromatography-high resolution mass spectrometry (LC-HRMS) as an analytical approach for untargeted brain analysis. The study included a characterization of the metabolite coverage provided by C18, mixed-mode (MM, with benzene sulfonic acid and C18 functionalities), and hydrophilic lipophilic balanced (HLB) particles as sorbents in SPME coatings after extraction from cow brain homogenate at static conditions. The effects of desorption solvent, extraction time, and chromatographic modes on the metabolite features detected were investigated. Method precision and absolute matrix effects were also assessed. Among the main findings of this work, it was observed that all three tested coating chemistries were able to provide comparable brain tissue information. HLB provided higher responses for polar metabolites; however, as these fibers were prepared in-house, higher inter-fiber relative standard deviations were also observed. C18 and HLB coatings offered similar responses with respect to lipid-related features, whereas MM and C18 provided the best results in terms of method precision. Our results also showed that the use of methanol is essential for effective desorption of non-polar metabolites. Using a reversed-phase chromatographic method, an average of 800 and 1200 brain metabolite features detected in positive and negative modes, respectively, met inter-fibre RSD values below 30% (n=4) after removal of fibre and solvent artefacts from the associated datasets. For features detected using a lipidomics method, a total of 900 and 1800 features detected using C18 fibers in positive and negative mode, respectively, met the same criteria. In terms of absolute matrix effects, the majority of the model metabolites tested showed values between 80 and 120%, which are within the acceptable range. Overall, the findings of this work lay the foundation for further optimization of parameters for SPME-LC-HRMS methods suitable for in vivo and ex vivo brain (and other tissue) untargeted studies, and support the applicability of this approach for non-destructive tissue metabolomics.

Practical Considerations in Method Development for Gas Chromatography-Based Metabolomic Profiling

This chapter discusses the fundamentals of gas chromatography (GC) to improve method development for metabolic profiling of complex biological samples. The selection of column geometry and phase ratio impacts analyte mass transfer, which must be carefully optimized for fast analysis. Stationary phase selection is critical to obtain baseline resolution of critical pairs, but such selection must consider important aspects of metabolomic protocols, such as derivatization and dependence of analyte identification on existing databases. Sample preparation methods are also addressed depending on the sample matrix, including liquid-liquid extraction and solid-phase microextraction.

Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review

Arboviruses, such as chikungunya, dengue, yellow fever, and zika, caused by the bite of the Aedes aegypti mosquito, have been a frequent public health problem, with a high incidence of outbreaks in tropical and subtropical countries. These diseases are easily confused with a flu-like illness and present very similar symptoms, difficult to distinguish, and treat appropriately. The effects that these infections cause in the organism are fundamentally derived from complex metabolic processes. A prominent area of science that investigates the changes in the metabolism of complex organisms is the metabolomics. Metabolomics measures the metabolites produced or altered in biological organisms, through the use of robust analytical platforms, such as separation techniques hyphenated with mass spectrometry, combined with bioinformatics. This review article presents an overview of the basic concepts of metabolomics workflow and advances in this field, and compiles research articles that use this omic approach to study these arboviruses. In this context, the metabolomics is applied to search new therapies, understand the viral replication mechanisms, and access the host-virus interactions.

Comprehensive Vitamer Profiling of Folate Mono- and Polyglutamates in Baker's Yeast (Saccharomyces cerevisiae) as a Function of Different Sample Preparation Procedures

Folates are a group of B9 vitamins playing an important role in many metabolic processes such as methylation reactions, nucleotide synthesis or oxidation and reduction processes. However, humans are not able to synthesize folates de novo and thus rely on external sources thereof. Baker's yeast (Saccharomyces cerevisiae) has been shown to produce high amounts of this vitamin but extensive identification of its folate metabolism is still lacking. Therefore, we optimized and compared different sample preparation and purification procedures applying solid phase extraction (SPE). Strong anion exchange (SAX), C18 and hydrophilic-lipophilic-balanced (HLB) materials were tested for their applicability in future metabolomics studies. SAX turned out to be the preferred material for the quantitative purification of folates. Qualification of several folate vitamers was achieved by ultra-high pressure liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-ToF-MS) measurements and quantification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS) applying stable isotope dilution assays (SIDAs). The oxidation product s-pyrazino-triazine (MeFox) was included into the SIDA method for total folate determination and validation. Applying the best protocol (SAX) in regard to folate recovery, we analyzed 32 different vitamers in different polyglutamate states up to nonaglutamates, of which we could further identify 26 vitamers based on tandem-MS (MS2) spectra. Total folate quantification revealed differences in formyl folate contents depending on the cartridge chemistry used for purification. These are supposedly a result of interconversion reactions occurring during sample preparation due to variation in pH adjustments for the different purification protocols. The occurrence of interconversion and oxidation reactions should be taken into consideration in sample preparation procedures for metabolomics analyses with a focus on folates.

General Guidelines for Sample Preparation Strategies in HR-µMAS NMR-based Metabolomics of Microscopic Specimens

The study of the metabolome within tissues, organisms, cells or biofluids can be carried out by several bioanalytical techniques. Among them, nuclear magnetic resonance (NMR) is one of the principal spectroscopic methods. This is due to a sample rotation technique, high-resolution magic angle spinning (HR-MAS), which targets the analysis of heterogeneous specimens with a bulk sample mass from 5 to 10 mg. Recently, a new approach, high-resolution micro-magic angle spinning (HR-μMAS), has been introduced. It opens, for the first time, the possibility of investigating microscopic specimens (<500 μg) with NMR spectroscopy, strengthening the concept of homogeneous sampling in a heterogeneous specimen. As in all bioanalytical approaches, a clean and reliable sample preparation strategy is a significant component in designing metabolomics (or -omics, in general) studies. The sample preparation for HR-μMAS is consequentially complicated by the μg-scale specimen and has yet to be addressed. This report details the strategies for three specimen types: biofluids, fluid matrices and tissues. It also provides the basis for designing future μMAS NMR studies of microscopic specimens.

Chinese Herbal Medicine (MaZiRenWan) Improves Bowel Movement in Functional Constipation Through Down-Regulating Oleamide

In a prospective, randomized, three-arms, controlled clinical study, Chinese Herbal Medicine MaZiRenWan (MZRW, also known as Hemp Seed Pill) demonstrates comparable efficacy with Senna for functional constipation (FC) during an 8-week treatment period. Both MZRW and Senna are better than a placebo; relative to Senna and a placebo, MZRW displayed a more sustained effect during the 8-week follow-up period. The characteristic pharmacological mechanism responsible for this observation is still unclear. To explore this, we collected pre- and post-treatment serum samples of 85 FC patients from MZRW/Senna/placebo treatment groups for pharmacometabolomic analysis. An ultrahigh-performance liquid chromatography-mass spectrometer (UPLC-MS) was used for metabolic profiling and quantification. In vivo studies were conducted in constipated C57BL/6J mice to verify the effects and corresponding mechanism(s) of the action of MZRW. Pearson correlation analysis, paired t-test, one-way ANOVA analysis, χ2 test, and Student t-test were used to interpret the clinical and preclinical data. Changes in levels of circulating oleamide and its derivatives negatively correlate with improvement in complete spontaneous bowel movement (CSBM) in the MZRW group (Pearson r = -0.59, p = 0.00057). The same did not hold true for either Senna or placebo groups. Oleamide is a known regulator of intestinal motility. MZRW treatment resulted in reduced levels of circulating oleamide in FC patients. Experimental verification showed that MZRW attenuated oleamide-induced slow intestinal motility in mice. MZRW decreased oleamide levels in serum, ileum, and colon in normal mice, but increased expression of colonic fatty acid amide hydrolase (FAAH). In conclusion, MZRW improved bowel movement in FC by down-regulating oleamide, possibly by enhancing FAAH-mediated degradation. Our findings suggest a novel therapeutic strategy for FC.

Metabolome response to anthropogenic contamination on microalgae: a review

BACKGROUND

Microalgae play a key role in ecosystems and are widely used in ecological status assessment. Research focusing on such organisms is then well developed and essential. Anyway, approaches for a better comprehension of their metabolome's response towards anthropogenic stressors are only emerging.

AIM OF REVIEW

This review presents the biochemical responses of various microalgae species towards several contaminants including metals and chemicals as pesticides or industrial compounds. We aim to provide a comprehensive and up-to-date overview of analytical approaches deciphering anthropogenic contaminants impact on microalgae metabolome dynamics, in order to bring out relevant biochemical markers that could be used for risk assessment.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Studies to date on ecotoxicological metabolomics on microalgae are highly heterogeneous in both analytical techniques and resulting metabolite identification. There is a real need for studies using complementary approaches to determine biomarkers usable for ecological risk assessment.

Experimental Design and Sample Preparation in Forest Tree Metabolomics

Appropriate experimental design and sample preparation are key steps in metabolomics experiments, highly influencing the biological interpretation of the results. The sample preparation workflow for plant metabolomics studies includes several steps before metabolite extraction and analysis. These include the optimization of laboratory procedures, which should be optimized for different plants and tissues. This is particularly the case for trees, whose tissues are complex matrices to work with due to the presence of several interferents, such as oleoresins, cellulose. A good experimental design, tree tissue harvest conditions, and sample preparation are crucial to ensure consistency and reproducibility of the metadata among datasets. In this review, we discuss the main challenges when setting up a forest tree metabolomics experiment for mass spectrometry (MS)-based analysis covering all technical aspects from the biological question formulation and experimental design to sample processing and metabolite extraction and data acquisition. We also highlight the importance of forest tree metadata standardization in metabolomics studies.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Evaluation of Sample Preparation Methods for the Analysis of Reef-Building Corals Using ¹H-NMR-Based Metabolomics

The field of metabolomics generally lacks standardized methods for the preparation of samples prior to analysis. This is especially true for metabolomics of reef-building corals, where the handful of studies that were published employ a range of sample preparation protocols. The utilization of metabolomics may prove essential in understanding coral biology in the face of increasing environmental threats, and an optimized method for preparing coral samples for metabolomics analysis would aid this cause. The current study evaluates three important steps during sample processing of stony corals: (i) metabolite extraction, (ii) metabolism preservation, and (iii) subsampling. Results indicate that a modified Bligh and Dyer extraction is more reproducible across multiple coral species compared to methyl tert-butyl ether and methanol extractions, while a methanol extraction is superior for feature detection. Additionally, few differences were detected between spectra from frozen or lyophilized coral samples. Finally, extraction of entire coral nubbins increased feature detection, but decreased throughput and was more susceptible to subsampling error compared to a novel tissue powder subsampling method. Overall, we recommend the use of a modified Bligh and Dyer extraction, lyophilized samples, and the analysis of brushed tissue powder for the preparation of reef-building coral samples for ¹H NMR metabolomics.

Sample Preparation and Reporting Standards for Metabolomics of Adherent Mammalian Cells

Metabolomics is an analytical technique that investigates the small molecules present within a biological system. Metabolomics of cultured cells allows profiling of the metabolic chemicals involved in a cell type-specific system and the response of that metabolome to external challenges, such as change in environment or exposure to drugs or toxins. The numerous benefits of in vitro metabolomics include a much greater control of external variables and reduced ethical concerns. There is potential for metabolomics of mammalian cells to uncover new information on mechanisms of action for drugs or toxins or to provide a more sensitive, human-specific early risk assessment in drug development or toxicology investigations. One way to achieve stronger biological outcomes from metabolomic data is via the use of these mammalian cultured cell models, particularly in a high-throughput context. With the sensitivity and quantity of data that metabolomics is able to provide, it is important to ensure that the sampling techniques have minimal interference when it comes to interpretation of any observed shifts in the metabolite profile. Here we describe a sampling procedure designed to ensure that the effects seen in metabolomic analyses are explained fully by the experimental factor and not other routine culture-specific activities.

Review of recent developments in GC-MS approaches to metabolomics-based research

BACKGROUND

Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available.

AIM OF REVIEW

This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

Opportunities for green microextractions in comprehensive two-dimensional gas chromatography / mass spectrometry-based metabolomics - A review

Microextractions have become an attractive class of techniques for metabolomics. The most popular technique is solid-phase microextraction that revolutionized the field of modern sample preparation in the early nineties. Ever since this milestone, microextractions have taken on many principles and formats comprising droplets, fibers, membranes, needles, and blades. Sampling devices may be customized to impart exhaustive or equilibrium-based characteristics to the extraction method. Equilibrium-based approaches may rely on additional methods for calibration, such as diffusion-based or on-fiber kinetic calibration to improve bioanalysis. In addition, microextraction-based methods may enable minimally invasive sampling protocols and measure the average free concentration of analytes in heterogeneous multiphasic biological systems. On-fiber derivatization has evidenced new opportunities for targeted and untargeted analysis in metabolomics. All these advantages have highlighted the potential of microextraction techniques for in vivo and on-site sampling and sample preparation, while many opportunities are still available for laboratory protocols. In this review, we outline and discuss some of the most recent applications using microextractions techniques for comprehensive two-dimensional gas chromatography-based metabolomics, including potential research opportunities.

Radionuclide X-ray fluorescence spectrometry of medical plant samples

The method of samples processing and subsequent their analysis using Radionuclide X-ray Fluorescence Spectrometry for medical plant samples and drugs has been developed. Technical aspects of the measurement such as mutual geometrical arrangement of tablets (of various size and mass), semiconductor Si/Li detector and the primary source of radiation, 238Pu, are discussed. Technique of Radionuclide X-ray Fluorescence Spectrometry (RXFS) has been applied on samples of medical products and medicines used to treat liver diseases. Medicinal herbs, teas in infusion bags and the drug from this group, were analysed in the solid state (in the form of tablets) or as the leachate, applied to the ion exchanger resin. Chelating Extraction Disks EmporeTM have proven the ability to extract elements from liquid samples under certain conditions and thus to prepare samples for RXFS analysis and evaluation. To ensure correct results, an optimal pH environment has been found. The detection limits of selected elements (Cr, Mn, Fe, Ni, Cu, Zn and Pb) have been calculated for both solid and liquid state samples. Standard addition method and calibration curve parameters have been used to evaluate the concentration of each element in studied samples. Determined concentrations of the examined elements were compared with permissible contaminant limits for the relevant food law in Slovak Republic.

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration

Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Extracellular Microbial Metabolomics: The State of the Art

Microorganisms produce and secrete many primary and secondary metabolites to the surrounding environment during their growth. Therefore, extracellular metabolites provide important information about the changes in microbial metabolism due to different environmental cues. The determination of these metabolites is also comparatively easier than the extraction and analysis of intracellular metabolites as there is no need for cell rupture. Many analytical methods are already available and have been used for the analysis of extracellular metabolites from microorganisms over the last two decades. Here, we review the applications and benefits of extracellular metabolite analysis. We also discuss different sample preparation protocols available in the literature for both types (e.g., metabolites in solution and in gas) of extracellular microbial metabolites. Lastly, we evaluate the authenticity of using extracellular metabolomics data in the metabolic modelling of different industrially important microorganisms.

Metabolomic signature of brain cancer

Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.

Chemical Profile and Antioxidant Properties of Extracts and Essential Oils from Citrus × limon (L.) Burm. cv. Femminello Comune

Citrus × limon cv. Femminello Comune (Rutaceae) from Rocca Imperiale (Italy), one of the six Protected Geographical Indication (PGI) Italian lemon crops, has been recently received renewed interest. In this work, fresh and dried peels and leaves were extracted by hydrodistillation, supercritical fluid extraction (SFE), and Soxhlet apparatus. Chemical profile was assessed by gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS). Except for leaves extracts obtained by Soxhlet apparatus, the monoterpene hydrocarbons fraction dominated. Limonene, γ-terpinene, and β-pinene were the main identified compounds. The antioxidant activity was investigated using different in vitro assays namely 2,2-diphenyl-1-picrylhydrazyl (DPPH), ABTS, ferric reducing ability power (FRAP), and β-carotene bleaching test. In DPPH test, the essential oil obtained by hydrodistillation of fresh peel exhibited the highest activity (IC50 of 1.17 mg/ml). Leaves extracted by SFE showed a good activity in both DPPH and β-carotene bleaching test with IC50 values of 2.20 and 6.66 mg/ml, respectively. Monoterpene hydrocarbons fraction exhibited a positive Pearson's correlation coefficient with all antioxidant assays. Leaves, often considered waste material, should be considered from a different point because they represent a matrix of indisputable interest.

Sample Preparation for Bioanalytical and Pharmaceutical Analysis

Biological and pharmaceutical samples represent formidable challenges in sample preparation that hold important consequences for bioanalysis and genotoxic impurity quantification. This Feature will emphasize significant advances toward the development of rapid, sensitive, and selective sample preparation methods.

Quantitative metabolomics of photoreceptor degeneration and the effects of stem cell-derived retinal pigment epithelium transplantation

Photoreceptor degeneration is characteristic of vision-threatening diseases including age-related macular degeneration. Photoreceptors are metabolically demanding cells in the retina, but specific details about their metabolic behaviours are unresolved. The quantitative metabolomics of retinal degeneration could provide valuable insights and inform future therapies. Here, we determined the metabolomic 'fingerprint' of healthy and dystrophic retinas in rat models using optimized metabolite extraction techniques. A number of classes of metabolites were consistently dysregulated during degeneration: vitamin A analogues, fatty acid amides, long-chain polyunsaturated fatty acids, acyl carnitines and several phospholipid species. For the first time, a distinct temporal trend of several important metabolites including DHA (4Z,7Z,10Z,13Z,16Z,19Z-docosahexaenoic acid), all-trans-retinal and its toxic end-product N-retinyl-N-retinylidene-ethanolamine were observed between healthy and dystrophic retinas. In this study, metabolomics was further used to determine the temporal effects of the therapeutic intervention of grafting stem cell-derived retinal pigment epithelium (RPE) in dystrophic retinas, which significantly prevented photoreceptor atrophy in our previous studies. The result revealed that lipid levels such as phosphatidylethanolamine in eyes were restored in those animals receiving the RPE grafts. In conclusion, this study provides insight into the metabolomics of retinal degeneration, and further understanding of the efficacy of RPE transplantation.This article is part of the themed issue 'Quantitative mass spectrometry'.

Partial least squares model and design of experiments toward the analysis of the metabolome of Jatropha gossypifolia leaves: Extraction and chromatographic fingerprint optimization

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.