Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry

Myricanol improves metabolic profiles in dexamethasone induced lipid and protein metabolism disorders in mice

Myricanol (MY) is one of the main active components from bark of Myrica Rubra. It is demonstrated that MY rescues dexamethasone (DEX)-induced muscle dysfunction via activating silent information regulator 1 (SIRT1) and increasing adenosine 5'-monophosphate-activated protein kinase (AMPK) phosphorylation. Since SIRT1 and AMPK are widely involved in the metabolism of nutrients, we speculated that MY may exert beneficial effects on DEX-induced metabolic disorders. This study for the first time applied widely targeted metabolomics to investigate the beneficial effects of MY on glucose, lipids, and protein metabolism in DEX-induced metabolic abnormality in mice. The results showed that MY significantly reversed DEX-induced soleus and gastrocnemius muscle weight loss, muscle fiber damage, and muscle strength loss. MY alleviated DEX-induced metabolic disorders by increasing SIRT1 and glucose transporter type 4 (GLUT4) expressions. Additionally, myricanol prevented muscle cell apoptosis and atrophy by inhibiting caspase 3 cleavages and muscle ring-finger protein-1 (MuRF1) expression. Metabolomics showed that MY treatment reversed the serum content of carnitine ph-C1, palmitoleic acid, PS (16:0_17:0), PC (14:0_20:5), PE (P-18:1_16:1), Cer (t18:2/38:1(2OH)), four amino acids and their metabolites, and 16 glycerolipids in DEX mice. Kyoto encyclopedia of genes and genomes (KEGG) and metabolic set enrichment analysis (MSEA) analysis revealed that MY mainly affected metabolic pathways, glycerolipid metabolism, lipolysis, fat digestion and absorption, lipid and atherosclerosis, and cholesterol metabolism pathways through regulation of metabolites involved in glutathione, butanoate, vitamin B6, glycine, serine and threonine, arachidonic acid, and riboflavin metabolism. Collectively, MY can be used as an attractive therapeutic agent for DEX-induced metabolic abnormalities.

High-level phenol bioproduction by engineered Pichia pastoris in glycerol fed-batch fermentation using an efficient pertraction system

This study aimed to establish a high-level phenol bioproduction system from glycerol through metabolic engineering of the yeast Pichia pastoris (Komagataella phaffii). Introducing tyrosine phenol-lyase to P. pastoris led to a production of 59 mg/L of phenol in flask culture. By employing a strain of P. pastoris that overproduces tyrosine-a precursor to phenol-we achieved a phenol production of 1052 mg/L in glycerol fed-batch fermentation. However, phenol concentrations exceeding 1000 mg/L inhibited P. pastoris growth. A phenol pertraction system utilizing a hollow fiber membrane contactor and tributyrin as the organic solvent was developed to reduce phenol concentration in the culture medium. Integrating this system with glycerol fed-batch fermentation resulted in a 214 % increase in phenol titer (3304 mg/L) compared to glycerol fed-batch fermentation alone. These approaches offer a significant framework for the microbial production of chemicals and materials that are highly toxic to microorganisms.

Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics

The analysis of the brain extracellular metabolome is of interest for numerous subdomains within neuroscience. Not only does it provide information about normal physiological functions, it is even more of interest for biomarker discovery and target discovery in disease. The extracellular analysis of the brain is particularly interesting as it provides information about the release of mediators in the brain extracellular fluid to look at cellular signaling and metabolic pathways through the release, diffusion and re-uptake of neurochemicals. In vivo samples are obtained through microdialysis, cerebral open-flow microperfusion or solid-phase microextraction. The analytes of potential interest are typically low in concentration and can have a wide range of physicochemical properties. Liquid chromatography coupled to mass spectrometry has proven its usefulness in brain metabolomics. It allows sensitive and specific analysis of low sample volumes, obtained through different approaches. Several strategies for the analysis of the extracellular fluid have been proposed. The most widely used approaches apply sample derivatization, specific stationary phases and/or hydrophilic interaction liquid chromatography. Miniaturization of these methods allows an even higher sensitivity. The development of chiral metabolomics is indispensable, as it allows to compare the enantiomeric ratio of compounds and provides even more challenges. Some limitations continue to exist for the previously developed methods and the development of new, more sensitive methods remains needed. This review provides an overview of the methods developed for sampling and liquid chromatography-mass spectrometry analysis of the extracellular metabolome.

Seaweed metabolomics: A review on its nutrients, bioactive compounds and changes in climate change

Seaweed, an important food resource in several Asian countries, contains various metabolites, including sugars, organic acids, and amino acids; however, their content is affected by prevailing environmental conditions. This review discusses seaweed metabolomics, especially the distribution of primary and functional secondary metabolites (e.g., carotenoids, polyphenols) in seaweed. Additionally, the effects of global warming on seaweed metabolite profile changes are discussed. For example, high temperatures can increase amino acid levels in seaweeds. Overall, understanding the effects of global warming on seaweed metabolite profiles can be useful for evaluating the nutritional composition of seaweeds as food. This review provides an overview of recent applications of metabolomics in seaweed research as well as a perspective on the nutrient content and cultivation of seaweeds under climate change scenarios.

Plasma galectins and metabolites in advanced head and neck carcinomas: evidence of distinct immune characteristics linked to hypopharyngeal tumors

Extra-cellular galectins 1, 3 and 9 (gal-1, -3 and -9) are known to act as soluble immunosuppressive agents in various malignancies. Previous publications have suggested that their expression is dependent on the metabolic status of producing cells and reciprocally that they can influence metabolic pathways in their target cells. Very little is known about the status of gal-1, -3 and -9 in patients bearing head and neck squamous cell carcinomas (HNSCC) and about their relationships with the systemic metabolic condition. This study was conducted in plasma samples from a prospective cohort of 83 HNSCC patients with advanced disease. These samples were used to explore the distribution of gal-1, -3 and -9 and simultaneously to profile a series of 87 metabolites assessed by mass spectrometry. We identified galectin and metabolic patterns within five disease categories defined according to the primary site and human papillomavirus (HPV) status (HPV-positive and -negative oropharyngeal carcinomas, carcinomas of the oral cavity, hypopharynx and larynx carcinomas). Remarkably, samples related to hypopharyngeal carcinomas displayed the highest average concentration of gal-9 (p = .017) and a trend toward higher concentrations of kynurenine, a potential factor of tumor growth and immune suppression. In contrast, there was a tendency toward higher concentrations of fatty acids in samples related to oral cavity. These observations emphasize the diversity of HPV-negative HNSCCs. Depending on their primary site, they evolve into distinct types of immune and metabolic landscapes that seem to be congruent with specific oncogenic mechanisms.

Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers

Mass spectrometry (MS) is one of the most widely used analytical techniques in many fields. Recent developments in chemical and biological researches have drawn much attention to the measurement of substances with low abundances in samples. Continuous efforts have been made consequently to further improve the sensitivity of MS. Modifications on the mass analyzers of mass spectrometers offer a direct, universal and practical way to obtain higher sensitivity. This review provides a comprehensive overview of the latest developments in mass analyzers for the improvement of mass spectrometers' sensitivity, including quadrupole, ion trap, time-of-flight (TOF) and Fourier transform ion cyclotron (FT-ICR), as well as different combinations of these mass analyzers. The advantages and limitations of different mass analyzers and their combinations are compared and discussed. This review provides guidance to the selection of suitable mass spectrometers in chemical and biological analytical applications. It is also beneficial to the development of novel mass spectrometers.

Hyphenated Mass Spectrometry versus Real-Time Mass Spectrometry Techniques for the Detection of Volatile Compounds from the Human Body

Mass spectrometry (MS) is an analytical technique that can be used for various applications in a number of scientific areas including environmental, security, forensic science, space exploration, agri-food, and numerous others. MS is also continuing to offer new insights into the proteomic and metabolomic fields. MS techniques are frequently used for the analysis of volatile compounds (VCs). The detection of VCs from human samples has the potential to aid in the diagnosis of diseases, in monitoring drug metabolites, and in providing insight into metabolic processes. The broad usage of MS has resulted in numerous variations of the technique being developed over the years, which can be divided into hyphenated and real-time MS techniques. Hyphenated chromatographic techniques coupled with MS offer unparalleled qualitative analysis and high accuracy and sensitivity, even when analysing complex matrices (breath, urine, stool, etc.). However, these benefits are traded for a significantly longer analysis time and a greater need for sample preparation and method development. On the other hand, real-time MS techniques offer highly sensitive quantitative data. Additionally, real-time techniques can provide results in a matter of minutes or even seconds, without altering the sample in any way. However, real-time MS can only offer tentative qualitative data and suffers from molecular weight overlap in complex matrices. This review compares hyphenated and real-time MS methods and provides examples of applications for each technique for the detection of VCs from humans.

GC-MS/MS Profiling of Plant Metabolites

Gas chromatography coupled to electron ionization (EI) quadrupole mass spectrometry (GC-MS) is currently one of the most developed and robust metabolomics technologies. This approach allows for simultaneous measurements of large number of chemically diverse compounds including organic acids, amino acids, sugars, sugar alcohols, aromatic amines, and fatty acids. Untargeted GC-MS profiling based on full scan data acquisition requires complicated raw data processing and sometime provides ambiguous metabolite identifications. Targeted analysis using GC-MS/MS can provide better specificity, increase sensitivity, and simplify data processing and compound identification but wider application of targeted GC-MS/MS approach in metabolomics is hampered by the lack of extensive databases of MRM transitions for non-derivatized and derivatized endogenous metabolites. The focus of this chapter is the automation of GC-MS/MS method development which makes it feasible to develop quantitative methods for several hundred metabolites and use this strategy for plant metabolomics applications.

The snapshot of metabolic health in evaluating micronutrient status, the risk of infection and clinical outcome of COVID-19

COVID-19 has re-established the significance of analyzing the organism through a metabolic perspective to uncover the dynamic interconnections within the biological systems. The role of micronutrient status and metabolic health emerge as pivotal in COVID-19 pathogenesis and the immune system's response. Metabolic disruption, proceeding from modifiable factors, has been proposed as a significant risk factor accounting for infection susceptibility, disease severity and risk for post-COVID complications. Metabolomics, the comprehensive study and quantification of intermediates and products of metabolism, is a rapidly evolving field and a novel tool in biomarker discovery. In this article, we propose that leveraging insulin resistance biomarkers along with biomarkers of micronutrient deficiencies, will allow for a diagnostic window and provide functional therapeutic targets. Specifically, metabolomics can be applied as: a. At-home test to assess the risk of infection and propose nutritional support, b. A screening tool for high-risk COVID-19 patients to develop serious illness during hospital admission and prioritize medical support, c(i). A tool to match nutritional support with specific nutrient requirements for mildly ill patients to reduce the risk for hospitalization, and c(ii). for critically ill patients to reduce recovery time and risk of post-COVID complications, d. At-home test to monitor metabolic health and reduce post-COVID symptomatology. Metabolic rewiring offers potential virtues towards disease prevention, dissection of high-risk patients, taking actionable therapeutic measures, as well as shielding against post-COVID syndrome.

Autophagy Deficiency by Atg4B Loss Leads to Metabolomic Alterations in Mice

Autophagy is an essential protective mechanism that allows mammalian cells to cope with a variety of stressors and contributes to maintaining cellular and tissue homeostasis. Due to these crucial roles and also to the fact that autophagy malfunction has been described in a wide range of pathologies, an increasing number of in vivo studies involving animal models targeting autophagy genes have been developed. In mammals, total autophagy inactivation is lethal, and constitutive knockout models lacking effectors of this route are not viable, which has hindered so far the analysis of the consequences of a systemic autophagy decline. Here, we take advantage of atg4b^−/− mice, an autophagy-deficient model with only partial disruption of the process, to assess the effects of systemic reduction of autophagy on the metabolome. We describe for the first time the metabolic footprint of systemic autophagy decline, showing that impaired autophagy results in highly tissue-dependent alterations that are more accentuated in the skeletal muscle and plasma. These changes, which include changes in the levels of amino-acids, lipids, or nucleosides, sometimes resemble those that are frequently described in conditions like aging, obesity, or cardiac damage. We also discuss different hypotheses on how impaired autophagy may affect the metabolism of several tissues in mammals.

Future perspectives on in-vitro diagnosis of drug allergy by the lymphocyte transformation test

This article aims to envisage future perspectives of the lymphocyte transformation test (LTT). We describe the select innovative techniques, which can be integrated at different stages of the LTT to potentially improve the sensitivity, specificity, or practicability of the LTT. We first focus upon the cell sorting techniques comprising immunomagnetic cell separation and flow cytometry, which can be implemented prior and after the LTT culturing step to concentrate and quantify specific immune cell types. Further, we elaborate upon three important omics techniques such as transcriptomics, proteomics, and metabolomics, which can be integrated downstream of the LTT to analyze molecular changes in specific immune cells following drug induced activation and proliferation. We also develop visions, how state of the art techniques used in other scientific fields, can be transferred and applied in the context of in-vitro detection of drug allergy.

The intracellular metabolome of starving cells

Fasting induces vast metabolic adaptations on the cellular level and leads to an organism-wide induction of autophagy. Autophagic degradation subserves resource recycling and facilitates the maintenance of energetic homeostasis. Mass spectrometry offers the possibility to assess changes in the metabolome that occur in conditions of nutrient deprivation and to profile such adaptations. Here we describe a detailed workflow for the targeted quantitation and untargeted profiling of metabolites that can be used to assess the intracellular metabolome of starving cells. Moreover, we outline a workflow for the use of non-radioactive isotope labeled metabolites. Altogether, we show that mass spectrometry is a powerful tool for monitoring metabolic changes in conditions of fasting.

Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics

Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Protective Mechanism of Acacia saligna Butanol Extract and Its Nano-Formulations against Ulcerative Colitis in Rats as Revealed via Biochemical and Metabolomic Assays

Ulcerative colitis (UC) is a relapsing inflammatory disease of unknown etiology. The increased risk of cancer in UC patients warrants for the development of novel drug treatments. Herein, this work concerns with the investigation of the protective effects of Acacia saligna butanol extract (ASBE) and its nanoformulations on UC in a rat model and its underlying mechanism. Colitis was induced by slow intrarectal infusion of 2 mL of 4% (v/v in 0.9% saline) acetic acid. Colon samples were evaluated macroscopically, microscopically, and assayed for pro-inflammatory cytokine levels. To monitor associated metabolic changes in acetic acid-induced UC model, serum samples were analyzed for primary metabolites using GC-MS followed by multivariate data analyses. Treatment with ASBE attenuated acetic acid-induced UC as revealed by reduction of colon weight, ulcer area, and ulcer index. ASBE treatment also reduced Cyclooxygenase-2 (COX-2), Prostaglandin E2 (PGE2) & Interleukin-1β (IL-1β) levels in the inflamed colon. The nano-formulation of ASBE showed better protection than the crude extract against ulcer indices, increased PGE2 production, and histopathological alterations such as intestinal mucosal lesions and inflammatory infiltration. Distinct metabolite changes were recorded in colitis rats including a decrease in oleamide and arachidonic acid along with increased levels of lactic acid, fructose, and pyroglutamic acid. Treatment with nano extract restored metabolite levels to normal and suggests that cytokine levels were regulated by nano extract in UC. Conclusion: ASBE nano extract mitigated against acetic acid-induced colitis in rats, and the underlying mechanism could be attributed to the modulatory effects of ASBE on the inflammatory cascades. The applicability of metabolomics developed in this rat model seems to be crucial for evaluating the anti-inflammatory mechanisms of new therapeutics for acute colitis.

Targeted toxicometabolomics of endosulfan sulfate in adult zebrafish (Danio rerio) using GC-MS/MS in multiple reaction monitoring mode

Endosulfan sulfate is a major oxidative metabolite of the chlorinated insecticide endosulfan. In this study, a targeted metabolomics approach was used to investigate the toxic mechanisms of endosulfan sulfate in adult zebrafish using the multiple reaction monitoring mode of a GC-MS/MS. The LC₅₀ of endosulfan sulfate in adult zebrafish was determined and then zebrafish were exposed to endosulfan sulfate at one-tenth the LC₅₀ (0.1LC₅₀) or the LC₅₀ for 24 and 48 h. After exposure, the fish were extracted, derivatized and analyzed by GC-MS/MS for 379 metabolites to identify 170 metabolites. Three experimental groups (control, 0.1LC₅₀ and LC₅₀) were clearly separated in PLS-DA score plots. Based on the VIP, ANOVA, and fold change results, 40 metabolites were selected as biomarkers. Metabolic pathways associated with those metabolites were identified using MetaboAnalyst 4.0 as follows: aminoacyl-tRNA biosynthesis, valine/leucine/isoleucine biosynthesis, citrate cycle, glycerolipid metabolism, and arginine/proline metabolism. Gene expression studies confirmed the activation of citrate cycle and glycerolipids metabolism. MDA levels of the exposed group significantly increased in oxidative toxicity assay tests. Such significant perturbations of important metabolites within key biochemical pathways must result in biologically hazardous effects in zebrafish.

Phytotoxicity induced by engineered nanomaterials as explored by metabolomics: Perspectives and challenges

Given the wide applications of engineered nanomaterials (ENMs) in various fields, the ecotoxicology of ENMs has attracted much attention. The traditional plant physiological activity (e.g., reactive oxygen species and antioxidant enzymes) are limited in that they probe one specific process of nanotoxicity, which may result in the loss of understanding of other important biological reactions. Metabolites, which are downstream of gene and protein expression, are directly related to biological phenomena. Metabolomics is an easily performed and efficient tool for solving the aforementioned problems because it involves the comprehensive exploration of metabolic profiles. To understand the roles of metabolomics in phytotoxicity, the analytical methods for metabolomics should be organized and discussed. Moreover, the dominant metabolites and metabolic pathways are similar in different plants, which determines the universal applicability of metabolomics analysis. The analysis of regulated metabolism will globally and scientifically help determine the ecotoxicology that is induced by ENMs. In the past several years, great developments in nanotoxicology have been achieved using metabolomics. However, many knowledge gaps remain, such as the relationships between biological responses that are induced by ENMs and the regulation of metabolism (e.g., carbohydrate, energy, amino acid, lipid and secondary metabolism). The phytotoxicity that is induced by ENMs has been explored by metabolomics, which is still in its infancy. The detrimental and defence mechanisms of plants in their response to ENMs at the level of metabolomics also deserve much attention. In addition, owing to the regulation of metabolism in plants by ENMs affected by multiple factors, it is meaningful to uniformly identify the key influencing factor.

Simultaneous quantification of fifty-one odor-causing compounds in drinking water using gas chromatography-triple quadrupole tandem mass spectrometry

A wide range of compounds with various structural features can cause taste and odor (T&O) problems in drinking water. It would be desirable to determine all of these compounds using a simple analytical method. In this paper, a sensitive method combining liquid-liquid extraction (LLE) with gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS) was established to simultaneously analyze 51 odor-causing compounds in drinking water, including organic sulfides, aldehydes, benzenes, phenols, ethers, esters, ketones, nitrogenous heterocyclic compounds, 2-methylisoborneol and geosmin. Three deuterated analogs of target analytes, dimethyl disulfide-d₆, benzaldehyde-d₆ and o-cresol-3,4,5,6-d_4, were used to correct the variations in recovery, and five isotope-labeled internal standards (4-chlorotoluene-d₄, 1, 4-dichlorobenzene-d₄, naphthalene-d₈, acenaphthene-d₁₀, phenanthrene-d₁₀ respectively) were used prior to analysis to correct the variations arising from instrument fluctuations and injection errors. The calibration curves of the target compounds showed good linearity (R² > 0.99, level = 7), and method detection limits (MDLs) below 1/10 of the odor threshold concentrations were achieved for most of the odorants (0.10-20.55 ng/L). The average recoveries of most of the analytes in tap water samples were between 70% and 120%, and the method was reproducible (RSD < 20%, n = 7). Additionally, concentrations of odor-causing compounds in water samples collected from three drinking water treatment plants (DWTPs) were analyzed by this method. According to the results, dimethyl trisulfide, dimethyl disulfide and indole were considered to be the key odorants responsible for the swampy/septic odor. 2-Methylisoborneol and geosmin were detected as the main odor-causing compounds for musty/earthy odor in DWTP B.

Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.

Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach

The diagnosis of asthma and chronic obstructive pulmonary disease (COPD) can be challenging due to the overlap in their clinical presentations in some patients. There is a need for a more objective clinical test that can be routinely used in primary care settings. Through an untargeted ¹H NMR urine metabolomic approach, we identified a set of endogenous metabolites as potential biomarkers for the differentiation of asthma and COPD. A subset of these potential biomarkers contains 7 highly polar metabolites of diverse physicochemical properties. To the best of our knowledge, there is no liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that evaluated more than two of the target metabolites in a single analytical run. The target metabolites belong to the families of monosaccharides, organic acids, amino acids, quaternary ammonium compounds and nucleic acids, rendering hydrophilic interaction liquid chromatography (HILIC) an ideal technology for their quantification. Since a clinical decision is to be made from patients data, a fully validated analytical method is required for biomarker validation. Method validation for endogenous metabolites is a daunting task since current guidelines were designed for exogenous compounds. As such, innovative approaches were adopted to meet the validation requirements. Herein, we describe a sensitive HILIC-MS/MS method for the quantification of the 7 endogenous urinary metabolites. Detection was achieved in the multiple reaction monitoring (MRM) mode with polarity switching, using quadrupole-linear ion trap instrument (QTRAP 6500) as well as single ion monitoring in the negative-ion mode. The method was fully validated according to the regulatory guidelines. Linearity was established between 6 and 21000 ng/mL and quality control samples demonstrated acceptable intra- and inter-day accuracy (85.7%-112%), intra- and inter-day precision (CV% <11.5%) as well as stability under various storage and sample processing conditions. To illustrate the method's applicability, the validated method was applied to the analysis of a small set of urine samples collected from asthma and COPD patients. Preliminary modelling of separation was generated using partial least square discriminant analysis (R² 0.752 and Q² 0.57). The adequate separation between patient samples confirms the diagnostic potential of these target metabolites as a proof-of-concept for the differentiation between asthma and COPD. However, more patient urine samples are needed in order to increase the statistical power of the analytical model.

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

Evaluation of microextraction by packed sorbent, liquid-liquid microextraction and derivatization pretreatment of diet-derived phenolic acids in plasma by gas chromatography with triple quadrupole mass spectrometry

Miniaturized sample pretreatments for the analysis of phenolic metabolites in plasma, involving protein precipitation, enzymatic deconjugation, extraction procedures, and different derivatization reactions were systematically evaluated. The analyses were conducted by gas chromatography with mass spectrometry for the evaluation of 40 diet-derived phenolic compounds. Enzyme purification was necessary for the phenolic deconjugation before extraction. Trimethylsilanization reagent and two different tetrabutylammonium salts for derivatization reactions were compared. The optimum reaction conditions were 50 μL of trimethylsilanization reagent at 90°C for 30 min, while tetrabutylammonium salts were associated with loss of sensitivity due to rapid activation of the inert gas chromatograph liner. Phenolic acids extractions from plasma were optimized. Optimal microextraction by packed sorbent performance was achieved using an octadecylsilyl packed bed and better recoveries for less polar compounds, such as methoxylated derivatives, were observed. Despite the low recovery for many analytes, repeatability using an automated extraction procedure in the gas chromatograph inlet was 2.5%. Instead, using liquid-liquid microextraction, better recoveries (80-110%) for all analytes were observed at the expense of repeatability (3.8-18.4%). The phenolic compounds in gerbil plasma samples, collected before and 4 h after the administration of a calafate extract, were analyzed with the optimized methodology.

Novel serum metabolomics-based approach by gas chromatography/triple quadrupole mass spectrometry for detection of human skin cancers: Candidate biomarkers

Skin cancer incidence rates are continuing to rise; however, if detected at an early stage, they can be cured with minimally invasive treatment. Therefore, the identification of novel and robust biomarkers for the early detection of skin cancer is required to improve the quality of life of the patient after treatment. In the present study, we aimed to identify novel biomarkers of skin cancers. We carried out serum metabolomics using gas chromatography/triple quadrupole mass spectrometry for two types of skin cancer: squamous cell carcinoma and melanoma. The changes in the expression of metabolites compared with healthy volunteers were analyzed by principal component analysis. Among all 118 metabolites, 27 in patients with squamous cell carcinoma and 33 in patients with melanoma showed significant changes in comparison with healthy volunteers. Principal component analysis showed that both skin cancer groups could be distinguished from the healthy volunteers group. We further investigated the specific metabolites most useful for these distinctions. In the squamous cell carcinoma group, these metabolites were glycerol, 4-hydroxybenzoic acid, sebacic acid, fucose and suberic acid. In the melanoma group, these metabolites were glutamic acid, sebacic acid, suberic acid, 4-hydroxybenzoic acid and phenylalanine. The present study identified several metabolites that were distinct for certain skin cancer types, which could potentially be used as diagnostic biomarkers leading to novel clinical management strategies.

Metabolomic and proteomic investigations of impacts of titanium dioxide nanoparticles on Escherichia coli

In a previous study, it was demonstrated that the toxic impact of titanium dioxide nanoparticles on Escherichia coli starts at 10 ppm and is closely related to the presence of little aggregates. It was also assumed that only a part of the bacterial population is able to adapt to this stress and attempts to survive. Proteomic analyses, supported by results from metabolomics, reveal that exposure of E. coli to nano-TiO2 induces two main effects on bacterial metabolism: firstly, the up-regulation of proteins and the increase of metabolites related to energy and growth metabolism; secondly, the down-regulation of other proteins resulting in an increase of metabolites, particularly amino acids. Some proteins, e.g. chaperonin 1 or isocitrate dehydrogenase, and some metabolites, e.g. phenylalanine or valine, might be used as biomarkers of nanoparticles stress. Astonishingly, the ATP content gradually rises in relation with the nano-TiO2 concentration in the medium, indicating a dramatic release of ATP by the damaged cells. These apparently contradictory results accredit the thesis of a heterogeneity of the bacterial population. This heterogeneity is also confirmed by SEM images which show that while some bacteria are fully covered by nano-TiO2, the major part of the bacterial population remains free from nanoparticles, resulting in a difference of proteome and metabolome. The use of combined-omics has allowed to better understand the heterogeneous bacterial response to nano-TiO2 stress due to heterogeneous contacts between the protagonists under environmental conditions.

Hyphenated MS-based targeted approaches in metabolomics

Review of targeted metabolomics, with a focus on the description of analytical methods.

Technical Challenges in Mass Spectrometry-Based Metabolomics

Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10-100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism.

Validation of Metabolic Alterations in Microscale Cell Culture Lysates Using Hydrophilic Interaction Liquid Chromatography (HILIC)-Tandem Mass Spectrometry-Based Metabolomics

By standard convention, in order to increase the efficacy of metabolite detection from cell culture lysates, metabolite extracts from a large quantity of cells are utilized for multiple reaction monitoring-based metabolomic studies. Metabolomics from a small number of cell extracts offers a potential economical alternative to increased cell numbers, in turn increasing the utility of cell culture-based metabolomics. However, the effect of reduced cell numbers on targeted metabolomic profiling is relatively unstudied. Considering the limited knowledge available of the feasibility and accuracy of microscale cell culture metabolomics, the present study analyzes differences in metabolomic profiles of different cell numbers of three pancreatic cancer cell lines. Specifically, it examines the effects of reduced cell numbers on metabolite profiles by obtaining extracts either directly from microscale culture plates or through serial dilution of increased numbers of cellular metabolite extracts. Our results indicate reduced cell numbers only modestly affect the number of metabolites detected (93% of metabolites detected in cell numbers as low as 10⁴ cells and 97% for 10⁵ cells), independent of the method used to obtain the cells. However, metabolite peak intensities were differentially affected by the reduced cell numbers, with some peak intensities inversely proportional to the cell numbers. To help eliminate such potential inverse relationships, peak intensities for increased cell numbers were excluded from the comparative analysis. Overall, metabolite profiles from microscale culture plates were observed to differ from the serial dilution samples, which may be attributable to the medium-to-cell-number ratios. Finally, findings identify perturbations in metabolomic profiling for cellular extracts from reduced cell numbers, which offer future applications in microscale metabolomic evaluations.

GC-MS metabolomics on PPARα-dependent exacerbation of colitis

Fenofibrate, a peroxisome proliferator-activated receptor α (PPARα) agonist, was found to exacerbate inflammation and tissue injury in experimental acute colitis mice. Through lipidomics analysis, bioactive sphingolipids were significantly up-regulated in the colitis group. In this study, to provide further insight into the PPARα-dependent exacerbation of colitis, gas chromatography-mass spectrometry (GC/MS) based metabolomics was employed to investigate the serum and colon of dextran sulfate sodium (DSS)-induced colitis mice treated with fenofibrate, with particular emphasis on changes in low-molecular-weight metabolites. With the aid of multivariate analysis and metabolic pathway analysis, potential metabolite markers in the amino acid metabolism, urea cycle, purine metabolism, and citrate cycle were highlighted, such as glycine, serine, threonine, malic acid, isocitric acid, uric acid, and urea. The level changes of these metabolites in either serum or colons of colitis mice were further potentiated following fenofibrate treatment. Accordingly, the expression of threonine aldolase and phosphoserine aminotransferase 1 was significantly up-regulated in colitis mice and further potentiated in fenofibrate/DSS-treated mice. It was revealed that beyond the control of lipid metabolism, PPARα also shows effects on the above pathways, resulting in enhanced protein catabolism and energy expenditure, increased bioactive sphingolipid metabolism and proinflammatory state, which were possibly related to the exacerbated colitis.

Sample-directed pseudotargeted method for the metabolic profiling analysis of rice seeds based on liquid chromatography with mass spectrometry

Rice is one of the most important food crops in the world. Metabolite composition in rice seeds varies significantly depending on genetic variety, climatic alternation and agricultural practice. Metabolomics is a powerful tool to reveal the metabolic response of rice to various conditions. In this work, a rice seed sample-directed pseudotargeted metabolomics method was first established and validated based on ultra high performance liquid chromatography with triple quadrupole mass spectrometry in the multiple reaction monitoring mode. A total of 749 and 617 ion pairs in positive and negative modes were achieved, respectively. Among them, about 200 metabolites were identified or tentatively identified. The developed method showed better linearity and repeatability than those of non-targeted metabolomics method. Good intra-day and inter-day precisions, recoveries and wide linear range were also obtained. Furthermore, the method was applied for the investigation of metabolic variation of rice seeds with two wild cultivars and their transgenic lines that were grown in two locations. Principal component analysis indicated that the effects of cultivar and location on metabolic variations were far more than those of gene modification. The nonparametric Mann-Whitney U test revealed that most metabolites were influenced by cultivar, location and gene modifications together.

Monitoring the Response of the Human Urinary Metabolome to Brief Maximal Exercise by a Combination of RP-UPLC-MS and (1)H NMR Spectroscopy

The delineation of exercise biochemistry by utilizing metabolic fingerprinting has become an established strategy. We present a combined RP-UPLC-MS and (1)H NMR strategy, supplemented by photometric assays, to monitor the response of the human urinary metabolome to short maximal exercise. Seventeen male volunteers performed two identical sprint sessions on separate days, consisting of three 80 m maximal runs. Using univariate and multivariate analyses, we followed the fluctuation of 37 metabolites at 1, 1.5, and 2 h postexercise. 2-Hydroxyisovalerate, 2-hydroxybutyrate, 2-oxoisocaproate, 3-methyl-2-oxovalerate, 3-hydroxyisobutyrate, 2-oxoisovalerate, 3-hydroxybutyrate, 2-hydroxyisobutyrate, alanine, pyruvate, and fumarate increased 1 h postexercise and then returned toward baseline. Lactate and acetate were higher than baseline at 1 and 1.5 h. Hypoxanthine and inosine remained above baseline throughout the postexercise period. Urate decreased at 1 h and increased at 1.5 h before returning to baseline. Valine, isoleucine, succinate, citrate, trimethylamine, trimethylamine N-oxide, tyrosine, and formate decreased at 1 h and/or 1.5 h postexercise and then returned to baseline. Creatinine gradually decreased over the sampling period. Glycine, 4-aminohippurate, and hippurate remained below baseline throughout the postexercise period. Our findings show that even one-half minute of maximal exercise elicited major perturbations in human metabolism, several of which persisted for at least 2 h.

Prospects of breeding high-quality rice using post-genomic tools

The holistic understanding derived from integrating grain quality and sensory research outcomes in breeding high-quality rice in the light of post-genomics resources has been synthesized. Acceptance of new rice genotypes by producers and consumers hinges not only on their potential for higher yield but recent emphasis has also been on premium-value genotypes that have the ability to satisfy consumer preferences for grain quality. This review article provides insights into how to link grain quality attributes and sensory perception to support breeding superior rice varieties. Recent advances in quality profiling and omics technologies have provided efficient approaches to identify the key genes and biochemical markers involved in rice quality traits. Emphasis has been given to the upcoming area of holistic understanding of grain quality and attributes derived from sensory evaluation to leverage integrative gene discovery strategies that enable breeding programs to efficiently tap the huge genetic diversity in rice for novel genes that enhance rice food quality.

Metabolomic analyses reveal that anti-aging metabolites are depleted by palmitate but increased by oleate in vivo

Recently, we reported that saturated and unsaturated fatty acids trigger autophagy through distinct signal transduction pathways. Saturated fatty acids like palmitate (PA) induce autophagic responses that rely on phosphatidylinositol 3-kinase, catalytic subunit type 3 (PIK3C3, best known as VPS34) and beclin 1 (BECN1). Conversely, unsaturated fatty acids like oleate (OL) promote non-canonical, PIK3C3- and BECN1-independent autophagy. Here, we explored the metabolic effects of autophagy-inducing doses of PA and OL in mice. Mass spectrometry coupled to principal component analysis revealed that PA and OL induce well distinguishable changes in circulating metabolites as well as in the metabolic profile of the liver, heart, and skeletal muscle. Importantly, PA (but not OL) causes the depletion of multiple autophagy-inhibitory amino acids in the liver. Conversely, OL (but not PA) increased the hepatic levels of nicotinamide adenine dinucleotide (NAD), an obligate co-factor for autophagy-stimulatory enzymes of the sirtuin family. Moreover, PA (but not OL) raised the concentrations of acyl-carnitines in the heart, a phenomenon that perhaps is linked to its cardiotoxicity. PA also depleted the liver from spermine and spermidine, 2 polyamines have been ascribed with lifespan-extending activity. The metabolic changes imposed by unsaturated and saturated fatty acids may contribute to their health-promoting and health-deteriorating effects, respectively.

Application of Metabolomics for High Resolution Phenotype Analysis

Metabolome, a total profile of whole metabolites, is placed on downstream of proteome. Metabolome is thought to be results of implementation of genomic information. In other words, metabolome can be called as high resolution phenotype. The easiest operation of metabolomics is the integration to the upstream ome information including transcriptome and/or proteome. Those trials have been reported at a certain scientific level. In addition, metabolomics can be operated in stand-alone mode without any other ome information. Among metabolomics tactics, the author's group is particularly focusing on metabolic fingerprinting, in which metabolome information is employed as explanatory variant to evaluate response variant. Metabolic fingerprinting technique is expected not only for analyzing slight difference depending on genotype difference but also for expressing dynamic variation of living organisms. The author introduces several good examples which he performed. Those are useful for easy understanding of the power of metabolomics. In addition, the author mentions the latest technology for analysis of metabolic dynamism. The author's group developed a facile analytical method for semi-quantitative metabolic dynamism. The author introduces the novel method that uses time dependent variation of isotope distribution based on stable isotope dilution.

Metabolomics for biomarker discovery in gastroenterological cancer

The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.

Molar-based targeted metabolic profiling of cyanobacterial strains with potential for biological production

Recently, cyanobacteria have become one of the most attractive hosts for biochemical production due to its high proliferative ability and ease of genetic manipulation. Several researches aimed at biological production using modified cyanobacteria have been reported previously. However, to improve the yield of bioproducts, a thorough understanding of the intercellular metabolism of cyanobacteria is necessary. Metabolic profiling techniques have proven to be powerful tools for monitoring cellular metabolism of various organisms and can be applied to elucidate the details of cyanobacterial metabolism. In this study, we constructed a metabolic profiling method for cyanobacteria using 13C-labeled cell extracts as internal standards. Using this method, absolute concentrations of 84 metabolites were successfully determined in three cyanobacterial strains which are commonly used as background strains for metabolic engineering. By comparing the differences in basic metabolic potentials of the three cyanobacterial strains, we found a well-correlated relationship between intracellular energy state and growth in cyanobacteria. By integrating our results with the previously reported biological production pathways in cyanobacteria, we found putative limiting step of carbon flux. The information obtained from this study will not only help gain insights in cyanobacterial physiology but also serve as a foundation for future metabolic engineering studies using cyanobacteria.

Metabolome analysis for discovering biomarkers of gastroenterological cancer

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis.