Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

Studying drug excretion into exhaled breath aerosol - A workflow based on an impaction sampling device and LC-HRMS/MS analysis

BACKGROUND

Exhaled breath (EB) aerosol was in principle shown to be a suitable matrix for bioanalysis of volatile but also non-volatile compounds. This attracted particular interest in the field of drug analysis. However, a big gap still exists in the understanding how and which drugs and/or their metabolites are excreted into exhaled breath and could thus actually be detected. The current study aimed to develop an analytical workflow for the qualitative detection of non-volatile drugs in EB aerosol microparticles.

RESULTS

The analyte selection covered different drug classes such as antihypertensives, anticonvulsants or opioid analgesics to investigate and understand the excretion of drugs and their metabolites into EB aerosol. A device for collecting aerosol particles from the lung through impaction was used for the non-invasive sampling procedure. Three expiration cycles per participant and device were collected. The sample preparation consisted of a collector extraction with methanol. Qualitative method development and validation were performed using reversed-phase liquid chromatography (LC) coupled to orbitrap-based high-resolution mass spectrometry (HRMS). Qualitative method validation was done according to published recommendations and international guidelines. Parameters such as selectivity, carry-over, limits of detection and identification, recovery, matrix effects, and long-term stability were evaluated. The limits of detection ranged from 100 pg/collector to 10,000 pg/collector. The procedure was finally used to analyze a total of 31 patient EB samples and demonstrated that e.g., tilidine and its metabolite nortilidine as well as tramadol and its active metabolite O-desmethyltramadol can be detected in EB aerosol.

SIGNIFICANCE AND NOVELTY

The work shows a comprehensive workflow for elucidating drug excretion into exhaled breath aerosol. This bioanalytical strategy and the corresponding novel data from this study are the foundation for further method development and to better understand, which drugs and their metabolites can be addressed by exhaled breath aerosol bioanalysis.

Combined non-targeted and targeted metabolomics reveals the mechanism of delaying aging of Ginseng fibrous root

Background: The fibrous root of ginseng (GFR) is the dried thin branch root or whisker root of Ginseng (Panax ginseng C. A. Mey). It is known for its properties such as tonifying qi, producing body fluid, and quenching thirst. Clinically, it is used to treat conditions such as cough, hemoptysis, thirst, stomach deficiency, and vomiting. While GFR and Ginseng share similar metabolites, they differ in their metabolites ratios and efficacy. Furthermore, the specific role of GFR in protecting the body remains unclear. Methods: We employed ultra-high performance liquid chromatography-triple quadrupole mass spectrometry to examine alterations in brain neurotransmitters and elucidate the impact of GFR on the central nervous system. Additionally, we analyzed the serum and brain metabolic profiles of rats using ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry to discern the effect and underlying mechanism of GFR in delaying aging in naturally aged rats. Results: The findings of the serum biochemical indicators indicate that the intervention of GFR can enhance cardiovascular, oxidative stress, and energy metabolism related indicators in naturally aging rats. Research on brain neurotransmitters suggests that GFR can augment physiological functions such as learning and memory, while also inhibiting central nervous system excitation to a certain degree by maintaining the equilibrium of central neurotransmitters in aged individuals. Twenty-four abnormal metabolites in serum and seventeen abnormal metabolites in brain could be used as potential biomarkers and were involved in multiple metabolic pathways. Among them, in the brain metabolic pathways, alanine, aspartate and glutamate metabolism, arginine and proline metabolism, histidine metabolism, and tyrosine metabolism were closely related to central neurotransmitters. Butanoate metabolism improves energy supply for life activities in the aging body. Cysteine and methionine metabolism contributes to the production of glutathione and taurine and played an antioxidant role. In serum, the regulation of glycerophospholipid metabolism pathway and proline metabolism demonstrated the antioxidant capacity of GFR decoction. Conclution: In summary, GFR plays a role in delaying aging by regulating central neurotransmitters, cardiovascular function, oxidative stress, energy metabolism, and other aspects of the aging body, which lays a foundation for the application of GFR.

PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

An exercise physiologist's guide to metabolomics

The field of exercise physiology has undergone significant technological advancements since the pioneering works of exercise physiologists in the early to mid-20th century. Historically, the ability to detect metabolites in biofluids from exercising participants was limited to single-metabolite analyses. However, the rise of metabolomics, a discipline focused on the comprehensive analysis of metabolites within a biological system, has facilitated a more intricate understanding of metabolic pathways and networks in exercise. This review explores some of the pivotal technological and bioinformatic advancements that have propelled metabolomics to the forefront of exercise physiology research. Metabolomics offers a unique 'fingerprint' of cellular activity, offering a broader spectrum than traditional single-metabolite assays. Techniques, including mass spectrometry and nuclear magnetic resonance spectroscopy, have significantly improved the speed and sensitivity of metabolite analysis. Nonetheless, challenges persist, including study design and data interpretation issues. This review aims to serve as a guide for exercise physiologists to facilitate better research design, data analysis and interpretation within metabolomics. The potential of metabolomics in bridging the gap between genotype and phenotype is emphasised, underscoring the critical importance of careful study design and the selection of appropriate metabolomics techniques. Furthermore, the paper highlights the need to deeply understand the broader scientific context to discern meaningful metabolic changes. The emerging field of fluxomics, which seeks to quantify metabolic reaction rates, is also introduced as a promising avenue for future research.

Impact of four different extraction methods and three different reconstitution solvents on the untargeted metabolomics analysis of human and rat urine samples

Unsuitable sample preparation may result in loss of important analytes and consequently affect the outcome of untargeted metabolomics. Due to species differences, different sample preparations may be required within the same biological matrix. The study aimed to compare the in-house sample preparation method for urine with methods from literature and to investigate the transferability of sample preparation from human urine to rat urine. A total of 12 different conditions for protein precipitation were tested, combining four different extraction solvents and three different reconstitution solvents using an untargeted liquid-chromatography high resolution mass spectrometry (LC-HRMS) metabolomics analysis. Evaluation was done based on the impact on feature count, their detectability, as well as the reproducibility of selected compounds. Results showed that a combination of methanol as extraction and acetonitrile/water (75/25) as reconstitution solvent provided improved results at least regarding the total feature count. Additionally, it was found that a higher amount of methanol was most suitable for extraction of rat urine among the tested conditions. In comparison, human urine requires significantly less volume of extraction solvent. Overall, it is recommended to systematically optimize both, the extraction method, and the reconstitution solvent for the used biofluid and the individual analytical settings.

Comparison of reversed-phase, hydrophilic interaction, and porous graphitic carbon chromatography columns for an untargeted toxicometabolomics study in pooled human liver microsomes, rat urine, and rat plasma

INTRODUCTION

Untargeted metabolomics studies are expected to cover a wide range of compound classes with high chemical diversity and complexity. Thus, optimizing (pre-)analytical parameters such as the analytical liquid chromatography (LC) column is crucial and the selection of the column depends primarily on the study purpose.

OBJECTIVES

The current investigation aimed to compare six different analytical columns. First, by comparing the chromatographic resolution of selected compounds. Second, on the outcome of an untargeted toxicometabolomics study using pooled human liver microsomes (pHLM), rat plasma, and rat urine as matrices.

METHODS

Separation and analysis were performed using three different reversed-phase (Phenyl-Hexyl, BEH C18, and Gold C18), two hydrophilic interaction chromatography (HILIC) (ammonium-sulfonic acid and sulfobetaine), and one porous graphitic carbon (PGC) columns coupled to high-resolution mass spectrometry (HRMS). Their impact was evaluated based on the column performance and the size of feature count, amongst others.

RESULTS

All three reversed-phase columns showed a similar performance, whereas the PGC column was superior to both HILIC columns at least for polar compounds. Comparing the size of feature count across all datasets, most features were detected using the Phenyl-Hexyl or sulfobetaine column. Considering the matrices, most significant features were detected in urine and pHLM after using the sulfobetaine and in plasma after using the ammonium-sulfonic acid column.

CONCLUSION

The results underline that the outcome of this untargeted toxicometabolomic study LC-HRMS metabolomic study was highly influenced by the analytical column, with the Phenyl-Hexyl or sulfobetaine column being the most suitable. However, column selection may also depend on the investigated compounds as well as on the investigated matrix.

Teaching mass spectrometry: A compilation of approaches to teaching theory and practice of mass spectrometry

The areas of mass spectrometry applications seem to be much larger than those of any other analytical techniques. They extend from the determination of molecular mass in organic chemistry, through the analytical applications in forensic, environmental and omics sciences, the application in extra-terrestrial exploration and many others. Mass spectrometry, usually coupled with chromatographic techniques, has also found wide application in the pharmaceutical industry, forensic laboratories, laboratories of sanitary inspection or environmental inspection, etc. The growing areas of applications give rise to the demand for the comprehensive mass spectrometry education of undergraduates. This overview covers the body of literature describing various interesting ideas that can be successfully used for teaching mass spectrometry. Since mass spectrometry is a multidisciplinary field, old but dynamically developing, teaching mass spectrometry may be more problematic in comparison to teaching other analytical techniques, for example, there is the problem of position of mass spectrometry in the chemistry curriculum. On the other hand, it is obvious that the mass spectrometry community, besides difficult scientific work, does great and admirable teaching work, in order to perfectly educate undergraduates in the field of mass spectrometry and to make learning mass spectrometry as attractive as possible.

Enhanced delignification and production of bioactive compounds in wheat straw by optimizing sterilization methods for Irpex lacteus fermentation

This study aimed to examine the effects of sterilization methods on the degradation ability and bioactive compound production of Irpex lacteus in wheat straw. Following 28 days of fermentation, the lignin content of samples autoclaved and pasteurized at pH 4.5 was reduced by 16.0 % - 21.7 % compared to pasteurized samples without pH adjustment, accompanied by a significant increase in sugar yield ranging from 83.30 % - 96.35 %. Autoclaved samples exhibited the lowest total phenol content and antioxidant activity (P < 0.05). Bacillus occupied an absolute advantage (89.1 %) in samples pasteurized at pH 4.5, whereas 10 bacterial genera exhibited abundances above 1 % in pasteurized samples without pH adjustment. Furthermore, 45.1 % - 47.2 % of the metabolites comprised lipids and lipid-like molecules, and some of them were improved by pasteurization at pH 4.5. Overall, pasteurization at acidic conditions is an effective sterilization method for the fungal conversion of wheat straw.

Evaluation of extraction methods for untargeted metabolomic studies for future applications in zebrafish larvae infection models

Sample preparation in untargeted metabolomics should allow reproducible extractions of as many molecules as possible. Thus, optimizing sample preparation is crucial. This study compared six different extraction procedures to find the most suitable for extracting zebrafish larvae in the context of an infection model. Two one-phase extractions employing methanol (I) and a single miscible phase of methanol/acetonitrile/water (II) and two two-phase methods using phase separation between chloroform and methanol/water combinations (III and IV) were tested. Additional bead homogenization was used for methods III and IV (III_B and IV_B). Nine internal standards and 59 molecules of interest (MoInt) related to mycobacterial infection were used for method evaluation. Two-phase methods (III and IV) led to a lower feature count, higher peak areas of MoInt, especially amino acids, and higher coefficients of variation in comparison to one-phase extractions. Adding bead homogenization increased feature count, peak areas, and CVs. Extraction I showed higher peak areas and lower CVs than extraction II, thus being the most suited one-phase method. Extraction III and IV showed similar results, with III being easier to execute and less prone to imprecisions. Thus, for future applications in zebrafish larvae metabolomics and infection models, extractions I and III might be chosen.

Advances in Microbial NMR Metabolomics

Confidently, nuclear magnetic resonance (NMR) is the most informative technique in analytical chemistry and its use as an analytical platform in metabolomics is well proven. This chapter aims to present NMR as a viable tool for microbial metabolomics discussing its fundamental aspects and applications in metabolomics using some chosen examples.

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.

Untargeted and targeted mass spectrometry reveal the effects of theanine on the central and peripheral metabolomics of chronic unpredictable mild stress-induced depression in juvenile rats

l-theanine has been shown to have a therapeutic effect on depression. However, whether l-theanine has an excellent preventive effect on depression in children and adolescents and what its mechanism is have not been well explained. Given the complexity of the pathogenesis of depression, this study investigated the preventive effect and mechanism of l-theanine on depression in juvenile rats by combining serum and hippocampal metabolomic strategies. Behavioral tests, hippocampal tissue sections, and serum and hippocampal biochemical indexes were studied, and the results confirmed the preventive effect of l-theanine. Untargeted reversed-phase liquid chromatography-quadrupole-time-of-flight mass spectrometry and targeted hydrophilic interaction liquid chromatography-triple quadrupole mass spectrometry were developed to analyze the metabolism changes in the serum and hippocampus to screen for potential biomarkers related to l-theanine treatment. The results suggested that 28 abnormal metabolites in the serum and hippocampus that were considered as potential biomarkers returned to near-normal levels after l-theanine administration. These biomarkers were involved in various metabolic pathways, mainly including amino acid metabolism and lipid metabolism. The levels of amino acids and neurotransmitters in the phenylalanine, tryptophan, and glutamic acid pathways were significantly reduced after l-theanine administration compared with chronic unpredictable mild stress-induced rats. In summary, l-theanine had a significant preventive effect on depression and achieved its preventive results on depression by regulating various aspects of the body, such as amino acids, lipids, and inflammation. This research systematically analyzed the mechanism of l-theanine in preventing depression and laid the foundation for applying l-theanine to prevent depression in children and adolescents.

In Vitro and In Vivo Toxicometabolomics of the Synthetic Cathinone PCYP Studied by Means of LC-HRMS/MS

Synthetic cathinones are one important group amongst new psychoactive substances (NPS) and limited information is available regarding their toxicokinetics and -dynamics. Over the past few years, nontargeted toxicometabolomics has been increasingly used to study compound-related effects of NPS to identify important exogenous and endogenous biomarkers. In this study, the effects of the synthetic cathinone PCYP (2-cyclohexyl-1-phenyl-2-(1-pyrrolidinyl)-ethanone) on in vitro and in vivo metabolomes were investigated. Pooled human-liver microsomes and blood and urine of male Wistar rats were used to generate in vitro and in vivo data, respectively. Samples were analyzed by liquid chromatography and high-resolution mass spectrometry using an untargeted metabolomics workflow. Statistical evaluation was performed using univariate and multivariate statistics. In total, sixteen phase I and one phase II metabolite of PCYP could be identified as exogenous biomarkers. Five endogenous biomarkers (e.g., adenosine and metabolites of tryptophan metabolism) related to PCYP intake could be identified in rat samples. The present data on the exogenous biomarker of PCYP are crucial for setting up analytical screening procedures. The data on the endogenous biomarker are important for further studies to better understand the physiological changes associated with cathinone abuse but may also serve in the future as additional markers for an intake.

Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress

Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.

Application of metabolomics and network analysis to reveal the ameliorating effect of four typical “hot” property herbs on hypothyroidism rats

Herbs with a “hot” properties are frequently used to treat cold symptoms in TCM. However, the underlying mechanisms of the herbs with “hot” properties on hypothyroidism have not been investigated. This study aimed to explore four typical “hot” and “cold” property herb on hypothyroidism. Firstly, the difference efficacy between the four typical “hot” property herbs and the four typical “cold” property herbs was assessed by physical signs, thyroid function, and the metabolic profile using multivariate statistical analysis. The influence of the four typical “hot” property herbs on hypothyroidism was validated pathologically. The impact mechanism of the four typical “hot” property herbs on hypothyroidism was investigated through a metabolomics method combined with network analysis. Na⁺/K⁺-ATP, ACC1 enzyme, UCP-1, and the PI3K-Akt pathway were used to confirm the metabolite pathways and target-associated metabolites. The results showed that the four typical “hot” property herbs could significantly improve physical signs, thyroid function, and the metabolic profile in hypothyroidism rats, the four typical “cold” property herbs did not show any benefit. Moreover, the four typical “hot” property herbs could improve lipid metabolism, energy metabolism, and thyroid hormone levels by the PI3K-Akt signaling pathway, Ca²⁺- AMPK signaling pathways, purine metabolism, and tryptophan metabolism. Additionally, the levels of UCP-1, Na+/K + -ATP enzyme, and ACC1 were ameliorated by the four typical “hot” property herbs in hypothyroidism rats. Therefore, a metabolomics strategy combined with network analysis was successfully performed and interpreted the mechanism of the four typical “hot” property herbs on hypothyroidism based on the theory of “cold and hot” properties of TCM well.

Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review

OBJECTIVE

To summarize the application of non-targeted metabolomics in epidemiological studies that assessed metabolite and metabolic pathway alterations associated with per- and polyfluoroalkyl substances (PFAS) exposure.

RECENT FINDINGS

Eleven human studies published before April 1st, 2021 were identified through database searches (PubMed, Dimensions, Web of Science Core Collection, Embase, Scopus), and citation chaining (Citationchaser). The sample sizes of these studies ranged from 40 to 965, involving children and adolescents (n = 3), non-pregnant adults (n = 5), or pregnant women (n = 3). High-resolution liquid chromatography-mass spectrometry was the primary analytical platform to measure both PFAS and metabolome. PFAS were measured in either plasma (n = 6) or serum (n = 5), while metabolomic profiles were assessed using plasma (n = 6), serum (n = 4), or urine (n = 1). Four types of PFAS (perfluorooctane sulfonate(n = 11), perfluorooctanoic acid (n = 10), perfluorohexane sulfonate (n = 9), perfluorononanoic acid (n = 5)) and PFAS mixtures (n = 7) were the most studied. We found that alterations to tryptophan metabolism and the urea cycle were most reported PFAS-associated metabolomic signatures. Numerous lipid metabolites were also suggested to be associated with PFAS exposure, especially key metabolites in glycerophospholipid metabolism which is critical for biological membrane functions, and fatty acids and carnitines which are relevant to the energy supply pathway of fatty acid oxidation. Other important metabolome changes reported included the tricarboxylic acid (TCA) cycle regarding energy generation, and purine and pyrimidine metabolism in cellular energy systems.

CONCLUSIONS

There is growing interest in using non-targeted metabolomics to study the human physiological changes associated with PFAS exposure. Multiple PFAS were reported to be associated with alterations in amino acid and lipid metabolism, but these results are driven by one predominant type of pathway analysis thus require further confirmation. Standardizing research methods and reporting are recommended to facilitate result comparison. Future studies should consider potential differences in study methodology, use of prospective design, and influence from confounding bias and measurement errors.

Metabolomics insight into the influence of environmental factors in responses of freshwater biofilms to the model herbicide diuron

Freshwater biofilms have been increasingly used during the last decade in ecotoxicology due to their ecological relevance to assess the effect(s) of environmental stress at the community level. Despite growing knowledge about the effect of various stressors on the structure and the function of these microbial communities, a strong research effort is still required to better understand their response to chemical stress and the influence of environmental stressors in this response. To tackle this challenge, untargeted metabolomics is an approach of choice because of its capacity to give an integrative picture of the exposure to multiple stress and associated effect as well as identifying the molecular pathways involved in these responses. In this context, the present study aimed to explore the use of an untargeted metabolomics approach to unravel at the molecular/biochemical level the response of the whole biofilm to chemical stress and the influence of various environmental factors in this response. To this end, archived high-resolution mass spectrometry data from previous experiments at our laboratory on the effect of the model photosynthesis inhibitor diuron on freshwater biofilm were investigated by using innovative solutions for OMICs data (e.g., DRomics) and more usual chemometric approaches (multivariate and univariate statistical analyses). The results showed a faster (1 min) and more sensitive response of the metabolome to diuron than usual functional descriptors, including photosynthesis. Also, the metabolomics response to diuron resulted from metabolites following various trends (increasing, decreasing, U/bell shape) along increasing concentration and time. This metabolomics response was influenced by the temperature, photoperiod, and flow. A focus on a plant-specific omega-3 (eicosapentaenoic acid) playing a key role in the trophic chain highlighted the potential relevance of metabolomics approach to establish the link between molecular alteration and ecosystem structure/functioning impairment but also how complex is the response and the influence of all the tested factors on this response at the metabolomics level. Altogether, our results underline that more fundamental researches are needed to decipher the metabolomics response of freshwater biofilm to chemical stress and its link with physiological, structural, and functional responses toward the unraveling of adverse outcome pathways (AOP) for key ecosystem functions (e.g., primary production).

Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features

Unknown features in untargeted metabolomics and non-targeted analysis (NTA) are identified using fragment ions from MS/MS spectra to predict the structures of the unknown compounds. The precursor ion selected for fragmentation is commonly performed using data dependent acquisition (DDA) strategies or following statistical analysis using targeted MS/MS approaches. However, the selected precursor ions from DDA only cover a biased subset of the peaks or features found in full scan data. In addition, different statistical analysis can select different precursor ions for MS/MS analysis, which make the post-hoc validation of ions selected following a secondary analysis impossible for precursor ions selected by the original statistical method. Here we propose an automated, exhaustive, statistical model-free workflow: paired mass distance-dependent analysis (PMDDA), for reproducible untargeted mass spectrometry MS2 fragment ion collection of unknown compounds found in MS1 full scan. Our workflow first removes redundant peaks from MS1 data and then exports a list of precursor ions for pseudo-targeted MS/MS analysis on independent peaks. This workflow provides comprehensive coverage of MS2 collection on unknown compounds found in full scan analysis using a “one peak for one compound” workflow without a priori redundant peak information. We compared pseudo-spectra formation and the number of MS2 spectra linked to MS1 data using the PMDDA workflow to that obtained using CAMERA and RAMclustR algorithms. More annotated compounds, molecular networks, and unique MS/MS spectra were found using PMDDA compared with CAMERA and RAMClustR. In addition, PMDDA can generate a preferred ion list for iterative DDA to enhance coverage of compounds when instruments support such functions. Finally, compounds with signals in both positive and negative modes can be identified by the PMDDA workflow, to further reduce redundancies. The whole workflow is fully reproducible as a docker image xcmsrocker with both the original data and the data processing template.

Urinary Mass Spectrometry Profiles in Age-Related Macular Degeneration

We and others have shown that patients with different severity stages of age-related macular degeneration (AMD) have distinct plasma metabolomic profiles compared to controls. Urine is a biofluid that can be obtained non-invasively and, in other fields, urine metabolomics has been proposed as a feasible alternative to plasma biomarkers. However, no studies have applied urinary mass spectrometry (MS) metabolomics to AMD. This study aimed to assess urinary metabolomic profiles of patients with different stages of AMD and a control group. We included two prospectively designed, multicenter, cross-sectional study cohorts: Boston, US (n = 185) and Coimbra, Portugal (n = 299). We collected fasting urine samples, which were used for metabolomic profiling (Ultrahigh Performance Liquid chromatography—Mass Spectrometry). Multivariable logistic and ordinal logistic regression models were used for analysis, accounting for gender, age, body mass index and use of AREDS supplementation. Results from both cohorts were then meta-analyzed. No significant differences in urine metabolites were seen when comparing patients with AMD and controls. When disease severity was considered as an outcome, six urinary metabolites differed significantly (p < 0.01). In particular, two of the metabolites identified have been previously shown by our group to also differ in the plasma of patients of AMD compared to controls and across severity stages. While there are fewer urinary metabolites associated with AMD than plasma metabolites, this study identified some differences across stages of disease that support previous work performed with plasma, thus highlighting the potential of these metabolites as future biomarkers for AMD.

Untargeted metabolomics analysis of the anti-diabetic effect of Red ginseng extract in Type 2 diabetes Mellitus rats based on UHPLC-MS/MS

Red ginseng is a traditional Chinese herbal medicine that has long been used to treat diabetes, and its blood sugar-lowering activity has been confirmed. However, the mechanism of action of red ginseng on type 2 diabetes mellitus (T2DM) at the metabolic level is still unclear. The purpose of this study is to investigate the effect of red ginseng extract in the treatment of T2DM rats based on untargeted metabolomics. The rat model of T2DM was induced by a high-fat diet (HFD) combined with streptozotocin (STZ), and serum samples were collected after four weeks of treatment. The ultra-high-performance liquid chromatography coupled with Q Exactive HF-X Mass Spectrometer was used to analyze the level of metabolites in serum to evaluate the differences in metabolic levels between different groups. The results of biochemical analysis showed that red ginseng extract intervention significantly improved the levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), serum glucose (GLU), and fasting insulin (FINS) after four weeks. Orthogonal partial least squares discriminant analysis was used to study the overall changes of rat metabolomics. After the intervention of red ginseng extract, 50 biomarkers showed a callback trend. Metabolic pathway enrichment analysis showed that the regulated pathways were D-arginine and D-ornithine metabolism, D-glutamine and D-glutamate metabolism, taurine and hypotaurine metabolism, arginine biosynthesis, and tryptophan metabolism. Generally, the results demonstrated that red ginseng extract had beneficial effects on T2DM, which could be mediated via ameliorating the metabolic disorders.

Metabolites and metabolic pathways associated with rheumatoid arthritis and systemic lupus erythematosus

Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are chronic autoimmune diseases that result from the combined influence of genetic and environmental factors that promotes the loss of tolerance to cellular components. The complexity of these diseases converts them into a major challenge at the diagnostic and treatment level. Therefore, it is convenient to implement the use of tools for a better understanding of the physiopathology of these diseases to propose reliable biomarkers. The "omics" disciplines like metabolomics and lipidomics allow to study RA and SLE in a higher degree of detail since they evaluate the metabolites and metabolic pathways involved in disease pathogenesis. This review has compiled the information of metabolomics and lipidomics studies where samples obtained from RA and SLE patients were evaluated to find the metabolites and pathways differences between patients and healthy controls. In both diseases, there is a decrease in several amino acids and oxidative stress-related metabolites like glutathione. These findings may be useful for functional metabolomics studies aiming to reprogram the metabolism in a disease setting to recover normal immune cell homeostasis and function.

Dietary Oxidized Linoleic Acids Modulate Fatty Acids in Mice

Objective

An elevated concentration of oxidized lipids along with the abnormal accumulation of lipids has been linked to the formation of atheromatous plaque and the development of cardiovascular diseases. This study aims to investigate if consumption of different concentrations of dietary oxidized linoleic acid alters the distribution of long chain fatty acids (LCFAs) within the liver relative to plasma in mice.

Methods

C57BL/6 male mice (n = 40) were divided into 4 groups: Standard chow as plain control (P group, n =10), Chow supplemented with linoleic acid 9 mg/mouse/day, linoleic control (C group, n=0), oxidized linoleic acid; 9 mg/mouse/day (A group, n=10) and oxidized linoleic acid 18 mg/mouse/day diet (B group, n=10). Liver and plasma samples were extracted, trans-esterified and subsequently analyzed using gas chromatography mass spectrometry (GC-MS) for LCFAs; palmitic acid, stearic acid, oleic acid, linoleic acid and arachidonic acid.

Results

LCFA methyl esters were eluted and identified based on their respective physiochemical characteristics of GCMS assay with inter assay coefficient of variation percentage (CV%, 1.81–5.28%), limits of quantification and limit of detection values (2.021–11.402 mg/mL and 1.016–4.430 mg/mL) respectively. Correlation analysis of liver and plasma lipids of the mice groups yielded coefficients (r=0.96, 0.6, 0.8 and 0.33) with fatty acid percentage total of (16%, 10%, 16% and 58%) for the P, C, A and B groups respectively.

Conclusion

The sustained consumption of a diet rich in oxidized linoleic acid disrupted fatty acid metabolism. The intake also resulted in elevated concentration of LCFAs that are precursors of bioactive metabolite molecule.

Mass Spectrometry-Based Zebrafish Toxicometabolomics: A Review of Analytical and Data Quality Challenges

Metabolomics has achieved great progress over the last 20 years, and it is currently considered a mature research field. As a result, the number of applications in toxicology, biomarker, and drug discovery has also increased. Toxicometabolomics has emerged as a powerful strategy to provide complementary information to study molecular-level toxic effects, which can be combined with a wide range of toxicological assessments and models. The zebrafish model has gained importance in recent decades as a bridging tool between in vitro assays and mammalian in vivo studies in the field of toxicology. Furthermore, as this vertebrate model is a low-cost system and features highly conserved metabolic pathways found in humans and mammalian models, it is a promising tool for toxicometabolomics. This short review aims to introduce zebrafish researchers interested in understanding the effects of chemical exposure using metabolomics to the challenges and possibilities of the field, with a special focus on toxicometabolomics-based mass spectrometry. The overall goal is to provide insights into analytical strategies to generate and identify high-quality metabolomic experiments focusing on quality management systems (QMS) and the importance of data reporting and sharing.

Altered metabolic pathways elucidated via untargeted in vivo toxicometabolomics in rat urine and plasma samples collected after controlled application of a human equivalent amphetamine dose

Amphetamine is widely consumed as drug of abuse due to its stimulating and cognitive enhancing effects. Since amphetamine has been on the market for quite a long time and it is one of the most commonly used stimulants worldwide, to date there is still limited information on its effects on the metabolome. In recent years, untargeted toxicometabolomics have been increasingly used to study toxicity-related pathways of such drugs of abuse to find and identify important endogenous and exogenous biomarkers. In this study, the acute effects of amphetamine intake on plasma and urinary metabolome in rats were investigated. For this purpose, samples of male Wistar rats after a single dose of amphetamine (5 mg/kg) were compared to a control group using an untargeted metabolomics approach. Analysis was performed using normal and reversed phase liquid chromatography coupled to high-resolution mass spectrometry using positive and negative ionization mode. Statistical evaluation was performed using Welch's two-sample t test, hierarchical clustering, as well as principal component analysis. The results of this study demonstrate a downregulation of amino acids in plasma samples after amphetamine exposure. Furthermore, four new potential biomarkers N-acetylamphetamine, N-acetyl-4-hydroxyamphetamine, N-acetyl-4-hydroxyamphetamine glucuronide, and amphetamine succinate were identified in urine. The present study complements previous data and shows that several studies are necessary to elucidate altered metabolic pathways associated with acute amphetamine exposure.

Metabolomics profiling predicts outcome of tocilizumab in rheumatoid arthritis: an exploratory study

INTRODUCTION

To study metabolic signatures can be used to identify predictive biomarkers for a patient's therapeutic response.

OBJECTIVES

We hypothesized that the characterization of a patients' metabolic profile, utilizing one-dimensional nuclear magnetic resonance (¹H-NMR), may predict a response to tocilizumab in patients with rheumatoid arthritis (RA).

METHODS

40 active RA patients meeting the 2010 ACR/EULAR classification criteria initiating treatment with tocilizumab were recruited. Clinical outcomes were determined at baseline, and after six and twelve months of treatment. EULAR response criteria at 6 and 12 months to categorize patients as responders and non-responders. Blood was collected at baseline and after six months of tocilizumab therapy. ¹H-NMR was used to acquire a spectra of plasma samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification. SPSS v.27 and MetaboAnalyst 4.0 were used for statistical and pathway analysis.

RESULTS

Isobutyrate, 3-hydroxybutyrate, lysine, phenylalanine, sn-glycero-3-phosphocholine, tryptophan and tyrosine were significantly elevated in responders at the baseline. OPLS-DA at baseline partially discriminated between RA responders and non-responders. A multivariate diagnostic model showed that concentrations of 3-hydroxybutyrate and phenylalanine improved the ability to specifically predict responders classifying 77.1% of the patients correctly. At 6 months, levels of methylamine, sn-glycero-3-phosphocholine and tryptophan tended to still be low in non-responders.

CONCLUSION

The relationship between plasma metabolic profiles and the clinical response to tocilizumab suggests that ¹H-NMR may be a promising tool for RA therapy optimization. More studies are needed to determine if metabolic profiling can predict the response to biological therapies in RA patients.

Dried Blood Spot (DBS) Methodology Study for Biomarker Discovery in Lysosomal Storage Disease (LSD)

Lysosomal storage diseases (LSDs) are a heterogeneous group of inherited metabolic diseases caused by mutations in genes encoding for proteins involved in the lysosomal degradation of macromolecules. They occur in approximately 1 in 5000 live births and pose a lifelong risk. Therefore, to achieve the maximum benefit from LSDs therapies, a fast and early diagnosis of the disease is required. In this framework, biomarker discovery is a significant factor in disease diagnosis and in predicting its outcomes. On the other hand, the dried blood spot (DBS) based metabolomics platform can open up new pathways for studying non-directional hypothesis approaches to biomarker discovery. This study aims to increase the efficiency of the developed methods for biomarker development in the context of rare diseases, with an improved impact on the reliability of the detected compounds. Thereby, we conducted two independent experiments and integrated them into the screening of the human blood metabolome: (1) comparison of EDTA blood and filter cards in terms of their suitability for metabolomics studies; (2) optimization of the extraction method: a side-by-side comparison of a series of buffers to the best utility to the disease of interest. The findings were compared to previous studies across parameters such as metabolite coverage, sample type suitability, and stability. The results indicate that measurements of metabolites are susceptible to differences in pre-analytical conditions and extraction solvents. This proposed approach can increase the positive rate of the future development of biomarkers. Altogether, the procedure can be easily adapted and applied to other studies, where the limited number of samples is a common barrier.

Gut microbiome composition and serum metabolome profile among individuals with spinal cord injury and normal glucose tolerance or prediabetes/type 2 diabetes

OBJECTIVE

To compare the gut microbiome composition and serum metabolome profile among individuals with spinal cord injury (SCI) and normal glucose tolerance (NGT) or prediabetes/type 2 diabetes (P/DM).

DESIGN

Cross-sectional design.

SETTING

Research university.

PARTICIPANTS

A total of 25 adults with SCI were included in the analysis and categorized as NGT (n=16) or P/DM (n=9) based on their glucose concentration at minute 120 during a 75-g oral glucose tolerance test. The American Diabetes Association diagnosis guideline was used for grouping participants.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE(S)

A stool sample was collected and used to assess the gut microbiome composition (alpha and beta diversity, microbial abundance) via the 16s rRNA sequencing technique. A fasting serum sample was used for liquid chromatography-mass spectrometry-based untargeted metabolomics analysis, the results from which reflect the relative quantity of metabolites detected and identified. Gut microbiome and metabolomics data were analyzed by the Quantitative Insights into Microbial Ecology 2 and Metaboanalyst platforms, respectively.

RESULTS

Gut microbiome alpha diversity (Pielou's evenness index, Shannon's index) and beta diversity (weighted UniFrac distances) differed between groups. Compared with participants with NGT, participants with P/DM had less evenness in microbial communities. In particular, those with P/DM had a lower abundance of the Clostridiales order and higher abundance of the Akkermansia genus, as well as higher serum levels of gut-derived metabolites, including indoxyl sulfate and phenylacetylglutamine (P < 0.05 for all).

CONCLUSION(S)

Our results provide evidence for altered gut microbiome composition and dysregulation of gut-derived metabolites in participants with SCI and P/DM. Both indoxyl sulfate and phenylacetylglutamine have been implicated in the development of cardiovascular diseases in the able-bodied population. These findings may inform future investigations in the field of SCI and cardio-metabolic health.

Current Situation of the Metabolomics Techniques Used for the Metabolism Studies of New Psychoactive Substances

PURPOSE

The purpose of this short overview is to summarize and discuss the English-written and PubMed-listed review articles and original studies published between January 2015 and April 2019 on the use of metabolomics techniques for investigating the metabolism of new psychoactive substances (NPS). First, a brief introduction is given on the metabolism of NPS and metabolomics techniques in general. Afterward, the selected original studies are summarized and discussed. Finally, a section dedicated to the studies on NPS beyond metabolism using metabolomics techniques is provided. Thereafter, both sections are concluded and perspectives are given.

METHODS

PubMed was searched for English-written literature published between January 1, 2015 and April 1, 2019.

RESULTS

The present short overview found that the current use of metabolomics techniques in investigating the metabolism of NPS is rather limited, but these techniques can support and facilitate traditional metabolism studies.

CONCLUSIONS

Thus, there may be a certain potential for using metabolomics techniques in the field of NPS research, but a great challenge remains to thoroughly adopt the existing metabolomics methods.

Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales

Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identifying unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challenging. As an environmental stress, the acoustic radiation has a significant effect on the alteration of lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics applications. This review concluded that a combination of many of the omics areas may elucidate the metabolism of lipids and possible hazards on lipids in toothed whales by radiation.

UAB-UCSD O'Brien Center for Acute Kidney Injury Research

Acute kidney injury (AKI) remains a significant clinical problem through its diverse etiologies, the challenges of robust measurements of injury and recovery, and its progression to chronic kidney disease (CKD). Bridging the gap in our knowledge of this disorder requires bringing together not only the technical resources for research but also the investigators currently endeavoring to expand our knowledge and those who might bring novel ideas and expertise to this important challenge. The University of Alabama at Birmingham-University of California-San Diego O'Brien Center for Acute Kidney Injury Research brings together technical expertise and programmatic and educational efforts to advance our knowledge in these diverse issues and the required infrastructure to develop areas of novel exploration. Since its inception in 2008, this O'Brien Center has grown its impact by providing state-of-the-art resources in clinical and preclinical modeling of AKI, a bioanalytical core that facilitates measurement of critical biomarkers, including serum creatinine via LC-MS/MS among others, and a biostatistical resource that assists from design to analysis. Through these core resources and with additional educational efforts, our center has grown its investigator base to include >200 members from 51 institutions. Importantly, this center has translated its pilot and catalyst funding program with a $37 return per dollar invested. Over 500 publications have resulted from the support provided with a relative citation ratio of 2.18 ± 0.12 (iCite). Through its efforts, this disease-centric O'Brien Center is providing the infrastructure and focus to help the development of the next generation of researchers in the basic and clinical science of AKI. This center creates the promise of the application at the bedside of the advances in AKI made by current and future investigators.

Applying metabolomics to veterinary pharmacology and therapeutics

Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.

Safety of high-dose Puerariae Lobatae Radix in adolescent rats based on metabolomics

Puerariae Lobatae Radix (PLR) is the dried root of the leguminous plant Pueraria lobata and is a common component of health products and medicines. Although it is considered safe, some studies have reported that PLR has hepatotoxicity and estrogen-like effects. In this study, the safety of high doses of PLR water extract administered to adolescent SD rats for 30 days was evaluated by biochemical, histopathological, and metabolomic analyses. Overall, there were no significant differences between the low-dose and blank control groups in parameter values, including organ wet weight, organ coefficient, routine blood indicators, serum biochemical indexes of liver and renal function, levels of estradiol and testosterone, histopathological parameters, and primary differential metabolite profiles. Compared with the blank control group, the high-dose group may have a certain effect on the liver. These effects might be mediated by abnormal phenylalanine, tyrosine, and tryptophan biosynthesis or phenylalanine metabolism. However, histopathological analyses did not show differences in the liver, kidney, breast, uterus, ovary, testis, and epididymis between the control group and the group treated with a high dose of PLR water extract. PLR water extract did not significantly promote the precocity of male and female sexual organs. Overall, PLR water extract is relatively safe for adolescent SD rats.

Overview of Experimental Methods and Study Design in Metabolomics, and Statistical and Pathway Considerations

Metabolomics has become a powerful tool in biological and clinical investigations. This chapter reviews the technological basis of metabolomics and the considerations in answering biomedical questions. The workflow of metabolomics is explained in the sequence of data processing, quality control, metabolite annotation, statistical analysis, pathway analysis, and multi-omics integration. Reproducibility in both sample analysis and data analysis is key to the scientific progress, and the recommendation is made on reporting standards in publications. This chapter explains the technical aspects of metabolomics in the context of systems biology and applications to human health.

Use of Untargeted Metabolomics to Explore the Air Pollution-Related Disease Continuum

PURPOSE OF REVIEW

The purpose of this review is to summarize the application of untargeted metabolomics to identify the perturbation of metabolites or metabolic pathways associated with air pollutant exposures.

RECENT FINDINGS

Twenty-three studies were included in this review, in adults, children, or pregnant women. The most commonly measured air pollutant is particulate matter smaller than 2.5 μm. Size-fractioned particles, particle chemical species, gas pollutants, or organic compounds were also investigated. The reviewed studies used a wide range of air pollution measurement techniques and metabolomics analyses. Identified metabolites were primarily related to oxidative stress and inflammatory responses, and a few were related to the alterations of steroid metabolic pathways. The observed metabolic perturbations can differ by disease status, sex, and age. Air pollution-related metabolic changes were also associated with health outcomes in some studies. Our review shows that air pollutant exposures are associated with metabolic pathways primarily related to oxidative stress, inflammation, as assessed through untargeted metabolomics in 23 studies. More metabolomic studies with larger sample sizes are needed to identify air pollution components most responsible for adverse health effects, elaborate on mechanisms for subpopulation susceptibility, and link air pollution exposure to specific adverse health effects.

Liquid Chromatography-High-Resolution Mass Spectrometry-Based In Vitro Toxicometabolomics of the Synthetic Cathinones 4-MPD and 4-MEAP in Pooled Human Liver Microsomes

Synthetic cathinones belong to the most often seized new psychoactive substances on an international level. This study investigated the toxicometabolomics, particularly the in vitro metabolism of 2-(methylamino)-1-(4-methylphenyl)-1-pentanone (4-MPD) and 2-(ethylamino)-1-(4-methylphenyl)-1-pentanone (4-MEAP) in pooled human liver microsomes (pHLM) using untargeted metabolomics techniques. Incubations were performed with the substrates in concentrations ranging from 0, 12.5, and 25 µM. Analysis was done by means of high-performance liquid chromatography coupled to high-resolution mass spectrometry (HPLC-HRMS/MS) in full scan only and the obtained data was evaluated using XCMS Online and MetaboAnalyst. Significant features were putatively identified using a separate parallel reaction monitoring method. Statistical analysis was performed using Kruskal-Wallis test for prefiltering significant features and subsequent hierarchical clustering, as well as principal component analysis (PCA). Hierarchical clustering or PCA showed a distinct clustering of all concentrations with most of the features z-scores rising with the concentration of the investigated substances. Identification of significant features left many of them unidentified but revealed metabolites of both 4-MPD and 4-MEAP. Both substances formed carboxylic acids, were hydroxylated at the alkyl chain, and formed metabolites after combined hydroxylation and reduction of the cathinone oxo group. 4-MPD additionally formed a dihydroxy metabolite and a hydroxylamine. 4-MEAP was additionally found reduced at the cathinone oxo group, N-dealkylated, and formed an oxo metabolite. These findings are the first to describe the metabolic pathways of 4-MPD and to extend our knowledge about the metabolism of 4-MEAP. Findings, particularly the MS data of the metabolites, are essential for setting up metabolite-based toxicological (urine) screening procedures.

An exploratory approach for an oriented development of an untargeted hydrophilic interaction liquid chromatography-mass spectrometry platform for polar metabolites in biological matrices

The analysis of polar metabolites based on liquid chromatography-mass spectrometry (LC-MS) methods should take into consideration the complexity of interactions in LC columns to be able to cover a broad range of metabolites of key biological pathways. Therefore, in this study, different chromatographic columns were tested for polar metabolites including reversed-phase and hydrophilic interaction liquid chromatography (HILIC) columns. Based on a column screening, two new generations of zwitterionic HILIC columns were selected for further evaluation. A tree-based method optimization was applied to investigate the chromatographic factors affecting the retention mechanisms of polar metabolites with zwitterionic stationary phases. The results were evaluated based on a scoring system which was applied for more than 80 polar metabolites with a high coverage of key human metabolic pathways. The final optimized methods showed high complementarity to analyze a wide range of metabolic classes including amino acids, small peptides, sugars, amino sugars, phosphorylated sugars, organic acids, nucleobases, nucleosides, nucleotides and acylcarnitines. Optimized methods were applied to analyze different biological matrices, including human urine, plasma and liver cell extracts using an untargeted approach. The number of high-quality features (< 30% median relative standard deviation) ranged from 3,755 for urine to 5,402 for the intracellular metabolome of liver cells, showing the potential of the methods for untargeted purposes.

Towards Best Practice in Hair Metabolomic Studies: Systematic Investigation on the Impact of Hair Length and Color

Untargeted metabolomic studies are used for large-scale analysis of endogenous compounds. Due to exceptional long detection windows of incorporated substances in hair, analysis of hair samples for retrospective monitoring of metabolome changes has recently been introduced. However, information on the general behavior of metabolites in hair samples is scarce, hampering correct data interpretation so far. The presented study aimed to investigate endogenous metabolites depending on hair color and along the hair strand and to propose recommendations for best practice in hair metabolomic studies. A metabolite selection was analyzed using untargeted data acquisition in genuine hair samples from different hair colors and after segmentation in 3 cm segments. Significant differences in metabolites among hair colors and segments were found. In conclusion, consideration of hair color and hair segments is necessary for hair metabolomic studies and, subsequently, recommendations for best practice in hair metabolomic studies were proposed.

Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data

The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normal- and reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions.

Protective Effects and Metabolic Regulatory Mechanisms of Shenyan Fangshuai Recipe on Chronic Kidney Disease in Rats

Background

Chronic kidney disease (CKD) is one of the major causes of renal damage. Shenyan Fangshuai Recipe (SFR), a modified prescription of traditional medicine in China, showed potent effects in alleviating edema, proteinuria, and hematuria of CKD in clinical practices. In this study, we aimed to investigate scientific evidence-based efficacy as well as metabolic regulations of SFR in CKD treatment.

Materials and Methods

The effect of SFR on CKD was observed in a rat model which is established with oral administration of adenine-ethambutol mixture for 21 days. Further, metabolites in serum were detected and identified with ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS). Metabolomics study was performed using Ingenuity Pathway Analysis (IPA) software.

Results

With H&E staining and Masson's trichrome, the results showed that chronic kidney damage is significantly rescued with SFR treatment and recovered to an approximately normal condition. Along with 44 differential metabolites discovered, the regulation of SFR on CKD was enriched in glycine biosynthesis I, mitochondrial L-carnitine shuttle pathway, phosphatidylethanolamine biosynthesis III, sphingosine-1-phosphate signaling, L-serine degradation, folate transformations I, noradrenaline and adrenaline degradation, salvage pathways of pyrimidine ribonucleotides, cysteine biosynthesis III (Mammalia), glycine betaine degradation, and cysteine biosynthesis/homocysteine degradation. Further, TGFβ-1 and MMP-9 were observed playing roles in this regulatory process by performing immunohistochemical staining.

Conclusion

SFR exerts potent effects of alleviating glomerular sclerosis and interstitial fibrosis in the kidney, mainly via integrated regulations on metabolism and production of homocysteine, L-carnitine, and epinephrine, as well as the expression of TGFβ-1. This study provides evidence for SFR's protective effects on CKD and reveals the metabolic mechanism behind these benefits for the first time.

NMR Metabolomics Applied on the Discrimination of Variables Influencing Tomato (Solanum lycopersicum)

Tomato composition and nutritional value are attracting increasing attention and interest from both consumers and producers. The interest in enhancing fruits' quality with respect to beneficious nutrients and flavor/aroma components is based not only in their economic added value but also in their implications involving organoleptic and healthy properties and has generated considerable research interest among nutraceutical and horticultural industries. The present article reviews up to March 2020 some of the most relevant studies based on the application of NMR coupled to multivariate statistical analysis that have addressed the investigation on tomato (Solanum lycopersicum). Specifically, the NMR untargeted technique in the agri-food sector can generate comprehensive data on metabolic networks and is paving the way towards the understanding of variables affecting tomato crops and composition such as origin, variety, salt-water irrigation, cultivation techniques, stage of development, among many others. Such knowledge is helpful to improve fruit quality through cultural practices that divert the metabolism towards the desired pathways and, probably more importantly, drives further efforts towards the differentiation of those crops developed under controlled and desired agronomical conditions.

Metabonomic analysis of hypophosphatemic laying fatigue syndrome in laying hens

Laying fatigue syndrome (LFS) is a common disease in poultry, which is characterized by low egg laying rate, increased broken and soft shell egg rate and osteoporosis, and even death of poultry. Insufficient phosphorus content in feed is one of the major causes of LFS. In this study, a total of 22-week-old Roman white shell hens were randomly divided into two groups, including control (group C) and low dietary phosphorus (group P) groups. The hens of groups C and P were fed with a full mixed diet and a mixed diet containing 0.18% available phosphorus content, respectively. At 25, 29 and 34 weeks, the production performance of hens was detected and the serum samples of hens were collected to detect the changes of serum phosphorus, calcium, osteopelectin (OPG), parathyroid hormone (PTH), estradiol (E₂), tartaric acid-resistant phosphatase (TRACP) and alkaline phosphatase (ALP). The keels were removed and x-rayed. In addition, all serum samples were tested by LC-MS metabolomics. Our results showed that low dietary phosphorus decreased the production performance, phosphorus content, and E₂ and OPG levels, while increased calcium and PTH levels, and ALP and TRACP activities in laying hens. The hens of group P had bent keels. Besides, small molecular metabolites in serum were enriched in 10 pathways and 17 metabolites were significantly different according to the area under the receiver operating characteristic curve (AUC) analysis. Our results showed that low phosphorus diet could induce LFS. Also, 17 metabolites detected by metabonomics can be used as biomarkers for clinical diagnosis and early warning of hypophosphatemic laying fatigue syndrome (HLFS). This study provides a scientific basis for the early prevention and treatment of HLFS.

A Novel Approach Based on Metabolomics Coupled With Intestinal Flora Analysis and Network Pharmacology to Explain the Mechanisms of Action of Bekhogainsam Decoction in the Improvement of Symptoms of Streptozotocin-Induced Diabetic Nephropathy in Mice

Bekhogainsam decoction (BHID), a representative prescription for the treatment of diabetes mellitus (DM) and diabetic complications in both traditional Korean and Chinese medicine, was examined for its ability to ameliorate diabetic nephropathy (DN), and its mechanism of action was evaluated by metabolomics, gut microbiota, and network pharmacology. In this study, male specific pathogen-free C57BL/6 mice were intraperitoneally injected with streptozotocin (STZ, 100 mg/kg) once per day for 3 days consecutively, and were then orally administered BHID at 100 and 500 mg/kg, and metformin at 250 mg/kg once per day for 4 weeks. Our results showed that the administration of BHID to mice with STZ-induced DN prevented physiological and serological changes, structural damage, and kidney dysfunction. Based on a metabolomics test with serum, the profoundly altered metabolites in the BHID treatment group were identified. Thirty-six BHID-related proteins and four signaling pathways, including valine, leucine, and isoleucine biosynthesis, nicotinate and nicotinamide metabolism, tryptophan metabolism, and alanine, aspartate, and glutamate metabolism pathways, were explored. Principal coordinates analysis (PCoA) of the gut microbiota revealed that BHID treatment significantly affected the flora composition. In addition, the network pharmacology analysis revealed that BHID acted through phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) and MAPK-related protein targets. Our findings on the anti-DN effects of BHID and its mechanism of action, from the perspective of systems biology, have provided scientific evidence to support the clinical treatment of patients with diabetes, and implied that BHID has the potential to prevent the progression of DN.

Fecal Volatile Organic Compound Profiles are Not Influenced by Gestational Age and Mode of Delivery: A Longitudinal Multicenter Cohort Study

Fecal volatile organic compounds (VOC) reflect human and gut microbiota metabolic pathways and their interaction. VOC behold potential as non-invasive preclinical diagnostic biomarkers in various diseases, e.g., necrotizing enterocolitis and late onset sepsis. There is a need for standardization and assessment of the influence of clinical and environmental factors on the VOC outcome before this technique can be applied in clinical practice. The aim of this study was to investigate the influence of gestational age (GA) and mode of delivery on the fecal VOC pattern in preterm infants born below 30 weeks of gestation. Longitudinal fecal samples, collected on days 7, 14, and 21 postnatally, were analyzed by an electronic nose device (Cyranose 320^®). In total, 58 preterm infants were included (29 infants born at GA 24–26 weeks vs. 29 at 27–29 completed weeks, 24 vaginally born vs. 34 via C-section). No differences were identified at any predefined time point in terms of GA and delivery mode (p > 0.05). We, therefore, concluded that correction for these factors in this population is not warranted when performing fecal VOC analysis in the first three weeks of life.

Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's

Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many exposures in humans, and the emerging metabolomics technology offers a means to read out both the biological activity and environmental impact in the same dataset. How to integrate exposome and metabolome in data analysis is still challenging. Here, we employ a hierarchical community network to investigate the global associations between the metabolome and mixed exposures including DDTs, PFASs and PCBs, in a women cohort with sera collected in California in the 1960s. Strikingly, this analysis revealed that the metabolite communities associated with the exposures were non-specific and shared among exposures. This suggests that a small number of metabolic phenotypes may account for the response to a large class of environmental chemicals.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial

Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.

Human Plasma Metabolomics in Age-Related Macular Degeneration: Meta-Analysis of Two Cohorts

The pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness worldwide, remains only partially understood. This has led to the current lack of accessible and reliable biofluid biomarkers for diagnosis and prognosis, and absence of treatments for dry AMD. This study aimed to assess the plasma metabolomic profiles of AMD and its severity stages with the ultimate goal of contributing to addressing these needs. We recruited two cohorts: Boston, United States (n = 196) and Coimbra, Portugal (n = 295). Fasting blood samples were analyzed using ultra-high performance liquid chromatography mass spectrometry. For each cohort, we compared plasma metabolites of AMD patients versus controls (logistic regression), and across disease stages (permutation-based cumulative logistic regression considering both eyes). Meta-analyses were then used to combine results from the two cohorts. Our results revealed that 28 metabolites differed significantly between AMD patients versus controls (false discovery rate (FDR) q-value: 4.1 × 10-2-1.8 × 10-5), and 67 across disease stages (FDR q-value: 4.5 × 10-2-1.7 × 10-4). Pathway analysis showed significant enrichment of glycerophospholipid, purine, taurine and hypotaurine, and nitrogen metabolism (p-value ≤ 0.04). In conclusion, our findings support that AMD patients present distinct plasma metabolomic profiles, which vary with disease severity. This work contributes to the understanding of AMD pathophysiology, and can be the basis of future biomarkers and precision medicine for this blinding condition.