Non-targeted metabolomic approach reveals urinary metabolites linked to steroid biosynthesis pathway after ingestion of citrus juice

The potential of glucosidase and glucose oxidase for aroma improvement in concentrated peach puree based on volatilomics and metabolomics

Cooked off-flavor was produced during the processing of concentrated peach puree (CPP), which led to aroma deterioration. Enzymatic treatment was beneficial in eliminating off-flavors and improving the aroma quality. Herein, the efficacy of glycosidase (AR2000), glucose oxidation (GOD), and their combination on the inhibition of off-flavors and aroma enhancement were evaluated. Compared with CPP, contents of benzaldehyde, benzyl alcohol, nonanal, and linalool increased by 198%, 1222%, 781%, and 71% after AR2000 treatment via the metabolisms of shikimate, glucose, linoleic acid, and linolenic acid, leading to the strengthening of floral and grassy. Due to the removal of 1-octen-3-one via linolenic acid metabolism, cooked off-flavor could be significantly weakened by GOD. Furthermore, Furthermore, the combination of AR2000 and GOD could not only inhibit the production of 1-octen-3-one to weaken the cooked note but also enhance grassy and floral attributes via the increase of aldehydes and alcohols.

Formation of key aroma-active and off-flavor components in concentrated peach puree

Non-volatiles offer some insight into the formation of aroma-active components in peach puree (PP), but more depth investigation is still needed. Formation pathways of key aroma-active and off-flavor components in PP during thermal concentration (PP + C) and sterilization (PP + C + S) are unclear. Therefore, GC-O-MS combined with UPLC-MS/MS was used to identify the volatile and nonvolatile components and their formation pathways. Among the 36 aroma-active compounds, the contents of γ-decalactone, hexyl acetate, leaf acetate, hexanal, and 1-hexanol (odor activity value ≥ 1) decreased by 46 %, 100 %, 100 %, 92 %, and 100 % between PP and PP + C + S, causing the weakening of "green" and "fruity" attributes. Off-flavor components including 1-octen-3-one, isobutyric acid, isothiazole, and isovaleric acid were identified during thermal processing. 1-Octen-3-one content increased by 75 % from PP to PP + C + S through linolenic acid metabolism, which contributed to "cooked"; the formation of isobutyric and isovaleric acids, isothiazole, resulted in the enhancement of "sour/rancid" via serine and leucine metabolism.

Comparison of chemometric strategies for potential exposure marker discovery and false-positive reduction in untargeted metabolomics: application to the serum analysis by LC-HRMS after intake of Vaccinium fruit supplements

Untargeted liquid chromatographic-high-resolution mass spectrometric (LC-HRMS) metabolomics for potential exposure marker (PEM) discovery in nutrikinetic studies generates complex outputs. The correct selection of statistically significant PEMs is a crucial analytical step for understanding nutrition-health interactions. Hence, in this paper, different chemometric selection workflows for PEM discovery, using multivariate or univariate parametric or non-parametric data analyses, were comparatively tested and evaluated. The PEM selection protocols were applied to a small-sample-size untargeted LC-HRMS study of a longitudinal set of serum samples from 20 volunteers after a single intake of (poly)phenolic-rich Vaccinium myrtillus and Vaccinium corymbosum supplements. The non-parametric Games-Howell test identified a restricted group of significant features, thus minimizing the risk of false-positive retention. Among the forty-seven PEMs exhibiting a statistically significant postprandial kinetics, twelve were successfully annotated as purine pathway metabolites, benzoic and benzodiol metabolites, indole alkaloids, and organic and fatty acids, and five (i.e. octahydro-methyl-β-carboline-dicarboxylic acid, tetrahydro-methyl-β-carboline-dicarboxylic acid, citric acid, caprylic acid, and azelaic acid) were associated to Vaccinium berry consumption for the first time. The analysis of the area under the curve of the longitudinal dataset highlighted thirteen statistically significant PEMs discriminating the two interventions, including four intra-intervention relevant metabolites (i.e. abscisic acid glucuronide, catechol sulphate, methyl-catechol sulphate, and α-hydroxy-hippuric acid). Principal component analysis and sample classification through linear discriminant analysis performed on PEM maximum intensity confirmed the discriminating role of these PEMs.

SteroidXtract: Deep Learning-Based Pattern Recognition Enables Comprehensive and Rapid Extraction of Steroid-Like Metabolic Features for Automated Biology-Driven Metabolomics

Despite the vast amount of metabolic information that can be captured in untargeted metabolomics, many biological applications are looking for a biology-driven metabolomics platform that targets a set of metabolites that are relevant to the given biological question. Steroids are a class of important molecules that play critical roles in many physiological systems and diseases. Besides known steroids, there are a large number of unknown steroids that have not been reported in the literature. The ability to rapidly detect and quantify both known and unknown steroid molecules in a biological sample can greatly accelerate a broad range of steroid-focused life science research. This work describes the development and application of SteroidXtract, a convolutional neural network (CNN)-based bioinformatics tool that can recognize steroid molecules in mass spectrometry (MS)-based untargeted metabolomics using their unique tandem MS (MS²) spectral patterns. SteroidXtract was trained using a comprehensive set of standard MS² spectra from MassBank of North America (MoNA) and an in-house steroid library. Data augmentation strategies, including intensity thresholding and Gaussian noise addition, were created and applied to minimize data overfitting caused by the limited number of standard steroid MS² spectra. The CNN model embedded in SteroidXtract was further compared with random forest and XGBoost using nested cross-validations to demonstrate its performance. Finally, SteroidXtract was applied in several metabolomics studies to demonstrate its sensitivity, specificity, and robustness. Compared to conventional statistics-driven metabolomics data interpretation, our work offers a novel automated biology-driven approach to interpreting untargeted metabolomics data, prioritizing biologically important molecules with high throughput and sensitivity.

Citrus Flavanones Upregulate Thyrotroph Sirt1 and Differently Affect Thyroid Nrf2 Expressions in Old-Aged Wistar Rats

A growing population of elderly people consume citrus flavanones, naringenin, and hesperetin in the form of fruits or juices. Flavanones are bioactives with potent antioxidant properties and have potential in slowing down the aging process. Because flavanones exert controversial effects on pituitary-thyroid functioning, our study on the old-aged rat model aimed to elucidate the mechanism by which naringenin and hesperetin affect this axis. Naringenin and hesperetin increased the Sirt1 mRNA level by 91 and 71% (p < 0.05), which was followed by increased Sirt1 expression by 20 and 15% (p < 0.05), respectively. Only naringenin decreased thyroid-stimulating hormone expression by 20% (p < 0.05). Thyroid peroxidase protein expression was upregulated after naringenin or hesperetin by 62 and 43% (p < 0.05), respectively. Naringenin lowered mRNA levels of Tpo, Sod1, Sod2, Cat, and Nrf2 by 50, 32, 45, 35, and 42% (p < 0.05), respectively, and increased Gpx by 54% (p < 0.05), while hesperetin decreased Sod1 and Sod2 mRNA levels by 46 and 55% (p < 0.05), respectively. Naringenin increased the protein expressions of Nrf2 and SOD2 by 58 and 50% (p < 0.05), respectively, and decreased SOD1 expression by 48% (p < 0.05), while hesperetin protein decreased expressions of SOD1 and Nrf2 by 63 and 32% (p < 0.05), respectively. Altogether, our findings suggest that citrus flavanones contribute to restoring the impaired thyroid functioning in the old-aged rats.

Recent Advances and Challenges in Steroid Metabolomics for Biomarker Discovery

BACKGROUND

Steroid hormones belong to a group of low-molecular weight compounds which are responsible for maintenance of various body functions, thus, their accurate assessment is crucial for evaluation of biosynthetic defects. The development of reliable methods allowing disease diagnosis is essential to improve early detection of various disorders connected with altered steroidogenesis. Currently, the field of metabolomics offers several improvements in terms of sensitivity and specificity of the diagnostic methods when opposed to classical diagnostic approaches. The combination of hyphenated techniques and pattern recognition methods allows to carry out a comprehensive assessment of the slightest alterations in steroid metabolic pathways and can be applied as a tool for biomarker discovery.

METHODS

We have performed an extensive literature search applying various bibliographic databases for peer-reviewed articles concentrating on the applications of hyphenated techniques and pattern recognition methods incorporated into the steroid metabolomic approach for biomarker discovery.

RESULTS

The review discusses strengths, challenges and recent developments in steroidbased metabolomics. We present methods of sample collection and preparation, methods of separation and detection of steroid hormones in biological material, data analysis, and interpretation as well as examples of applications of steroid metabolomics for biomarker discovery (cancer, mental and central nervous system disorders, endocrine diseases, monitoring of drug therapy and doping control).

CONCLUSION

Information presented in this review will be valuable to anyone interested in the application of metabolomics for biomarker discovery with a special emphasis on disorders of steroid hormone synthesis and metabolism.

A review of nanoscale LC-ESI for metabolomics and its potential to enhance the metabolome coverage

Liquid chromatography-electrospray ionisation-mass spectrometry (LC-ESI-MS) platforms are widely used to perform high throughput untargeted profiling of biological samples for metabolomics-based approaches. However, these LC-ESI platforms usually favour the detection of metabolites present at relatively high concentrations because of analytical limitations such as ion suppression, thus reducing overall sensitivity. To counter this issue of sensitivity, the latest in terms of analytical platforms can be adopted to enable a greater portion of the metabolome to be analysed in a single analytical run. Here, nanoflow liquid chromatography-nanoelectrospray ionisation (nLC-nESI), which has previously been utilised successfully in proteomics, is explored for use in metabolomic and exposomic research. As a discovery based field, the markedly increased sensitivity of these nLC-nESI platforms offer the potential to uncover the roles played by low abundant signalling metabolites (e.g. steroids, eicosanoids) in health and disease studies, and would also enable an improvement in the detection of xenobiotics present at trace levels in biological matrices to better characterise the chemical exposome. This review aims to give an insight into the advantages associated with nLC-nESI for metabolomics-based approaches. Initially we detail the source of improved sensitivity prior to reviewing the available approaches to achieving nanoflow rates and nanospray ionisation for metabolomics. The robustness of nLC-nESI platforms was then assessed using the literature available from a metabolomic viewpoint. We also discuss the challenging point of sample preparation which needs to be addressed to fully enjoy the benefits of these nLC-nESI platforms. Finally, we assess metabolomic analysis utilising nano scale platforms and look ahead to the future of metabolomics using these new highly sensitive platforms.

Single-platform ‘multi-omic’ profiling: unified mass spectrometry and computational workflows for integrative proteomics–metabolomics analysis

Advances in instrumentation and analysis tools are permitting evermore comprehensive interrogation of diverse biomolecules and allowing investigators to move from linear signaling cascades to network models, which more accurately reflect the molecular basis of biological systems and processes.

Present and foreseeable future of metabolomics in forensic analysis

The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed.

Lipidomic approach in young adult triathletes: effect of supplementation with a polyphenols-rich juice on neuroprostane and F2-dihomo-isoprostane markers

With adequate training, our juice rich in polyphenolic compounds has been able to influence the excretion values of oxidative stress biomarkers associated with the central nervous system.

Inhibitory effects of amines from Citrus reticulata on bleomycin-induced pulmonary fibrosis in rats

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease for which, thus far, there are no effective treatments. The pericarp of Citrus reticulata, as a traditional herbal drug, has been used for the clinical treatment of lung-related diseases in China for many years. In the present study, the amines from the pericarp of Citrus reticulata were isolated, and their hydrochlorides were prepared. The results of screening using cultured human embryonic lung fibroblasts (hELFs) revealed that, of the amines, 4-methoxyphenethylamine hydrochloride (designated as amine hydrochloride 1) possessed the most potent inhibitory effect. Further in vivo experiments using a rat model of bleomycin-induced pulmonary fibrosis demonstrated that the oral administration of amine hydrochloride 1 significantly lowered the hydroxyproline content in both serum and lung tissue, and alleviated pulmonary alveolitis and fibrosis. Immunohistochemical analysis revealed that amine hydrochloride 1 exerted its inhibitory effect against IPF through the downregulation of lung transforming growth factor (TGF)-β1 protein expression. Our results demonstrated that amine hydrochloride 1 prevented the development of bleomycin‑induced lung fibrosis in rats. Thus, our data suggest that the amines from the pericarp of Citrus reticulata have therapeutic potential for use in the treatment of IPF.

Physiological conditions can be reflected in human urine proteome and metabolome

Biomarkers are the measurable changes associated with physiological or pathophysiological processes. Urine, unlike blood, lacks mechanisms for maintaining homeostasis: it is therefore an ideal source of biomarkers that can reflect systemic changes. Urinary proteome and metabolome have been studied for their diagnostic capabilities, ability to monitor disease and prognostic utility. In this review, the effects of common physiological conditions such as gender, age, diet, daily rhythms, exercise, hormone status, lifestyle and extreme environments on human urine are discussed. These effects should be considered when biomarker studies of diseases are conducted. More importantly, if physiological changes can be reflected in urine, we have reason to expect that urine will become widely used to detect small and early changes in pathological and/or pharmacological conditions.

Metabolic faecal fingerprinting of trans-resveratrol and quercetin following a high-fat sucrose dietary model using liquid chromatography coupled to high-resolution mass spectrometry

Faecal non-targeted metabolomics deciphers metabolic end-products resulting from the interactions among food, host genetics, and gut microbiota. Faeces from Wistar rats fed a high-fat sucrose (HFS) diet supplemented with trans-resveratrol and quercetin (separately or combined) were analysed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Metabolomics in faeces are categorised into four clusters based on the type of treatment. Tentative identification of significantly differing metabolites highlighted the presence of carbohydrate derivatives or conjugates (3-phenylpropyl glucosinolate and dTDP-D-mycaminose) in the quercetin group. The trans-resveratrol group was differentiated by compounds related to nucleotides (uridine monophosphate and 2,4-dioxotetrahydropyrimidine D-ribonucleotide). Marked associations between bacterial species (Clostridium genus) and the amount of some metabolites were identified. Moreover, trans-resveratrol and resveratrol-derived microbial metabolites (dihydroresveratrol and lunularin) were also identified. Accordingly, this study confirms the usefulness of omics-based techniques to discriminate individuals depending on the physiological effect of food constituents and represents an interesting tool to assess the impact of future personalized therapies.

Validation of a two-step quality control approach for a large-scale human urine metabolomic study conducted in seven experimental batches with LC/QTOF-MS

After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets.

Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC–MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.

Rapid comparison of metabolites in humans and rats of different sexes using untargeted UPLC-TOFMS and an in-house software platform

Metabolite differences between sexes have rarely been observed in a global manner, but it has recently been made possible by the advancement in metabolomics techniques. In this study, untargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry and an in-house software platform were used for a rapid comparison of sex differences in urinary metabolites in humans and in urinary and serum metabolites in Sprague Dawley (SD) rats. In addition, the species differences of urinary metabolites between humans and SD rats were also observed. Principle component analysis showed that all the observed metabolite sex differences were more distinct in SD rats than in humans, indicating that the sex differences of human urinary metabolites is small compared with that of SD rats. In SD rats, the observed metabolite sex differences were more distinct in urine than in serum, indicating the importance of urine analysis for metabolomics studies. The species differences in the urinary metabolites of humans and SD rats were much more distinct than any of the observed sex differences. Many sex- and species-related markers were discovered and putatively identified. In both humans and SD rats, steroid metabolites appeared to constitute a major sex difference in urinary metabolites. This provides new proof of the special importance of steroid metabolites in sex differences from an untargeted metabolomics investigation, which is rare for sex differences. Contrary patterns involving adrenocortical activity appeared to exist between rodents and humans, which agrees with previous reports. In the serum metabolites of SD rats, sex differences in ascorbic acid or its isomer and pantothenic acid or its isomer, but not in steroid metabolites, were prominent. Human-specific α-N- phenylacetyl-l-glutamine and androsterone glucuronide were among the putative identities of the markers discriminating humans and SD rats. This study demonstrated the feasibility of an in-house software platform and provides metabolite-related information on sex and species differences.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics.

Non-targeted metabolomic reveals the effect of salt stress on global metabolite of halotolerant yeast Candida versatilis and principal component analysis

As one of the major microbes in the soy sauce fermentation, Candida versatilis enriches the flavor and improves the quality of soy sauce. In this study, a combination of five different GC-MS and LC-MS-based metabolome analytical approaches was used to analyze the intracellular, extracellular and whole metabolites of C. versatilis. Our results found out that a total of 132, 244 and 267 different metabolites were detectable from the intracellular, extracellular and whole part, respectively. When exposed to 0. 9 and 18 % salt, respectively, 114, 123 and 129 different intracellular metabolites, 184, 200 and 178 extracellular metabolites and 177, 188 and 186 whole metabolites were detected, respectively. Our data showed that salt enhances the metabolic capacity of C. versatilis, especially its amino acid and enhances the synthesis and secretion of some metabolites of C. versatilis, especially the aldehydes and phenols, such as vanillin, guaiacol and 5-hydroxymethylfurfural. Our data also showed that special attention has to be paid to the generation of biogenic amines when C. versatilis was treated with salt.

A new approach for plasma (xeno)metabolomics based on solid-phase extraction and nanoflow liquid chromatography-nanoelectrospray ionisation mass spectrometry

Current metabolite profiling methods based on liquid chromatography-mass spectrometry (LC-MS) platforms do not detect many of the components present at trace concentrations in extracts of plasma due to their low ionisation efficiency or to interference from highly abundant compounds. Nanoflow LC-nanospray MS platforms, which are commonly used in proteomics, could overcome these limitations and significantly increase analytical sensitivity and coverage of the plasma (xeno)metabolome (i.e., metabolites and xenobiotics), but require small injection volumes (<0.5μL). In this study, we developed sample preparation methods to remove ion suppressive phospholipids and concentrate remaining components of the plasma (xeno)metabolome in order to analyse sub-microliter volumes of plasma extracts for nanoflow ultra-high-performance liquid chromatography-nanoelectrospray ionisation-time-of-flight mass spectrometry (nUHPLC-nESI-TOFMS). These methods use phospholipid filtration plates in combination with polymeric or mixed mode exchange solid-phase extraction (SPE). The phospholipid filtration plates removed >94% of the predominant phospholipid/lysophospholipid species from plasma, whilst absolute recoveries of 63 selected (xeno)metabolites from spiked plasma were generally between 60 and 104%. After a further SPE step, recoveries of test compounds were between 50 and 81%. Studies revealed that both the sample preparation methodology and nUHPLC-nESI-TOFMS analyses gave acceptable repeatability. A qualitative comparison of SPE methods revealed that sample concentration by either polymer or mixed mode ion-exchange SPE gave comprehensive metabolite coverage of plasma extracts, but the use of cation exchange SPE significantly increased detection of many cationic compounds in the sample extracts. Method detection limits for steroid, eicosanoid and bile metabolites were <1.0ng/mL plasma and for pharmaceutical contaminants were between 0.01 and 30ng/mL plasma. Comparison of the phospholipid removal/cation exchange SPE and the classical protein precipitation (PPT) sample preparation methodologies revealed that both methods detected the same range of (xeno)metabolites. However, unlike PPT extracts, the SPE preparations allowed direct injection of more concentrated plasma extracts onto the nUHPLC-nESI-TOFMS platform without blockage of the nanocolumn or nanospray, thus resulting in a wider coverage of the (xeno)metabolome. This is the first work to demonstrate the significantly enhanced sensitivity arising from the use of concentrated SPE sample preparations and direct nUHPLC-nESI-TOFMS analysis for untargeted profiling of plasma samples and constitutes a step forward for identifying mixtures of chemical stressors accumulated in blood as well as the disruption of key metabolite pathways in the same sample.