UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research

Metabolic perturbations in zebrafish (Danio rerio) larvae exposed to sulfentrazone and imidacloprid

The intensive and widespread application of pesticides in agroecosystems can lead to the simultaneous exposure of non-target aquatic organisms to insecticides and herbicides. However, the underlying mechanisms through which aquatic organisms undergo metabolic reprogramming to withstand the combined effects of the insecticide imidacloprid (IMI) and herbicide sulfentrazone (SUL) remain poorly elucidated. This study employs metabolomics to investigate the effects of individual and combined exposures to IMI and SUL on zebrafish (Danio rerio), aiming to simulate complex environmental conditions. Metabolomics analysis revealed extensive metabolic reprogramming in larvae induced by the selected agrochemicals. Both individual and combined exposures disrupted nucleotide metabolism, inhibited glycolysis, and led to the accumulation of acetylcholine through the shared modulation of differential metabolites. Notably, individual exposure exhibited a unique mode of action. Larvae exposed to IMI alone showed mitochondrial dysfunction, potentially stemming from interference with the electron transport chain, while SUL-induced disruptions were associated with glycerophospholipid accumulation, marking it as a critical target. Additionally, calculations of the metabolic effect level index indicated antagonistic interactions between SUL and IMI mixtures at an overall metabolic level. The results obtained through investigating the lethal and sub-lethal effects also revealed that the simultaneous application of SUL and IMI may have the potential to diminish acute and developmental toxicity in zebrafish. This study underscores the significance of metabolomics as a valuable and effective strategy for deciphering the toxicity and interactions of agrochemical mixtures.

Is Lipid Metabolism of Value in Cancer Research and Treatment? Part I- Lipid Metabolism in Cancer

For either healthy or diseased organisms, lipids are key components for cellular membranes; they play important roles in numerous cellular processes including cell growth, proliferation, differentiation, energy storage and signaling. Exercise and disease development are examples of cellular environment alterations which produce changes in these networks. There are indications that alterations in lipid metabolism contribute to the development and progression of a variety of cancers. Measuring such alterations and understanding the pathways involved is critical to fully understand cellular metabolism. The demands for this information have led to the emergence of lipidomics, which enables the large-scale study of lipids using mass spectrometry (MS) techniques. Mass spectrometry has been widely used in lipidomics and allows us to analyze detailed lipid profiles of cancers. In this article, we discuss emerging strategies for lipidomics by mass spectrometry; targeted, as opposed to global, lipid analysis provides an exciting new alternative method. Additionally, we provide an introduction to lipidomics, lipid categories and their major biological functions, along with lipidomics studies by mass spectrometry in cancer samples. Further, we summarize the importance of lipid metabolism in oncology and tumor microenvironment, some of the challenges for lipodomics, and the potential for targeted approaches for screening pharmaceutical candidates to improve the therapeutic efficacy of treatment in cancer patients.

Evidence for ethnicity and location as regulators of the newborn blood metabolome: a monozygous twin study

Introduction

Monochorionic, diamniotic (MCDA) monozygotic twins share nearly all genetic variation and a common placenta in utero. Despite this, MCDA twins are often discordant for a range of common phenotypes, including early growth and birth weight. As such, MCDA twins represent a unique model to explore variation in early growth attributable primarily to in utero environmental factors.

Methods

MCDA twins with a range of within-pair birth weight discordance were sampled from the peri/postnatal epigenetic twin study (PETS, Melbourne; n = 26 pairs), Beijing twin study (BTS, Beijing; n = 25), and the Chongqing longitudinal twin study (LoTiS, Chongqing; n = 22). All PETS participants were of European-Australian ancestry, while all Chinese participants had Han ancestry. The average of the birth weight difference between the larger and smaller co-twins for all twin pairs was determined and metabolomic profiles of amino acids, TCA cycle intermediates, fatty acids, organic acids, and their derivatives generated from cord blood plasma by gas chromatograph mass spectrometry. Within and between co-twin pair analyses were performed to identify metabolites specifically associated with discordance in birth weight. Multivariable regression and pathway enrichment analyses between different regions were performed to evaluate the geographical effects on the metabolism of MCDA twin pairs.

Results

PETS twins showed a markedly different metabolic profile at birth compared to the two Chinese samples. Within-pair analysis revealed an association of glutathione, creatinine, and levulinic acid with birth weight discordance. Caffeine, phenylalanine, and several saturated fatty acid levels were uniquely elevated in PETS twins and were associated with maternal BMI and average within pair birth weight, in addition to birth weight discordance. LoTiS twins had higher levels of glutathione, tyrosine, and gamma-linolenic acid relative to PETS and BTS twins, potentially associated with eating habits.

Conclusion

This study highlights the potential role of underlying genetic variation (shared by MZ twins), in utero (non-shared by MZ twins) and location-specific (shared by MZ twins) environmental factors, in regulating the cord blood metabolome of uncomplicated MCDA twins. Future research is needed to unravel these complex relationships that may play a key role in phenotypic metabolic alterations of twins independent of genetic diversity.

Improving ribonucleic acid production in Saccharomyces pastorianus via in silico genome-scale metabolic network model

Ribonucleic acid (RNA) and its degradation products are important biomolecules widely used in the food and pharmaceutical industries for their flavoring and nutritional functions. In this study, we used a genome-scale metabolic network model (GSMM) to explore genetic targets for nucleic acid synthesis in a Saccharomyces pastorianus strain (G03). Yeast 8.5.0 was used as the base model, which accurately predicted G03's growth. Using OptForce, we found that overexpression of ARO8 and ATP1 among six different strategies increased the RNA content of G03 by 58.0% and 74.8%, respectively. We also identified new metabolic targets for improved RNA production using a modified GSMM called TissueModel, constructed using the GIMME transcriptome constraint tool to remove low-expressed reactions in the model. After running OptKnock, the RNA content of G03-△BNA1 and G03-△PMA1 increased by 44.6% and 39.8%, respectively, compared to G03. We suggest that ATP1, ARO8, BNA1, and PMA1 regulate cell fitness, which affects RNA content. This study is the first to identify strategies for RNA overproduction using GSMM and to report that regulation of ATP1, ARO8, BNA1, and PMA1 can increase RNA content in S. pastorianus. These findings also provide valuable knowledge on model reconstruction for S. pastorianus.

Identification of a biosynthetic gene cluster for a red pigment cristazarin produced by a lichen-forming fungus Cladonia metacorallifera

Lichens are known to produce many novel bioactive metabolites. To date, approximately 1,000 secondary metabolites have been discovered, which are predominantly produced by the lichen mycobionts. However, despite the extensive studies on production of lichen secondary metabolites, little is known about the responsible biosynthetic gene clusters (BGCs). Here, we identified a putative BGC that is implicated in production of a red pigment, cristazarin (a naphthazarin derivative), in Cladonia metacorallifera. Previously, cristazarin was shown to be specifically induced in growth media containing fructose as a sole carbon source. Thus, we performed transcriptome analysis of C. metacorallifera growing on different carbon sources including fructose to identify the BGC for cristazarin. Among 39 polyketide synthase (PKS) genes found in the genome of C. metacorallifera, a non-reducing PKS (coined crz7) was highly expressed in growth media containing either fructose or glucose. The borders of a cristazarin gene cluster were delimited by co-expression patterns of neighboring genes of the crz7. BGCs highly conserved to the cristazarin BGC were also found in C. borealis and C. macilenta, indicating that these related species also have metabolic potentials to produce cristazarin. Phylogenetic analysis revealed that the Crz7 is sister to fungal PKSs that biosynthesize an acetylated tetrahydoxynaphthalene as a precursor of melanin pigment. Based on the phylogenetic placement of the Crz7 and putative functions of its neighboring genes, we proposed a plausible biosynthetic route for cristazarin. In this study, we identified a lichen-specific BGC that is likely involved in the biosynthesis of a naphthazarin derivative, cristazarin, and confirmed that transcriptome profiling under inducing and non-inducing conditions is an effective strategy for linking metabolites of interest to biosynthetic genes.

Profile of Human Milk Phospholipids at Different Lactation Stages with UPLC/Q-TOF-MS: Characterization, Distribution, and Differences

Human milk phospholipids are important for the regular growth and development of infants. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS) was employed to qualitatively and quantitatively analyze 277 phospholipid molecular species in 112 human milk samples to obtain a detailed profile of human milk phospholipids along the lactation stage. MS/MS fragmentation patterns of sphingomyelin, phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, and phosphatidylserine were characterized in detail. Phosphatidylcholine is the most dominant group, followed by sphingomyelin. PC(18:0/18:2), SM(d18:1/24:1), PE(18:0/18:0), PS(18:0/20:4), and PI(18:0/18:2) showed the highest average concentration among all of the phosphatidylcholine, sphingomyelin, phosphatidylethanolamine, phosphatidylserine, and phosphatidylinositol molecular species, respectively. The fatty acids attached to the phospholipid molecules were mainly palmitic, stearic, oleic, and linoleic acids, and the plasmalogens decreased along the lactation stage. The increase of sphingomyelins and phosphatidylethanolamines and the decrease of phosphatidylcholines are the key changes from colostrum to transitional milk; the increase of lysophosphatidylcholines and lysophosphatidylethanolamines and the continuous decrease of phosphatidylcholines are the vital changes from transitional milk to mature milk.

Metabolomics- and systems-biology-guided discovery of metabolite lead compounds and druggable targets

Metabolomics enables the comprehensive and unbiased analysis of metabolites and lipids in biological systems. In conjunction with high-throughput activity screening, big data and synthetic biology, metabolomics can guide the discovery of lead compounds with pharmacological activity from natural sources and the gut microbiome. In combination with other omics, metabolomics can further unlock the elucidation of compound toxicity, the mode of action and novel druggable targets of disease. Here, we discuss the workflows, limitations and future opportunities to leverage metabolomics and big data in conjunction with systems and synthetic biology for streamlining the discovery and development of molecules of pharmaceutical interest.

Linking Lichen Metabolites to Genes: Emerging Concepts and Lessons from Molecular Biology and Metagenomics

Lichen secondary metabolites have tremendous pharmaceutical and industrial potential. Although more than 1000 metabolites have been reported from lichens, less than 10 have been linked to the genes coding them. The current biosynthetic research focuses strongly on linking molecules to genes as this is fundamental to adapting the molecule for industrial application. Metagenomic-based gene discovery, which bypasses the challenges associated with culturing an organism, is a promising way forward to link secondary metabolites to genes in non-model, difficult-to-culture organisms. This approach is based on the amalgamation of the knowledge of the evolutionary relationships of the biosynthetic genes, the structure of the target molecule, and the biosynthetic machinery required for its synthesis. So far, metagenomic-based gene discovery is the predominant approach by which lichen metabolites have been linked to their genes. Although the structures of most of the lichen secondary metabolites are well-documented, a comprehensive review of the metabolites linked to their genes, strategies implemented to establish this link, and crucial takeaways from these studies is not available. In this review, I address the following knowledge gaps and, additionally, provide critical insights into the results of these studies, elaborating on the direct and serendipitous lessons that we have learned from them.

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

Discovery of potential hypoglycemic metabolites in Cassiae Semen by coupling UHPLC-QTOF-MS/MS combined plant metabolomics and spectrum-effect relationship analyses

Cassiae Semen (CS) is consumed as fried tea or medicinal food in Asian areas. Its two commercial forms, namely raw and fried CS, exert different clinical applications, in which fried CS is commonly applied as a functional tea for losing weight. To prevent confusion in the use of the two forms of CS, a comprehensive strategy by combining plant metabolomics and spectrum-effect relationship analyses was developed for the fast and efficient discrimination of raw and fried CS, and further for the discovery of the potential hypoglycemic metabolites of CS to control its quality. First, the plant metabolic profiling of raw and processed samples was performed by UHPLC-QTOF-MS/MS. A total of 1111 differential metabolites were found to well distinguish the raw and fried CS after analyzing by MPP software. Subsequently, α-glucosidase inhibition of raw and fried CS was investigated. As a result, fried CS demonstrated much stronger α-glucosidase inhibition activity than the raw sample. By analyzing the spectrum-effect relationship with GRA, BCA, and PLSR, 14 potential hypoglycemic-related compounds were discovered. As anticipated, they were also found as the differential metabolites of the raw and fried samples with a potential hypoglycemic effect, which might be beneficial for the quality control of CS tea. Additionally, molecular docking analysis was conducted to reveal the underlying inhibition mechanisms of the four most critical constituents, including physcion, chrysoobtusin, aurantio-obtusin, and obtusifolin. This study provides a powerful tool for the discrimination of processed samples and fast screening of the active constituents in complex natural products on a high-throughput basis.

Metabolomic Analysis Reveals that SPHK1 Promotes Oral Squamous Cell Carcinoma Progression through NF-κB Activation

BACKGROUND

Metabolic disorders are significant in the occurrence and development of malignant tumors. Changes of specific metabolites and metabolic pathways are molecular therapeutic targets. This study aims to determine the metabolic differences between oral squamous cell carcinoma (OSCC) tissues and paired adjacent noncancerous tissues (ANT) through liquid chromatography-mass spectrometry (LC-MS). SPHK1 is a key enzyme in sphingolipid metabolism. This study also investigates the potential role of SPHK1 in OSCC.

MATERIALS AND METHODS

This study used LC-MS to analyze metabolic differences between OSCC tissues and paired ANT. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied to explain the significance of phospholipid metabolism pathways in the occurrence and development of OSCC. Through further experiments, we confirmed the oncogenic phenotypes of SPHK1 in vitro and in vivo, including proliferation, migration, and invasion.

RESULTS

The sphingolipid metabolic pathway was significantly activated in OSCC, and the key enzyme SPHK1 was significantly upregulated in oral cancer tissues, predicting poor OSCC prognosis. In this study, SPHK1 overexpression was associated with high-grade malignancy and poor OSCC prognosis. SPHK1 targeted NF-κB by facilitating p65 expression to regulate OSCC tumor progression and promote metastasis.

CONCLUSIONS

This study identified metabolic differences between OSCC and paired ANT, explored the carcinogenic role of overexpressed SPHK1, and revealed the association of SPHK1 with poor OSCC prognosis. SPHK1 targets NF-κB signaling by facilitating p65 expression to regulate tumor progression and promote tumor metastasis, providing potential therapeutic targets for diagnosing and treating oral tumors.

Host and microbial-derived metabolites for Clostridioides difficile infection: Contributions, mechanisms and potential applications

Clostridioides difficile infection (CDI), which mostly occurs in hospitalized patients, is the most common and costly health care-associated disease. However, the biology of C. difficile remains incompletely understood. Current therapeutics are still challenged by the frequent recurrence of CDI. Advances in metabolomics facilitate our understanding of the etiology of CDI, which is not merely an alteration in the structure of the gut microbial community but also a dysbiosis metabolic setting promoting the germination, expansion and virulence of C. difficile. Therefore, we summarized the gut microbial and metabolic profiles for CDI under different conditions, such as those of postantibiotic treatment and postfecal microbiota transplantation. The current understanding of the role of host and gut microbial-derived metabolites as well as other nutrients in preventing or alleviating the disease symptoms of CDI will also be provided in this review. We hope that a specific nutrient-centric dietary strategy or the administration of certain nutrients to the colon could serve as an alternate line of investigation for the prophylaxis and mitigation of CDI in the future. Nevertheless, rigorously designed basic studies and randomized controlled trials need to be conducted to assess the functional mechanisms and effects of such therapeutics.

Subchronic Graphene Exposure Reshapes Skin Cell Metabolism

In recent years, the toxicity of graphene-related materials (GRMs) has been evaluated in diverse models to guarantee their safety. In most applications, sublethal doses of GRMs contact human barriers such as skin in a subchronic way. Herein, the subchronic effect (30 day exposure) of three GRMs (GO 1, GO 2, and FLG) with different oxidation degrees and sizes was studied. The effects of these materials on human skin cells, HaCaTs, were assayed through high-throughput metabolic-based readout and other cell-based assays. A differential effect was found between the different GRMs. GO 2 induced a metabolic remodeling in epithelial cells, increasing the level of tricarboxylic acid components, mirrored by increased cell proliferation and changes in cell phenotype. The oxidation degree, size, and method of manufacture of GRMs dictated harmful effects on cell metabolism and behavior generated by nontoxic exposures. Therefore, a “safe by design” procedure is necessary when working with these nanomaterials.

Origin, evolution, breeding, and omics of Apiaceae: a family of vegetables and medicinal plants

Many of the world's most important vegetables and medicinal crops, including carrot, celery, coriander, fennel, and cumin, belong to the Apiaceae family. In this review, we summarize the complex origins of Apiaceae and the current state of research on the family, including traditional and molecular breeding practices, bioactive compounds, medicinal applications, nanotechnology, and omics research. Numerous molecular markers, regulatory factors, and functional genes have been discovered, studied, and applied to improve vegetable and medicinal crops in Apiaceae. In addition, current trends in Apiaceae application and research are also briefly described, including mining new functional genes and metabolites using omics research, identifying new genetic variants associated with important agronomic traits by population genetics analysis and GWAS, applying genetic transformation, the CRISPR-Cas9 gene editing system, and nanotechnology. This review provides a reference for basic and applied research on Apiaceae vegetable and medicinal plants.

[Lipid metabolomic analysis in exosomes of osteonecrosis of the femoral head based on ultra performance liquid chromatography-tandem mass spectrometry]

Osteonecrosis of the femoral head (ONFH) can lead to its collapse which requires total hip arthroplasty. Exosomes, which are important for intercellular communication are involved in a series of physiological and pathological processes, and therefore play a unique role in disease diagnosis and treatment. In this study, untargeted metabolomics was used to investigate the metabolic characteristics of lipids in exosomes of femoral head tissue with osteonecrosis and to explain the metabolic changes that occur in the body during this disease. Ultracentrifugation was used to separate and enrich exosomes from femoral head tissue with osteonecrosis. Exosomes were identified using dynamic light scattering (DLS), Western blotting, and transmission electron microscopy (TEM). Gradient elution was performed with ultrapure water and acetonitrile as mobile phases using a Kinetex XB-C18 column (100 mm×2.1 mm, 2.6 μm). The column oven temperature, flow rate of the mobile phase, and duration were 30 ℃, 300 μL/min, and 15 min, respectively. A triple TOF 4600 high resolution mass spectrometry system was used, and the mass scan range of m/z was set at 100 -1000. Other conditions were as follows: sheath gas, 380 kPa; auxiliary gas, 380 kPa; curtain gas, 170 kPa; and atomization temperature, 600 ℃. Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with multivariate statistical analysis was used to identify the lipid metabolic profile of ONFH-derived exosomes. The exosome metabolites were characterized in detail, which enables their identification and provided a reliable method for quality evaluation. After transforming the obtained original data using MarkView software, peak identification, peak alignment, subtraction of solvent peak, impurity peak, noise filtering, and other treatments, a three-dimensional matrix was obtained from the exported data table. Principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) in the SIMCA-P14.1 software were used for multivariate statistical analysis of differentially expressed exosome lipid metabolites. This strategy was validated using lipid metabolites from patients with ONFH and healthy controls. The correlation distribution was shown according to the point dispersion of the PCA score plot, and lipid metabolites from the same disease showed ideal clustering. This result indicates a small difference between the groups. A good clustering effect is also obtained using OPLS-DA, and the statistical model has high reliability. A total of 18 significantly altered lipid metabolites were detected in the exosomes, including acrylolipids, fatty acid esters, glycerides, and their derivatives. The pathway analysis was conducted with MetaboAnalyst (https://www.metaboanalyst.ca/) via database source including the HMDB (http://www.hmdb.ca/) and MMCD (http://mmcd.nmrfam.wisc.edu/) for confirming the impacted metabolic pathways and visualization. Metabolic pathway analysis showed that glycerophospholipid and sphingolipid metabolism were the most significantly altered in exosomes. An imbalance between sphingolipids and glycerophospholipids leads to lipotoxic damage, which is implicated in the pathophysiology of common metabolic diseases. Furthermore, glycerophospholipids are correlated with cell proliferation, differentiation, and apoptosis, and the change in glycerophospholipid ratio can reflect the disturbance in lipid metabolism. The metabolic changes in exosomes may reflect the metabolic changes in ONFH. In this study, lipid metabolomics analysis based on UPLC-MS/MS was used to determine metabolic differences between exosomes extracted from ONFN and femoral neck fracture (FNF). Metabolomic analysis of necrotic femoral head tissue-derived exosomes can help explore the most relevant pathways for assessing the changes in exosome metabolism that affect exosome metabolism in necrotic bone tissue.

Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics

Metabolite profiling of cancer cells presents many opportunities for anticancer drug discovery. The Chinese, Indian, and African flora, in particular, offers a diverse source of anticancer therapeutics as documented in traditional folklores. In-depth scientific information relating to mechanisms of action, quality control, and safety profile will promote their extensive usage in cancer therapy. Metabolomics may be a more holistic strategy to gain valuable insights into the anticancer mechanisms of action of plants but this has remained largely unexplored. This review, therefore, presents the available metabolomics studies on the anticancer effects of herbal medicines commonly used in Africa and Asia. In addition, we present some scientifically understudied ‘candidate plants’ for cancer metabolomics studies and highlight the relevance of metabolomics in addressing other challenges facing the drug development of anticancer herbs. Finally, we discussed the challenges of using metabolomics to uncover the underlying mechanisms of potential anticancer herbs and the progress made in this regard.

Single-Cell Multiomics Analysis for Drug Discovery

Given the heterogeneity seen in cell populations within biological systems, analysis of single cells is necessary for studying mechanisms that cannot be identified on a bulk population level. There are significant variations in the biological and physiological function of cell populations due to the functional differences within, as well as between, single species as a result of the specific proteome, transcriptome, and metabolome that are unique to each individual cell. Single-cell analysis proves crucial in providing a comprehensive understanding of the biological and physiological properties underlying human health and disease. Omics technologies can help to examine proteins (proteomics), RNA molecules (transcriptomics), and the chemical processes involving metabolites (metabolomics) in cells, in addition to genomes. In this review, we discuss the value of multiomics in drug discovery and the importance of single-cell multiomics measurements. We will provide examples of the benefits of applying single-cell omics technologies in drug discovery and development. Moreover, we intend to show how multiomics offers the opportunity to understand the detailed events which produce or prevent disease, and ways in which the separate omics disciplines complement each other to build a broader, deeper knowledge base.

Chromatographic methods coupled to mass spectrometry for the determination of oncometabolites in biological samples-A review

It is now well-established that dysregulation of the tricarboxylic acid (TCA) cycle enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase leads to the abnormal cellular accumulation of succinate, fumarate, and 2-hydroxyglutarate, respectively, which contribute to the formation and malignant progression of numerous types of cancers. Thus, these metabolites, called oncometabolites, could potentially be useful as tumour-specific biomarkers and as therapeutic targets. For this reason, the development of analytical methodologies for the accurate identification and determination of their levels in biological matrices is an important task in the field of cancer research. Currently, hyphenated gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) techniques are the most powerful analytical tools in what concerns high sensitivity and selectivity to achieve such difficult task. In this review, we first provide a brief description of the biological formation of oncometabolites and their oncogenic properties, and then we present an overview and critical assessment of the GC-MS and LC-MS based analytical approaches that are reported in the literature for the determination of oncometabolites in biological samples, such as biofluids, cells, and tissues. Advantages and drawbacks of these approaches will be comparatively discussed. We believe that the present review represents the first attempt to summarize the applications of these hyphenated techniques in the context of oncometabolite analysis, which may be useful to new and existing researchers in this field.

Cleavage rules of mass spectrometry fragments and rapid identification of chemical components of Radix Paeoniae Alba using UHPLC-Q-TOF-MS

INTRODUCTION

Radix Paeoniae Alba (RPA) presents several pharmacological effects, including analgesia, liver protection, and toxicity reduction. RPA consists mostly of monoterpenes and their glycosides, tannins, flavonoids, and organic acids, with monoterpenes being the main active pharmaceutical ingredients.

OBJECTIVE

To establish an effective method for rapid classification and identification of the main monoterpenes, flavonoids, and organic acids in RPA.

METHODS

We used ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) and data post-processing technology to rapidly classify and identify the monoterpenoids, flavonoids, and organic acids in RPA. We also summarised the diagnostic product ions and neutral losses of monoterpenoids, flavonoids, and organic acids in RPA reported in the literature.

RESULTS

We identified 24 components, namely 18 monoterpenoids, one flavonoid, and five organic acids.

CONCLUSION

In this study, we analysed the chemically active pharmaceutical ingredients and assessed the quality of RPA. In addition, we demonstrated that UHPLC-Q-TOF-MS can be used to qualitatively classify and identify the variety of chemical components of traditional Chinese medicines (TCMs) to a certain extent. Moreover, we confirmed that mass spectrometry can be used to identify the components of TCMs.

Development of a UPLC-MS/MS method for the determination of narciclasine and 7-deoxynarciclasine in mouse blood and its application in pharmacokinetics

In this study, we used ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to measure the concentration of narciclasine and 7-deoxynarciclasine in mouse blood after intravenous (i.v.) and oral administration (p.o.), and we used this method to investigate their pharmacokinetics profiles in mice. Chromatographic separation of the analytes was achieved using a UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 μm) with a mobile phase consisting of acetonitrile-water (0.1% formic acid) by gradient elution. Electrospray ionization (ESI positive-ion mode)-tandem mass spectrometry in multiple reaction monitoring (MRM) mode was employed for quantitative analysis of the analytes in mouse blood samples. Twelve mice were administered narciclasine and 7-deoxynarciclasine (2 mg/kg) intravenously (iv), while the other twelve mice were administered narciclasine and 7-deoxynarciclasine (10 mg/kg) orally. The mouse blood was withdrawn from the caudal vein to be processed, after which the blood was analyzed by UPLC-MS/MS, and the corresponding data were fitted using the Drug and Statistics (DAS) software. Standard curves of narciclasine and 7-deoxynarciclasine were generated over the concentration range of 5-5000 ng/mL. The intra-day accuracy of narciclasine and 7-deoxynarciclasine was 90-105%, and the corresponding inter-day accuracy was 87-108%. The intra-day precision was less than 13%, while the inter-day precision was less than 14%. Matrix effects were also observed (between 94% and 104%), and the recovery calculated was higher than 70%. The developed and validated UPLC-MS/MS method was then successfully applied in determining the mouse pharmacokinetics of narciclasine and 7-deoxynarciclasine. From this, thebioavailabilityofnarciclasine and 7-deoxynarciclasinewasdetermined to be 10.3%and35.4%, respectively.

Urinary metabolomics analysis of the protective effects of Daming capsule on hyperlipidemia rats using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry

Hyperlipidemia is recognized as one of the most important risk factors for morbidity and mortality due to cardiovascular diseases. Daming capsule, a Chinese patent medicine, has shown definitive efficacy in patients with hyperlipidemia. In this study, serum biochemistry and histopathology assessment were used to investigate the lipid-lowering effect of Daming capsule. Furthermore, urinary metabolomics based on ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry was conducted to identify the urinary biomarkers associated with hyperlipidemia and discover the underlying mechanisms of the antihyperlipidemic action of Daming capsule. After 10 weeks of treatment, Daming capsule significantly lowered serum lipid levels and ameliorated hepatic steatosis induced by a high-fat diet. A total of 33 potential biomarkers associated with hyperlipidemia were identified, among which 26 were robustly restored to normal levels after administration of Daming capsule. Pathway analysis revealed that the lipid-lowering effect of Daming capsule is related to the regulation of multiple metabolic pathways including vitamin B and amino acid metabolism, tricarboxylic acid cycle, and pentose phosphate pathway. Notably, the study demonstrates that metabolomics is a powerful tool to elucidate the multitarget mechanism of traditional Chinese medicines, thereby promoting their research and development.

Metabolomic Laboratory-Developed Tests: Current Status and Perspectives

Laboratory-developed tests (LDTs) are a subset of in vitro diagnostic devices, which the US Food and Drug Administration defines as "tests that are manufactured by and used within a single laboratory". The review describes the emergence and history of LDTs. The current state and development prospects of LDTs based on metabolomics are analyzed. By comparing LDTs with the scientific metabolomics study of human bio samples, the characteristic features of metabolomic LDT are shown, revealing its essence, strengths, and limitations. The possibilities for further developments and scaling of metabolomic LDTs and their potential significance for healthcare are discussed. The legal aspects of LDT regulation in the United States, European Union, and Singapore, demonstrating different approaches to this issue, are also provided. Based on the data presented in the review, recommendations were made on the feasibility and ways of further introducing metabolomic LDTs into practice.

Analysis of serum metabolome of workers occupationally exposed to hexavalent chromium: A preliminary study

Hexavalent chromium (Cr(VI)) compound is considered as a common environmental and occupational pollutant due to widespread application in industry and agriculture. Cr(VI) as a carcinogen poses a serious threat to human health and the underlying mechanisms need further investigation. Previous studies had demonstrated the characteristic expression profiling after Cr(VI) treatment in vitro and in vivo at the levels of gene and protein. The comprehensive metabolic signatures were also conducive to discover potential biomarkers for effects assessment of Cr(VI) toxicity. In the current study, Ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) non-targeted metabolomics was applied to analyze serum metabolic changes in 77 chromate exposure workers and 62 controls. Thirteen metabolites were found significantly decreased and 41 metabolites were increased, which were involved in arginine and proline metabolism, and glycerophospholipid metabolism by bioinformatic analysis. Furthermore, there were significant negative correlations between blood Cr level and Arginine, PC(18:2/24:4) and PC(14:0/16:0), subgroup analyses indicated that these correlations were observed in male-only subgroups, and were not found among chromate workers and controls separately. Diet could be a potential confounder which was not controlled rigorously in this study. These findings provided preliminary clues to investigate the underlying mechanisms of Cr(VI)-induced toxicity and were required to be further verified in future researches.

Mass spectrometry-based metabolomics diagnostics - myth or reality?

ABSTACTIntroduction: Metabolomics, one of the most high-promising technologies, is the most recently developed post-genomics discipline for developing new diagnostic tests for future implementation in medicine. More than 2,000 scientific papers, using mass spectrometry-based (MS-based) metabolomics analysis for human disease diagnostics, have been published during the past two decades, and almost every metabolomics study shows high diagnostic accuracy. However, despite the great results and promising perspectives, there are currently no diagnostic tests based on metabolomics that have been approved and introduced into clinics.Areas covered: In this report, the advantages and challenges of MS-based metabolomics are discussed with a focus on its developing role in diagnostics, and the current trends in implementing metabolomics diagnostics in the clinic.Expert opinion: In the development of new clinical diagnostics tests, MS-based metabolomics has potential as both a preliminary discovery base for routine testing and a multi-test prototype, which is hoped to be introduced into clinical practice in the near future. A laboratory-developed test (LDT) is one possible way that multi-testing could be developed.

Metabolomics study of cerebrospinal fluid from diabetic rats with cognitive impairment simultaneously treated with Panax quinquefolius and Acorus gramineus

A metabolomics approach was used to explore the effects of Panax quinquefolius (PQ) and Acorus gramineus (AG) on learning and memory in rats with diabetic-induced cognitive impairment. Thirty Wistar rats were divided into three groups, namely, the normal group, model group, and PQ-AG group (PQ-AG group, 1.80 g/kg/d). Diabetes was induced by intraperitoneal injection of streptozotocin (65 mg/kg). Cerebrospinal fluid (CSF) was collected via cisterna magna puncture, and the Morris water maze method was used to evaluate learning and memory in rats after 11 weeks of PQ-AG treatment. Metabolic profiling of CSF samples was performed by using UPLC-Q-TOF-MS. Compared with the normal group, the escape latency of the Morris water maze was significantly prolonged in model group rats after 12 weeks (p < 0.01). Compared with the model group, however, the escape latency was significantly shortened in PQ-AG group rats (p < 0.05). In multivariate statistical analysis, we identified 33 potential biomarkers, and six biomarkers were altered by PQ-AG. These biomarkers were involved in the metabolism of pyrimidine; nicotinate, and nicotinamide; glycine, serine, and threonine; and ascorbate and aldarate. Taken collectively, our results indicate that PQ-AG can attenuate diabetic-induced cognitive impairment by affecting a variety of metabolic pathways. Our results provide an experimental basis for studying the mechanism of action of PQ-AG.

Capillary ultrahigh-pressure liquid chromatography-mass spectrometry for fast and high resolution metabolomics separations

LC-MS is an important tool for metabolomics due its high sensitivity and broad metabolite coverage. The goal of improving resolution and decreasing analysis time in HPLC has led to the use of 5 - 15 cm long columns packed with 1.7 - 1.9 µm particles requiring pressures of 8 - 12 kpsi. We report on the potential for capillary LC-MS based metabolomics utilizing porous C18 particles down to 1.1 µm diameter and columns up to 50 cm long with an operating pressure of 35 kpsi. Our experiments show that it is possible to pack columns with 1.1 µm porous particles to provide predicted improvements in separation time and efficiency. Using kinetic plots to guide the choice of column length and particle size, we packed 50 cm long columns with 1.7 µm particles and 20 cm long columns with 1.1 µm particles, which should produce equivalent performance in shorter times. Columns were tested by performing isocratic and gradient LC-MS analyses of small molecule metabolites and extracts from plasma. These columns provided approximately 100,000 theoretical plates for metabolite standards and peak capacities over 500 in 100 min for a complex plasma extract with robust interfacing to MS. To generate a given peak capacity, the 1.1 µm particles in 20 cm columns required roughly 75% of the time as 1.7 µm particles in 50 cm columns with both operated at 35 kpsi. The 1.1 µm particle packed columns generated a given peak capacity nearly 3 times faster than 1.7 µm particles in 15 cm columns operated at ~10 kpsi. This latter condition represents commercial state of the art for capillary LC. To consider practical benefits for metabolomics, the effect of different LC-MS variables on mass spectral feature detection was evaluated. Lower flow rates (down to 700 nL/min) and larger injection volumes (up to 1 µL) increased the features detected with modest loss in separation performance. The results demonstrate the potential for fast and high resolution separations for metabolomics using 1.1 µm particles operated at 35 kpsi for capillary LC-MS.

Application of Metabolomics in Diagnosis and Treatment of Chronic Liver Diseases

Chronic liver disease represents stepwise destruction of the liver parenchyma after chronic liver injury, which is often difficult to be diagnosed accurately. Thus, the development of specific biomarkers of chronic liver disease is important. Metabolomics is a powerful tool for biomarker exploration, which enables the exploration of disease pathogenesis or drug action mechanisms at the global metabolic level. The metabolomics workflow generally includes collection, preparation, and analysis of samples, and data processing and bioinformatics. A metabolomics study can simultaneously detect the dysfunctions in the glucose, lipid, amino-acid, and nucleotide metabolisms. Hence, it facilitates the obtaining of a better understanding of the pathogenesis of chronic liver disease and its diagnosis. Many effective drugs could reverse the change of comprehensive biochemical phenotypes induced by chronic liver disease. They can even potentially restore the normal metabolic signatures of patients. Increasingly more researchers have begun to apply metabolomics technologies to diagnose chronic liver disease and investigate the mechanism of action of effective drugs or the variations in drug responses. We are convinced that deepening the understanding of the metabolic alterations could extend their use as powerful biomarkers, promoting the more effective clinical diagnosis and treatment of chronic liver disease in the future.

Alterations of Gut Microbiome and Metabolite Profiling in Mice Infected by Schistosoma japonicum

Schistosoma japonicum (S. japonicum) is one of the etiological agents of schistosomiasis, a widespread zoonotic parasitic disease. However, the mechanism of the balanced co-existence between the host immune system and S. japonicum as well as their complex interaction remains unclear. In this study, 16S rRNA gene sequencing, combined with metagenomic sequencing approach as well as ultraperformance liquid chromatography–mass spectrometry metabolic profiling, was applied to demonstrate changes in the gut microbiome community structure during schistosomiasis progression, the functional interactions between the gut bacteria and S. japonicum infection in BALB/c mice, and the dynamic metabolite changes of the host. The results showed that both gut microbiome and the metabolites were significantly altered at different time points after the infection. Decrease in richness and diversity as well as differed composition of the gut microbiota was observed in the infected status when compared with the uninfected status. At the phylum level, the gut microbial communities in all samples were dominated by Firmicutes, Bacteroidetes, Proteobacteria, and Deferribacteres, while at the genus level, Lactobacillus, Lachnospiraceae NK4A136 group, Bacteroides, Staphylococcus, and Alloprevotella were the most abundant. After exposure, Roseburia, and Ruminococcaceae UCG-014 decreased, while Staphylococcus, Alistipes, and Parabacteroides increased, which could raise the risk of infections. Furthermore, LEfSe demonstrated several bacterial taxa that could discriminate between each time point of S. japonicum infection. Besides that, metagenomic analysis illuminated that the AMP-activated protein kinase (AMPK) signaling pathway and the chemokine signaling pathway were significantly perturbed after the infection. Phosphatidylcholine and colfosceril palmitate in serum as well as xanthurenic acid, naphthalenesulfonic acid, and pimelylcarnitine in urine might be metabolic biomarkers due to their promising diagnostic potential at the early stage of the infection. Alterations of glycerophospholipid and purine metabolism were also discovered in the infection. The present study might provide further understanding of the mechanisms during schistosome infection in aspects of gut microbiome and metabolites, and facilitate the discovery of new targets for early diagnosis and prognostic purposes. Further validations of potential biomarkers in human populations are necessary, and the exploration of interactions among S. japonicum, gut microbiome, and metabolites is to be deepened in the future.

Non-targeted metabolomics of quinoa seed filling period based on liquid chromatography-mass spectrometry

Quinoa (Chenopodium quinoa Willd.), an herb belonging to the amaranth family, is rich in minerals, amino acids, vitamins, proteins, and flavonoids. Its grain, compared with other major grains, has unique nutritional value with tremendous applications. This study used four independently bred high-generation lines (seed colors) of quinoa as materials to further understand the metabolic differences in the filling periods of quinoa varieties. Additionally, the non-targeted metabolome of quinoa seeds 35 and 42 days after flowering, respectively, were studied via liquid chromatography-mass spectrometry. The two filling periods of yellow, white, black, and red quinoa grains resulted in significant differences in the metabolites, particularly in L-methionine, S-adenosyl-L-homocysteine, S-adenosyl-L-methionine, pyruvate, fumarate, and oxaloacetate. Soluble sugar, amino acid, and fatty acid contents in quinoa increased after 42 days of flowering. There were metabolic differences between the sugar phosphates (L-fucose, D-mannose-6-phosphate, xylulose-5-phosphate, sedoheptulose-7-phosphate), amino acid (alanine), and organic compounds (kynurenate, tryptamine, serotonin, bilirubin) among the four quinoa varieties. The relative difference in the metabolites was largest when the yellow quinoa grain was compared with the other quinoa varieties and smallest when the red and black varieties were compare. The results of this study provide a basis for the reproduction and identification of new quinoa varieties, as well as for screening potential quality control target genes by combining genomics and transcriptomics.

Precision Medicine: Steps along the Road to Combat Human Cancer

The diagnosis and treatment of diseases such as cancer is becoming more accurate and specialized with the advent of precision medicine techniques, research and treatments. Reaching down to the cellular and even sub-cellular level, diagnostic tests can pinpoint specific, individual information from each patient, and guide providers to a more accurate plan of treatment. With this advanced knowledge, researchers and providers can better gauge the effectiveness of drugs, radiation, and other therapies, which is bound to lead to a more accurate, if not more positive, prognosis. As precision medicine becomes more established, new techniques, equipment, materials and testing methods will be required. Herein, we will examine the recent innovations in assays, devices and software, along with next generation sequencing in genomics diagnostics which are in use or are being developed for personalized medicine. So as to avoid duplication and produce the fullest possible benefit, all involved must be strongly encouraged to collaborate, across national borders, public and private sectors, science, medicine and academia alike. In this paper we will offer recommendations for tools, research and development, along with ideas for implementation. We plan to begin with discussion of the lessons learned to date, and the current research on pharmacogenomics. Given the steady stream of advances in imaging mass spectrometry and nanoLC-MS/MS, and use of genomic, proteomic and metabolomics biomarkers to distinguish healthy tissue from diseased cells, there is great potential to utilize pharmacogenomics to tailor a drug or drugs to a particular cohort of patients. Such efforts very well may bring increased hope for small groups of non-responders and those who have demonstrated adverse reactions to current treatments.

Analytical techniques for metabolomic studies: a review

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

Cancer metabolomic markers in urine: evidence, techniques and recommendations

Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.

Mass spectrometry-based metabolomics in health and medical science: a systematic review

Metabolomics is the study of the investigation of small molecules derived from cellular and organism metabolism, which reflects the outcomes of the complex network of biochemical reactions in living systems.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.

Experimentally Validating Open Tubular Liquid Chromatography for a Peak Capacity of 2000 in 3 h

The advancements in life science research mandate effective tools capable of analyzing large numbers of samples with low quantities and high complexities. As an essential analytical tool for this research, liquid chromatography (LC) encounters an ever-increasing demand for enhanced resolving power, accelerated analysis speed, and reduced limit of detection. Although theoretical studies have indicated that open tubular (OT) columns can produce superior resolving power under comparable elution pressures and analysis times, ultrahigh-resolution and ultrahigh-speed open tubular liquid chromatography (OTLC) separations have never been reported. Here we present experimental results to demonstrate the predicted potential of this technique. We use a 2 μm i.d. × 75 cm long OT column coated with trimethoxy(octadecyl)silane for separating pepsin/trypsin digested E. coli lysates and routinely produce exceptionally high peak capacities (e.g., 1900-2000 in 3-5 h). We reduce the column length to 2.7 cm and exhibit the capability of OTLC for ultrafast separations. Under an elution pressure of 227.5 bar, we complete the separation of six amino acids in ∼800 ms and resolve these compounds within ∼400 ms. In addition, we show that OTLC has low attomole limits of detection (LOD) and each separation requires samples of only a few picoliters. Importantly, no ultrahigh elution pressures are required. With the ultrahigh resolution, ultrahigh speed, low LOD, and low sample volume requirement, OTLC can potentially be a powerful tool for biotech research, especially single cell analysis.

Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science. Omics techniques provide a more holistic molecular perspective of studied biological systems compared to traditional approaches. However, due to their inherent data differences, integrating multiple omics platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products of multiple interactions between genes, transcripts, and proteins, metabolomics, the tools and approaches routinely used in this field could assist with the integration of these complex multi-omics data sets. The question is, how? Here we provide some answers (in terms of methods, software tools and databases) along with a variety of recommendations and a list of continuing challenges as identified during a peer session on multi-omics integration that was held at the recent 'Australian and New Zealand Metabolomics Conference' (ANZMET 2018) in Auckland, New Zealand (Sept. 2018). We envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies. We also believe that these ideas may allow the full promise of integrated multi-omics research and, ultimately, of systems biology to be realized.

Metabolomics biotechnology, applications, and future trends: a systematic review

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed. Mass spectrometry-based metabolomics has been used in a variety of disease research areas. However, the deep research of metabolites remains a difficult and lengthy process. Fortunately, mass spectrometry is considered to be a universal tool with high specificity and sensitivity and is widely used around the world. Mass spectrometry technology has been applied to various basic disciplines, providing technical support for the discovery and identification of endogenous substances in living organisms. The combination of metabolomics and mass spectrometry is of great significance for the discovery and identification of metabolite biomarkers. The mass spectrometry tool could further improve and develop the exploratory research of the life sciences. This mini review discusses metabolomics biotechnology with a focus on recent applications of metabolomics as a powerful tool to elucidate metabolic disturbances and the related mechanisms of diseases.

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed.

A study of the microbial metabolomics analysis of subsurface wastewater infiltration system

Microbial action in SWIS is one of the main ways to remove contaminants. Studying the metabolic processes and pathways of microorganisms is helpful to reveal the mechanism of pollutant removal in the “black box” process of SWIS. In this study, based on metabolomics and UPLC-MS, partial least squares (PLS-DA), principal component analysis (PCA) pattern recognition and cluster analysis were used to classify the microbial samples. According to the model's variable importance factor (VIP value) being greater than 1.5, a total of 53 potential biomarkers were screened out. There was a significant correlation between the microbial metabolites and soil profile. Most microbial metabolites were concentrated in the H2 layer (subsurface layer of SWIS), while there were relatively few in the H4 and H6 layers (middle and lower layers of SWIS); organic acids and alcohol metabolites mainly existed in the anoxic environment (H4 layer); antibiotics, growth hormones and pigments and other small molecule metabolites mainly existed under anaerobic conditions (H6 layer). The results of RDA analysis indicated that environmental factors had an effect on the microbial metabolites. With the variation of different height profiles, the metabolites were significantly affected by ORP and NO₃⁻, which were negatively correlated. The above conclusions indicated that metabolomics is a reliable, accurate and effective method to quantitatively characterize the stability of SWIS.

Microbial action in SWIS is one of the main ways to remove contaminants.

The metabolomic quest for a biomarker in chronic kidney disease

Chronic kidney disease (CKD) is a growing burden on people and on healthcare for which the diagnostics are niether disease-specific nor indicative of progression. Biomarkers are sought to enable clinicians to offer more appropriate patient-centred treatments, which could come to fruition by using a metabolomics approach. This mini-review highlights the current literature of metabolomics and CKD, and suggests additional factors that need to be considered in this quest for a biomarker, namely the diet and the gut microbiome, for more meaningful advances to be made.

Analyzing protein glycosylation using UHPLC: a review

Ultrahigh performance liquid chromatography (UHPLC) uses small stationary-phase particle size (<2 μm) and high pressure in order to achieve rapid and efficient separations. The speed and high resolution of this method has made it a valuable tool for analyzing the complex glycosylation patterns found in post-translationally modified proteins. This article highlights the differences between UHPLC and HPLC and reviews recent UHPLC applications and developments for detecting glycosylated proteins (e.g., glycomics studies) and characterizing glycosylated pharmaceuticals (e.g., monoclonal antibodies).

Concentration of Lactoferrin in Human Milk and Its Variation during Lactation in Different Chinese Populations

BACKGROUND

Lactoferrin (Lf) is a multifunctional protein and one of the most abundant proteins in human milk. Various factors may affect its concentration in human milk, such as stage of lactation, ethnicity, and diet.

OBJECTIVES

The objectives of the present study were to examine the dynamic change in milk Lf throughout the course of lactation and explore factors associated with milk Lf concentrations in various Chinese populations.

METHODS

This investigation was a part of a large cross-sectional study conducted in 11 provinces/autonomous regions/municipalities (Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Inner Mongolia, Shandong, Shanghai, Xinjiang, Yunnan, and Zhejiang) across China between 2011 and 2013. Lactating women (n = 6481) within 0⁻330 days postpartum were recruited in the original study. A sub-sample of 824 women was randomly selected, and milk Lf concentrations were determined by UPLC/MS.

RESULTS

The Lf concentration in milk from women delivering at term was 3.16 g/L, 1.73 g/L and 0.90 g/L for colostrum, transitional milk, and mature milk, respectively. Lf concentrations differed significantly between stages of lactation (colostrum vs. transitional milk, colostrum vs. mature milk, transitional milk vs. mature milk, all p < 0.001). Maternal BMI, age, mode of delivery, parturition, protein intake, and serum albumin concentration were not correlated with milk Lf concentration. However, milk Lf concentrations varied among different geographical regions (Guangdong (1.91 g/L) vs. Heilongjiang (1.44 g/L), p = 0.037; Guangdong (1.91 g/L) vs. Gansu (1.43 g/L), p = 0.041) and ethnicities (Dai (1.80 g/L) vs. Tibetan (0.99 g/L), p = 0.007; Han (1.62 g/L) vs. Tibetan (0.99 g/L), p = 0.002) in China.

CONCLUSIONS

The concentration of Lf in human milk changes dynamically throughout lactation. Few maternal characteristics affect the milk Lf concentration, but it varies across different geographical regions and ethnicities in China.

Metabolomics-based evidence of the hypoglycemic effect of Ge-Gen-Jiao-Tai-Wan in type 2 diabetic rats via UHPLC-QTOF/MS analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Ge-Gen-Jiao-Tai-Wan (GGJTW) formula, derived from traditional Chinese herbal medicine, is composed of Pueraria montana var. lobata (Willd.) Sanjappa & Pradeep (Ge-Gen in Chinese), Coptis chinensis Franch (Huang-Lian), and Cinnamomum cassia (L.) J. Presl (Rou-Gui). GGJTW is used for treatment of diabetes in China, reflecting the potent hypoglycemic effect of its ingredients. However, little is known of the hypoglycemic effect of GGJTW and the underlying metabolic mechanism.

AIM OF THE STUDY

This study aimed to investigate the hypoglycemic effect of GGJTW in type 2 diabetic rats and the metabolic mechanism of action.

MATERIALS AND METHODS

Ultra high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF/MS)-based metabolomics approach was used for monitoring hyperglycaemia induced by high-sugar high-fat fodder and streptozotocin (STZ), and the protective effect of GGJTW. Dynamic fasting blood glucose (FBG) levels, body weight, and biochemical parameters, including lipid levels, hepatic-renal function, and hepatic histopathology were used to confirm the hyperglycaemic toxicity and attenuation effects. An orthogonal partial least squared-discriminant analysis (OPLS-DA) approach highlighted significant differences in the metabolome of the healthy control, diabetic, and drug-treated rats. The metabolomics pathway analysis (MetPA) and Kyoto encyclopedia of genes and genomes (KEGG) database were used to investigate the underlying metabolic pathways.

RESULTS

Metabolic profiling revealed 37 metabolites as the most potential biomarker metabolites distinguishing GGJTW-treated rats from model rats. Most of the metabolites were primarily associated with bile acid metabolism and lipid metabolism. The most critical pathway was primary bile acid biosynthesis pathway involving the up-regulation of the levels of cholic acid (CA), chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), taurochenodesoxycholic acid (TCDCA), and taurine.

CONCLUSIONS

The significantly-altered metabolite levels indicated the hypoglycemic effect of GGJTW on diabetic rats and the underlying metabolic mechanism. This study will be meaningful for the clinical application of GGJTW and valuable for further exploration of the mechanism.

Application of Metabolomics in Alzheimer's Disease

Progress toward the development of efficacious therapies for Alzheimer’s disease (AD) is halted by a lack of understanding early underlying pathological mechanisms. Systems biology encompasses several techniques including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Metabolomics is the newest omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual’s metabolome reflects alterations in genetic, transcript, and protein profiles and influences from the environment. Advancements in the field of metabolomics have demonstrated the complexity of dynamic changes associated with AD progression underscoring challenges with the development of efficacious therapeutic interventions. Defining systems-level alterations in AD could provide insights into disease mechanisms, reveal sex-specific changes, advance the development of biomarker panels, and aid in monitoring therapeutic efficacy, which should advance individualized medicine. Since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. A summary of recent developments in the application of metabolomics to advance the AD field is provided below.