Metabolomics: an integral technique in systems biology

Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments

Direct-to-Mass Spectrometry and ambient ionization techniques can be used for biochemical fingerprinting in a fast way. Data processing is typically accomplished with vendor-provided software tools. Here, a novel, open-source functionality, entitled Tidy-Direct-to-MS, was developed for data processing of direct-to-MS data sets. It allows for fast and user-friendly processing using different modules for optional sample position detection and separation, mass-to-charge ratio drift detection and correction, consensus spectra calculation, and bracketing across sample positions as well as feature abundance calculation. The tool also provides functionality for the automated comparison of different sets of parameters, thereby assisting the user in the complex task of finding an optimal combination to maximize the total number of detected features while also checking for the detection of user-provided reference features. In addition, Tidy-Direct-to-MS has the capability for data quality review and subsequent data analysis, thereby simplifying the workflow of untargeted ambient MS-based metabolomics studies. Tidy-Direct-to-MS is implemented in the Python programming language as part of the TidyMS library and can thus be easily extended. Capabilities of Tidy-Direct-to-MS are showcased in a data set acquired in a marine metabolomics study reported in MetaboLights (MTBLS1198) using a transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS)-based method.

Dysregulations of amino acid metabolism and lipid metabolism in urine of children and adolescents with major depressive disorder: a case-control study

RATIONALE

The mechanisms underlying major depressive disorder (MDD) in children and adolescents are unclear. Metabolomics has been utilized to capture metabolic signatures of various psychiatric disorders; however, urinary metabolic profile of MDD in children and adolescents has not been studied.

OBJECTIVES

We analyzed urinary metabolites in children and adolescents with MDD to identify potential biomarkers and metabolic signatures.

METHODS

Here, liquid chromatography-mass spectrometry was used to profile metabolites in urine samples from 192 subjects, comprising 80 individuals with antidepressant-naïve MDD (AN-MDD), 37 with antidepressant-treated MDD (AT-MDD) and 75 healthy controls (HC). We performed orthogonal partial least squares discriminant analysis to identify differential metabolites and employed logistic regression and receiver operating characteristic analysis to establish a diagnostic panel.

RESULTS

In total, 143 and 71 differential metabolites were identified in AN-MDD and AT-MDD, respectively. These were primarily linked to lipid metabolism, molecular transport, and small molecule biochemistry. AN-MDD additionally exhibited dysregulated amino acid metabolism. Compared to HC, a diagnostic panel of seven metabolites displayed area under the receiver operating characteristic curves of 0.792 for AN-MDD, 0.828 for AT-MDD, and 0.799 for all MDD. Furthermore, the urinary metabolic profiles of children and adolescents with MDD significantly differed from those of adult MDD.

CONCLUSIONS

Our research suggests dysregulated amino acid metabolism and lipid metabolism in the urine of children and adolescents with MDD, similar to results in plasma metabolomics studies. This contributes to the comprehension of mechanisms underlying children and adolescents with MDD.

PMhub 1.0: a comprehensive plant metabolome database

The Plant Metabolome Hub (PMhub), available at https://pmhub.org.cn, is a valuable resource designed to provide scientists with comprehensive information on plant metabolites. It offers extensive details about their reference spectra, genetic foundations, chemical reactions, metabolic pathways and biological functions. The PMhub contains chemical data for 188 837 plant metabolites gathered from various sources, with 1 467 041 standard/in-silico high-resolution tandem mass-spectrometry (HRMS/MS) spectra corresponding to these metabolites. Beyond its extensive literature-derived data, PMhub also boasts a sizable collection of experimental metabolites; it contains 144 366 detected features in 10 typical plant species, with 16 423 successfully annotated by using standard/in-silico HRMS/MS data, this collection is further supplemented with thousands of features gathered from reference metabolites. For each metabolite, the PMhub enables the reconstructed of a simulated network based on structural similarities and existing metabolic pathways. Unlike previous plant-specific metabolome databases, PMhub not only contains a vast amount of metabolic data but also assembles the corresponding genomic and/or transcriptomic information, incorporating multiple methods for the comprehensive genetic analysis of metabolites. To validate the practicality, we verified a synthetic pathway for N-p-coumaroyltyramine by in vitro enzymatic activity experiments. In summary, the robust functionality provided by the PMhub will make it an indispensable tool for studying plant metabolomics.

Application of Data Fusion in Traditional Chinese Medicine: A Review

Traditional Chinese medicine is characterized by numerous chemical constituents, complex components, and unpredictable interactions among constituents. Therefore, a single analytical technique is usually unable to obtain comprehensive chemical information. Data fusion is an information processing technology that can improve the accuracy of test results by fusing data from multiple devices, which has a broad application prospect by utilizing chemometrics methods, adopting low-level, mid-level, and high-level data fusion techniques, and establishing final classification or prediction models. This paper summarizes the current status of the application of data fusion strategies based on spectroscopy, mass spectrometry, chromatography, and sensor technologies in traditional Chinese medicine (TCM) in light of the latest research progress of data fusion technology at home and abroad. It also gives an outlook on the development of data fusion technology in TCM analysis to provide references for the research and development of TCM.

A multimodal pipeline using NMR spectroscopy and MALDI-TOF mass spectrometry imaging from the same tissue sample

NMR spectroscopy and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) are both commonly used to detect large numbers of metabolites and lipids in metabolomic and lipidomic studies. We have demonstrated a new workflow, highlighting the benefits of both techniques to obtain metabolomic and lipidomic data, which has realized for the first time the combination of these two complementary and powerful technologies. NMR spectroscopy is frequently used to obtain quantitative metabolite information from cells and tissues. Lipid detection is also possible with NMR spectroscopy, with changes being visible across entire classes of molecules. Meanwhile, MALDI MSI provides relative measures of metabolite and lipid concentrations, mapping spatial information of many specific metabolite and lipid molecules across cells or tissues. We have used these two complementary techniques in combination to obtain metabolomic and lipidomic measurements from triple-negative human breast cancer cells and tumor xenograft models. We have emphasized critical experimental procedures that ensured the success of achieving NMR spectroscopy and MALDI MSI in a combined workflow from the same sample. Our data show that several phospholipid metabolite species were differentially distributed in viable and necrotic regions of breast tumor xenografts. This study emphasizes the power of combined NMR spectroscopy-MALDI imaging to advance metabolomic and lipidomic studies.

Plant associated protists-Untapped promising candidates for agrifood tools

The importance of host-associated microorganisms and their biotic interactions for plant health and performance has been increasingly acknowledged. Protists, main predators and regulators of bacteria and fungi, are abundant and ubiquitous eukaryotes in terrestrial ecosystems. Protists are considered to benefit plant health and performance, but the community structure and functions of plant-associated protists remain surprisingly underexplored. Harnessing plant-associated protists and other microbes can potentially enhance plant health and productivity and sustain healthy food and agriculture systems. In this review, we summarize the knowledge of multifunctionality of protists and their interactions with other microbes in plant hosts, and propose a future framework to study plant-associated protists and utilize protists as agrifood tools for benefiting agricultural production.

PANOMICS at the interface of root-soil microbiome and BNI

Nitrification and denitrification are soil biological processes responsible for large nitrogen losses from agricultural soils and generation of the greenhouse gas (GHG) N₂O. Increased use of nitrogen fertilizer and the resulting decline in nitrogen use efficiency (NUE) are a major concern in agroecosystems. This nitrogen cycle in the rhizosphere is influenced by an intimate soil microbiome-root exudate interaction and biological nitrification inhibition (BNI). A PANOMICS approach can dissect these processes. We review breakthroughs in this area, including identification and characterization of root exudates by metabolomics and proteomics, which facilitate better understanding of belowground chemical communications and help identify new biological nitrification inhibitors (BNIs). We also address challenges for advancing the understanding of the role root exudates play in biotic and abiotic stresses.

Antiviral COVID-19 protein and molecular docking: In silico characterization of various antiviral compounds extracted from Arisaema jacquemontii Blume

Arisaema jacquemontii Blume is a highly medicinal and poisonous plant belong to the family Araceae. It is used to treat several deadly diseases, including viral infections. It has antioxidant, anti-cancerous, antimalarial, anti-vermicidal, and antiviral activities. Therefore, five parts of the Arisaema jacquemontii Blume plant, such as leaf, seed, stem, pulp, and rhizome extract, were evaluated for metabolic and in silico characterization of probable compounds using gas chromatography-mass spectrometry (GC-MS) analysis. A total of 22 compounds were isolated from the methanolic extracts of A. jacquemontii Blume. A selected antiviral COVID-19 protein i.e., protease (6LU7) was docked against the obtained compounds. Different affinities were obtained through various compounds. The best results were shown by three different compounds identified in the rhizome. The maximum binding affinity of these compounds is 8.1 kJ/mol. Molecular docking (MD) indicate that these molecules have the highest binding energies and hydrogen bonding interactions. The binding mode of interaction was discovered to be reasonably effective for counteracting the SARS virus COVID-19. The findings of this study could be extremely useful in the development of more phytochemical-based COVID-19 therapeutics.

Advances in Metabolomics-Driven Diagnostic Breeding and Crop Improvement

Climate change continues to threaten global crop output by reducing annual productivity. As a result, global food security is now considered as one of the most important challenges facing humanity. To address this challenge, modern crop breeding approaches are required to create plants that can cope with increased abiotic/biotic stress. Metabolomics is rapidly gaining traction in plant breeding by predicting the metabolic marker for plant performance under a stressful environment and has emerged as a powerful tool for guiding crop improvement. The advent of more sensitive, automated, and high-throughput analytical tools combined with advanced bioinformatics and other omics techniques has laid the foundation to broadly characterize the genetic traits for crop improvement. Progress in metabolomics allows scientists to rapidly map specific metabolites to the genes that encode their metabolic pathways and offer plant scientists an excellent opportunity to fully explore and rationally harness the wealth of metabolites that plants biosynthesize. Here, we outline the current application of advanced metabolomics tools integrated with other OMICS techniques that can be used to: dissect the details of plant genotype–metabolite–phenotype interactions facilitating metabolomics-assisted plant breeding for probing the stress-responsive metabolic markers, explore the hidden metabolic networks associated with abiotic/biotic stress resistance, facilitate screening and selection of climate-smart crops at the metabolite level, and enable accurate risk-assessment and characterization of gene edited/transgenic plants to assist the regulatory process. The basic concept behind metabolic editing is to identify specific genes that govern the crucial metabolic pathways followed by the editing of one or more genes associated with those pathways. Thus, metabolomics provides a superb platform for not only rapid assessment and commercialization of future genome-edited crops, but also for accelerated metabolomics-assisted plant breeding. Furthermore, metabolomics can be a useful tool to expedite the crop research if integrated with speed breeding in future.

Traditional Chinese Medicine Constitution Discrimination Model Based on Metabolomics and Random Forest Decision Tree Algorithm

Constitution refers to the comprehensive and relatively stable characteristics of the genetic or acquired morphological structure, physiological function, and psychological state in the process of human individual life. A special metabolomics data processing method is established to find the unique m/z value of each constitution. Combined with the random forest decision tree algorithm, the discrimination model of 9 constitutions in traditional Chinese medicine is constructed, and the model is verified and tested. The test results show that the classification accuracy of each constitution is higher than 80%, indicating that the model can well identify nine constitutions of traditional Chinese medicine. The classification accuracy is related to the difficulty of distinguishing between constitutions. In a word, this study provides a fast and accurate method to distinguish the constitution of traditional Chinese medicine, provides an objective representation for the classification and judgment of clinical constitution of traditional Chinese medicine, and provides a scientific basis for the modernization of traditional Chinese medicine.

Tuberculous Granuloma: Emerging Insights From Proteomics and Metabolomics

Mycobacterium tuberculosis infection, which claims hundreds of thousands of lives each year, is typically characterized by the formation of tuberculous granulomas — the histopathological hallmark of tuberculosis (TB). Our knowledge of granulomas, which comprise a biologically diverse body of pro- and anti-inflammatory cells from the host immune responses, is based mainly upon examination of lungs, in both human and animal studies, but little on their counterparts from other organs of the TB patient such as the brain. The biological heterogeneity of TB granulomas has led to their diverse, relatively uncoordinated, categorization, which is summarized here. However, there is a pressing need to elucidate more fully the phenotype of the granulomas from infected patients. Newly emerging studies at the protein (proteomics) and metabolite (metabolomics) levels have the potential to achieve this. In this review we summarize the diverse nature of TB granulomas based upon the literature, and amplify these accounts by reporting on the relatively few, emerging proteomics and metabolomics studies on TB granulomas. Metabolites (for example, trimethylamine-oxide) and proteins (such as the peptide PKAp) associated with TB granulomas, and knowledge of their localizations, help us to understand the resultant phenotype. Nevertheless, more multidisciplinary ‘omics studies, especially in human subjects, are required to contribute toward ushering in a new era of understanding of TB granulomas – both at the site of infection, and on a systemic level.

Dimethylcysteine (DiCys)/o-Phthalaldehyde Derivatization for Chiral Metabolite Analyses: Cross-Comparison of Six Chiral Thiols

Metabolomics profiling using liquid chromatography-mass spectrometry (LC-MS) has become an important tool in biomedical research. However, resolving enantiomers still represents a significant challenge in the metabolomics study of complex samples. Here, we introduced N,N-dimethyl-l-cysteine (dimethylcysteine, DiCys), a chiral thiol, for the o-phthalaldehyde (OPA) derivatization of enantiomeric amine metabolites. We took interest in DiCys because of its potential for multiplex isotope-tagged quantification. Here, we characterized the usefulness of DiCys in reversed-phase LC-MS analyses of chiral metabolites, compared against five commonly used chiral thiols: N-acetyl-l-cysteine (NAC); N-acetyl-d-penicillamine (NAP); isobutyryl-l-cysteine (IBLC); N-(tert-butoxycarbonyl)-l-cysteine methyl ester (NBC); and N-(tert-butylthiocarbamoyl)-l-cysteine ethyl ester (BTCC). DiCys and IBLC showed the best overall performance in terms of chiral separation, fluorescence intensity, and ionization efficiency. For chiral separation of amino acids, DiCys/OPA also outperformed Marfey’s reagents: 1-fluoro-2-4-dinitrophenyl-5-l-valine amide (FDVA) and 1-fluoro-2-4-dinitrophenyl-5-l-alanine amide (FDAA). As proof of principle, we compared DiCys and IBLC for detecting chiral metabolites in aqueous extracts of rice. By LC–MS analyses, both methods detected twenty proteinogenic l-amino acids and seven d-amino acids (Ala, Arg, Lys, Phe, Ser, Tyr, and Val), but DiCys showed better analyte separation. We conclude that DiCys/OPA is an excellent amine-derivatization method for enantiomeric metabolite detection in LC-MS analyses.

Urine 5-Eicosatetraenoic Acids as Diagnostic Markers for Obstructive Sleep Apnea

Early detection of obstructive sleep apnea (OSA) is needed to reduce cardiovascular sequelae and mortality. Full-night polysomnography has been used for diagnosing OSA, but it is too expensive and inconvenient for patients to handle. Metabolome-wide analyses were performed to find and validate surrogate markers for OSA. We further investigated the mechanism underlying hypoxic induction of the markers in human cells and mice. Arachidonic acid derivatives 5-HETE and 5-oxoETE were detected in urine samples. The levels (mean ± SD, ng per mg creatinine) of 5-HETE and 5-oxoETE were 56.4 ± 26.2 and 46.9 ± 18.4 in OSA patients, respectively, which were significantly higher than those in controls (22.5 ± 4.6 and 18.7 ± 3.6). Both levels correlated with the apnea-hypopnea index and the lowest oxygen saturation on polysomnography. After the treatment with the continuous positive airway pressure, the metabolite levels were significantly reduced compared with those before the treatment. In human mononuclear cells subjected to intermittent hypoxia, 5-HETE and 5-oxoETE productions were induced by hypoxia-inducible factor 1 and glutathione peroxidase. When mice were exposed to intermittent hypoxia, 5-HETE and 5-oxoETE were excreted more in urine. They were identified and verified as new OSA markers reflecting hypoxic stress. The OSA markers could be used for OSA diagnosis and therapeutic evaluation.

The Efficacy of Pilates on Urinary Incontinence in Korean Women: A Metabolomics Approach

Pilates has been known as exercise intervention that improves the function of pelvic floor muscle (PFM) associated with impacting urinary incontinence (UI). This study investigated the effect of Pilates on UI in Korean women by determining the change in functional movement of PFM (FMP) and metabolic profiles. UI group with Pilates (UIP, n = 13) participated in 8-weeks Oov Pilates program, and 8 subjects were assigned to Control and UI group with no Pilates (UINP), respectively. Before and after 8 weeks, plasma samples were collected from all participants, and ultrasonography was used to measure the functional change of PFM for calculating FMP ratio. Plasma samples were analyzed by mass spectrometry to identify the change of metabolic features. After 8-weeks intervention, FMP ratio was remarkably decreased in UIP (48.1% ↓, p < 0.001), but not in Control and UINP (p > 0.05). In metabolic features, L-Glutamine (m/z: 147.07 [M + H]⁺), L-Cystathionine (m/z: 240.09 [M + NH₄]⁺), L-Arginine (m/z: 197.1 [M + Na]⁺), and L-1-Pyrroline-3-hydroxy-5-carboxylate (m/z: 147.07 [M + NH₄]⁺) were significantly elevated solely in UIP (p < 0.001). Our study elucidated that Pilates can ameliorate the FMP and enhance the specific metabolic characteristics, which was potentially associated with invigorated PFM contractility to effectively control the bladder base and continence.

Applications of Multi-Omics Technologies for Crop Improvement

Multiple "omics" approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the "phenotype to genotype" and "genotype to phenotype" concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Metabolomics in the study of spontaneous animal diseases

Using analytical chemistry techniques such as nuclear magnetic resonance (NMR) spectroscopy and liquid or gas chromatography-mass spectrometry (LC/GC-MS), metabolomics allows detection of most endogenous and exogenous metabolites in a biological sample. Metabolomics has a wide range of applications, and has been employed in nutrition science, toxicology, environmental studies, and systems biology. Metabolomics is particularly useful in biomedical science, and has been used for diagnostic laboratory testing, identifying targets for drug development, and monitoring drug metabolism, mode of action, and toxicity. Despite its immense potential, metabolomics remains underutilized in the study of spontaneous animal diseases. Our aim was to comprehensively review the existing literature on the use of metabolomics in spontaneous veterinary diseases. Three databases were used to find journal articles that applied metabolomics in veterinary medicine. A screening process was then conducted to eliminate references that did not meet the eligibility criteria; only primary research studies investigating spontaneous animal disease were included; 38 studies met the inclusion criteria. The main techniques used were NMR and MS. All studies detected metabolite alterations in diseased animals compared with non-diseased animals. Metabolomics was mainly used to study diseases of the digestive, reproductive, and musculoskeletal systems. Inflammatory conditions made up the largest proportion of studies when articles were categorized by disease process. Following a comprehensive analysis of the literature on metabolomics in spontaneous veterinary diseases, we concluded that metabolomics, although in its early stages in veterinary research, is a promising tool regarding diagnosis, biomarker discovery, and in uncovering new insights into disease pathophysiology.

Study on Urinary Candidate Metabolome for the Early Detection of Breast Cancer

A metabolomic study for determination of certain urinary metabolomes, 1-methyladenosine (1-MA), 1-methylguanosine (1-MG), and 8-hydroxy-2' deoxyguanosine (8-OHdG) in urine specimens of breast cancer patients. The accuracy of these metabolites and their combined score with cancer antigen 15-3 (CA15-3) was developed to improve the early detection of breast cancer. This study recruited 52 healthy individuals, 47 benign breast tumors, and 167 malignant breast tumor patients. Urine samples were handled to adjust the creatinine concentrations to 8 mg/dL (0.7 mmol/L) and analyzed using GC-MS to detect and quantify the selected urinary metabolomes in urine samples of all participants. The accuracy of individual urinary metabolomes and their combination with CA15-3 were evaluated using multivariate statistical analysis. The cutoff value of CA15-3 was 32.5 U/mL. Cutoff values of 1-MA, 1-MG, and 8-OHdG were 2.19, 2.1, and 7.3 µmol/mmol creatinine, respectively. The concentrations of 1-MA, 1-MG, and 8-OHdG were significantly higher in breast cancer patients, especially in the early-stage. The combination of three urinary metabolomes with CA15-3 improves the diagnostic sensitivity of breast cancer. For the combined score, the area under the curve (AUC) value of combined score ranged from 0.820 to 0.950, with high accuracy, ranged from 77.0 to 95.5%. The most significant AUC (0.973), sensitivity (90.1%), selectivity (94.0%) was recorded at comparing the healthy control with the early-stage of malignant breast cancer. In conclusion, the combination of three urinary metabolomes with serum CA15-3 improves the diagnostic sensitivity of breast cancer.

Analysis of Antioxidant Activity and Flavonoids Metabolites in Peel and Flesh of Red-Fleshed Apple Varieties

In this research, we compared the phenotypical characters, total anthocyanins content, total phenols content, and antioxidant activity of red-fleshed apple cultivars ‘XJ4’, ‘QN-5’, ‘DH’ and ‘HX1’ at three fruit developmental stages. A further flavonoids metabolites study was conducted in ‘XJ4’ and ‘DH’. We found broader variation of total anthocyanins content in the peel of the four cultivars, which might result in larger differences of free radicals scavenging rate. The most significant difference in fruit phenotype, anthocyanins content, and DPPH scavenging rate was observed between ‘XJ4’ and ‘DH’ at mature stage. Therefore, the flavonoids metabolites of ‘XJ4’ and ‘DH’ at mature stage were compared to unveil the details of anthocyanins compounds. The unique compounds pelargonidin 3-O-β-d-glucoside and cyanidin-3-O-malonylhexoside were detected only in peel and flesh of ‘XJ4’ but not in ‘DH’, which might contribute to the purple peel and dark-red flesh color of ‘XJ4’. Significantly decreased upstream metabolites in the early biosynthetic genes regulated domain were found only in ‘XJ4’ peel but not in the flesh. This might explain why the anthocyanins content in ‘XJ4’ peel was decreased largely at the mature stage. Taken together, our findings will give some insight into the metabolites study in flavonoid biosynthetic pathway of red-fleshed apple.

Metabolomics analysis of Actinosynnema pretiosum with improved AP-3 production by enhancing UDP-glucose biosynthesis

Ansamitocin P-3 (AP-3) shows strong anticancer effects and has used as a payload for antibody-drug conjugates. Our previous study have shown that although genetically engineered Actinosynnema pretiosum strains with enhanced UDP-glucose (UDPG) biosynthesis displayed improved AP-3 production compared to the wild-type strain, the increase in yield was far from meeting the industrial demand. In this study, comparative metabolomics analysis complemented with quantitative real-time PCR analysis was performed for the wild-type strain and two mutants (OpgmOugp, ΔzwfΔgnd) to identify possible metabolic bottlenecks and non-intuitive targets for further enhancement of AP-3 production. We observed that enhancing intracellular UDPG availability facilitated the accumulation of intracellular N-demethyl-AP-3 and AP-3, where the transporting of them outside the cell still needs to be developed. We also found that the UDPG biosynthesis was closely associated with the availability of fructose in the medium and a suitable fructose feeding strategy could promote the further improvement of AP-3 titer. In addition, pathway abundance analysis revealed that undesired fatty acid accumulation and down-regulation of amino acid metabolism may be unfavorable for ansamitocin biosynthesis in later stage of production. These results indicate that genetic modification of the UDPG biosynthetic pathways may have pleiotropic effects on AP-3 production. Efforts must be made to eliminate these newly identified metabolic bottlenecks to boost AP-3 production in A. pretiosum.

Comparative study of five different amine-derivatization methods for metabolite analyses by liquid chromatography-tandem mass spectrometry

Current metabolomics research utilizes liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses to handle biological samples that contain thousands of quantifiable metabolites. However, no LC-MS/MS condition is suitable for directly analyzing all metabolites. An alternative approach is to derivatize metabolites to impart desirable properties such as better chromatographic separation, enhanced ionization efficiency, or fluorescence detection. An important category of metabolites is amine-containing compounds, which includes amino acids, neurotransmitters, alkaloids, biogenic amines, etc. Various derivatization methods have been developed for amine groups, but few studies have compared their relative strengths and weaknesses. We chose Dansyl-Cl, o-phthalaldehyde (OPA), Fmoc-Cl, Dabsyl-Cl, and Marfey's reagent to systematically compare their reactivity, absorbance, fluorescence, chromatographic separation, and ionization efficiencies under three pH conditions-2.6, 5.0, and 8.0. Their MS/MS fragmentation patterns were also examined under different collision energies. Overall, Dansyl-Cl is a very versatile derivatization method, generating products with fluorescence and high ionization efficiency. Fmoc-Cl is similarly useful under highly acidic chromatography conditions. Dabsyl-Cl may be a good alternative at weakly acidic and weakly basic conditions. OPA is a versatile fluorogenic reagent and its chemistry may be fine-tuned by incorporating different thiol molecules. Marfey's reagent is suboptimal in general, but its chiral property is useful for the separation of enantiomers. All five were applied to the analyses of Coptis chinensis, a Chinese medical herb, identifying hundreds of amine-containing metabolites through MS/MS analyses. None of the five methods is clearly superior, and their compound coverage profiles are rather distinct. A combination of multiple derivatization reagents is required for comprehensive coverage. Our comparative data provide useful guidelines for designing more efficient metabolomics experiments for different analytical goals.

The roles of metabolic pathways in maintaining primary dormancy of Pinus koraiensis seeds

BACKGROUND

Korean pine seeds have primary dormancy following dispersal, leading to poor seed germination and seedling establishment. Metabolic homeostasis determines whether the seeds are dormant or non-dormant. However, the specific metabolic pathways that maintain the primary dormancy of pine seeds are poorly understood.

RESULTS

Metabolic analysis was employed on the embryos of PDRS (seeds released from primary dormancy) and PDS (primary dormant seeds) on days 0, 5 and 11 after incubation under a germination-inductive temperature. A larger metabolic switch occurred in PDRS embryos from days 0 to 11. The contents of ninety metabolites were significantly changed from days 0 to 5, 83% of which (including most sugars, organic acids and amino acids) increased, reflecting that biosynthetic metabolism processes are initiated. The contents of ninety-two metabolites showed distinct variations from days 5 to 11, 71% of which (including most organic acids and almost all amino acids) reduced substantially. Fructose 6-phosphate, inositol-3-phosphate, 3-phosphoglyceric and D-glucose-6-phosphate contents showed the most decrease with decreasing 409-, 75-, 58- and 41-fold, indicating that the glycolysis and tricarboxylic acid (TCA) cycle strongly slowed down. The contents of the most metabolites in PDS embryos also displayed a relatively larger alteration only from days 0 to 5. Although 64% of metabolites increased from days 0 to 5, their levels were still lower compared with PDRS embryos. Furthermore, most metabolites were not further accumulated from days 5 to 11. Unlike PDRS embryos, almost all amino acids in PDS embryos did not exhibit a substantial decrease from days 5 to 11. Also, there was not a major decrease in the levels of metabolites involved mainly in glycolysis and TCA cycle, while some intermediates even increased.

CONCLUSIONS

The attenuated biosynthetic metabolism processes, the lower utilization rate of amino acids and the higher operation rate of glycolysis and TCA in embryos maintain primary dormancy.

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics.

Metabolomics in Plant Stress Physiology

Metabolomics is an essential technology for functional genomics and systems biology. It plays a key role in functional annotation of genes and understanding towards cellular and molecular, biotic and abiotic stress responses. Different analytical techniques are used to extend the coverage of a full metabolome. The commonly used techniques are NMR, CE-MS, LC-MS, and GC-MS. The choice of a suitable technique depends on the speed, sensitivity, and accuracy. This chapter provides insight into plant metabolomic techniques, databases used in the analysis, data mining and processing, compound identification, and limitations in metabolomics. It also describes the workflow of measuring metabolites in plants. Metabolomic studies in plant responses to stress are a key research topic in many laboratories worldwide. We summarize different approaches and provide a generic overview of stress responsive metabolite markers and processes compiled from a broad range of different studies. Graphical Abstract.

Wen-Luo-Tong Decoction Attenuates Paclitaxel-Induced Peripheral Neuropathy by Regulating Linoleic Acid and Glycerophospholipid Metabolism Pathways

Chemotherapy-induced peripheral neuropathy (CIPN) is a serious dose-limiting toxicity of many anti-neoplastic agents, especially paclitaxel, and oxaliplatin. Up to 62% of patients receiving paclitaxel regimens turn out to develop CIPN. Unfortunately, there are so few agents proved effective for prevention or management of CIPN. The reason for the current situation is that the mechanisms of CIPN are still not explicit. Traditional Chinese Medicine (TCM) has unique advantages for dealing with complex diseases. Wen-Luo-Tong (WLT) is a TCM ointment for topical application. It has been applied for prevention and management of CIPN clinically for more than 10 years. Previous animal experiments and clinical studies had manifested the availability of WLT. However, due to the unclear mechanisms of WLT, further transformation has been restricted. To investigate the therapeutic mechanisms of WLT, a metabolomic method on the basis of UPLC- MS was developed in this study. Multivariate analysis techniques, such as principal component analysis (PCA) and partial least squares discriminate analysis (PLS-DA), were applied to observe the disturbance in the metabolic state of the paclitaxel-induced peripheral neuropathy (PIPN) rat model, as well as the recovering tendency of WLT treatment. A total of 19 significant variations associated with PIPN were identified as biomarkers. Results of pathway analysis indicated that the metabolic disturbance of pathways of linoleic acid (LA) metabolism and glycerophospholipid metabolism. WLT attenuated mechanical allodynia and rebalanced the metabolic disturbances of PIPN by primarily regulating LA and glycerophospholipid metabolism pathway. Further molecular docking analysis showed some ingredients of WLT, such as hydroxysafflor yellow A (HSYA), icariin, epimedin B and 4-dihydroxybenzoic acid (DHBA), had high affinity to plenty of proteins within these two pathways.

Unraveling Key Metabolomic Alterations in Wheat Embryos Derived from Freshly Harvested and Water-Imbibed Seeds of Two Wheat Cultivars with Contrasting Dormancy Status

Untimely rains in wheat fields during harvest season can cause pre-harvest sprouting (PHS), which deteriorates the yield and quality of wheat crop. Metabolic homeostasis of the embryo plays a role in seed dormancy, determining the status of the maturing grains either as dormant (PHS-tolerant) or non-dormant (PHS-susceptible). Very little is known for direct measurements of global metabolites in embryonic tissues of dormant and non-dormant wheat seeds. In this study, physiologically matured and freshly harvested wheat seeds of PHS-tolerant (cv. Sukang, dormant) and PHS-susceptible (cv. Baegjoong, non-dormant) cultivars were water-imbibed, and the isolated embryos were subjected to high-throughput, global non-targeted metabolomic profiling. A careful comparison of identified metabolites between Sukang and Baegjoong embryos at 0 and 48 h after imbibition revealed that several key metabolic pathways [such as: lipids, fatty acids, oxalate, hormones, the raffinose family of oligosaccharides (RFOs), and amino acids] and phytochemicals were differentially regulated between dormant and non-dormant varieties. Most of the membrane lipids were highly reduced in Baegjoong compared to Sukang, which indicates that the cell membrane instability in response to imbibition could also be a key factor in non-dormant wheat varieties for their untimely germination. This study revealed that several key marker metabolites (e.g., RFOs: glucose, fructose, maltose, and verbascose), were highly expressed in Baegjoong after imbibition. Furthermore, the data showed that the key secondary metabolites and phytochemicals (vitexin, chrysoeriol, ferulate, salidroside and gentisic acid), with known antioxidant properties, were comparatively low at basal levels in PHS-susceptible, non-dormant cultivar, Baegjoong. In conclusion, the results of this investigation revealed that after imbibition the metabolic homeostasis of dormant wheat is significantly less affected compared to non-dormant wheat. The inferences from this study combined with proteomic and transcriptomic studies will advance the molecular understanding of the pathways and enzyme regulations during PHS.

Mini review: Recombinant production of tailored bio-pharmaceuticals in different Bacillus strains and future perspectives

Bio-pharmaceuticals like antibodies, hormones and growth factors represent about one-fifth of commercial pharmaceuticals. Host candidates of growing interest for recombinant production of these proteins are strains of the genus Bacillus, long being established for biotechnological production of homologous and heterologous proteins. Bacillus strains benefit from development of efficient expression systems in the last decades and emerge as major industrial workhorses for recombinant proteins due to easy cultivation, non-pathogenicity and their ability to secrete recombinant proteins directly into extracellular medium allowing cost-effective downstream processing. Their broad product portfolio of pharmaceutically relevant recombinant proteins described in research include antibody fragments, growth factors, interferons and interleukins, insulin, penicillin G acylase, streptavidin and different kinases produced in various cultivation systems like microtiter plates, shake flasks and bioreactor systems in batch, fed-batch and continuous mode. To further improve production and secretion performance of Bacillus, bottlenecks and limiting factors concerning proteases, chaperones, secretion machinery or feedback mechanisms can be identified on different cell levels from genomics and transcriptomics via proteomics to metabolomics and fluxomics. For systematical identification of recurring patterns characteristic of given regulatory systems and key genetic targets, systems biology and omics-technology provide suitable and promising approaches, pushing Bacillus further towards industrial application for recombinant pharmaceutical protein production.

LC-MS Untargeted Metabolomics To Explain the Signal Metabolites Inducing Browning in Fresh-Cut Lettuce

Enzymatic browning is one of the main causes of quality loss in lettuce as a prepared and ready-to-eat cut salad. An untargeted metabolomics approach using UPLC-ESI-QTOF-MS was performed to explain the wound response of lettuce after cutting and to identify the metabolites responsible of browning. Two cultivars of Romaine lettuce with different browning susceptibilities were studied at short time intervals after cutting. From the total 5975 entities obtained from the raw data after alignment, filtration reduced the number of features to 2959, and the statistical analysis found that only 1132 entities were significantly different. Principal component analysis (PCA) clearly showed that these samples grouped according to cultivar and time after cutting. From those, only 15 metabolites belonging to lysophospholipids, oxylipin/jasmonate metabolites, and phenolic compounds were able to explain the browning process. These selected metabolites showed different trends after cutting; some decreased rapidly, others increased but decreased thereafter, whereas others increased during the whole period of storage. In general, the fast-browning cultivar showed a faster wound response and a higher raw intensity of some key metabolites than the slow-browning one. Just after cutting, the fast-browning cultivar contained 11 of the 15 browning-associated metabolites, whereas the slow-browning cultivar only had 5 of them. These metabolites could be used as biomarkers in breeding programs for the selection of lettuce cultivars with lower browning potential for fresh-cut applications.

Hepatocyte-secreted extracellular vesicles modify blood metabolome and endothelial function by an arginase-dependent mechanism

Hepatocytes release extracellular vesicles (EVs) loaded with signaling molecules and enzymes into the bloodstream. Although the importance of EVs in the intercellular communication is already recognized, the metabolic impact of the enzymes carried by these vesicles is still unclear. We evaluated the global effect of the enzymatic activities of EVs by performing untargeted metabolomic profiling of serum samples after their exposure to EVs. This approach revealed a significant change in the abundance of 94 serum metabolic signals. Our study shows that these vesicles modify the concentration of metabolites of different chemical nature including metabolites related to arginine metabolism, which regulates vascular function. To assess the functional relevance of this finding, we examined the levels of arginase-1 protein and its activity in the hepatic EVs carrying the exosomal markers CD81 and CD63. Remarkably, the arginase activity was also detected in EVs isolated from the serum in vivo, and this vesicular activity significantly increased under liver-damaging conditions. Finally, we demonstrated that EVs secreted by hepatocytes inhibited the acetylcholine-induced relaxation in isolated pulmonary arteries, via an arginase-dependent mechanism. In summary, our study demonstrates that the hepatocyte-released EVs are metabolically active, affecting a number of serum metabolites involved in oxidative stress metabolism and the endothelial function.

System level analysis of cacao seed ripening reveals a sequential interplay of primary and secondary metabolism leading to polyphenol accumulation and preparation of stress resistance

Theobroma cacao and its popular product, chocolate, are attracting attention due to potential health benefits including antioxidative effects by polyphenols, anti-depressant effects by high serotonin levels, inhibition of platelet aggregation and prevention of obesity-dependent insulin resistance. The development of cacao seeds during fruit ripening is the most crucial process for the accumulation of these compounds. In this study, we analyzed the primary and the secondary metabolome as well as the proteome during Theobroma cacao cv. Forastero seed development by applying an integrative extraction protocol. The combination of multivariate statistics and mathematical modelling revealed a complex consecutive coordination of primary and secondary metabolism and corresponding pathways. Tricarboxylic acid (TCA) cycle and aromatic amino acid metabolism dominated during the early developmental stages (stages 1 and 2; cell division and expansion phase). This was accompanied with a significant shift of proteins from phenylpropanoid metabolism to flavonoid biosynthesis. At stage 3 (reserve accumulation phase), metabolism of sucrose switched from hydrolysis into raffinose synthesis. Lipids as well as proteins involved in lipid metabolism increased whereas amino acids and N-phenylpropenoyl amino acids decreased. Purine alkaloids, polyphenols, and raffinose as well as proteins involved in abiotic and biotic stress accumulated at stage 4 (maturation phase) endowing cacao seeds the characteristic astringent taste and resistance to stress. In summary, metabolic key points of cacao seed development comprise the sequential coordination of primary metabolites, phenylpropanoid, N-phenylpropenoyl amino acid, serotonin, lipid and polyphenol metabolism thereby covering the major compound classes involved in cacao aroma and health benefits.

Comparison and optimization of methods for the simultaneous extraction of DNA, RNA, proteins, and metabolites

The challenge of performing a time-resolved comprehensive analysis of molecular systems has led to the quest to optimize extraction methods. When the size of a biological sample is limited, there is demand for the simultaneous extraction of molecules representing the four areas of "omics": genomics, transcriptomics, proteomics, and metabolomics. Here we optimized a protocol for the simultaneous extraction of DNA, RNA, proteins, and metabolites and compared it with two existing protocols. Our optimization comprised the addition of a methanol/chloroform metabolite purification before the separation of DNA/RNA and proteins. Extracted DNA, RNA, proteins, and metabolites were quantitatively and/or qualitatively analyzed. Of the three methods, only the newly developed protocol yielded all biomolecule classes of adequate quantity and quality.

Chemometrics applied to quality control and metabolomics for traditional Chinese medicines

Traditional Chinese medicines (TCMs) bring a great challenge in quality control and evaluating the efficacy because of their complexity of chemical composition. Chemometric techniques provide a good opportunity for mining more useful chemical information from TCMs. Then, the application of chemometrics in the field of TCMs is spontaneous and necessary. This review focuses on the recent various important chemometrics tools for chromatographic fingerprinting, including peak alignment information features, baseline correction and applications of chemometrics in metabolomics and modernization of TCMs, including authentication and evaluation of the quality of TCMs, evaluating the efficacy of TCMs and essence of TCM syndrome. In the conclusions, the general trends and some recommendations for improving chromatographic metabolomics data analysis are provided.

Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several studies on proteomics and metabolomics in model and crop legumes have been discussed. Additionally, applications of advanced proteomics and metabolomics approaches have also been included in this review for future applications in legume research. The integration of these "omics" approaches will greatly support the identification of accurate biomarkers in legume smart breeding programs.

Elevated sphingosine-1-phosphate promotes sickling and sickle cell disease progression

Sphingosine-1-phosphate (S1P) is a bioactive lipid that regulates multicellular functions through interactions with its receptors on cell surfaces. S1P is enriched and stored in erythrocytes; however, it is not clear whether alterations in S1P are involved in the prevalent and debilitating hemolytic disorder sickle cell disease (SCD). Here, using metabolomic screening, we found that S1P is highly elevated in the blood of mice and humans with SCD. In murine models of SCD, we demonstrated that elevated erythrocyte sphingosine kinase 1 (SPHK1) underlies sickling and disease progression by increasing S1P levels in the blood. Additionally, we observed elevated SPHK1 activity in erythrocytes and increased S1P in blood collected from patients with SCD and demonstrated a direct impact of elevated SPHK1-mediated production of S1P on sickling that was independent of S1P receptor activation in isolated erythrocytes. Together, our findings provide insights into erythrocyte pathophysiology, revealing that a SPHK1-mediated elevation of S1P contributes to sickling and promotes disease progression, and highlight potential therapeutic opportunities for SCD.

Revisiting Protocols for the NMR Analysis of Bacterial Metabolomes

Over the past decade, metabolomics has emerged as an important technique for systems biology. Measuring all the metabolites in a biological system provides an invaluable source of information to explore various cellular processes, and to investigate the impact of environmental factors and genetic modifications. Nuclear magnetic resonance (NMR) spectroscopy is an important method routinely employed in metabolomics. NMR provides comprehensive structural and quantitative information useful for metabolomics fingerprinting, chemometric analysis, metabolite identification and metabolic pathway construction. A successful metabolomics study relies on proper experimental protocols for the collection, handling, processing and analysis of metabolomics data. Critically, these protocols should eliminate or avoid biologically-irrelevant changes to the metabolome. We provide a comprehensive description of our NMR-based metabolomics procedures optimized for the analysis of bacterial metabolomes. The technical details described within this manuscript should provide a useful guide to reliably apply our NMR-based metabolomics methodology to systems biology studies.

Analyzing methods for path mining with applications in metabolomics

Metabolomics is one of the key approaches of systems biology that consists of studying biochemical networks having a set of metabolites, enzymes, reactions and their interactions. As biological networks are very complex in nature, proper techniques and models need to be chosen for their better understanding and interpretation. One of the useful strategies in this regard is using path mining strategies and graph-theoretical approaches that help in building hypothetical models and perform quantitative analysis. Furthermore, they also contribute to analyzing topological parameters in metabolome networks. Path mining techniques can be based on grammars, keys, patterns and indexing. Moreover, they can also be used for modeling metabolome networks, finding structural similarities between metabolites, in-silico metabolic engineering, shortest path estimation and for various graph-based analysis. In this manuscript, we have highlighted some core and applied areas of path-mining for modeling and analysis of metabolic networks.

Phytochemical composition of Potentilla anserina L. analyzed by an integrative GC-MS and LC-MS metabolomics platform

Potentilla anserina L. (Rosaceae) is known for its beneficial effects of prevention of pre-menstrual syndrome (PMS). For this reason P. anserina is processed into many food supplements and pharmaceutical preparations. Here we analyzed hydroalcoholic reference extracts and compared them with various extracts of different pharmacies using an integrative metabolomics platform comprising GC-MS and LC-MS analysis and software toolboxes for data alignment (MetMAX Beta 1.0) and multivariate statistical analysis (COVAIN 1.0). Multivariate statistics of the integrated GC-MS and LC-MS data showed strong differences between the different plant extract formulations. Different groups of compounds such as chlorogenic acid, kaempferol 3-O-rutinoside, acacetin 7-O-rutinoside, and genistein were reported for the first time in this species. The typical fragmentation pathway of the isoflavone genistein confirmed the identification of this active compound that was present with different abundances in all the extracts analyzed. As a result we have revealed that different extraction procedures from different vendors produce different chemical compositions, e.g. different genistein concentrations. Consequently, the treatment may have different effects. The integrative metabolomics platform provides the highest resolution of the phytochemical composition and a mean to define subtle differences in plant extract formulations.

Targeting proteomics to investigate metastasis-associated mitochondrial proteins

Mitochondria are essential organelles in eukaryotic cells and are responsible for regulating energy metabolism, ROS production, and cell survival. Recently, various cellular pathogeneses, including tumorigenesis and metastasis, have been reported to be associated with mitochondrial homeostasis. Consequently, exploiting the correlation between dysfunctional mitochondria and tumor progression has been implicated in the understanding of tumorigenesis, tumor metastasis, and chemoresistance, along with novel strategies to develop cancer therapeutics. To comprehensively understand the role of the mitochondria in cancer metastasis, it is necessary to resolve thousands of mitochondrial proteins and their post-translational modifications with high-throughput global assessments. We introduce mitochondrial proteomic strategies in this review and a discussion on their recent findings related to cancer metastasis. Additionally, the mitochondrial respiratory chain is believed to be a major site for ROS production, and elevated ROS is likely a key source to trigger dysfunctional mitochondria and impaired mitochondrial metabolism that subsequently contribute to the development of cancer progression. Equipment-based metabolomic analysis now allows the monitoring of disease progression and diagnosis. These newly emerging techniques, including proteomics, redox-proteomics, and metabolomics, are described in this review.

Characterization of global metabolic responses of glucose-6-phosphate dehydrogenase-deficient hepatoma cells to diamide-induced oxidative stress

Glucose-6-phosphate dehydrogenase (G6PD) is crucial to NADPH generation and redox homeostasis. We have recently shown that G6PD deficiency predisposes cells to oxidant-induced cell death, and it is associated with the impairment of glutathione regeneration. It remains unclear what other metabolic pathways are affected by G6PD deficiency and whether the altered metabolism disturbs cellular redox homeostasis and underlies increased susceptibility to oxidants. In this study, we examined the effects of diamide on global metabolite profiles of SK-Hep1-derived SK-i-Gi and SK-i-Sc cells, which could inducibly express short hairpin RNA (shRNA) against G6PD (Gi) and control shRNA (Sc), respectively. There was no significant difference in their metabolite profiles under uninduced conditions. Doxycycline (Dox) addition resulted in over 70% decrease in G6PD activity in SK-i-Gi cells. This was accompanied by relatively minor changes in the metabolome of SK-i-Gi cells. Upon further diamide treatment, the metabolite profiles of both SK-i-Gi and SK-i-Sc cells changed in a time-dependent manner. A number of metabolic pathways, including those involved in energy metabolism and metabolism of amino acids and glutathione, were affected. However, the changes in the metabolite profile of Dox-treated SK-i-Gi cells were distinct from those of control cells (i.e., Dox-treated SK-i-Sc, SK-i-Gi, and SK-i-Sc cells). Cellular glutathione was depleted, whereas its disulfide form increased significantly in diamide, Dox-treated SK-i-Gi cells. Metabolites related to energy metabolism, such as AMP, ADP, and acetylcarnitine, increased to a greater extent in these cells than in diamide-treated control cells. In contrast, NAD and glutathione dropped to lower levels in SK-i-Gi cells than in control cells. The NAD(+) depletion in SK-i-Gi cells was accompanied by a significant increase in NAD kinase activity. Targeted analyses revealed that NADP(+) and NADPH increased significantly in diamide, Dox-treated SK-i-Gi cells compared with similarly treated control cells. Our results suggest that diamide induces oxidation and depletion of glutathione in SK-i-Gi cells under conditions of G6PD shRNA induction and subsequently induces conversion of NAD(+) to NADP(+) through enhanced NAD kinase activity. This may represent a compensatory mechanism to restore cellular NADPH reserve in G6PD-deficient cells. It is accompanied by alteration in pathways of cellular energy metabolism, such as glycolysis and β-oxidation.

Potential metabolic mechanism of girls' central precocious puberty: a network analysis on urine metabonomics data

BACKGROUND

Central precocious puberty (CPP) is a common pediatric endocrine disease caused by early activation of hypothalamic-putuitary-gonadal (HPG) axis, yet the exact mechanism was poorly understood. Although there were some proofs that an altered metabolic profile was involved in CPP, interpreting the biological implications at a systematic level is still in pressing need. To gain a systematic understanding of the biological implications, this paper analyzed the CPP differential urine metabolites from a network point of view.

RESULTS

In this study, differential urine metabolites between CPP girls and age-matched normal ones were identified by LC-MS. Their basic topological parameters were calculated in the background network. The network decomposition suggested that CPP differential urine metabolites were most relevant to amino acid metabolism. Further proximity analysis of CPP differential urine metabolites and neuro-endocrine metabolites showed a close relationship between CPP metabolism and neuro-endocrine system. Then the core metabolic network of CPP was successfully constructed among all these differential urine metabolites. As can be demonstrated in the core network, abnormal aromatic amino acid metabolism might influence the activity of HPG and hypothalamic pituitary adrenal (HPA) axis. Several adjustments to the early activation of puberty in CPP girls could also be revealed by urine metabonomics.

CONCLUSIONS

The present article demonstrated the ability of urine metabonomics to provide several potential metabolic clues for CPP's mechanism. It was revealed that abnormal metabolism of amino acid, especially aromatic amino acid, might have a close correlation with CPP's pathogenesis by activating HPG axis and suppressing HPA axis. Such a method of network-based analysis could also be applied to other metabonomics analysis to provide an overall perspective at a systematic level.

Metabolomic analysis of the effects of edible dry beans (Phaseolus vulgaris L.) on tissue lipid metabolism and carcinogenesis in rats

Metabolite profiling using liquid chromatography-time-of-flight MS was undertaken to identify candidate metabolic processes that account for dry bean effects on disease risk with a specific focus on the development of breast cancer. Normal mammary gland and mammary carcinomas from previously reported experiments were evaluated. Principal component analysis (PCA) of mass spectral data revealed that tissue of both types from control-fed v. bean-fed rats could be distinguished by their metabolomic profiles. Candidate ion identification using MassTRIX analysis software revealed that alterations in eicosanoid, fatty acid, TAG and steroid metabolism partially accounted for the differences observed in both PCA. In addition, evidence was obtained consistent with the hypothesis that the varying inhibitory effects on mammary carcinogenesis of genetically distinct dry bean types were mirrored by differential patterns of lipid metabolites in mammary carcinoma. The use of MassTRIX provided links for metabolite profile enrichment with metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes. Implicated pathways included a linkage between diacylglycerol and protein kinase C and eicosanoid metabolites and inducible cyclo-oxygenase-2 and/or eicosanoid degradation mediated via 15-PG dehydrogenase. These pathways have been reported to be misregulated during the development of cancer. The differences observed between control-fed and bean-fed rats in lipid metabolism require validation using targeted analytical methods and detailed analyses of how bean bioactive food components regulate genes that control lipid biosynthesis, interconversion and catabolism.