PubMed

Longitudinal study of pesticide residue levels in human milk from Western Australia during 12 months of lactation: Exposure assessment for infants. Sci Rep. 2016 Dec 07;6:38355 Authors: Du J, Gridneva Z, Gay MC, Lai CT, Trengove RD, Hartmann PE, Geddes DT Abstract The presence of pesticides in human milk (HM) is of great concern due to the potential health effects for the breastfed infant. To determine the relationships between HM pesticides and infant growth and development, a longitudinal study was conducted. HM samples (n = 99) from 16 mothers were collected at 2, 5, 9 and 12 months of lactation. A validated QuEChERS method and Gas chromatography-tandem mass spectrometry (GC-MS/MS) were used for the analysis of 88 pesticides in HM. Only p,p'-DDE, p,p'-DDT and β-HCH were detected with a mean concentration (±SD) of 52.25 ± 49.88 ng/g fat, 27.67 ± 20.96 ng/g fat and 48.00 ± 22.46 ng/g fat respectively. The concentrations of the detected pesticides decreased significantly throughout the first year of lactation. No significant relationships between HM p,p'-DDE and infant growth outcomes: weight, length, head circumference and percentage fat mass were detected. The actual daily intake (ADI) of total DDTs in this cohort was 14-1000 times lower than the threshold reference and significantly lower than the estimated daily intake (EDI). Further, the ADI decreased significantly throughout the first 12 months of lactation. PMID: 27924835 [PubMed - in process]

Metabolomics of Healthy Berry Fruits. Curr Med Chem. 2016 Dec 05; Authors: D Urso G, Piacente S, Pizza C, Montoro P Abstract The consumption of berry-type fruits has become very popular in recent years because of their positive effects on human health. Berries are in fact widely known for their health-promoting benefits, including prevention of chronic disease, cardiovascular disease and cancer. Berries are a rich source of bioactive metabolites, such as vitamins, minerals, and phenolic compounds, mainly anthocyanins. Numerous in vitro and in vivo studies recognized the health effects of berries and their function as bioactive modulators of various cell functions associated with oxidative stress. Plants have one of the largest metabolome¬ databases, with over 1200 papers on plant metabolomics published only in the last decade. Mass spectrometry (MS) and NMR (Nuclear Magnetic Resonance) are the most important analytical technologies on which the emerging ''omics'' approaches are based. They may provide detection and quantization of thousands of biologically active metabolites from a tissue, working in a ''global'' or ''targeted'' manner, down to ultra-trace levels. In the present review, we highlighted the use of MS and NMR-based strategies and Multivariate Data Analysis for the valorization of berries known for their biological activities, important as food and often used in the preparation of nutraceutical formulations. PMID: 27924727 [PubMed - as supplied by publisher]

Related Articles NMR-Based Metabolomics of Oral Biofluids. Methods Mol Biol. 2017;1537:79-105 Authors: Schirra HJ, Ford PJ Abstract NMR-based metabolomics is an established technique for characterizing the metabolite profile of biological fluids and investigating how metabolite profiles change in response to biological and/or clinical stimuli. Thus, NMR-based metabolomics has the potential to discover biomarkers for diagnosis, prognosis, and/or therapy of clinical conditions, as well as to unravel the physiology underlying clinical conditions. Here, we describe a detailed protocol for NMR-based metabolomics of oral biofluids, including sample collection, sample handling, NMR data acquisition, and processing. In addition, we give a general overview of the statistical analysis of the resulting metabolomic data. PMID: 27924589 [PubMed - in process]

Related Articles Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry. J Am Soc Mass Spectrom. 2016 Dec 06; Authors: Kilgour DP, Hughes S, Kilgour SL, Mackay CL, Palmblad M, Tran BQ, Goo YA, Ernst RK, Clarke DJ, Goodlett DR Abstract We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. Graphical Abstract ᅟ. PMID: 27924495 [PubMed - as supplied by publisher]

Related Articles Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice. Theranostics. 2016;6(12):2161-2169 Authors: Larkin JR, Dickens AM, Claridge TD, Bristow C, Andreou K, Anthony DC, Sibson NR Abstract Over 20% of cancer patients will develop brain metastases. Prognosis is currently extremely poor, largely owing to late-stage diagnosis. We hypothesized that biofluid metabolomics could detect tumours at the micrometastatic stage, prior to the current clinical gold-standard of blood-brain barrier breakdown. Metastatic mammary carcinoma cells (4T1-GFP) were injected into BALB/c mice via intracerebral, intracardiac or intravenous routes to induce differing cerebral and systemic tumour burdens. B16F10 melanoma and MDA231BR-GFP human breast carcinoma cells were used for additional modelling. Urine metabolite composition was analysed by (1)H NMR spectroscopy. Statistical pattern recognition and modelling was applied to identify differences or commonalities indicative of brain metastasis burden. Significant metabolic profile separations were found between control cohorts and animals with tumour burdens at all time-points for the intracerebral 4T1-GFP time-course. Models became stronger, with higher sensitivity and specificity, as the time-course progressed indicating a more severe tumour burden. Sensitivity and specificity for predicting a blinded testing set were 0.89 and 0.82, respectively, at day 5, both rising to 1.00 at day 35. Significant separations were also found between control and all 4T1-GFP injected mice irrespective of route. Likewise, significant separations were observed in B16F10 and MDA231BR-GFP cell line models. Metabolites underpinning each separation were identified. These findings demonstrate that brain metastases can be diagnosed in an animal model based on urinary metabolomics from micrometastatic stages. Furthermore, it is possible to separate differing systemic and CNS tumour burdens, suggesting a metabolite fingerprint specific to brain metastasis. This method has strong potential for clinical translation. PMID: 27924154 [PubMed - in process]

Related Articles Quorum Sensing Coordinates Cooperative Expression of Pyruvate Metabolism Genes To Maintain a Sustainable Environment for Population Stability. MBio. 2016 Dec 06;7(6): Authors: Hawver LA, Giulietti JM, Baleja JD, Ng WL Abstract Quorum sensing (QS) is a microbial cell-cell communication system that regulates gene expression in response to population density to coordinate collective behaviors. Yet, the role of QS in resolving the stresses caused by the accumulation of toxic metabolic by-products at high cell density is not well defined. In response to cell density, QS could be involved in reprogramming of the metabolic network to maintain population stability. Using unbiased metabolomics, we discovered that Vibrio cholerae mutants genetically locked in a low cell density (LCD) QS state are unable to alter the pyruvate flux to convert fermentable carbon sources into neutral acetoin and 2,3-butanediol molecules to offset organic acid production. As a consequence, LCD-locked QS mutants rapidly lose viability when grown with fermentable carbon sources. This key metabolic switch relies on the QS-regulated small RNAs Qrr1-4 but is independent of known QS regulators AphA and HapR. Qrr1-4 dictate pyruvate flux by translational repression of the enzyme AlsS, which carries out the first step in acetoin and 2,3-butanediol biosynthesis. Consistent with the idea that QS facilitates the expression of a common trait in the population, AlsS needs to be expressed cooperatively in a group of cells. Heterogeneous populations with high percentages of cells not expressing AlsS are unstable. All of the cells, regardless of their respective QS states, succumb to stresses caused by toxic by-product accumulation. Our results indicate that the ability of the bacteria to cooperatively control metabolic flux through QS is critical in maintaining a sustainable environment and overall population stability. IMPORTANCE: Our work reveals a novel role for Vibrio cholerae quorum sensing (QS) in relieving the stresses caused by toxic metabolite accumulation when the population becomes crowded through metabolic reprogramming. QS enables V. cholerae switching from a low cell density energy-generating metabolism that is beneficial to individuals at the expense of the environment to a high cell density mode that preserves environmental habitability by sacrificing individual fitness. This cooperative switch provides a stable environment as the common good in maintaining the stability of the community. However, the common good can be exploited by uncooperative mutants that pollute the environment, causing population collapse. Our findings provide insights into the metabolic stress response of a major human pathogen, with implications for our understanding of microbial social biology and cooperation from an ecological and evolutionary perspective. PMID: 27923919 [PubMed - in process]

Related Articles Using silver and bighead carp cell lines for the identification of a unique metabolite fingerprint from thiram-specific chemical exposure. Chemosphere. 2016 Dec 03;: Authors: Putnam JG, Nelson JE, Leis EM, Erickson RA, Hubert TD, Amberg JJ Abstract Conservation biology often requires the control of invasive species. One method is the development and use of biocides. Identifying new chemicals as part of the biocide registration approval process can require screening millions of compounds. Traditionally, screening new chemicals has been done in vivo using test organisms. Using in vitro (e.g., cell lines) and in silico (e.g., computer models) methods decrease test organism requirements and increase screening speed and efficiency. These methods, however, would be greatly improved by better understanding how individual fish species metabolize selected compounds. We combined cell assays and metabolomics to create a powerful tool to facilitate the identification of new control chemicals. Specifically, we exposed cell lines established from bighead carp and silver carp larvae to thiram (7 concentrations) then completed metabolite profiling to assess the dose-response of the bighead carp and silver carp metabolome to thiram. Forty one of the 700 metabolomic markers identified in bighead carp exhibited a dose-response to thiram exposure compared to silver carp in which 205 of 1590 metabolomic markers exhibited a dose-response. Additionally, we identified 11 statistically significant metabolomic markers based upon volcano plot analysis common between both species. This smaller subset of metabolites formed a thiram-specific metabolomic fingerprint which allowed for the creation of a toxicant specific, rather than a species-specific, metabolomic fingerprint. Metabolomic fingerprints may be used in biocide development and improve our understanding of ecologically significant events, such as mass fish kills. PMID: 27923506 [PubMed - as supplied by publisher]

Related Articles Combined transcriptome and metabolome analyses to understand the dynamic responses of rice plants to attack by the rice stem borer Chilo suppressalis (Lepidoptera: Crambidae). BMC Plant Biol. 2016 Dec 07;16(1):259 Authors: Liu Q, Wang X, Tzin V, Romeis J, Peng Y, Li Y Abstract BACKGROUND: Rice (Oryza sativa L.), which is a staple food for more than half of the world's population, is frequently attacked by herbivorous insects, including the rice stem borer, Chilo suppressalis. C. suppressalis substantially reduces rice yields in temperate regions of Asia, but little is known about how rice plants defend themselves against this herbivore at molecular and biochemical level. RESULTS: In the current study, we combined next-generation RNA sequencing and metabolomics techniques to investigate the changes in gene expression and in metabolic processes in rice plants that had been continuously fed by C. suppressalis larvae for different durations (0, 24, 48, 72, and 96 h). Furthermore, the data were validated using quantitative real-time PCR. There were 4,729 genes and 151 metabolites differently regulated when rice plants were damaged by C. suppressalis larvae. Further analyses showed that defense-related phytohormones, transcript factors, shikimate-mediated and terpenoid-related secondary metabolism were activated, whereas the growth-related counterparts were suppressed by C. suppressalis feeding. The activated defense was fueled by catabolism of energy storage compounds such as monosaccharides, which meanwhile resulted in the increased levels of metabolites that were involved in rice plant defense response. Comparable analyses showed a correspondence between transcript patterns and metabolite profiles. CONCLUSION: The current findings greatly enhance our understanding of the mechanisms of induced defense response in rice plants against C. suppressalis infestation at molecular and biochemical levels, and will provide clues for development of insect-resistant rice varieties. PMID: 27923345 [PubMed - in process]

Related Articles Direct infusion mass spectrometry for metabolomic phenotyping of diseases. Bioanalysis. 2017 Jan;9(1):131-148 Authors: González-Domínguez R, Sayago A, Fernández-Recamales Á Abstract Metabolomics based on direct mass spectrometry (MS) analysis, either by direct infusion or flow injection of crude sample extracts, shows a great potential for metabolic fingerprinting because of its high-throughput screening capability, wide metabolite coverage and reduced time of analysis. Considering that numerous metabolic pathways are significantly perturbed during the initiation and progression of diseases, these metabolomic tools can be used to get a deeper understanding about disease pathogenesis and discover potential biomarkers for early diagnosis. In this work, we describe the most common metabolomic platforms used in biomedical research, with special focus on strategies based on direct MS analysis. Then, a comprehensive review on the application of direct MS fingerprinting in clinical issues is provided. PMID: 27921460 [PubMed - in process]

Related Articles Investigation of the derivatization conditions for GC-MS metabolomics of biological samples. Bioanalysis. 2017 Jan;9(1):53-65 Authors: Moros G, Chatziioannou AC, Gika HG, Raikos N, Theodoridis G Abstract AIM: Metabolomics applications represent an emerging field where significant efforts are directed. Derivatization consists prerequisite for GC-MS metabolomics analysis. METHODS: Common silylation agents were tested for the derivatization of blood plasma. Optimization of methoxyamination and silylation reactions was performed on a mixture of reference standards, consisting of 46 different metabolites. Stability of derivatized metabolites was tested at 4°C. RESULTS: Optimum results were achieved using N-methyl-N-(trimethylsilyl)trifluoroacetamide. Methoxyamination at room temperature for 24 h followed by 2-h silylation at high temperature lead to efficient derivatization. CONCLUSION: Formation and stability of derivatives among metabolites differ greatly, so derivatization should be studied before application in metabolomics studies. PMID: 27921459 [PubMed - in process]

Related Articles Metabolic profile of human coelomic fluid. Bioanalysis. 2017 Jan;9(1):37-51 Authors: Virgiliou C, Valianou L, Witting M, Moritz F, Fotakis C, Zoumpoulakis P, Chatziioannou AC, Lazaros L, Makrydimas G, Chatzimeletiou K, Raikos N, Theodoridis GA Abstract AIM: Till now there is very limited knowledge on the molecular content of coelomic fluid and cells. This study presents the first attempt to elucidate the metabolic profile of such samples. METHODOLOGY: Samples were collected via coelocentesis from 41 women during the first trimester of gestation. Metabolic content was assessed using four different analytical platforms. For targeted analysis a hydrophilic interaction chromatography ultra high performance LC-MS/MS method was applied. Holistic analysis performed by GC-MS, NMR spectroscopy and ion cyclotron ultra-high resolution MS (FT-ICR-MS) instrumentation. RESULTS & CONCLUSIONS: Our observations suggest coelomic fluid and cells as promising biosamples, rich in metabolites with potential use in mammalian system biology studies. PMID: 27921458 [PubMed - in process]

Related Articles Impact of exercise on fecal and cecal metabolome over aging: a longitudinal study in rats. Bioanalysis. 2017 Jan;9(1):21-36 Authors: Deda O, Gika H, Panagoulis T, Taitzoglou I, Raikos N, Theodoridis G Abstract AIM: Physical exercise can reduce adverse conditions during aging, while both exercise and aging act as metabolism modifiers. The present study investigates rat fecal and cecal metabolome alterations derived from exercise during rats' lifespan. METHODS & RESULTS: Groups of rats trained life-long or for a specific period of time were under study. The training protocol consisted of swimming, 15-18 min per day, 3-5 days per week, with load of 4-0% of rat's weight. Fecal samples and cecal extracts were analyzed by targeted and untargeted metabolic profiling methods (GC-MS and LC-MS/MS). Effects of exercise and aging on the rats' fecal and cecal metabolome were observed. CONCLUSION: Fecal and cecal metabolomics are a promising field to investigate exercise biochemistry and age-related alterations. PMID: 27921457 [PubMed - in process]

Related Articles Capillary electrophoresis mass spectrometry as a tool for untargeted metabolomics. Bioanalysis. 2017 Jan;9(1):99-130 Authors: García A, Godzien J, López-Gonzálvez Á, Barbas C Abstract Highly polar and ionic metabolites, such as sugars, most amino acids, organic acids or nucleotides are not retained by conventional reversed-phase LC columns and polar stationary phases and hydrophilic-interaction LC lacks of robustness, which is still limiting their applications for untargeted metabolomics where reproducibility is a must. Biological samples such as blood, urine or even tissues include many hydrophilic compounds secreted from cells, their analysis is essential for biomarker discovery, disease progression or treatment effects. This review focuses on CE coupled to MS as a mature technique for untargeted metabolomics including sample pretreatment, types of matrices, analytical methods, applications and data treatment strategies for polar compound analysis in biological matrices. The main applications and results of CE-MS in untargeted metabolomics are discussed and presented in a tabulated format. PMID: 27921456 [PubMed - in process]

Related Articles Lipoprotein profiling methodology based on determination of apolipoprotein concentration. Bioanalysis. 2017 Jan;9(1):9-19 Authors: Takeda H, Izumi Y, Tomita A, Koike T, Shiomi M, Fukusaki E, Matsuda F, Bamba T Abstract AIM: Abnormal lipid metabolism results in the alteration of lipid compositions in lipoproteins; therefore an accurate and quantitative analytical approach is required for the detailed structural characterization of lipoproteins. However, the specific lipid composition of each lipoprotein particle is poorly understood. MATERIALS & METHODS: Lipid composition of very-low-density lipoprotein and low-density lipoprotein particles derived from myocardial infarction-prone rabbits was determined by normalization of lipidomics data using apoB-100 levels. RESULTS: The ratio of lipid levels between very-low-density lipoprotein and low-density lipoprotein particles was different according to not only lipid classes, but also phosphatidylethanolamine subclasses by applying our developed methodology to myocardial infarction-prone rabbits. CONCLUSION: Our novel analytical approach represents to be a potentially useful tool to obtain particle-specific lipid components of lipoproteins. PMID: 27921455 [PubMed - in process]

Related Articles Methods and techniques for metabolic phenotyping. Bioanalysis. 2017 Jan;9(1):1-3 Authors: Wilson I PMID: 27921454 [PubMed - in process]

Related Articles Simultaneous profiling of 17 steroid hormones for the evaluation of endocrine-disrupting chemicals in H295R cells. Bioanalysis. 2017 Jan;9(1):67-69 Authors: Jumhawan U, Yamashita T, Ishida K, Fukusaki E, Bamba T Abstract AIM: There is urgent need to develop a new protocol for the evaluation of chemical substances to potentially interact with the endocrine system and induce numerous pathological issues. The recently validated in vitro screening assay is limited on monitoring two steroid hormones. Methodology & results: The H295R model cell was exposed to seven endocrine disrupting chemicals (EDCs). The levels of 17 steroid hormones in cell extracts were subsequently determined by a quantitative targeted GC/MS/MS method. Through wide coverage, this system managed to capture the effects of exposure to increasing EDCs concentrations in the entire steroidogenic pathways. CONCLUSION: The developed approach could be beneficial for the mechanistic investigation of EDCs. PMID: 27921452 [PubMed - in process]

Related Articles Targeted full-scan LC-MS metabolomics: simultaneous quantitation of knowns and feature discovery provide the best of both worlds. Bioanalysis. 2017 Jan;9(1):5-8 Authors: Rosebrock AP PMID: 27921451 [PubMed - in process]

Related Articles UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research. Drug Discov Today. 2016 Dec 02;: Authors: Nassar AF, Wu T, Nassar SF, Wisnewski AV Abstract Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development. PMID: 27919805 [PubMed - as supplied by publisher]

Related Articles Metabolomics identifies perturbations in amino acid metabolism in the prefrontal cortex of the learned helplessness rat model of depression. Neuroscience. 2016 Dec 02;: Authors: Zhou X, Liu L, Zhang Y, Pu J, Yang L, Zhou C, Yuan S, Zhang H, Xie P Abstract Major depressive disorder is a serious psychiatric condition associated with high rates of suicide and is a leading cause of health burden worldwide. However, the underlying molecular mechanisms of major depression are still essentially unclear. In our study, a non-targeted gas chromatography-mass spectrometry-based metabolomics approach was used to investigate metabolic changes in the prefrontal cortex of the learned helplessness rat model of depression. Body-weight measurements and behavioral tests including the active escape test, sucrose preference test, forced swimming test, elevated plus-maze and open field test were used to assess changes in the behavioral spectrum after inescapable footshock stress. Rats in the stress group exhibited significant learned helpless and depression-like behaviors, while without any significant change in anxiety-like behaviors. Using multivariate and univariate statistical analysis, a total of 18 differential metabolites were identified after the footshock stress protocol. Ingenuity Pathways Analysis and MetaboAnalyst were applied for predicted pathways and biological functions analysis. "Amino Acid Metabolism, Molecule Transport, Small Molecule Biochemistry" was the most significantly altered network in the learned helplessness model. Amino acid metabolism, particularly glutamate metabolism, cysteine and methionine metabolism, arginine and proline metabolism, was significantly perturbed in the prefrontal cortex of learned helplessness rats. PMID: 27919695 [PubMed - as supplied by publisher]

Metabolomics and Its Application in the Development of Discovering Biomarkers for Osteoporosis Research. Int J Mol Sci. 2016 Dec 02;17(12): Authors: Lv H, Jiang F, Guan D, Lu C, Guo B, Chan C, Peng S, Liu B, Guo W, Zhu H, Xu X, Lu A, Zhang G Abstract Osteoporosis is a progressive skeletal disorder characterized by low bone mass and increased risk of fracture in later life. The incidence and costs associated with treating osteoporosis cause heavy socio-economic burden. Currently, the diagnosis of osteoporosis mainly depends on bone mineral density and bone turnover markers. However, these indexes are not sensitive and accurate enough to reflect the osteoporosis progression. Metabolomics offers the potential for a holistic approach for clinical diagnoses and treatment, as well as understanding of the pathological mechanism of osteoporosis. In this review, we firstly describe the study subjects of osteoporosis and bio-sample preparation procedures for different analytic purposes, followed by illustrating the biomarkers with potentially predictive, diagnosis and pharmaceutical values when applied in osteoporosis research. Then, we summarize the published metabolic pathways related to osteoporosis. Furthermore, we discuss the importance of chronological data and combination of multi-omics in fully understanding osteoporosis. The application of metabolomics in osteoporosis could provide researchers the opportunity to gain new insight into the metabolic profiling and pathophysiological mechanisms. However, there is still much to be done to validate the potential biomarkers responsible for the progression of osteoporosis and there are still many details needed to be further elucidated. PMID: 27918446 [PubMed - in process]