PubMed

Metabolomic association between venous thromboembolism in critically ill trauma patients and kynurenine pathway of tryptophan metabolism. Thromb Res. 2018 Mar 08;165:6-13 Authors: Voils SA, Shahin MH, Garrett TJ, Frye RF Abstract OBJECTIVE: Incidence of venous thromboembolism (VTE) in critically ill patients remains unacceptably high despite widespread use of thromboprophylaxis. A systems biology approach may be useful in understanding disease pathology and predicting response to treatment. Metabolite profile under specific environmental conditions provides the closest link to phenotype, but the relationship between metabolomics and risk of VTE in critically ill patients is unknown. In this study, metabolomics signatures are compared in patients with and without VTE. DESIGN: Multicenter case-control study using prospectively collected data from the Inflammation and Host Response to Injury program, with pathway and in silico gene expression analyses. SETTING: Eight level 1 US trauma centers. PATIENTS: Critically ill adults with blunt trauma who developed VTE within the first 28 days of hospitalization compared to patients without VTE (N-VTE). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients included in the study (n = 20 VTE, n = 20 N-VTE) were mean age of 34 years, injury severity score of 35, and VTE diagnosed a median of 10.5 days after admission. Global metabolomics revealed two kynurenine metabolites, N-formylkynurenine (AUC = 0.77; 95% CI: 0.59-0.89) and 5-hydroxy-N-formylkynurenine (AUC = 0.80; 95% CI:0.63-0.90) significantly discriminated VTE and N-VTE; ratio between N-formylkynurenine/5-hydroxy-N-formylkynurenine improved predictive power (AUC = 0.87; 95% CI: 0.74-0.95). In the pathway analysis, tryptophan was the only significant metabolic pathway including N-formylkynurenine and 5-hydroxy-N-formylkynurenine (p < 0.001), and 8 proteins directly or indirectly interacted with these metabolites in the interaction network analysis. Of the 8 genes tested in the in silico gene expression analyses, KYNU (p < 0.001), CCBL1 (p < 0.001), and CCBL2 (p = 0.001) were significantly different between VTE and N-VTE, controlling for age and sex. CONCLUSIONS: Two novel kynurenine metabolites in the tryptophan pathway associated with hospital-acquired VTE, and 3 candidate genes were identified via pathway and interaction network analyses. Future studies are warranted to validate these findings in diverse populations using a multi-omics approach. PMID: 29544199 [PubMed - as supplied by publisher]

Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach. J Pharm Biomed Anal. 2018 Feb 23;154:95-101 Authors: Peng F, Liu Y, He C, Kong Y, Ouyang Q, Xie X, Liu T, Liu Z, Peng J Abstract Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment. PMID: 29544107 [PubMed - as supplied by publisher]

CRH/CRHR1 mediates prenatal synthetic glucocorticoid programming of depression-like behavior across 2 generations. FASEB J. 2018 Mar 15;:fj201700948RR Authors: Xu YJ, Sheng H, Wu TW, Bao QY, Zheng Y, Zhang YM, Gong YX, Lu JQ, You ZD, Xia Y, Ni X Abstract Pregnant women at risk of preterm labor usually receive synthetic glucocorticoids (sGCs) to promote fetal lung development. Emerging evidence indicates that antenatal sGC increases the risk of affective disorders in offspring. Data from animal studies show that such disorders can be transmitted to the second generation. However, the molecular mechanisms underlying the intergenerational effects of prenatal sGC remain largely unknown. Here we show that prenatal dexamethasone (Dex) administration in late pregnancy induced depression-like behavior in first-generation (F1) offspring, which could be transmitted to second-generation (F2) offspring with maternal dependence. Moreover, corticotropin-releasing hormone (CRH) and CRH receptor type 1 (CRHR1) expression in the hippocampus was increased in F1 Dex offspring and F2 offspring from F1 Dex female rats. Administration of a CRHR1 antagonist to newborn F1 Dex offspring alleviated depression-like behavior in these rats at adult. Furthermore, we demonstrated that increased CRHR1 expression in F1 and F2 offspring was associated with hypomethylation of CpG islands in Crhr1 promoter. Our results revealed that prenatal sGC exposure could program Crh and Crhr1 gene expression in hippocampus across 2 generations, thereby leading to depression-like behavior. Our study indicates that prenatal sGC can cause epigenetic instability, which increases the risk of disease development in the offspring's later life.-Xu, Y.-J., Sheng, H., Wu, T.-W., Bao, Q.-Y., Zheng, Y., Zhang, Y.-M., Gong, Y.-X., Lu, J.-Q., You, Z.-D., Xia, Y., Ni, X. CRH/CRHR1 mediates prenatal synthetic glucocorticoid programming of depression-like behavior across 2 generations. PMID: 29543532 [PubMed - as supplied by publisher]

1H NMR metabolic profiling of gastric cancer patients with lymph node metastasis. Metabolomics. 2018;14(4):47 Authors: Zhang H, Cui L, Liu W, Wang Z, Ye Y, Li X, Wang H Abstract Introduction: Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients. Objectives: We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC. Methods: 1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n = 40), LNM-negative GC patients (n = 40) and normal controls (n = 40). Results: There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM. Conclusion: To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC. PMID: 29541009 [PubMed]

Alpha-oxoglutarate inhibits the proliferation of immortalized normal bladder epithelial cells via an epigenetic switch involving ARID1A. Sci Rep. 2018 Mar 14;8(1):4505 Authors: Shahid M, Gull N, Yeon A, Cho E, Bae J, Yoon HS, You S, Yoon H, Kim M, Berman BP, Kim J Abstract Interstitial cystitis (IC) is a chronic urinary tract disease that is characterized by unpleasant sensations, such as persistent pelvic pain, in the absence of infection or other identifiable causes. We previously performed comprehensive metabolomics profiling of urine samples from IC patients using nuclear magnetic resonance and gas-chromatography/mass spectrometry and found that urinary α-oxoglutarate (α-OG), was significantly elevated. α-OG, a tricarboxylic acid (TCA) cycle intermediate, reportedly functions to suppress the proliferation of immortalized normal human bladder epithelial cells. Here, we identified AT-rich interactive domain 1 A (ARID1A), a key chromatin remodeler, as being hypomethylated and upregulated by α-OG treatment. This was done through EPIC DNA methylation profiling and subsequent biochemical approaches, including quantitative RT-PCR and western blot analyses. Furthermore, we found that α-OG almost completely suppresses ten-eleven translocation (TET) activity, but does not affect DNA methyltransferase (DNMT) activity. Altogether, our studies reveal the potential role of α-OG in epigenetic remodeling through its effects on ARID1A and TET expression in the bladder. This may provide a new possible therapeutic strategy in treating IC. PMID: 29540744 [PubMed - in process]

Metabolomics reveals critical adrenergic regulatory checkpoints in glycolysis and pentose-phosphate pathways in embryonic heart. J Biol Chem. 2018 Mar 14;: Authors: Peoples JNR, Maxmillian T, Le Q, Nadtochiy SM, Brookes PS, Porter GA, Davidson VL, Ebert SN Abstract Cardiac energy demands during early embryonic periods are sufficiently met through glycolysis, but as development proceeds, oxidative phosphorylation in mitochondria becomes increasingly vital. Adrenergic hormones are known to stimulate metabolism in adult mammals and are essential for embryonic development, but relatively little is known about their effects on metabolism in the embryonic heart.  Here, we show that embryos lacking adrenergic stimulation have approximately 10-fold less cardiac ATP compared to littermate controls. Despite this deficit in steady-state ATP, neither the rates of ATP formation or degradation were affected in adrenergic-deficient hearts, suggesting that ATP synthesis and hydrolysis mechanisms were fully operational.  We thus hypothesized that adrenergic hormones stimulate metabolism of glucose to provide chemical substrates for oxidation in mitochondria. To test this hypothesis, we employed a metabolomics-based approach using liquid chromatography/mass spectrometry (LC/MS). Our results showed glucose-1-phosphate and glucose-6-phosphate concentrations were not significantly altered, but several downstream metabolites in both glycolytic and pentose-phosphate pathways were significantly lower compared to controls.  Further, we identified glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and glucose-6-phosphate dehydrogenase (G-6-PDH) as key enzymes in those respective metabolic pathways whose activity was significantly (p < 0.05) and substantially (80% and 40%, respectively) lower in adrenergic-deficient hearts.  Addition of pyruvate and to a lesser extent, ribose, led to significant recovery of steady-state ATP concentrations. These results demonstrate that without adrenergic stimulation, glucose metabolism in the embryonic heart is severely impaired in multiple pathways, ultimately leading to insufficient metabolic substrate availability for successful transition to aerobic respiration needed for survival. PMID: 29540484 [PubMed - as supplied by publisher]

Related Articles Cellular and Subcellular Level Localization of Maize Lipids and Metabolites Using High-Spatial Resolution MALDI Mass Spectrometry Imaging. Methods Mol Biol. 2018;1676:217-231 Authors: Dueñas ME, Feenstra AD, Korte AR, Hinners P, Lee YJ Abstract Recent technological advances have pushed the achievable spatial resolution for mass spectrometry imaging (MSI) to cellular and subcellular levels. Direct visualization of maize tissues by this tool has provided key insights into the localization of metabolites and lipids. This chapter outlines methodology for sample preparation, data acquisition, and data analysis of maize tissue sections using high-spatial resolution matrix-assisted laser desorption ionization (MALDI)-MSI, as well as the incorporation of a multi-resolution optical system, which allows for simple inter-conversion between different resolution setups (5, 10, and 50 μm imaging). PMID: 28986913 [PubMed - indexed for MEDLINE]

Related Articles Coupled brain and urine spectroscopy - in vivo metabolomic characterization of HMG-CoA lyase deficiency in 5 patients. Mol Genet Metab. 2017 Jun;121(2):111-118 Authors: Roland D, Jissendi-Tchofo P, Briand G, Vamecq J, Fontaine M, Ultré V, Acquaviva-Bourdain C, Mention K, Dobbelaere D Abstract BACKGROUND: 3-Hydroxy-3-Methylglutaryl-Coenzyme A (HMG-CoA) lyase deficiency is a rare inborn error of leucine metabolism and ketogenesis. Despite recurrent hypoglycemia and metabolic decompensations, most patients have a good clinical and neurological outcome contrasting with abnormal brain magnetic resonance imaging (MRI) signals and consistent abnormal brain proton magnetic resonance spectroscopy (1H-MRS) metabolite peaks. Identifying these metabolites could provide surrogate markers of the disease and improve understanding of MRI-clinical discrepancy and follow-up of affected patients. METHODS: Urine samples, brain MRI and 1H-MRS in 5 patients with HMG-CoA lyase deficiency (4 boys and 1 girl aged from 25days to 10years) were, for each patient, obtained on the same day. Brain and urine spectroscopy were performed at the same pH by studying urine at pH 7.4. Due to pH-induced modifications in chemical shifts and because reference 1H NMR spectra are obtained at pH 2.5, spectroscopy of normal urine added with the suspected metabolite was further performed at this pH to validate the correct identification of compounds. RESULTS: Mild to extended abnormal white matter MRI signals were observed in all cases. Brain spectroscopy abnormal peaks at 0.8-1.1ppm, 1.2-1.4ppm and 2.4ppm were also detected by urine spectroscopy at pH 7.4. Taking into account pH-induced changes in chemical shifts, brain abnormal peaks in patients were formally identified to be those of 3-hydroxyisovaleric, 3-methylglutaconic, 3-methylglutaric and 3-hydroxy-3-methylglutaric acids. CONCLUSION: 3-Methylglutaric, 3-hydroxyisovaleric and 3-hydroxy-3-methylglutaric acids identified on urine 1H-NMR spectra of 5 patients with HMG-CoA lyase deficiency are responsible for the cerebral spectroscopy signature seen in these patients, validating their local involvement in brain and putative contribution to brain neuropathology. PMID: 28396157 [PubMed - indexed for MEDLINE]

Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites. Cell Rep. 2018 Mar 13;22(11):3072-3086 Authors: Fujisaka S, Avila-Pacheco J, Soto M, Kostic A, Dreyfuss JM, Pan H, Ussar S, Altindis E, Li N, Bry L, Clish CB, Kahn CR Abstract Diet, genetics, and the gut microbiome are determinants of metabolic status, in part through production of metabolites by the gut microbiota. To understand the mechanisms linking these factors, we performed LC-MS-based metabolomic analysis of cecal contents and plasma from C57BL/6J, 129S1/SvImJ, and 129S6/SvEvTac mice on chow or a high-fat diet (HFD) and HFD-treated with vancomycin or metronidazole. Prediction of the functional metagenome of gut bacteria by PICRUSt analysis of 16S sequences revealed dramatic differences in microbial metabolism. Cecal and plasma metabolites showed multifold differences reflecting the combined and integrated effects of diet, antibiotics, host background, and the gut microbiome. Eighteen plasma metabolites correlated positively or negatively with host insulin resistance across strains and diets. Over 1,000 still-unidentified metabolite peaks were also highly regulated by diet, antibiotics, and genetic background. Thus, diet, host genetics, and the gut microbiota interact to create distinct responses in plasma metabolites, which can contribute to regulation of metabolism and insulin resistance. PMID: 29539432 [PubMed - in process]

Metabolomic profiling of macrophages determines the discrete metabolomic signature and metabolomic interactome triggered by polarising immune stimuli. PLoS One. 2018;13(3):e0194126 Authors: Rattigan KM, Pountain AW, Regnault C, Achcar F, Vincent IM, Goodyear CS, Barrett MP Abstract Priming and activating immune stimuli have profound effects on macrophages, however, studies generally evaluate stimuli in isolation rather than in combination. In this study we have investigated the effects of pro-inflammatory and anti-inflammatory stimuli either alone or in combination on macrophage metabolism. These stimuli include host factors such as IFNγ and ovalbumin-immunoglobulin immune complexes, or pathogen factors such as LPS. Untargeted LC-MS based metabolomics provided an in-depth profile of the macrophage metabolome, and revealed specific changes in metabolite abundance upon either individual stimuli or combined stimuli. Here, by factoring in an interaction term in the linear model, we define the metabolome interactome. This approach allowed us to determine whether stimuli interact in a synergistic or antagonistic manner. In conclusion this study demonstrates a robust approach to interrogate immune-metabolism, especially systems that model host-pathogen interactions. PMID: 29538444 [PubMed - in process]

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration. Methods Mol Biol. 2018;1754:265-292 Authors: Cheng J, Lan W, Zheng G, Gao X Abstract Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level. PMID: 29536449 [PubMed - in process]

Promises and pitfalls of untargeted metabolomics. J Inherit Metab Dis. 2018 Mar 13;: Authors: Gertsman I, Barshop BA Abstract Metabolomics is one of the newer omics fields, and has enabled researchers to complement genomic and protein level analysis of disease with both semi-quantitative and quantitative metabolite levels, which are the chemical mediators that constitute a given phenotype. Over more than a decade, methodologies have advanced for both targeted (quantification of specific analytes) as well as untargeted metabolomics (biomarker discovery and global metabolite profiling). Untargeted metabolomics is especially useful when there is no a priori metabolic hypothesis. Liquid chromatography coupled to mass spectrometry (LC-MS) has been the preferred choice for untargeted metabolomics, given the versatility in metabolite coverage and sensitivity of these instruments. Resolving and profiling many hundreds to thousands of metabolites with varying chemical properties in a biological sample presents unique challenges, or pitfalls. In this review, we address the various obstacles and corrective measures available in four major aspects associated with an untargeted metabolomics experiment: (1) experimental design, (2) pre-analytical (sample collection and preparation), (3) analytical (chromatography and detection), and (4) post-analytical (data processing). PMID: 29536203 [PubMed - as supplied by publisher]

Multiomics tools for the diagnosis and treatment of rare neurological disease. J Inherit Metab Dis. 2018 Mar 13;: Authors: Crowther LM, Poms M, Plecko B Abstract Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease. PMID: 29536202 [PubMed - as supplied by publisher]

Physiological and Metabolic Responses Triggered by Omeprazole Improve Tomato Plant Tolerance to NaCl Stress. Front Plant Sci. 2018;9:249 Authors: Rouphael Y, Raimondi G, Lucini L, Carillo P, Kyriacou MC, Colla G, Cirillo V, Pannico A, El-Nakhel C, De Pascale S Abstract Interest in the role of small bioactive molecules (< 500 Da) in plants is on the rise, compelled by plant scientists' attempt to unravel their mode of action implicated in stimulating growth and enhancing tolerance to environmental stressors. The current study aimed at elucidating the morphological, physiological and metabolomic changes occurring in greenhouse tomato (cv. Seny) treated with omeprazole (OMP), a benzimidazole inhibitor of animal proton pumps. The OMP was applied at three rates (0, 10, or 100 μM) as substrate drench for tomato plants grown under nonsaline (control) or saline conditions sustained by nutrient solutions of 1 or 75 mM NaCl, respectively. Increasing NaCl concentration from 1 to 75 mM decreased the tomato shoot dry weight by 49% in the 0 μM OMP treatment, whereas the reduction was not significant at 10 or 100 μM of OMP. Treatment of salinized (75 mM NaCl) tomato plants with 10 and especially 100 μM OMP decreased Na+ and Cl- while it increased Ca2+ concentration in the leaves. However, OMP was not strictly involved in ion homeostasis since the K+ to Na+ ratio did not increase under combined salinity and OMP treatment. OMP increased root dry weight, root morphological characteristics (total length and surface), transpiration, and net photosynthetic rate independently of salinity. Metabolic profiling of leaves through UHPLC liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry facilitated identification of the reprogramming of a wide range of metabolites in response to OMP treatment. Hormonal changes involved an increase in ABA, decrease in auxins and cytokinin, and a tendency for GA down accumulation. Cutin biosynthesis, alteration of membrane lipids and heightened radical scavenging ability related to the accumulation of phenolics and carotenoids were observed. Several other stress-related compounds, such as polyamine conjugates, alkaloids and sesquiterpene lactones, were altered in response to OMP. Although a specific and well-defined mechanism could not be posited, the metabolic processes involved in OMP action suggest that this small bioactive molecule might have a hormone-like activity that ultimately elicits an improved tolerance to NaCl salinity stress. PMID: 29535755 [PubMed]

Genome-Wide Association Study on Immunoglobulin G Glycosylation Patterns. Front Immunol. 2018;9:277 Authors: Wahl A, van den Akker E, Klaric L, Štambuk J, Benedetti E, Plomp R, Razdorov G, Trbojević-Akmačić I, Deelen J, van Heemst D, Slagboom PE, Vučković F, Grallert H, Krumsiek J, Strauch K, Peters A, Meitinger T, Hayward C, Wuhrer M, Beekman M, Lauc G, Gieger C Abstract Immunoglobulin G (IgG), a glycoprotein secreted by plasma B-cells, plays a major role in the human adaptive immune response and are associated with a wide range of diseases. Glycosylation of the Fc binding region of IgGs, responsible for the antibody's effector function, is essential for prompting a proper immune response. This study focuses on the general genetic impact on IgG glycosylation as well as corresponding subclass specificities. To identify genetic loci involved in IgG glycosylation, we performed a genome-wide association study (GWAS) on liquid chromatography electrospray mass spectrometry (LC-ESI-MS)-measured IgG glycopeptides of 1,823 individuals in the Cooperative Health Research in the Augsburg Region (KORA F4) study cohort. In addition, we performed GWAS on subclass-specific ratios of IgG glycans to gain power in identifying genetic factors underlying single enzymatic steps in the glycosylation pathways. We replicated our findings in 1,836 individuals from the Leiden Longevity Study (LLS). We were able to show subclass-specific genetic influences on single IgG glycan structures. The replicated results indicate that, in addition to genes encoding for glycosyltransferases (i.e., ST6GAL1, B4GALT1, FUT8, and MGAT3), other genetic loci have strong influences on the IgG glycosylation patterns. A novel locus on chromosome 1, harboring RUNX3, which encodes for a transcription factor of the runt domain-containing family, is associated with decreased galactosylation. Interestingly, members of the RUNX family are cross-regulated, and RUNX3 is involved in both IgA class switching and B-cell maturation as well as T-cell differentiation and apoptosis. Besides the involvement of glycosyltransferases in IgG glycosylation, we suggest that, due to the impact of variants within RUNX3, potentially mechanisms involved in B-cell activation and T-cell differentiation during the immune response as well as cell migration and invasion involve IgG glycosylation. PMID: 29535710 [PubMed]

Quality Variation of Goji (Fruits of Lycium spp.) in China: A Comparative Morphological and Metabolomic Analysis. Front Pharmacol. 2018;9:151 Authors: Yao R, Heinrich M, Zou Y, Reich E, Zhang X, Chen Y, Weckerle CS Abstract Goji (fruits of Lycium barbarum L. and L. chinense Mill.) has been used in China as food and medicine for millennia, and globally has been consumed increasingly as a healthy food. Ningxia, with a semi-arid climate, always had the reputation of producing best goji quality (daodi area). Recently, the increasing market demand pushed the cultivation into new regions with different climates. We therefore ask: How does goji quality differ among production areas of various climatic regions? Historical records are used to trace the spread of goji production in China over time. Quality measurements of 51 samples were correlated with the four main production areas in China: monsoon (Hebei), semi-arid (Ningxia, Gansu, and Inner Mongolia), plateau (Qinghai) and arid regions (Xinjiang). We include morphological characteristics, sugar and polysaccharide content, antioxidant activity, and metabolomic profiling to compare goji among climatic regions. Goji cultivation probably began in the East (Hebei) of China around 100 CE and later shifted westward to the semi-arid regions. Goji from monsoon, plateau and arid regions differ according to its fruit morphology, whereas semi-arid goji cannot be separated from the other regions. L. chinense fruits, which are exclusively cultivated in Hebei (monsoon), are significantly lighter, smaller and brighter in color, while the heaviest and largest fruits (L. barbarum) stem from the plateau. The metabolomic profiling separates the two species but not the regions of cultivation. Lycium chinense and samples from the semi-arid regions have significantly (p < 0.01) lower sugar contents and L. chinense shows the highest antioxidant activity. Our results do not justify superiority of a specific production area over other areas. Instead it will be essential to distinguish goji from different regions based on the specific morphological and chemical traits with the aim to understand what its intended uses are. PMID: 29535631 [PubMed]

Comparative metabolism of tripolide and triptonide using metabolomics. Food Chem Toxicol. 2018 Mar 10;: Authors: Hu DD, Chen XL, Xiao XR, Wang YK, Liu F, Zhao Q, Li X, Yang XW, Li F PMID: 29534979 [PubMed - as supplied by publisher]

Laboratory evolution reveals regulatory and metabolic trade-offs of glycerol utilization in Saccharomyces cerevisiae. Metab Eng. 2018 Mar 10;: Authors: Strucko T, Zirngibl K, Pereira F, Kafkia E, Mohamed ET, Rettel M, Stein F, Feist AM, Jouhten P, Patil KR, Forster J Abstract Most microbial species, including model eukaryote Saccharomyces cerevisiae, possess genetic capability to utilize many alternative nutrient sources. Yet, it remains an open question whether these manifest into assimilatory phenotypes. Despite possessing all necessary pathways, S. cerevisiae grows poorly or not at all when glycerol is the sole carbon source. Here we discover, through multiple evolved lineages, genetic determinants underlying glycerol catabolism and the associated fitness trade-offs. Most evolved lineages adapted through mutations in the HOG pathway, but showed hampered osmotolerance. In the other lineages, we find that only three mutations cause the improved phenotype. One of these contributes counter-intuitively by decoupling the TCA cycle from oxidative phosphorylation, and thereby hampers ethanol utilization. Transcriptomics, proteomics and metabolomics analysis of the re-engineered strains affirmed the causality of the three mutations at molecular level. Introduction of these mutations resulted in improved glycerol utilization also in industrial strains. Our findings not only have a direct relevance for improving glycerol-based bioprocesses, but also illustrate how a metabolic pathway can remain unexploited due to fitness trade-offs in other, ecologically important, traits. PMID: 29534903 [PubMed - as supplied by publisher]

Nanoparticle-Assisted Metabolomics. Metabolites. 2018 Mar 13;8(1): Authors: Zhang B, Xie M, Bruschweiler-Li L, Brüschweiler R Abstract Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics. PMID: 29533993 [PubMed]

Quantitation of the anticancer drug abiraterone and its metabolite Δ(4)-abiraterone in human plasma using high-resolution mass spectrometry. J Pharm Biomed Anal. 2018 Mar 06;154:66-74 Authors: Bhatnagar A, McKay MJ, Crumbaker M, Ahire K, Karuso P, Gurney H, Molloy MP Abstract Abiraterone acetate is administered as a prodrug to patients with metastatic, castration-resistant prostate cancer (mCRPC) and is readily metabolized into the potent 17a-hydroxylase/17,20-lyase (CYP17) enzyme inhibitor and androgen receptor inhibitor abiraterone and Δ(4)-abiraterone (D4A), respectively. To investigate pharmacokinetic variability in abiraterone acetate metabolism we developed highly sensitive liquid chromatography/mass spectrometry (LC/MS) assays for the simultaneous quantitation of abiraterone and D4A in human plasma using high-resolution mass spectrometry (HRMS) on an Orbitrap mass spectrometer. This study demonstrates the quantitative performance of HRMS and compares the conventional Parallel Reaction Monitoring (PRM) mode of quantitation with the unconventional Full scan MS mode conducted at high resolution (>70,000 resolution). The use of HRMS for quantitation of abiraterone and D4A yielded assays that were linear over a broad concentration range (0.074-509.6 ng/mL for abiraterone; 0.075-59.93 ng/mL for D4A) in both Full scan MS and PRM modes. The assay precision for abiraterone and D4A was below 5% in PRM mode and 7% in Full scan MS mode. Accuracies fell within 98-107% for abiraterone and 104-112% for D4A in PRM mode, and 96-116% for abiraterone and 96-105% for D4A in Full scan MS mode, each meeting the acceptance criteria of FDA approved guidelines for bioanalytical methods The PRM analysis of abiraterone and D4A provided high specificity and reduced background interference, however the Full scan MS detection at a resolution of 70,000 was advantageous in that it required minimal optimization, was simple to implement, yielded comparable quantitative characteristics to PRM and the data is useful for re-analysis. Use of the assays were demonstrated for quantitation of these metabolites in steady state trough level plasma of seventeen (17) patients with mCRPC, demonstrating the inter-patient variability of up to 10-fold concentration. PMID: 29533860 [PubMed - as supplied by publisher]