PubMed

Related Articles Combined Metabolomics and Genome-Wide Transcriptomics Analyses Show Multiple HIF1α-Induced Changes in Lipid Metabolism in Early Stage Clear Cell Renal Cell Carcinoma. Transl Oncol. 2019 Dec 19;13(2):177-185 Authors: van der Mijn JC, Fu L, Khani F, Zhang T, Molina AM, Barbieri CE, Chen Q, Gross SS, Gudas LJ, Nanus DM Abstract The accumulation of lipids is a hallmark of human clear cell renal cell carcinoma (ccRCC). Advanced ccRCC tumors frequently show increased lipid biosynthesis, but the regulation of lipid metabolism in early stage ccRCC tumors has not been studied. Here, we performed combined transcriptomics and metabolomics on a previously characterized transgenic mouse model (TRAnsgenic Cancer of the Kidney, TRACK) of early stage ccRCC. We found that in TRACK kidneys, HIF1α activation increases transcripts of lipid receptors (Cd36, ACVRL1), lipid storage genes (Hilpda and Fabp7), and intracellular levels of essential fatty acids, including linoleic acid and linolenic acid. Feeding the TRACK mice a high-fat diet enhances lipid accumulation in the kidneys. These results show that HIF1α increases the uptake and storage of dietary lipids in this early stage ccRCC model. By then analyzing early stage human ccRCC specimens, we found similar increases in CD36 transcripts and increases in linoleic and linolenic acid relative to normal kidney samples. CD36 mRNA levels decreased, while FASN transcript levels increased with increasing ccRCC tumor stage. These results suggest that an increase in the lipid biosynthesis pathway in advanced ccRCC tumors may compensate for a decreased capacity of these advanced ccRCCs to scavenge extracellular lipids. PMID: 31865180 [PubMed - as supplied by publisher]

Related Articles Silybin ameliorates hepatic lipid accumulation and modulates global metabolism in an NAFLD mouse model. Biomed Pharmacother. 2019 Dec 19;123:109721 Authors: Sun R, Xu D, Wei Q, Zhang B, Aa J, Wang G, Xie Y Abstract Silybin shows good effects against obesity and metabolic syndrome, but the systemic modulation effect of silybin has not been fully revealed. This study aims to investigate the metabolic regulation by silybin of nonalcoholic fatty liver disease (NAFLD). C57BL/6 J mice were fed a high-fat/high-cholesterol diet for 8 weeks and treated with silybin (50 or 100 mg/kg/day) and sodium tauroursodeoxycholate (TUDCA, 50 mg/kg/day) by gavage for the last 4 weeks. Blood biochemical indexes and hepatic lipid measurement as well as Oil red O staining of the liver were conducted to evaluate the model and the lipid-lowering effect of silybin and TUDCA. Furthermore, serum and liver samples were detected by a metabolomic platform based on gas chromatography-mass spectrometry (GC/MS). Multivariate/univariate data analysis and pathway analysis were used to investigate differential metabolites and metabolic pathways. The results showed that the mouse NAFLD model was established successfully and that silybin and TUDCA significantly lowered both serum and hepatic lipid accumulation. Metabolomic analysis of serum and liver showed that a high-fat/high-cholesterol diet caused abnormal metabolism of metabolites involved in lipid metabolism, polyol metabolism, amino acid metabolism, the urea cycle and the TCA cycle. Silybin and TUDCA treatment both reversed metabolic disorders caused by HFD feeding. In conclusion, a high-fat/high-cholesterol diet caused metabolic abnormalities in the serum and liver of mice, and silybin treatment improved hepatic lipid accumulation and modulated global metabolic pathways, which provided a possible explanation of its multiple target mechanism. PMID: 31865143 [PubMed - as supplied by publisher]

Related Articles De Novo Peptide Sequencing Reveals Many Cyclopeptides in the Human Gut and Other Environments. Cell Syst. 2019 Dec 12;: Authors: Behsaz B, Mohimani H, Gurevich A, Prjibelski A, Fisher M, Vargas F, Smarr L, Dorrestein PC, Mylne JS, Pevzner PA Abstract Cyclic and branch cyclic peptides (cyclopeptides) represent a class of bioactive natural products that include many antibiotics and anti-tumor compounds. Despite the recent advances in metabolomics analysis, still little is known about the cyclopeptides in the human gut and their possible interactions due to a lack of computational analysis pipelines that are applicable to such compounds. Here, we introduce CycloNovo, an algorithm for automated de novo cyclopeptide analysis and sequencing that employs de Bruijn graphs, the workhorse of DNA sequencing algorithms, to identify cyclopeptides in spectral datasets. CycloNovo reconstructed 32 previously unreported cyclopeptides (to the best of our knowledge) in the human gut and reported over a hundred cyclopeptides in other environments represented by various spectra on Global Natural Products Social Molecular Network (GNPS). https://github.com/bbehsaz/cyclonovo. PMID: 31864964 [PubMed - as supplied by publisher]

Related Articles Hepatic one-carbon metabolism enzyme activities and intermediate metabolites are altered by prepartum body condition score and plane of nutrition in grazing Holstein dairy cows. J Dairy Sci. 2019 Dec 18;: Authors: Vailati-Riboni M, Crookenden M, Kay JK, Meier S, Mitchell MD, Heiser A, Roche JR, Loor JJ Abstract Precalving feeding level and body condition score (BCS) alter postcalving energy balance and oxidant status of dairy cows. We hypothesized that the reported benefits of a controlled restriction precalving depend on precalving BCS. The objective was to identify alterations in activity and intermediates of the hepatic one-carbon metabolism, transsulfuration, and tricarboxylic acid pathways. Twenty-eight pregnant and nonlactating grazing dairy cows of mixed age and breed (Friesian, Friesian × Jersey) were randomly allocated to 1 of 4 treatment groups in a 2 × 2 factorial design: 2 prepartum BCS categories [4.0 (thin, BCS4) and 5.0 (optimal, BCS5); 10-point scale], by managing cows in late lactation to achieve the 2 groups at dry-off, and 2 levels of energy intake during the 3 wk preceding calving (75 or 125% of estimated requirements), obtained via allowance (m2/cow) of fresh pasture composed of mostly perennial ryegrass and white cover. Average (± standard deviation) age was 6 ± 2, 6 ± 3, 5 ± 1, and 7 ± 3 yr for BCS4 fed 75 and 125%, and BCS5 fed 75 and 125%, respectively. Breed distribution (average ± standard deviation) for the 4 groups was 79 ± 21, 92 ± 11, 87 ± 31, and 74 ± 23% Friesian, and 17 ± 20, 8 ± 11, 13 ± 31, and 25 ± 23% Jersey. Liver tissue was collected by biopsy at -7, 7, and 28 d relative to calving. Tissue was used for 14C radio-labeling assays to measure betaine-homocysteine S-methyltransferase, 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and cystathionine-β-synthase (CBS) activity. Liver metabolomics was undertaken using a targeted liquid chromatography with tandem mass spectrometry-based profiling approach. After initial liquid chromatography separation, mass spectra were acquired under both positive and negative ionization, whereas multiple reaction monitoring was used to measure target compound signal response (peak area count). Enzyme activity and metabolite peak area count were normalized with the homogenate protein concentration. Repeated measures analysis of variance via PROC MIXED in SAS (SAS Institute Inc., Cary, NC), with BCS, feeding, and time as fixed effects, and cow as random effect was used. All enzyme activities were affected by time, with betaine-homocysteine S-methyltransferase activity peaking at 7 d, whereas CBS and MTR activity decreased postpartum. Overall, thin cows had greater MTR activity, whereas cows fed 125% requirements had greater CBS activity. An interaction was detected between BCS and feeding for CBS activity, as thin cows fed 125% of requirements had greater overall activity. Compared with liver from BCS4 cows, BCS5 cows had overall greater betaine, glycine, butyrobetaine/acetylcholine, serine, and taurine concentrations. The same metabolites, plus choline and N-N-dimethylglycine, were overall greater in liver of cows fed 75% compared with those fed 125% of requirements. An interaction of BCS and feeding level was detected for the aforementioned metabolites plus methionine, cystathionine, cysteinesulfinate, and hypotaurine, due to greater overall concentrations in BCS5 cows fed 75% of requirements compared with other groups. Overall, differences in hepatic enzyme activity and intermediate metabolites suggest that both BCS and feeding level can alter the internal antioxidant system (e.g., glutathione and taurine) throughout the periparturient period. Further studies are needed to better understand potential mechanisms involved. PMID: 31864735 [PubMed - as supplied by publisher]

Related Articles A comprehensive automatic data analysis strategy for gas chromatography-mass spectrometry based untargeted metabolomics. J Chromatogr A. 2019 Dec 12;:460787 Authors: Zhang YY, Zhang Q, Zhang YM, Wang WW, Zhang L, Yu YJ, Bai CC, Guo JZ, Fu HY, She Y Abstract Automatic data analysis for gas chromatography-mass spectrometry (GC-MS) is a challenging task in untargeted metabolomics. In this work, we provide a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (autoGCMSDataAnal) by developing a new automatic strategy for performing TIC peak detection and resolution and proposing a novel time-shift correction and component registration algorithm. autoGCMSDataAnal uses original acquired GC-MS datafiles as input to automatically perform TIC peak detection, component resolution, time-shift correction and component registration, statistical analysis, and compound identification. We utilize standards and complex plant samples to comprehensively investigate the performance of autoGCMSDataAnal. The results suggest that the developed strategy is comparable with several state-of-the-art methods that are widely used in GC-MS-based untargeted metabolomics. Based on the proposed strategy, we develop a user-friendly MATLAB GUI for users who are unfamiliar with programming languages to facilitate their routine analysis, which can be freely downloaded at: http://software.tobaccodb.org/software/autogcmsdataanal. PMID: 31864723 [PubMed - as supplied by publisher]

Related Articles Metabolomics study of the prefrontal cortex in a rat model of attention deficit hyperactivity disorder reveals the association between cholesterol metabolism disorder and hyperactive behavior. Biochem Biophys Res Commun. 2019 Dec 18;: Authors: Chen T, Yuan H, Sun YB, Song YC, Lu M, Ni X, Han X Abstract Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disease for which specific biomarkers and pathological mechanisms have yet to be identified. Methylphenidate (MPH) is commonly used to treat ADHD, but its therapeutic mechanisms and its impact on brain metabolites remain unclear. Metabolomics can help to discover biomarkers and identify pathophysiological mechanisms. We adopted an untargeted metabolomics approach based on gas chromatography-mass spectrometry to investigate the potential biomarkers and pathogenesis of ADHD. Ten Wistar-Kyoto (WKY) rats were chosen as healthy controls (vehicle, i.g.). Twenty young spontaneously hypertensive rats (SHR) were randomly allocated to the SHR group (vehicle, i.g.) and MPH group (2 mg/kg/day, i.g.). We identified 103 metabolites from the prefrontal cortex (PFC). Orthogonal partial least square-discriminate analysis showed the differential expression of these metabolites between the groups. Multivariate and univariate statistical analyses isolated 12 metabolites that differed significantly between the WKY and SHR groups: 3-hydroxymethylglutaric acid, 3-phosphoglyceric acid, adenosine monophosphate, cholesterol, lanosterol, and o-phosphoethanolamine; 3-hydroxymethylglutaric acid and cholesterol were reversed with MPH treatment. Pathway and enrichment analyses revealed that the altered metabolites belonged to the cholesterol metabolism pathways. ELISA and western blotting showed that the activity of 3-hydroxy-3-methyl-glutaryl-CoA reductase and the expression of sterol regulatory element-binding protein-2 and ATP-binding cassette transporter A1 were reduced in the PFC of the SHR; the latter two proteins were upregulated by MPH. In conclusion, metabolomics analysis identified potential biomarkers that influence cholesterol metabolism and may be implicated in the development of ADHD-like behavior. MPH can regulate cholesterol metabolism in the PFC of ADHD models. This study uncovered potential biomarkers and pathways involved in ADHD, providing new insight into its pathogenesis. PMID: 31864712 [PubMed - as supplied by publisher]

Related Articles Composite score analysis for unsupervised comparison and network visualization of metabolomics data. Anal Chim Acta. 2020 Jan 25;1095:38-47 Authors: Kellogg JJ, Kvalheim OM, Cech NB Abstract Metabolomics-based approaches are becoming increasingly popular to interrogate the chemical basis for phenotypic differences in biological systems. Successful metabolomics studies employ multivariate data analysis to compare large and highly complex datasets. A primary tool for unsupervised statistical analyses, principal component analysis (PCA), relies on the selection of a subsection of a maximum of three components from a larger model to visually represent similarity. The use of only three principal components limits the comprehensiveness of the model and can mask discrimination between samples. We have developed a new statistical metric, the composite score (CS), as a univariate statistic that incorporates multiple principal components to calculate a correlation matrix that enables quantitative comparisons of sample similarity between samples within one dataset based upon measured metabolome profiles. Composite score values were tabulated using profiles of complex extracts of dietary supplements from the plant Hydrastis canadensis (goldenseal) as a case study. Several outliers were unambiguously identified, and a PCA composite score network was developed to provide a graphical representation of the composite score matrix. Comparison with visualization using PCA score plots or dendrograms from hierarchical clustering analysis (HCA) demonstrates the utility of the composite score to as a tool for metabolomics studies that seek to quantify similarity among samples. An R-script for the calculation of composite score has been made available. PMID: 31864629 [PubMed - in process]

17 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/12/22PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition. PLoS Biol. 2019 Dec 20;17(12):e3000572 Authors: Kettunen J, Holmes MV, Allara E, Anufrieva O, Ohukainen P, Oliver-Williams C, Wang Q, Tillin T, Hughes AD, Kähönen M, Lehtimäki T, Viikari J, Raitakari OT, Salomaa V, Järvelin MR, Perola M, Davey Smith G, Chaturvedi N, Danesh J, Di Angelantonio E, Butterworth AS, Ala-Korpela M Abstract Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very LDL (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18-26 nm) (-0.02 SD LDL defined by particle size; 95% CI: -0.10 to 0.05 for CETP versus -0.24 SD, 95% CI -0.30 to -0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18-1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies. PMID: 31860674 [PubMed - as supplied by publisher]

Related Articles In situ metabolomics of the honeybee brain: the metabolism of L-arginine through the polyamine pathway in the proboscis extension response (PER). J Proteome Res. 2019 Dec 20;: Authors: Pratavieira M, da Silva Menegasso AR, Roat T, Malaspina O, Palma MS Abstract The proboscis extension response (PER) reflex may be used to condition the pairing of an odor with sucrose, which is applied to the antennae, in experiments to induce learning, where the odor represents a conditioned stimulus, while sucrose represents an unconditioned stimulus. A series of studies have been conducted with honeybees relating learning and memory acquisition / retrieval using the PER as a strategy for accessing their ability to exhibit an unconditioned stimulus; however, the major metabolic processes involved in the PER are not well known. Thus, the aim of this investigation is profiling the metabolome of the honeybee brain involved in the PER. In the present study, a semiquantitative approach of MALDI mass spectral imaging (MSI) was used to profile the most abundant metabolites of the honeybee brain that support the PER. It was reported that execution of the PER requires the metabolic transformations of arginine, ornithine, and lysine as substrates for the production of putrescine, cadaverine, spermine, spermidine, 1,3-diaminopropane, and GABA. Considering the global metabolome of the brain of honeybee workers, the PER requires the consumption of large amounts of cadaverine and 1,3-diaminopropane, in parallel with the biosynthesis of high amounts of spermine, spermidine, and ornithine. To exhibit the PER, the brain of honeybee workers processes the conversion of L-arginine and L-lysine through the polyamine pathway, with different regional metabolomic profiles at the individual neuropil level. Using this metabolic route as a reference, the outcomes of the this study are indicating that the antennal lobes and the calices (medial and lateral) were the most active brain regions for supporting the PER. PMID: 31859515 [PubMed - as supplied by publisher]

Related Articles Nuclear magnetic resonance (NMR)-based metabolome profile evaluation in dairy cows with and without displaced abomasum. Vet Q. 2019 Dec 20;:1-18 Authors: Basoglu A, Baspinar N, Tenori L, Licari C, Gulersoy E Abstract Background: Displaced abomasum (DA) is a condition of dairy cows that severely impacts animal welfare and causes huge economic losses.Objective: To assess the metabolic status of the disease using metabolomics in serum, urine and liver samples aimed at both water soluble and lipid soluble fractions.Methods: Fifty Holstein multiparous cows with DA (42 left, 8 right) and 20 clinically healthy Holstein multiparous cows were used. Left DA was associated with concomitant ketosis in 19 animals and right in two. NMR-based metabolomics approach and hematological and biochemical analyses were performed. Statistical analysis was carried out on 1HNMR data after they have been normalized using PQN method.Results: Contrary to generated PCA score plots the OPLS-supervised method revealed differences between healthy animals and diseased ones based on serum water-soluble samples. While water and lipid soluble metabolites decreased in serum samples, fatty acid fractions and cholesterol were increased in liver samples in DA affected cows. The metabolomic and chemical profiles clearly revealed that cows with DA (especially with LDA) were at risk of ketosis and fatty liver. Serum hippuric acid concentration was significantly higher in healthy cows in comparison with LDA, whereas serum glycine concentration was reported higher for healthy when compared to RDA affected animals.Conclusion: A biochemical network and pathway mapping revealed 'valine, leucine and isoleucine biosynthesis' and 'phenylalanine, tyrosine and tryptophan biosynthesis' as the most probable altered metabolic pathway in DA condition. Serum was advocated as the optimal biological matrix for the 1H-NMR analysis. PMID: 31858882 [PubMed - as supplied by publisher]

Related Articles A metabolomics strategy for authentication of plant medicines with multiple botanical origins, a case study of Uncariae Rammulus Cum Uncis. J Sep Sci. 2019 Dec 19;: Authors: Pan H, Yao C, Yao S, Yang W, Wu W, Guo DA Abstract Source authentication of herbal medicines was essential for ensuring their safety, efficacy and quality consistency, especially those with multiple botanical origins. This study proposed a metabolomics strategy for species discrimination and source recognition. Uncariae Rammulus Cum Uncis, officially stipulating the stems with hooks of five Uncaria species as its origins, was taken as a case study. Firstly, an untargeted MSE method was developed by ultra-high performance liquid chromatography hyphenated with quadrupole time-of-flight mass spectrometry for global metabolite characterization. Subsequently, data pretreatment was conducted by using a Progenesis QI software and screening rules. The obtained metabolite features were defined as variables for statistical analyses. Principal component analysis and chemical fingerprinting spectra suggested that five official species were differentiated from each other except for Uncaria hirsuta and Uncaria sinensis. Furthermore, orthogonal partial least squares discrimination analysis was performed to discriminate confused two species, and resulted in the discovery of nine contributing markers. Ultimately, a Support Vector Machine model was developed to recognize five species and predict origins of commercial materials. The study demonstrated that the developed strategy was effective in discrimination and recognition of confused species, and promising in tracking botanical origins of commercial materials. This article is protected by copyright. All rights reserved. PMID: 31858716 [PubMed - as supplied by publisher]

Related Articles Sportomics: metabolomics applied to sports. The new revolution? Eur Rev Med Pharmacol Sci. 2019 Dec;23(24):11011-11019 Authors: Bongiovanni T, Pintus R, Dessì A, Noto A, Sardo S, Finco G, Corsello G, Fanos V Abstract Sportomics is the application of metabolomics in sports to investigate the metabolic effects of physical exercise on individuals, whether they are professional athletes or not. Metabolomics is one of the "omics" sciences that provide a picture of the metabolic state of a person in physiological or pathological conditions. This is achieved through the analysis of metabolites present in a biological fluid, such as saliva, blood, feces, and urine. The authors revised the recent literature concerning this topic and discussed the useful information that sportomics can provide and the limits of the current experimental settings. Furthermore, in the future, sportomics analyses could be used to prevent and manage injuries as it would be known in advance if an athlete is more prone to experience muscular damage or fatigue. Following more trials, it would also be possible to set the best diet and training programs to get the best performances out of the athletes. Moreover, based on their metabolic profiles, both adults and children could choose tailored physical training in order to preserve and improve their health. PMID: 31858572 [PubMed - in process]

Related Articles A Computational Statistics Approach to Evaluate Blood Biomarkers for Breast Cancer Risk Stratification. Horm Cancer. 2019 Dec 19;: Authors: Oktay K, Santaliz-Casiano A, Patel M, Marino N, Storniolo AMV, Torun H, Acar B, Madak Erdogan Z Abstract Breast cancer is the second leading cause of cancer mortality among women. Mammography and tumor biopsy followed by histopathological analysis are the current methods to diagnose breast cancer. Mammography does not detect all breast tumor subtypes, especially those that arise in younger women or women with dense breast tissue, and are more aggressive. There is an urgent need to find circulating prognostic molecules and liquid biopsy methods for breast cancer diagnosis and reducing the mortality rate. In this study, we systematically evaluated metabolites and proteins in blood to develop a pipeline to identify potential circulating biomarkers for breast cancer risk. Our aim is to identify a group of molecules to be used in the design of portable and low-cost biomarker detection devices. We obtained plasma samples from women who are cancer free (healthy) and women who were cancer free at the time of blood collection but developed breast cancer later (susceptible). We extracted potential prognostic biomarkers for breast cancer risk from plasma metabolomics and proteomics data using statistical and discriminative power analyses. We pre-processed the data to ensure the quality of subsequent analyses, and used two main feature selection methods to determine the importance of each molecule. After further feature elimination based on pairwise dependencies, we measured the performance of logistic regression classifier on the remaining molecules and compared their biological relevance. We identified six signatures that predicted breast cancer risk with different specificity and selectivity. The best performing signature had 13 factors. We validated the difference in level of one of the biomarkers, SCF/KITLG, in plasma from healthy and susceptible individuals. These biomarkers will be used to develop low-cost liquid biopsy methods toward early identification of breast cancer risk and hence decreased mortality. Our findings provide the knowledge basis needed to proceed in this direction. PMID: 31858384 [PubMed - as supplied by publisher]

Related Articles Citrate NMR peak irreproducibility in blood samples after reacquisition of spectra. Metabolomics. 2019 Dec 19;16(1):7 Authors: Hanifa MA, Maltesen RG, Rasmussen BS, Buggeskov KB, Ravn HB, Skott M, Nielsen S, Frøkiær J, Ring T, Wimmer R Abstract BACKGROUND: In our metabolomics studies we have noticed that repeated NMR acquisition on the same sample can result in altered metabolite signal intensities. AIMS: To investigate the reproducibility of repeated NMR acquisition on selected metabolites in serum and plasma from two large human metabolomics studies. METHODS: Two peak regions for each metabolite were integrated and changes occurring after reacquisition were correlated. RESULTS: Integral changes were generally small, but serum citrate signals decreased significantly in some samples. CONCLUSIONS: Several metabolite integrals were not reproducible in some of the repeated spectra. Following established protocols, randomising analysis order and biomarker validation are important. PMID: 31858270 [PubMed - in process]

Related Articles Accumulation of Carboxylate and Aromatic Fluorophores by a Pest-Resistant Sweet Sorghum [Sorghum bicolor (L.) Moench] Genotype. ACS Omega. 2019 Dec 10;4(24):20519-20529 Authors: Uchimiya M, Knoll JE Abstract The sugary juice from sweet sorghum [Sorghum bicolor (L.) Moench] stalks can be used to produce edible syrup, biofuels, or bio-based chemical feedstock. The current cultivars are highly susceptible to damage from sugarcane aphids [Melanaphis sacchari (Zehntner)], but development of new cultivars is hindered by a lack of rapid analytical methods to screen for juice quality traits. The mechanism of aphid resistance/tolerance is also largely unknown, though the importance of defense phytochemicals has been suggested. The purpose of this study was to develop low-cost methods sensitive to fluorescent fingerprints in sweet sorghum juice, which is a complex mixture of saccharides, carboxylates, polyphenols, and metal ions. Of primary juice components, tryptophan and trans-aconitic acid were the highest intensity contributors to the overall fluorescence and UV/visible absorbance, respectively, while tyrosine and polyphenols contributed to a less extent. In a test of 24 sweet sorghum cultivars, tryptophan and tyrosine contents were the highest in the aphid-susceptible hybrid N109A x Chinese, while sucrose, trans-aconitic acid, and polyphenols were the highest in the resistant line No. 5 Gambela. This suggests that the accumulation of carboxylate (trans-aconitic acid) and polyphenolic secondary products in No. 5 Gambela may contribute to its aphid resistance, thus allowing it to maintain sucrose production. Rapid detection of these chemical signatures could be used to prescreen the breeding material for potential resistance and juice quality traits, without analytical separation required for metabolomics. PMID: 31858036 [PubMed]

Related Articles Biomarkers in Autism Spectrum Disorders: Current Progress. Clin Chim Acta. 2019 Dec 16;: Authors: Shen L, Liu X, Zhang H, Lin J, Feng C, Iqbal J Abstract Autism spectrum disorder (ASD) refers to a group of complex neurodevelopmental disorders characterized by social interaction and communication deficits and repetitive and stereotyped behaviors. As the etiology and pathogenesis of the disorder have not yet been elucidated, specific treatment and reliable diagnostic biomarkers are not available. Early behavioral interventions have been shown to substantially improve symptoms in children with ASD. Given the rapidly increasing prevalence of ASD, there is an urgent need to identify related diagnostic biomarkers. Although specific diagnostic markers for ASD have not been identified, the related research has made progress in different aspects. This review summarizes recent findings of the use of genes, proteins, peptides, and metabolites as diagnostic markers for ASD. The associated techniques include genetic testing and proteomic and metabolomic analyses. In addition, some studies have focused on single or several proteins and metabolites. Moreover, transcriptomic analysis, immune disturbances and cytokine may also be used for this purpose. The pathogenesis involving genes, proteins, and metabolites is also discussed here. PMID: 31857069 [PubMed - as supplied by publisher]

Related Articles Combining transcriptomics and metabolomics to reveal the underlying molecular mechanism of ergosterol biosynthesis during the fruiting process of Flammulina velutipes. BMC Genomics. 2019 Dec 19;20(1):999 Authors: Wang R, Ma P, Li C, Xiao L, Liang Z, Dong J Abstract BACKGROUND: Flammulina velutipes has been recognized as a useful basidiomycete with nutritional and medicinal values. Ergosterol, one of the main sterols of F. velutipes is an important precursor of novel anticancer and anti-HIV drugs. Therefore, many studies have focused on the biosynthesis of ergosterol and have attempted to upregulate its content in multiple organisms. Great progress has been made in understanding the regulation of ergosterol biosynthesis in Saccharomyces cerevisiae. However, this molecular mechanism in F. velutipes remains largely uncharacterized. RESULTS: In this study, nine cDNA libraries, prepared from mycelia, young fruiting bodies and mature fruiting bodies of F. velutipes (three replicate sets for each stage), were sequenced using the Illumina HiSeq™ 4000 platform, resulting in at least 6.63 Gb of clean reads from each library. We studied the changes in genes and metabolites in the ergosterol biosynthesis pathway of F. velutipes during the development of fruiting bodies. A total of 13 genes (6 upregulated and 7 downregulated) were differentially expressed during the development from mycelia to young fruiting bodies (T1), while only 1 gene (1 downregulated) was differentially expressed during the development from young fruiting bodies to mature fruiting bodies (T2). A total of 7 metabolites (3 increased and 4 reduced) were found to have changed in content during T1, and 4 metabolites (4 increased) were found to be different during T2. A conjoint analysis of the genome-wide connection network revealed that the metabolites that were more likely to be regulated were primarily in the post-squalene pathway. CONCLUSIONS: This study provides useful information for understanding the regulation of ergosterol biosynthesis and the regulatory relationship between metabolites and genes in the ergosterol biosynthesis pathway during the development of fruiting bodies in F. velutipes. PMID: 31856715 [PubMed - in process]

Related Articles Identification of Auxin Metabolites in Brassicaceae by Ultra-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry. Molecules. 2019 Jul 18;24(14): Authors: Revelou PK, Kokotou MG, Constantinou-Kokotou V Abstract Auxins are signaling molecules involved in multiple stages of plant growth and development. The levels of the most important auxin, indole-3-acetic acid (IAA), are regulated by the formation of amide and ester conjugates with amino acids and sugars. In this work, IAA and IAA amide conjugates with amino acids bearing a free carboxylic group or a methyl ester group, along with some selected IAA metabolites, were studied in positive and negative electrospray ionization (ESI) modes, utilizing high-resolution mass spectrometry (HRMS) as a tool for their structural analysis. HRMS/MS spectra revealed the fragmentation patterns that enable us to identify IAA metabolites in plant extracts from eight vegetables of the Brassicaceae family using a fast and reliable ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS) method. The accurate m/z (mass to charge) ratio and abundance of the molecular and fragment ions of the studied compounds in plant extracts matched those obtained from commercially available or synthesized compounds and confirmed the presence of IAA metabolites. PMID: 31323791 [PubMed - indexed for MEDLINE]

Related Articles Drug monitoring of tamoxifen metabolites predicts vaginal dryness and verifies a low discontinuation rate from the Norwegian Prescription Database. Breast Cancer Res Treat. 2019 Aug;177(1):185-195 Authors: Helland T, Hagen KB, Haugstøyl ME, Kvaløy JT, Lunde S, Lode K, Lind RA, Gripsrud BH, Jonsdottir K, Gjerde J, Bifulco E, Hustad S, Jonassen J, Aas T, Lende TH, Lien EA, Janssen EAM, Søiland H, Mellgren G Abstract PURPOSE: Tamoxifen is an important targeted endocrine therapy in breast cancer. However, side effects and early discontinuation of tamoxifen remains a barrier for obtaining the improved outcome benefits of long-term tamoxifen treatment. Biomarkers predictive of tamoxifen side effects remain unidentified. The objective of this prospective population-based study was to investigate the value of tamoxifen metabolite concentrations as biomarkers for side effects. A second objective was to assess the validity of discontinuation rates obtained through pharmacy records with the use of tamoxifen drug monitoring. METHODS: Longitudinal serum samples, patient-reported outcome measures and pharmacy records from 220 breast cancer patients were obtained over a 6-year period. Serum concentrations of tamoxifen metabolites were measured by LC-MS/MS. Associations between metabolite concentrations and side effects were analyzed by logistic regression and cross table analyses. To determine the validity of pharmacy records we compared longitudinal tamoxifen concentrations to discontinuation rates obtained through the Norwegian Prescription database (NorPD). Multivariable Cox regression models were performed to identify predictors of discontinuation. RESULTS: At the 2nd year of follow-up, a significant association between vaginal dryness and high concentrations of tamoxifen, Z-4'-OHtam and tam-NoX was identified. NorPD showed a tamoxifen-discontinuation rate of 17.9% at 5 years and drug monitoring demonstrated similar rates. Nausea, vaginal dryness and chemotherapy-naive status were significant risk factors for tamoxifen discontinuation. CONCLUSIONS: This real-world data study suggests that measurements of tamoxifen metabolite concentrations may be predictive of vaginal dryness in breast cancer patients and verifies NorPD as a reliable source of adherence data. PMID: 31144152 [PubMed - indexed for MEDLINE]