PubMed

Related Articles UPLC-QTOF/MS-based metabolomics analysis of plasma reveals an effect of Xue-Fu-Zhu-Yu capsules on blood-stasis syndrome in CHD rats. J Ethnopharmacol. 2019 Apr 25;:111908 Authors: Zhao Y, Nie S, Yi M, Wu N, Wang W, Zhang Z, Yao Y, Wang D Abstract ETHNOPHARMACOLOGICAL RELEVANCE: Blood-stasis syndrome (BSS) is a specific ZHENG type of coronary heart disease (CHD) in traditional Chinese medicine (TCM). The Xue-Fu-Zhu-Yu (XFZY) decoction is a common herbal formula that has been used for several centuries to treat BSS, but its mechanism has not been thoroughly elucidated to date. AIM OF THE STUDY: In this study, serum lipid, blood haemorheology and metabolomics analyses were performed to depict a complete profile of XFZY capsules for the treatment of CHD with BSS and to reveal the potential mechanism of the XFZY capsules. MATERIALS AND METHODS: The rat model of CHD with BSS was performed by combining high-fat diet (HFD) treatment with a left anterior descending coronary artery (LAD) ligation. After four weeks of treatment with XFZY capsules or simvastatin pills, an echocardiography was implemented for a therapeutic evaluation. Blood samples and heart tissues were then collected for further analyses. A UPLC-QTOF/MS-based metabolomics analysis of the plasma was performed, and all metabolic features were fit by PCA and OPLS-DA pattern for the biomarker screen. The identified biomarkers were later implemented into a metabolic pathway analysis. Furthermore, we used qRT-PCR and Western blotanalyses to verify the treatment effects of the XFZY capsules. RESULTS: A total of 49 metabolites (VIP>1.0, p < 0.05, RSD%<20%) were identified in the model rats, and 27 metabolites (VIP>1.0, p < 0.05, RSD%<20%) were identified in the XFZY-H rats. The results of the pathway analysis indicated that the XFZY capsules treated CHD primarily by regulating cardiac energy, phospholipid, polyunsaturated fatty acid (PUFA) and amino acid metabolism. In addition, blood viscosity and serum lipid assays suggested that XFZY capsules could decrease serum TG, TC, LDL-c and whole blood viscosity at a low shear rate. CONCLUSION: This study demonstrated that the XFZY capsule effectively decreases the serum lipid and whole blood viscosity in CHD with BSS. The underlying metabolic mechanism mainly included improving cardiac energy supply, reducing phospholipid peroxide, maintaining the PUFA metabolic balance and regulating amino acid metabolism. PMID: 31029757 [PubMed - as supplied by publisher]

Related Articles A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification. Gigascience. 2019 May 01;8(5): Authors: Chung RH, Kang CY Abstract BACKGROUND: An integrative multi-omics analysis approach that combines multiple types of omics data including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics has become increasing popular for understanding the pathophysiology of complex diseases. Although many multi-omics analysis methods have been developed for complex disease studies, only a few simulation tools that simulate multiple types of omics data and model their relationships with disease status are available, and these tools have their limitations in simulating the multi-omics data. RESULTS: We developed the multi-omics data simulator OmicsSIMLA, which simulates genomics (i.e., single-nucleotide polymorphisms [SNPs] and copy number variations), epigenomics (i.e., bisulphite sequencing), transcriptomics (i.e., RNA sequencing), and proteomics (i.e., normalized reverse phase protein array) data at the whole-genome level. Furthermore, the relationships between different types of omics data, such as methylation quantitative trait loci (SNPs influencing methylation), expression quantitative trait loci (SNPs influencing gene expression), and expression quantitative trait methylations (methylations influencing gene expression), were modeled. More importantly, the relationships between these multi-omics data and the disease status were modeled as well. We used OmicsSIMLA to simulate a multi-omics dataset for breast cancer under a hypothetical disease model and used the data to compare the performance among existing multi-omics analysis methods in terms of disease classification accuracy and runtime. We also used OmicsSIMLA to simulate a multi-omics dataset with a scale similar to an ovarian cancer multi-omics dataset. The neural network-based multi-omics analysis method ATHENA was applied to both the real and simulated data and the results were compared. Our results demonstrated that complex disease mechanisms can be simulated by OmicsSIMLA, and ATHENA showed the highest prediction accuracy when the effects of multi-omics features (e.g., SNPs, copy number variations, and gene expression levels) on the disease were strong. Furthermore, similar results can be obtained from ATHENA when analyzing the simulated and real ovarian multi-omics data. CONCLUSIONS: OmicsSIMLA will be useful to evaluate the performace of different multi-omics analysis methods. Sample sizes and power can also be calculated by OmicsSIMLA when planning a new multi-omics disease study. PMID: 31029063 [PubMed - in process]

Related Articles Characterization of synovial fluid metabolomic phenotypes of cartilage morphological changes associated with osteoarthritis. Osteoarthritis Cartilage. 2019 Apr 24;: Authors: Carlson AK, Rawle RA, Wallace CW, Brooks EG, Adams E, Greenwood MC, Olmer M, Lotz MK, Bothner B, June RK Abstract OBJECTIVE: Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolomic phenotypes from human synovial fluid. DESIGN: Post mortem synovial fluids (n=75) were analyzed by high performance-liquid chromatography mass spectrometry (LC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression. RESULTS: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Synovial fluid metabolomic phenotypes exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid. CONCLUSION: These results revealed distinct metabolic phenotypes in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers, and can move toward developing personalized interventions for subgroups of OA patients. PMID: 31028882 [PubMed - as supplied by publisher]

Related Articles Mapping the metabolism of five amino acids in bloodstream form Trypanosoma brucei using U13C-labelled substrates and LC-MS. Biosci Rep. 2019 Apr 26;: Authors: Johnston K, Kim DH, Kerkhoven EJ, Burchmore RJS, Barrett M, Achcar F Abstract The metabolism of the parasite Trypanosoma brucei has been the focus of numerous studies since the 1940's. Recently it was shown, using metabolomics coupled with heavy-atom isotope-labelled glucose, that the metabolism of the bloodstream form parasite is more complex than previously thought. This study also raised a number of questions regarding the origin of several metabolites, for example succinate, only a proportion of which derives from glucose. In order to answer some of these questions and explore the metabolism of bloodstream form T. brucei in more depth we followed the fate of five heavy-labelled amino acids - glutamine, proline, methionine, cysteine and arginine - using an LC-MS based metabolomics approach. We found that some of these amino acids have roles beyond those previously thought and we have tentatively identified some unexpected metabolites which need to be confirmed and their function determined. PMID: 31028136 [PubMed - as supplied by publisher]

Related Articles Transcriptional profiling and metabolomic analysis of Staphylococcus aureus grown on autoclaved chicken breast. Food Microbiol. 2019 Sep;82:46-52 Authors: Dupre JM, Johnson WL, Ulanov AV, Li Z, Wilkinson BJ, Gustafson JE Abstract Although Staphylococcus aureus is a major cause of food poisoning, little is known about its response to growth on food. Utilizing a transcriptional profiling and metabolomics approach, we compared S. aureus grown on autoclaved chicken breast (ACB) to Luria broth agar. ACB cultures demonstrated increased expression of genes associated with protein synthesis, cofactors, secondary metabolites, nitrogen and nucleotide metabolism, amino acid transport, and reduced expression of general stress, lipid metabolism, and virulence genes. The ACB culture also displayed characteristics of catabolite de-repression and anaerobic growth, and increased expression of arginine biosynthesis genes (argFGH) and an arginine/ornithine antiporter gene (arcD). S. aureus synthesizes arginine from proline and the ACB culture exhibited increased expression of proline transport genes (opuBA, opuBB and putP) and increased proline accumulation. Amino acid and sugar content in the ACB grown culture increased, and this was attributed to the consumption of ACB, transport of amino acids, and gluconeogenesis. Genes involved with biotin biosynthesis and uptake were upregulated and biotin is required for amino acid catabolism. Genes encoding urease and urease activity were upregulated in ACB cultures, while urea levels were reduced. This research provides fundamental information on the response of S. aureus growing on chicken meat that could find application in future attempts to reduce the growth of S. aureus in food. PMID: 31027806 [PubMed - in process]

Related Articles Validated comprehensive metabolomics and lipidomics analysis of colon tissue and cell lines. Anal Chim Acta. 2019 Aug 20;1066:79-92 Authors: Rombouts C, De Spiegeleer M, Van Meulebroek L, De Vos WH, Vanhaecke L Abstract Current untargeted approaches for metabolic fingerprinting of colon tissue and cell lines lack validation of reproducibility and/or focus on a selection of metabolites as opposed to the entire metabolome. Yet, both are critical to ensure reliable results and pursue a fully holistic analysis. Therefore, we have optimized and validated a platform for analyzing the polar metabolome and lipidome of colon-derived cell and tissue samples based on a consecutive extraction of polar and apolar components. Peak areas of selected targeted analytes and the number of untargeted components were assessed. Analysis was performed using ultra-high performance liquid-chromatography (UHPLC) coupled to hybrid quadrupole-Orbitrap high-resolution mass spectrometry (HRMS). This resulted in an optimized extraction protocol using 50% methanol/ultrapure water to obtain the polar fraction followed by a dichloromethane-based lipid extraction. Using this comprehensive approach, we have detected more than 15,000 components with CV < 30% in internal quality control (IQC) samples and were able to discriminate the non-transformed (NT) and transformed (T) state in human colon tissue and cell lines based on validated OPLS-DA models (R2Y > 0.719 and Q2 > 0.674). To conclude, our validated polar metabolomics and lipidomics fingerprinting approach could be of great value to reveal gastrointestinal disease-associated biomarkers and mechanisms. PMID: 31027537 [PubMed - in process]

Related Articles Alterations in the gut microbiome and metabolism with coronary artery disease severity. Microbiome. 2019 Apr 26;7(1):68 Authors: Liu H, Chen X, Hu X, Niu H, Tian R, Wang H, Pang H, Jiang L, Qiu B, Chen X, Zhang Y, Ma Y, Tang S, Li H, Feng S, Zhang S, Zhang C Abstract BACKGROUND: Coronary artery disease (CAD) is associated with gut microbiota alterations in different populations. Gut microbe-derived metabolites have been proposed as markers of major adverse cardiac events. However, the relationship between the gut microbiome and the different stages of CAD pathophysiology remains to be established by a systematic study. RESULTS: Based on multi-omic analyses (sequencing of the V3-V4 regions of the 16S rRNA gene and metabolomics) of 161 CAD patients and 40 healthy controls, we found that the composition of both the gut microbiota and metabolites changed significantly with CAD severity. We identified 29 metabolite modules that were separately classified as being positively or negatively correlated with CAD phenotypes, and the bacterial co-abundance group (CAG) with characteristic changes at different stages of CAD was represented by Roseburia, Klebsiella, Clostridium IV and Ruminococcaceae. The result revealed that certain bacteria might affect atherosclerosis by modulating the metabolic pathways of the host, such as taurine, sphingolipid and ceramide, and benzene metabolism. Moreover, a disease classifier based on differential levels of microbes and metabolites was constructed to discriminate cases from controls and was even able to distinguish stable coronary artery disease from acute coronary syndrome accurately. CONCLUSION: Overall, the composition and functions of the gut microbial community differed from healthy controls to diverse coronary artery disease subtypes. Our study identified the relationships between the features of the gut microbiota and circulating metabolites, providing a new direction for future studies aiming to understand the host-gut microbiota interplay in atherosclerotic pathogenesis. PMID: 31027508 [PubMed - in process]

Related Articles Metabolome and Transcriptome Association Analysis Reveals Dynamic Regulation of Purine Metabolism and Flavonoid Synthesis in Transdifferentiation during Somatic Embryogenesis in Cotton. Int J Mol Sci. 2019 Apr 26;20(9): Authors: Guo H, Guo H, Zhang L, Tang Z, Yu X, Wu J, Zeng F Abstract Plant regeneration via somatic embryogenesis (SE) is a key step during genetic engineering. In the current study, integrated widely targeted metabolomics and RNA sequencing were performed to investigate the dynamic metabolic and transcriptional profiling of cotton SE. Our data revealed that a total of 581 metabolites were present in nonembryogenic staged calli (NEC), primary embryogenic calli (PEC), and initiation staged globular embryos (GE). Of the differentially accumulated metabolites (DAMs), nucleotides, and lipids were specifically accumulated during embryogenic differentiation, whereas flavones and hydroxycinnamoyl derivatives were accumulated during somatic embryo development. Additionally, metabolites related to purine metabolism were significantly enriched in PEC vs. NEC, whereas in GE vs. PEC, DAMs were remarkably associated with flavonoid biosynthesis. An association analysis of the metabolome and transcriptome data indicated that purine metabolism and flavonoid biosynthesis were co-mapped based on the Kyoto encyclopedia of genes and genomes (KEGG) database. Moreover, purine metabolism-related genes associated with signal recognition, transcription, stress, and lipid binding were significantly upregulated. Moreover, several classic somatic embryogenesis (SE) genes were highly correlated with their corresponding metabolites that were involved in purine metabolism and flavonoid biosynthesis. The current study identified a series of potential metabolites and corresponding genes responsible for SE transdifferentiation, which provides a valuable foundation for a deeper understanding of the regulatory mechanisms underlying cell totipotency at the molecular and biochemical levels. PMID: 31027387 [PubMed - in process]

Related Articles The Proteome of Tetrasphaera elongata is adapted to Changing Conditions in Wastewater Treatment Plants. Proteomes. 2019 Apr 25;7(2): Authors: Herbst FA, Dueholm MS, Wimmer R, Nielsen PH Abstract The activated sludge in wastewater treatment plants (WWTP) designed for enhanced biological phosphorus removal (EBPR) experiences periodically changing nutrient and oxygen availability. Tetrasphaera is the most abundant genus in Danish WWTP and represents up to 20-30% of the activated sludge community based on 16S rRNA amplicon sequencing and quantitative fluorescence in situ hybridization analyses, although the genus is in low abundance in the influent wastewater. Here we investigated how Tetrasphaera can successfully out-compete most other microorganisms in such highly dynamic ecosystems. To achieve this, we analyzed the physiological adaptations of the WWTP isolate T. elongata str. LP2 during an aerobic to anoxic shift by label-free quantitative proteomics and NMR-metabolomics. Escherichia coli was used as reference organism as it shares several metabolic capabilities and is regularly introduced to wastewater treatment plants without succeeding there. When compared to E. coli, only minor changes in the proteome of T. elongata were observed after the switch to anoxic conditions. This indicates that metabolic pathways for anaerobic energy harvest were already expressed during the aerobic growth. This allows continuous growth of Tetrasphaera immediately after the switch to anoxic conditions. Metabolomics furthermore revealed that the substrates provided were exploited far more efficiently by Tetrasphaera than by E. coli. These results suggest that T. elongata prospers in the dynamic WWTP environment due to adaptation to the changing environmental conditions. PMID: 31027192 [PubMed]

Related Articles Surfactant Lipidomics of Alveolar Lavage Fluid in Mice Based on Ultra-High-Performance Liquid Chromatography Coupled to Hybrid Quadrupole-Exactive Orbitrap Mass Spectrometry. Metabolites. 2019 Apr 25;9(4): Authors: Yang R, Zhang Y, Qian W, Peng L, Lin L, Xu J, Xie T, Ji J, Zhan X, Shan J Abstract Surfactant lipid metabolism is closely related to pulmonary diseases. Lipid metabolism disorder can cause lung diseases, vice versa. With this rationale, a useful method was established in this study to determine the lipidome in bronchoalveolar lavage fluid (BALF) of mice. The lipid components in BALF were extracted by liquid-liquid extraction (methanol and methyl tert-butyl ether, and water). Ultra-high-performance liquid chromatography coupled to hybrid Quadrupole-Exactive Orbitrap mass spectrometry was used to analyze the extracted samples, which showed a broad scanning range of 215-1800 m/z. With MS-DIAL software and built-in LipidBlast database, we identified 38 lipids in positive, and 31 lipids in negative, ion mode, including lysophosphatidylcholine (lysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), etc. Then, the changes of lipids in BALF of mice with acute lung injury (ALI) induced by lipopolysaccharide (LPS) was investigated, which may contribute to further exploration of the pathogenesis of ALI. PMID: 31027159 [PubMed]

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Related Articles Effect of CAX1a TILLING mutations and calcium concentration on some primary metabolism processes in Brassica rapa plants. J Plant Physiol. 2019 Apr 18;237:51-60 Authors: Navarro-León E, Ruiz JM, Albacete A, Blasco B Abstract Cation/H+ exchanger transporters (CAXs) are crucial in Ca2+ homeostasis and in the generation of Ca2+ profiles involved in signalling processes. Given the crucial role of CAX1 in Ca2+ homeostasis, CAX1 modifications could have effects on plant metabolism. Three Brassica rapa mutants for CAX1 were obtained through TILLING. The aim of this work is to assess the effect of the different mutations and different Ca2+ doses on plant metabolism. For this, the mutants and the parental line were grown under low, control and high Ca2+ doses and parameters related to nitrogen (N) and tricarboxylic acid (TCA) metabolisms, and amino acid (AAs) and phytohormone profiles were measured. The results show that BraA.cax1a mutations affect metabolism especially under high Ca2+ dose. Thus, BraA.cax1a-7 inhibited some N metabolism enzymes and activated photorespiration activity. On the opposite side, BraA.cax1a-12 mutation provides a better tolerance to high Ca2+ dose. This tolerance could be provided by an improved N and TCA metabolisms enzymes, and a higher glutamate, malate, indole-3-acetic acid and abscisic acid concentrations. Therefore, BraA.cax1a-12 mutation could be used for B. rapa improving; the metabolomics changes observed in this mutant could be responsible for a better tolerance to high Ca2+. PMID: 31022665 [PubMed - as supplied by publisher]

Related Articles NMR for sample quality assessment in metabolomics. N Biotechnol. 2019 Apr 22;: Authors: Ghini V, Quaglio D, Luchinat C, Turano P Abstract The EU Framework 7 project SPIDIA was the occasion for development of NMR approaches to evaluate the impact of different pre-analytical treatments on the quality of biological samples dedicated to metabolomics. Systematic simulation of different pre-analytical procedures was performed on urine and blood serum and plasma. Here we review the key aspects of these studies that have led to the development of CEN technical specifications, to be translated into ISO/IS in the course of the EU Horizon 2020 project SPIDIA4P. Inspired by the SPIDIA results, follow-up research was performed, extending the analysis to different sample types and to the different effects of long-term storage. The latter activity was in conjunction with the local European da Vinci Biobank. These results (which partially contributed to the ANNEX of CEN/TS 16945 "MOLECULAR IN VITRO DIAGNOSTIC EXAMINATIONS - SPECIFICATIONS FOR PRE-EXAMINATION PROCESSES FOR METABOLOMICS IN URINE, VENOUS BLOOD SERUM AND PLASMA") are presented in detail. PMID: 31022482 [PubMed - as supplied by publisher]

Related Articles Targeted metabolomics analysis of maternal-placental-fetal metabolism in pregnant swine reveals links in fetal bile acid homeostasis and sulfation capacity. Am J Physiol Gastrointest Liver Physiol. 2019 Apr 25;: Authors: Wang P, Zhong H, Song Y, Yuan P, Li Y, Lin S, Zhang X, Li J, Che L, Feng B, Lin Y, Xu S, Zhuo Y, Tian G, Chen D, Wu, Burrin DG, Fang Z Abstract Cholestasis of pregnancy endangers fetal and neonatal survival, yet systematic knowledge of the cause and effect of disrupted bile acid (BA) homeostasis in pregnancy is limited. Here we show that gestation stage-associated BA dysregulation in swine correlated with fetal death resulting from compromised capacity for BA secretion and increased alternative systemic efflux. The balance of BA input and output in the developing uterus suggested little uptake and metabolism of maternal BA by the placenta-fetus unit, implying a protection role of placenta in preventing maternal BA transported into fetus. We showed that the maternal origin of BA accounted for the increase in placental TBA leading to dysregulated expression of genes involved in BA transport and potentially impaired transplacental export of fetus-derived BA. Correspondingly, the secondary BA, mainly derived from the mother, gradually decreased in fetus. Finally, we identified that sulfation rather than glucuronidation played pivotal roles in maintaining BA homeostasis of developing fetus. These novel and systemic findings contribute to a whole picture of BA metabolism in pregnancy, and provide new insights into mechanisms responsible for maternal and fetal BA homeostasis. PMID: 31021171 [PubMed - as supplied by publisher]

Related Articles Comprehensive transcriptomics, proteomics, and metabolomics analyses of the mechanisms regulating tiller production in low-tillering wheat. Theor Appl Genet. 2019 Apr 16;: Authors: Wang Z, Shi H, Yu S, Zhou W, Li J, Liu S, Deng M, Ma J, Wei Y, Zheng Y, Liu Y Abstract KEY MESSAGE: Tiller development in low-tillering wheat is related to several differentially expressed genes, proteins, and metabolites, as determined by an integrated omics approach combining transcriptome analysis, iTRAQ, and HPLC-MS on multiple NILs. Tillering is an important aspect of plant morphology that affects spike number, thereby contributing to the final crop yield. However, the mechanisms inhibiting tiller production in low-tillering wheat are poorly characterized. To investigate this aspect of wheat biology, two pairs of near-isogenic lines were developed, and an integrated omics approach combining transcriptome analysis, isobaric tags for relative and absolute quantification, and high-performance liquid chromatography-mass spectrometry were used to compare the free-tillering and low-tillering caused by an allele at Qltn.sicau-2D in wheat samples. Overall, 474 genes, 166 proteins, and 28 metabolites were identified as tillering-associated differentially expressed genes, proteins, and metabolites (DEGs, DEPs, and DEMs, respectively). Functional analysis indicated that the abundance of DEGs/DEPs/DEMs was related to lignin and cellulose metabolism, cell division, cell cycle processes, and glycerophospholipid metabolism; three transcription factor families, GRAS, GRF, and REV, might be related to the decrease in tillering in low-tillering wheat. These findings contribute to improve our understanding of the mechanisms responsible for the inhibition of tiller development in low-tillering wheat cultivars. PMID: 31020386 [PubMed - as supplied by publisher]

Related Articles Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance. mSystems. 2019 Mar-Apr;4(2): Authors: Henson MA, Orazi G, Phalak P, O'Toole GA Abstract Cystic fibrosis (CF) is a fatal genetic disease characterized by chronic lung infections due to aberrant mucus production and the inability to clear invading pathogens. The traditional view that CF infections are caused by a single pathogen has been replaced by the realization that the CF lung usually is colonized by a complex community of bacteria, fungi, and viruses. To help unravel the complex interplay between the CF lung environment and the infecting microbial community, we developed a community metabolic model comprised of the 17 most abundant bacterial taxa, which account for >95% of reads across samples, from three published studies in which 75 sputum samples from 46 adult CF patients were analyzed by 16S rRNA gene sequencing. The community model was able to correctly predict high abundances of the "rare" pathogens Enterobacteriaceae, Burkholderia, and Achromobacter in three patients whose polymicrobial infections were dominated by these pathogens. With these three pathogens removed, the model correctly predicted that the remaining 43 patients would be dominated by Pseudomonas and/or Streptococcus. This dominance was predicted to be driven by relatively high monoculture growth rates of Pseudomonas and Streptococcus as well as their ability to efficiently consume amino acids, organic acids, and alcohols secreted by other community members. Sample-by-sample heterogeneity of community composition could be qualitatively captured through random variation of the simulated metabolic environment, suggesting that experimental studies directly linking CF lung metabolomics and 16S sequencing could provide important insights into disease progression and treatment efficacy. IMPORTANCE Cystic fibrosis (CF) is a genetic disease in which chronic airway infections and lung inflammation result in respiratory failure. CF airway infections are usually caused by bacterial communities that are difficult to eradicate with available antibiotics. Using species abundance data for clinically stable adult CF patients assimilated from three published studies, we developed a metabolic model of CF airway communities to better understand the interactions between bacterial species and between the bacterial community and the lung environment. Our model predicted that clinically observed CF pathogens could establish dominance over other community members across a range of lung nutrient conditions. Heterogeneity of species abundances across 75 patient samples could be predicted by assuming that sample-to-sample heterogeneity was attributable to random variations in the CF nutrient environment. Our model predictions provide new insights into the metabolic determinants of pathogen dominance in the CF lung and could facilitate the development of improved treatment strategies. PMID: 31020043 [PubMed]

Related Articles Ketamine's Effects on the Glutamatergic and GABAergic Systems: A Proteomics and Metabolomics Study in Mice. Mol Neuropsychiatry. 2019 Mar;5(1):42-51 Authors: Weckmann K, Deery MJ, Howard JA, Feret R, Asara JM, Dethloff F, Filiou MD, Labermaier C, Maccarrone G, Lilley KS, Mueller M, Turck CW Abstract Ketamine, a noncompetitive, voltage-dependent N-Methyl-D-aspartate receptor (NMDAR) antagonist, has been shown to have a rapid antidepressant effect and is used for patients experiencing treatment-resistant depression. We carried out a time-dependent targeted mass spectrometry-based metabolomics profiling analysis combined with a quantitative based on in vivo 15N metabolic labeling proteome comparison of ketamine- and vehicle-treated mice. The metabolomics and proteomics datasets were used to further elucidate ketamine's mode of action on the gamma-aminobutyric acid (GABA)ergic and glutamatergic systems. In addition, myelin basic protein levels were analyzed by Western Blot. We found altered GABA, glutamate and glutamine metabolite levels and ratios as well as increased levels of putrescine and serine - 2 positive modulators of the NMDAR. In addition, GABA receptor (GABAR) protein levels were reduced, whereas the alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunit Gria2 protein levels were increased upon ketamine treatment. The significantly altered metabolite and protein levels further significantly correlated with the antidepressant-like behavior, which was assessed using the forced swim test. In conclusion and in line with previous research, our data indicate that ketamine impacts the AMPAR subunit Gria2 and results in decreased GABAergic inhibitory neurotransmission leading to increased excitatory neuronal activity. PMID: 31019917 [PubMed]

Related Articles Metabolomic profiling to identify effects of dietary calcium reveal the influence of the individual and postprandial dynamics on the canine plasma metabolome. J Nutr Sci. 2019;8:e13 Authors: Allaway D, Gilham M, Wagner-Golbs A, Maldonado SG, Haydock R, Colyer A, Stockman J, Watson P Abstract Short-term feeding studies have highlighted a phenomenon in Ca regulation that raises concerns around Ca absorption in dogs that may make an impact on commercial diets near to the maximum recommended level. A recent study to determine responses in dogs fed one of two diets differing in dietary Ca over 40 weeks found no evidence to suggest a concern across a range of biological parameters hypothesised to be affected by Ca. Unforeseen consequences of dietary Ca could have occurred and metabolic profiling was deemed a suitable data-driven approach to identify effects of dietary Ca. The objectives were to compare the fasted plasma metabolome (sampled at 8-week intervals over 40 weeks) of dogs fed one of two diets, near to the minimum and maximum recommended levels of dietary Ca. Comparisons with the control diet were also investigated across the postprandial time course (1-4 h) following acute (1 d) and long-term (24 weeks) feeding of the test diet. Comparing fasted plasma samples at each time point, no significant effect (adjusted P < 0·05) of diet on metabolites was observed. In the postprandial state, only phosphate was consistently different between diets and was explained by additional dietary P to maintain Ca:P. Metabolic profiling analysis supports the view that the dietary Ca upper limit is safe. Additionally, the canine plasma metabolome was characterised, providing insights into the stability of individual profiles across 40 weeks, the response to consumption of a nutritionally complete meal over a 4 h postprandial time course and different kinetic categories of postprandial absorption. PMID: 31019684 [PubMed]

Related Articles Deep undepleted human serum proteome profiling toward biomarker discovery for Alzheimer's disease. Clin Proteomics. 2019;16:16 Authors: Dey KK, Wang H, Niu M, Bai B, Wang X, Li Y, Cho JH, Tan H, Mishra A, High AA, Chen PC, Wu Z, Beach TG, Peng J Abstract Background: Blood-based protein measurement is a routine practice for detecting biomarkers in human disease. Comprehensive profiling of blood/plasma/serum proteome is a challenge due to an extremely large dynamic range, as exemplified by a small subset of highly abundant proteins. Antibody-based depletion of these abundant proteins alleviates the problem but introduces experimental variations. We aimed to establish a method for direct profiling of undepleted human serum and apply the method toward biomarker discovery for Alzheimer's disease (AD), as AD is the most common form of dementia without available blood-based biomarkers in clinic. Methods: We present an ultra-deep analysis of undepleted human serum proteome by combining the latest 11-plex tandem-mass-tag (TMT) labeling, exhaustive two-dimensional liquid chromatography (LC/LC) fractionation (the 1st LC: 3 h for 180 fractions, and the 2nd LC: 3 h gradient per fraction), coupled with high resolution tandem mass spectrometry (MS/MS). AD (n = 6) and control (n = 5) sera were analyzed in this pilot study. In addition, we implemented a multiplexed targeted LC-MS3 method (TOMAHAQ) for the validation of selected target proteins. Results: The TMT-LC/LC-MS/MS platform is capable of analyzing 4826 protein components (4368 genes), covering at least 6 orders of magnitude in dynamic range, representing one of the deepest serum proteome analysis. We defined intra- and inter- group variability in the AD and control groups. Statistical analysis revealed differentially expressed proteins in AD (26 decreased and 4 increased). Notably, these altered proteins are enriched in the known pathways of mitochondria, fatty acid beta oxidation, and AGE/RAGE. Finally, we set up a TOMAHAQ method to confirm the decrease of PCK2 and AK2 in our AD samples. Conclusions: Our results show an ultra-deep serum discovery study by TMT-LC/LC-MS/MS, and a validation experiment by TOMAHAQ targeted LC-MS3. The MS-based discovery and validation methods are of general use for biomarker discovery from complex biofluids (e.g. serum proteome). This pilot study also identified deregulated proteins, in particular proteins associated with mitochondrial function in the AD serum samples. These proteins may serve as novel AD candidate biomarkers. PMID: 31019427 [PubMed]

Related Articles The mercapturomic profile of health and non-communicable diseases. High Throughput. 2019 Apr 23;8(2): Authors: Gonçalves-Dias C, Morello J, Semedo V, Correia MJ, Coelho NR, Monteiro EC, Antunes AMM, Pereira SA Abstract The mercapturate pathway is a unique metabolic circuitry that detoxifies electrophiles upon adducts formation with glutathione. Since its discovery over a century ago, most of the knowledge on the mercapturate pathway has been provided from biomonitoring studies on environmental exposure to toxicants. However, the mercapturate pathway-related metabolites that is formed in humans-the mercapturomic profile-in health and disease is yet to be established. In this paper, we put forward the hypothesis that these metabolites are key pathophysiologic factors behind the onset and development of non-communicable chronic inflammatory diseases. This review goes from the evidence in the formation of endogenous metabolites undergoing the mercapturate pathway to the methodologies for their assessment and their association with cancer and respiratory, neurologic and cardiometabolic diseases. PMID: 31018482 [PubMed]