PubMed

Heterologous phosphoketolase expression redirects flux towards acetate, perturbs sugar phosphate pools and increases respiratory demand in Saccharomyces cerevisiae. Microb Cell Fact. 2019 Feb 01;18(1):25 Authors: Bergman A, Hellgren J, Moritz T, Siewers V, Nielsen J, Chen Y Abstract INTRODUCTION: Phosphoketolases (Xfpk) are a non-native group of enzymes in yeast, which can be expressed in combination with other metabolic enzymes to positively influence the yield of acetyl-CoA derived products by reducing carbon losses in the form of CO2. In this study, a yeast strain expressing Xfpk from Bifidobacterium breve, which was previously found to have a growth defect and to increase acetate production, was characterized. RESULTS: Xfpk-expression was found to increase respiration and reduce biomass yield during glucose consumption in batch and chemostat cultivations. By cultivating yeast with or without Xfpk in bioreactors at different pHs, we show that certain aspects of the negative growth effects coupled with Xfpk-expression are likely to be explained by proton decoupling. At low pH, this manifests as a reduction in biomass yield and growth rate in the ethanol phase. Secondly, we show that intracellular sugar phosphate pools are significantly altered in the Xfpk-expressing strain. In particular a decrease of the substrates xylulose-5-phosphate and fructose-6-phosphate was detected (26% and 74% of control levels) together with an increase of the products glyceraldehyde-3-phosphate and erythrose-4-phosphate (208% and 542% of control levels), clearly verifying in vivo Xfpk enzymatic activity. Lastly, RNAseq analysis shows that Xfpk expression increases transcription of genes related to the glyoxylate cycle, the TCA cycle and respiration, while expression of genes related to ethanol and acetate formation is reduced. The physiological and transcriptional changes clearly demonstrate that a heterologous phosphoketolase flux in combination with endogenous hydrolysis of acetyl-phosphate to acetate increases the cellular demand for acetate assimilation and respiratory ATP-generation, leading to carbon losses. CONCLUSION: Our study shows that expression of Xfpk in yeast diverts a relatively small part of its glycolytic flux towards acetate formation, which has a significant impact on intracellular sugar phosphate levels and on cell energetics. The elevated acetate flux increases the ATP-requirement for ion homeostasis and need for respiratory assimilation, which leads to an increased production of CO2. A majority of the negative growth effects coupled to Xfpk expression could likely be counteracted by preventing acetate accumulation via direct channeling of acetyl-phosphate towards acetyl-CoA. PMID: 30709397 [PubMed - in process]

Evaluation of the Hepatotoxicity of the Zhi-Zi-Hou-Po Decoction by Combining UPLC-Q-Exactive-MS-Based Metabolomics and HPLC-MS/MS-Based Geniposide Tissue Distribution. Molecules. 2019 Jan 31;24(3): Authors: Wang Y, Feng F Abstract With traditional Chinese medicine (TCM) becoming widespread globally, its safety has increasingly become a concern, especially its hepatoxicity. For example, Gardenia jasminoides Ellis is a key ingredient in the Zhi-Zi-Hou-Po decoction (ZZHPD), which is a commonly-used clinically combined prescription of TCM that may induce hepatoxicity. However, the underlying toxicity mechanism of ZZHPD is not fully understood. In this study, a plasma metabolomics strategy was used to investigate the mechanism of ZZHPD-induced hepatotoxicity through profiling entire endogenous metabolites. Twenty-four Sprague-Dawley rats were randomly assigned into four groups, which were orally administered with 0.9% saline, as well as 2.7 g/kg/day, 8.1 g/kg/day, or 27 g/kg/day of ZZHPD for 30 consecutive days, respectively. Biochemical assay and metabolomics assay were used to detect serum and plasma samples, whilst histopathological assay was used for detecting liver tissues, and the geniposide distribution in tissues was simultaneously measured. The results showed that the concentration of 20 metabolites linked to amino acid, lipid, and bile acid metabolism had significant changes in the ZZHPD-treated rats. Moreover, toxic effects were aggravated with serum biochemical and histopathological examines in liver tissues as the dosage increased, which may be associated with the accumulation of geniposide in the liver as the dosage increased. Notably, our findings also demonstrated that the combined metabolomics strategy with tissue distribution had significant potential for elucidating the mechanistic complexity of the toxicity of TCM. PMID: 30708983 [PubMed - in process]

16 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 2019/02/02PubMed 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 Interaction of Clopidogrel and Fufang Danshen Dripping Pills Assay in Coronary Heart Disease based on Non-target Metabolomics. J Ethnopharmacol. 2019 Jan 28;: Authors: Mengzhe G, Tianyun W, Jian Y, Chang H, Ji S, Daoquan T Abstract ETHNOPHARMACOLOGICAL RELEVANCE: Clopidogrel is the recommended treatment by current clinical practice guidelines to prevent adverse cardiovascular events in patients with coronary heart disease (CHD), but this treatment regimen still fails and 5%-40% patients display inadequate antiplatelet responses. Fufang Danshen Dripping Pill (FDDP) was used as the combination with clopidogrel to improve the therapeutic effect. However, the mechanism of the interaction between clopidogrel and FDDP has not been elucidated. MATERIALS AND METHODS: We have used non-targeted metabolism method based on GC-MS and LC-MS for the investigation of drug interactions between clopidogrel and FDDP. 63 patients were divided into four groups with different dosage regimen and the serum samples were collected for the analysis. RESULTS: We have found 5 and 55 differential metabolites between health volunteer group and CHD patients group, respectively. The contents of these differential metabolites had diverse changes in clopidogrel group, FDDP group, and drug combination group, indicating that the clopidogrel and FDDP combination can adjust the glycometabolism, lipid metabolism, and phospholipid metabolism, sequentially made the content of downstream related metabolites towards to the health volunteer group. CONCLUSION: This work has explained the mechanism of the interaction between clopidogrel and FDDP from the point of view of metabolic product change, and revealed the potential metabolic pathways it affects, which provided the new ideas for clinical medication. PMID: 30703494 [PubMed - as supplied by publisher]

Related Articles Comprehensive and empirical evaluation of machine learning algorithms for small molecule LC retention time prediction. Anal Chem. 2019 Jan 31;: Authors: Bouwmeester R, Martens L, Degroeve S Abstract Liquid chromatography is a core component of almost all mass spectrometric analyses of (bio)molecules. Because of the high-throughput nature of mass spectrometric analyses, the interpretation of these chromatographic data increasingly relies on informatics solutions that attempt to predict an analyte's retention time. The key components of such predictive algorithms are the features these are supplies with, and the actual machine learning algorithm used to fit the model parameters. Therefore, we have evaluated the performance of seven machine learning algorithms on 36 distinct metabolomics data sets, using two distinct feature sets. Interestingly, the results show that no single learning algorithm performs optimally for all data sets, with different types of algorithms achieving top performance for different types of analytes or different protocols. Our results thus show that an evaluation of machine learning algorithms for retention time prediction is needed to find a suitable algorithm for specific analytes or protocols. Importantly, however, our results also show that blending different types of models together decreases the error on outliers, indicating that the combination of several approaches holds substantial promise for the development of more generic, high-performing algorithms. PMID: 30702864 [PubMed - as supplied by publisher]

Related Articles Metabolic Discrimination of Breast Cancer Subtypes at Single-Cell Level by Multiple Microextraction Coupled with Mass Spectrometry. Anal Chem. 2019 Jan 31;: Authors: Wang R, Zhao H, Zhang X, Zhao X, Song Z, Ouyang J Abstract Discrimination of cancer subtypes at the single-cell level is critical for the early diagnosis and accurate treatment of cancer. However, the discrimination of breast cancer subtypes based on their metabolite information, which could provide a new perspective of the cellular metabolomics, is still in its infancy. Herein, a high-coverage single cell metabolic analysis was carried out for the discrimination of breast cancer subtypes by combining multiple microextraction with mass spectrometry (MS). About 4300 ion signals were extracted from each cell and assigned to lipids, energy metabolites, etc. Based on the multivariate analysis of the metabolite information, four subtypes of breast cancer were successfully discriminated. Characteristic components of each subtype were also identified as potential biomarkers such as phosphatidylcholine (PC) (PC (32:1), PC (34:1)), UDP/UDP-HexNAc, and Hex-bis-P/Hex-P). Moreover, metabolomics correlation analysis at the single-cell level further revealed the co-regulation clusters of the identified components, which provided more metabolites data for bioinformatics studies. Over-all, our results on single cell metabolic analysis could give new insights to precision medicine, early diagnosis and cancer treatments. PMID: 30702862 [PubMed - as supplied by publisher]

Related Articles Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer. Clin Transl Gastroenterol. 2019 Jan;10(1):e00003 Authors: Herreros-Villanueva M, Duran-Sanchon S, Martín AC, Pérez-Palacios R, Vila-Navarro E, Marcuello M, Diaz-Centeno M, Cubiella J, Diez MS, Bujanda L, Lanas A, Jover R, Hernández V, Quintero E, José Lozano J, García-Cougil M, Martínez-Arranz I, Castells A, Gironella M, Arroyo R Abstract OBJECTIVES: Specific microRNA (miRNA) signatures in biological fluids can facilitate earlier detection of the tumors being then minimally invasive diagnostic biomarkers. Circulating miRNAs have also emerged as promising diagnostic biomarkers for colorectal cancer (CRC) screening. In this study, we investigated the performance of a specific signature of miRNA in plasma samples to design a robust predictive model that can distinguish healthy individuals from those with CRC or advanced adenomas (AA) diseases. METHODS: Case control study of 297 patients from 8 Spanish centers including 100 healthy individuals, 101 diagnosed with AA, and 96 CRC cases. Quantitative real-time reverse transcription was used to quantify a signature of miRNA (miRNA19a, miRNA19b, miRNA15b, miRNA29a, miRNA335, and miRNA18a) in plasma samples. Binary classifiers (Support Vector Machine [SVM] linear, SVM radial, and SVM polynomial) were built for the best predictive model. RESULTS: Area under receiving operating characteristic curve of 0.92 (95% confidence interval 0.871-0.962) was obtained retrieving a model with a sensitivity of 0.85 and specificity of 0.90, positive predictive value of 0.94, and negative predictive value of 0.76 when advanced neoplasms (CRC and AA) were compared with healthy individuals. CONCLUSIONS: We identified and validated a signature of 6 miRNAs (miRNA19a, miRNA19b, miRNA15b, miRNA29a, miRNA335, and miRNA18a) as predictors that can differentiate significantly patients with CRC and AA from those who are healthy. However, large-scale validation studies in asymptomatic screening participants should be conducted. PMID: 30702491 [PubMed - in process]

Related Articles Flexible nitrogen utilisation by the metabolic generalist pathogen Mycobacterium tuberculosis. Elife. 2019 Jan 31;8: Authors: Agapova A, Serafini A, Petridis M, Hunt DM, Garza-Garcia A, Sohaskey CD, de Carvalho LPS Abstract Bacterial metabolism is fundamental to survival and pathogenesis. We explore how Mycobacterium tuberculosis utilises amino acids as nitrogen sources, using a combination of bacterial physiology and stable isotope tracing coupled to mass spectrometry metabolomics methods. Our results define core properties of the nitrogen metabolic network from M. tuberculosis, such as: (i) the lack of homeostatic control of certain amino acid pool sizes; (ii) similar rates of utilisation of different amino acids as sole nitrogen sources; (iii) improved nitrogen utilisation from amino acids compared to ammonium; and (iv) co-metabolism of nitrogen sources. Finally, we discover that alanine dehydrogenase, is involved in ammonium assimilation in M. tuberculosis, in addition to its essential role in alanine utilisation as a nitrogen source. This study represents the first in-depth analysis of nitrogen source utilisation by M. tuberculosis and reveals a flexible metabolic network with characteristics that are likely product of evolution in the human host. PMID: 30702426 [PubMed - as supplied by publisher]

Related Articles What is 'LDL cholesterol'? Nat Rev Cardiol. 2019 Jan 30;: Authors: Holmes MV, Ala-Korpela M Abstract PMID: 30700860 [PubMed - as supplied by publisher]

Related Articles Dissecting metabolism using zebrafish models of disease. Biochem Soc Trans. 2019 Jan 30;: Authors: Salmi TM, Tan VWT, Cox AG Abstract Zebrafish (Danio rerio) are becoming an increasingly powerful model organism to study the role of metabolism in disease. Since its inception, the zebrafish model has relied on unique attributes such as the transparency of embryos, high fecundity and conservation with higher vertebrates, to perform phenotype-driven chemical and genetic screens. In this review, we describe how zebrafish have been used to reveal novel mechanisms by which metabolism regulates embryonic development, obesity, fatty liver disease and cancer. In addition, we will highlight how new approaches in advanced microscopy, transcriptomics and metabolomics using zebrafish as a model system have yielded fundamental insights into the mechanistic underpinnings of disease. PMID: 30700500 [PubMed - as supplied by publisher]

Related Articles Low Molecular Mass Myocardial Hyaluronan in Human Hypertrophic Cardiomyopathy. Cells. 2019 Jan 29;8(2): Authors: Lorén CE, Dahl CP, Do L, Almaas VM, Geiran OR, Mörner S, Hellman U Abstract During the development of hypertrophic cardiomyopathy, the heart returns to fetal energy metabolism where cells utilize more glucose instead of fatty acids as a source of energy. Metabolism of glucose can increase synthesis of the extracellular glycosaminoglycan hyaluronan, which has been shown to be involved in the development of cardiac hypertrophy and fibrosis. The aim of this study was to investigate hyaluronan metabolism in cardiac tissue from patients with hypertrophic cardiomyopathy in relation to cardiac growth. NMR and qRT-PCR analysis of human cardiac tissue from hypertrophic cardiomyopathy patients and healthy control hearts showed dysregulated glucose and hyaluronan metabolism in the patients. Gas phase electrophoresis revealed a higher amount of low molecular mass hyaluronan and larger cardiomyocytes in cardiac tissue from patients with hypertrophic cardiomyopathy. Histochemistry showed high concentrations of hyaluronan around individual cardiomyocytes in hearts from hypertrophic cardiomyopathy patients. Experimentally, we could also observe accumulation of low molecular mass hyaluronan in cardiac hypertrophy in a rat model. In conclusion, the development of hypertrophic cardiomyopathy with increased glucose metabolism affected both hyaluronan molecular mass and amount. The process of regulating cardiomyocyte size seems to involve fragmentation of hyaluronan. PMID: 30699940 [PubMed]

Related Articles Metabolomic and Transcriptomic Analyses of Escherichia coli for Efficient Fermentation of L-Fucose. Mar Drugs. 2019 Jan 29;17(2): Authors: Kim J, Cheong YE, Jung I, Kim KH Abstract L-Fucose, one of the major monomeric sugars in brown algae, possesses high potential for use in the large-scale production of bio-based products. Although fucose catabolic pathways have been enzymatically evaluated, the effects of fucose as a carbon source on intracellular metabolism in industrial microorganisms such as Escherichia coli are still not identified. To elucidate the effects of fucose on cellular metabolism and to find clues for efficient conversion of fucose into bio-based products, comparative metabolomic and transcriptomic analyses were performed on E. coli on L-fucose and on D-glucose as a control. When fucose was the carbon source for E. coli, integration of the two omics analyses revealed that excess gluconeogenesis and quorum sensing led to severe depletion of ATP, resulting in accumulation and export of fucose extracellularly. Therefore, metabolic engineering and optimization are needed for E. coil to more efficiently ferment fucose. This is the first multi-omics study investigating the effects of fucose on cellular metabolism in E. coli. These omics data and their biological interpretation could be used to assist metabolic engineering of E. coli producing bio-based products using fucose-containing brown macroalgae. PMID: 30699916 [PubMed - in process]

20 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 2019/01/31PubMed 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.

20 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 2019/01/31PubMed 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.

18 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 2019/01/30PubMed 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.

18 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 2019/01/30PubMed 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.

38 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 2019/01/29PubMed 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.

Impaired Pentose Phosphate Pathway in the Spinal Cord of the hSOD1G93A Mouse Model of Amyotrophic Lateral Sclerosis. Mol Neurobiol. 2019 Jan 26;: Authors: Tefera TW, Bartlett K, Tran SS, Hodson MP, Borges K Abstract Impairments in energy metabolism in amyotrophic lateral sclerosis (ALS) have long been known. However, the changes in the energy-producing pathways in ALS are not comprehensively understood. To investigate specific alterations in glucose metabolism in glycolytic, pentose phosphate, and TCA cycle pathways, we injected uniformly labeled [U-13C]glucose to wild-type and hSOD1G93A mice at symptom onset (80 days). Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), levels of metabolites were determined in extracts of the cortex and spinal cord. In addition, the activities of several enzymes involved in glucose metabolism were quantified. In the spinal cord, the levels of pentose phosphate pathway (PPP) intermediate ribose 5-phosphate (p = 0.037) were reduced by 37% in hSOD1G93A mice, while the % 13C enrichments in glucose 6-phosphate were increased threefold. The maximal activities of the enzyme glucose 6-phosphate dehydrogenase were decreased by 24% in the spinal cord (p = 0.005), suggesting perturbations in the PPP. The total amount of pyruvate in the cortex (p = 0.039) was reduced by 20% in hSOD1G93A mice. Also, the activities of the glycolytic enzyme pyruvate kinase were reduced in the cortex by 31% (p = 0.002), indicating alterations in glycolysis. No significant differences were seen in the total amounts as well as % 13C enrichments in most TCA cycle intermediates, suggesting largely normal TCA cycle function. On the other hand, oxoglutarate dehydrogenase activity was decreased in the cortex, which may indicate increased oxidative stress. Overall, this study revealed decreased activity of the PPP in the spinal cord and alterations in glycolysis in hSOD1G93A mouse CNS tissues at the early symptomatic stage of disease. PMID: 30685842 [PubMed - as supplied by publisher]

Precision Diabetes is Slowly Becoming a Reality. Med Princ Pract. 2019 Jan 27;: Authors: Mohan V, Radha V Abstract The concept of precision medicine is becoming increasingly popular. The use of big data, genomics and other 'omics' like metabolomics, proteomics and trancriptomics could make the dream of personalized medicine become a reality in the near future. As far as polygenic forms of diabetes like type 2 diabetes (T2DM) and type 1 diabetes (T1DM) are concerned, interesting leads are emerging, but precision diabetes is still in its infancy. However, with regard to monogenic forms of diabetes like Maturity-Onset-diabetes of the young (MODY) and Neonatal Diabetes Mellitus (NDM), rapid strides have been made and precision diabetes has already become part of the clinical tools used at advanced diabetes centres. In patients with some monogenic forms of diabetes, if the appropriate gene defects are identified, insulin injections can be stopped and they can be replaced with oral sulphonylurea (SU) drugs. In the coming years, rapid strides can be expected to be made in the field of precision diabetes, thereby making the control of diabetes more effective and hopefully leading to prevention of its complications and improvement of the quality of life of people afflicted with diabetes. PMID: 30685765 [PubMed - as supplied by publisher]

Exploration of microbiota targets for major depressive disorder and mood related traits. J Psychiatr Res. 2019 Jan 19;111:74-82 Authors: Chung YE, Chen HC, Chou HL, Chen IM, Lee MS, Chuang LC, Liu YW, Lu ML, Chen CH, Wu CH, Huang MC, Liao SC, Ni YH, Lai MS, Shih WL, Kuo PH Abstract Growing evidence suggests the link between gut microbiota and mood regulation. The current study aimed to identify microbiota targets for major depressive disorder (MDD) and mood-related traits in Taiwanese samples, while taking into account the influence of dietary patterns. We recruited 36 MDD patients and 37 healthy controls for 16S rRNA gene sequencing. We assessed nutrient content using food frequency questionnaire, and mood related phenotypes, including depressive severity, anxiety, and perceived stress. Analysis of composition of microbiomes (ANCOM) models were performed to evaluate microbiota compositions between patients and controls, while adjusted for fat intake% and sequencing platforms. We found 23 taxa (4 phyla, 7 families and 12 genera) to be associated with depression and beta diversity was differed between groups. Phylum Actinobacteria and Firmicutes were overrepresented in MDD patients. At genus level, Bifidobacterium (7%) and Blautia (8%) had relatively high abundance among MDD patients, while Prevotella (16%) had high abundance in controls. Holdemania exhibited moderate correlation with anxiety (r = 0.65) and perceived stress level (r = 0.49) mainly in MDD patients but not controls. Pathway analyses revealed that pentose phosphate and starch and sucrose metabolism processes were important pathways for depression via microbiota functions. In conclusion, our results revealed microbiota targets for depression that are independent of fat intake. It is worthwhile to conduct further studies to replicate the current findings and to integrate with biochemistry and metabolomics data to better understand the functions of identified targets. PMID: 30685565 [PubMed - as supplied by publisher]