Project description:Background: Cyanobacteria are ecologically significant prokaryotes that can be found in heavy metals contaminated environments. As their photosynthetic machinery imposes high demands for metals, homeostasis of these micronutrients has been extensively considered in cyanobacteria. Recently, most studies have been focused on different habitats using microalgae leads to a remarkable reduction of an array of organic and inorganic nutrients, but what takes place in the extracellular environment when cells are exposed to external supplementation with heavy metals remains largely unknown. Methods: Here, extracellular polymeric substances (EPS) production in strains Nostoc sp. N27P72 and Nostoc sp. FB71 was isolated from different habitats and thenthe results were compared and reported . Result: Cultures of both strains, supplemented separately with either glucose, sucrose, lactose, or maltose showed that production of EPS and cell dry weight were boosted by maltose supplementation. The production of EPS (9.1 ± 0.05 μg/ml) and increase in cell dry weight (1.01 ± 0.06 g/l) were comparatively high in Nostoc sp. N27P72 which was isolated from lime stones.The cultures were evaluated for their ability to remove Cu (II), Cr (III), and Ni (II) in culture media with and without maltose. The crude EPS showed metal adsorption capacity assuming the order Ni (II)> Cu (II)> Cr (III) from the metal-binding experiments .Nickel was preferentially biosorbed with a maximal uptake of 188.8 ± 0.14 mg (g cell dry wt) -1 crude EPS. We found that using maltose as a carbon source can increase the production of EPS, protein, and carbohydrates content and it could be a significant reason for the high ability of metal absorbance. FT-IR spectroscopy revealed that the treatment with Ni can change the functional groups and glycoside linkages in both strains. Results of Gas Chromatography-Mass Spectrometry (GC–MS) were used to determine the biochemical composition of Nostoc sp. N27P72, showed that strong Ni (II) removal capability could be associated with the high silicon containing heterocyclic compound and aromatic diacid compounds content. Conclusion: The results of this studyindicatede that strains Nostoc sp. N27P72 can be a good candidate for the commercial production of EPS and might be utilized in bioremediation field as an alternative to synthetic and abiotic flocculants.
Project description:Background: Cyanobacteria are ecologically significant prokaryotes that can be found in heavy metals contaminated environments. As their photosynthetic machinery imposes high demands for metals, homeostasis of these micronutrients has been extensively considered in cyanobacteria. Recently, most studies have been focused on different habitats using microalgae leads to a remarkable reduction of an array of organic and inorganic nutrients, but what takes place in the extracellular environment when cells are exposed to external supplementation with heavy metals remains largely unknown. Methods: Here, extracellular polymeric substances (EPS) production in strains Nostoc sp. N27P72 and Nostoc sp. FB71 was isolated from different habitats and thenthe results were compared and reported . Result: Cultures of both strains, supplemented separately with either glucose, sucrose, lactose, or maltose showed that production of EPS and cell dry weight were boosted by maltose supplementation. The production of EPS (9.1 ± 0.05 μg/ml) and increase in cell dry weight (1.01 ± 0.06 g/l) were comparatively high in Nostoc sp. N27P72 which was isolated from lime stones.The cultures were evaluated for their ability to remove Cu (II), Cr (III), and Ni (II) in culture media with and without maltose. The crude EPS showed metal adsorption capacity assuming the order Ni (II)> Cu (II)> Cr (III) from the metal-binding experiments .Nickel was preferentially biosorbed with a maximal uptake of 188.8 ± 0.14 mg (g cell dry wt) -1 crude EPS. We found that using maltose as a carbon source can increase the production of EPS, protein, and carbohydrates content and it could be a significant reason for the high ability of metal absorbance. FT-IR spectroscopy revealed that the treatment with Ni can change the functional groups and glycoside linkages in both strains. Results of Gas Chromatography-Mass Spectrometry (GC–MS) were used to determine the biochemical composition of Nostoc sp. N27P72, showed that strong Ni (II) removal capability could be associated with the high silicon containing heterocyclic compound and aromatic diacid compounds content.
Project description:Oncogene-associated metabolic signatures in prostate cancer, identified by an integrative analysis of cultured cells and murine and human tumors, suggest that AKT activation results in a glycolytic phenotype whereas MYC induces aberrant lipid metabolism. Heterogeneity in human tumors makes this simplistic interpretation obtained from experimental models more challenging. Metabolic reprogramming as a function of distinct molecular aberrations has major diagnostic and therapeutic implications.
Project description:The aim of the present study was to screen differential metabolites of gastric cancer (GC) and identify the key metabolic pathways of GC. GC (n=28) and matched paracancerous (PC) tissues were collected, and LC-MS/MS analysis were performed to detect metabolites of GC and PC tissues. Metabolite pathways based on differential metabolites were enriched by MetaboAnalyst, and genes related to metabolite pathways were identified using the KEGGREST function of the R software package. Transcriptomics data from The Cancer Genome Atlas (TCGA) was analyzed to obtain differentially expressed genes (DEGs) of GC. Overlapping genes were acquired from metabonimics and transcriptomics data. Pathway enrichment analysis was performed using String. The protein expression of genes was validated by the Human Protein Atlas (HPA) database. A total of 325 key metabolites were identified, 111 of which were differentially expressed between the GC and PC groups. Seven metabolite pathways enriched by MetaboAnalyst were chosen, and 361 genes were identified by KEGGREST. A total of 2831 DEGs were identified from the TCGA cohort. Of these, 1317 were down-regulated, and 1636 were up-regulated. Twenty-two overlapping genes were identified between genes related to metabolism and DEGs. Glycerophospholipid (GPL) metabolism is likely associated with GC, of which AGPAT9 and ETNPPL showed lower expressed in GC tissues. We investigated the tissue-based metabolomics profile of GC, and several differential metabolites were identified. GPL metabolism may affect on progression of GC.
Project description:Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.
Project description:BackgroundBiologic pathways and metabolic mechanisms underpinning early systemic disease in cystic fibrosis (CF) are poorly understood. The Baby Observational and Nutrition Study (BONUS) was a prospective multi-center study of infants with CF with a primary aim to examine the current state of nutrition in the first year of life. Its secondary aim was to prospectively explore concurrent nutritional, metabolic, respiratory, infectious, and inflammatory characteristics associated with early CF anthropometric measurements. We report here metabolomics differences within the urine of these infants as compared to infants without CF.MethodsUrine metabolomics was performed for 85 infants with predefined clinical phenotypes at approximately one year of age enrolled in BONUS via Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Samples were stratified by disease status (non-CF controls (n = 22); CF (n = 63, All-CF)) and CF clinical phenotype: respiratory hospitalization (CF Resp, n = 22), low length (CF LL, n = 23), and low weight (CF LW, n = 15).ResultsGlobal urine metabolomics profiles in CF were heterogeneous, however there were distinct metabolic differences between the CF and non-CF groups. Top pathways altered in CF included tRNA charging and methionine degradation. ADCYAP1 and huntingtin were identified as predicted unique regulators of altered metabolic pathways in CF compared to non-CF. Infants with CF displayed alterations in metabolites associated with bile acid homeostasis, pentose sugars, and vitamins.ConclusionsPredicted metabolic pathways and regulators were identified in CF infants compared to non-CF, but metabolic profiles were unable to discriminate between CF phenotypes. Targeted metabolomics provides an opportunity for further understanding of early CF disease.Trial registrationUnited States ClinicalTrials.Gov registry NCT01424696 (clinicaltrials.gov).
Project description:Chagas disease is a trypanosomiasis whose causative agent is the protozoan parasite Trypanosoma cruzi, which is transmitted to humans by hematophagous insects known as triatomines and affects a large proportion of South America. The digestive tract of the insect vectors in which T. cruzi develops constitutes a dynamic environment that affects the development of the parasite. Thus, we set out to investigate the chemical composition of the triatomine intestinal tract through a metabolomics approach. We performed Direct Infusion Fourier Transform Ion Cyclotron Resonance Mass Spectrometry on fecal samples of three triatomine species (Rhodnius prolixus, Triatoma infestans, Panstrongylus megistus) fed with rabbit blood. We then identified groups of metabolites whose frequencies were either uniform in all species or enriched in each of them. By querying the Human Metabolome Database, we obtained putative identities of the metabolites of interest. We found that a core group of metabolites with uniform frequencies in all species represented approximately 80% of the molecules detected, whereas the other 20% varied among triatomine species. The uniform core was composed of metabolites of various categories, including fatty acids, steroids, glycerolipids, nucleotides, sugars, and others. Nevertheless, the metabolic fingerprint of triatomine feces differs depending on the species considered. The variable core was mainly composed of prenol lipids, amino acids, glycerolipids, steroids, phenols, fatty acids and derivatives, benzoic acid and derivatives, flavonoids, glycerophospholipids, benzopyrans, and quinolines. Triatomine feces constitute a rich and varied chemical medium whose constituents are likely to affect T. cruzi development and infectivity. The complexity of the fecal metabolome of triatomines suggests that it may affect triatomine vector competence for specific T. cruzi strains. Knowledge of the chemical environment of T. cruzi in its invertebrate host is likely to generate new ways to understand the factors influencing parasite proliferation as well as methods to control Chagas disease.
Project description:Background and aimsThe important metabolic features of acute pulmonary embolism (APE) risk stratification and their underlying biological basis remain elusive. Our study aims to develop early diagnostic models and classification models by analyzing the plasma metabolic profile of patients with APE.Materials and methodsSerum samples were collected from 68 subjects, including 19 patients with confirmed APE, 35 patients with confirmed NSTEMI, and 14 healthy individuals. A comprehensive metabolic assessment was performed using ultra-performance liquid chromatography-mass spectrometry based on an untargeted metabolomics approach. In addition, an integrated machine learning strategy based on LASSO and logistic regression was used for feature selection and model building.ResultsThe metabolic profiles of patients with acute pulmonary embolism and NSTEMI is significantly altered relative to that of healthy individuals. KEGG pathway enrichment analysis revealed differential metabolites between acute pulmonary embolism and healthy individuals mainly involving glycerophosphate shuttle, riboflavin metabolism, and glycerolipid metabolism. A panel of biomarkers was defined to distinguish acute pulmonary embolism, NSTEMI, and healthy individuals with an area under the receiver operating characteristic curve exceeding 0.9 and higher than that of D-dimers.ConclusionThis study contributes to a better understanding of the pathogenesis of APE and facilitates the discovery of new therapeutic targets. The metabolite panel can be used as a potential non-invasive diagnostic and risk stratification tool for APE.
Project description:As a follow-up to a previous article, this review provides several in-depth concepts regarding a survival analysis. Also, several codes for specific survival analysis are listed to enhance the understanding of such an analysis and to provide an applicable survival analysis method. A proportional hazard assumption is an important concept in survival analysis. Validation of this assumption is crucial for survival analysis. For this purpose, a graphical analysis method and a goodnessof- fit test are introduced along with detailed codes and examples. In the case of a violated proportional hazard assumption, the extended models of a Cox regression are required. Simplified concepts of a stratified Cox proportional hazard model and time-dependent Cox regression are also described. The source code for an actual analysis using an available statistical package with a detailed interpretation of the results can enable the realization of survival analysis with personal data. To enhance the statistical power of survival analysis, an evaluation of the basic assumptions and the interaction between variables and time is important. In doing so, survival analysis can provide reliable scientific results with a high level of confidence.
Project description:Metabolomics has been used to explore the molecular mechanism and screen biomarkers. However, the critical metabolic signatures associated with benzene-induced hematotoxicity remain elusive. Here, we performed a plasma metabolomics study in 86 benzene-exposed workers and 76 healthy controls, followed by a validation analysis in mice, to investigate the dynamical change of the metabolic profile. We found that 8 fatty acids were significantly altered in both benzene-exposed worker and benzene-exposed animal models. These metabolites were significantly associated with S-phenylmercapturic acid and WBC, and they mediated the benzene-induced WBC decline. Furthermore, in vivo results confirm that fatty acid levels were dynamically altered, characterized by a decrease at 15 days and then sharp increases at 30 and 45 days. Following these identified fatty acids, the potential metabolic pathways were investigated. Fatty acids, as precursors for fatty acid oxidation, may disturb the balance of fatty acid biosynthesis and degradation. Our results reveal that fatty acid metabolism was strongly reprogrammed after benzene exposure. This abnormal change of fatty acids might be the key metabolic signature associated with benzene-induced hematotoxicity.