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13 C-Metabolic flux analysis (13 C-MFA) has greatly contributed to our understanding of plant metabolic regulation. However, the generation of detailed in vivo flux maps remains a major challenge. Flux investigations based on nuclear magnetic resonance have resolved small networks with high accuracy. Mass spectrometry (MS) approaches have broader potential, but have hitherto been limited in their power to deduce flux information due to lack of atomic level position information. Herein we established a gas chromatography (GC) coupled to MS-based approach that provides 13 C-positional labelling information in glucose, malate and glutamate (Glu). A map of electron impact (EI)-mediated MS fragmentation was created and validated by 13 C-positionally labelled references via GC-EI-MS and GC-atmospheric pressure chemical ionization-MS technologies. The power of the approach was revealed by analysing previous 13 C-MFA data from leaves and guard cells, and 13 C-HCO3 labelling of guard cells harvested in the dark and after the dark-to-light transition. We demonstrated that the approach is applicable to established GC-EI-MS-based 13 C-MFA without the need for experimental adjustment, but will benefit in the future from paired analyses by the two GC-MS platforms. We identified specific glucose carbon atoms that are preferentially labelled by photosynthesis and gluconeogenesis, and provide an approach to investigate the phosphoenolpyruvate carboxylase (PEPc)-derived 13 C-incorporation into malate and Glu. Our results suggest that gluconeogenesis and the PEPc-mediated CO2 assimilation into malate are activated in a light-independent manner in guard cells. We further highlight that the fluxes from glycolysis and PEPc toward Glu are restricted by the mitochondrial thioredoxin system in illuminated leaves.

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BACKGROUND: Efficient xylose fermentation still demands knowledge regarding xylose catabolism. In this study, metabolic flux analysis (MFA) and metabolomics were used to improve our understanding of xylose metabolism. Thus, a stoichiometric model was constructed to simulate the intracellular carbon flux and used to validate the metabolome data collected within xylose catabolic pathways of non-Saccharomyces xylose utilizing yeasts. RESULTS: A metabolic flux model was constructed using xylose fermentation data from yeasts Scheffersomyces stipitis, Spathaspora arborariae, and Spathaspora passalidarum. In total, 39 intracellular metabolic reactions rates were utilized validating the measurements of 11 intracellular metabolites, acquired by mass spectrometry. Among them, 80% of total metabolites were confirmed with a correlation above 90% when compared to the stoichiometric model. Among the intracellular metabolites, fructose-6-phosphate, glucose-6-phosphate, ribulose-5-phosphate, and malate are validated in the three studied yeasts. However, the metabolites phosphoenolpyruvate and pyruvate could not be confirmed in any yeast. Finally, the three yeasts had the metabolic fluxes from xylose to ethanol compared. Xylose catabolism occurs at twice-higher flux rates in S. stipitis than S. passalidarum and S. arborariae. Besides, S. passalidarum present 1.5 times high flux rate in the xylose reductase reaction NADH-dependent than other two yeasts. CONCLUSIONS: This study demonstrated a novel strategy for metabolome data validation and brought insights about naturally xylose-fermenting yeasts. S. stipitis and S. passalidarum showed respectively three and twice higher flux rates of XR with NADH cofactor, reducing the xylitol production when compared to S. arborariae. Besides then, the higher flux rates directed to pentose phosphate pathway (PPP) and glycolysis pathways resulted in better ethanol production in S. stipitis and S. passalidarum when compared to S. arborariae.

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In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a 13C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% 13C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genome-scale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.

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The yeast Scheffersomyces stipitis naturally produces ethanol from xylose, however reaching high ethanol yields is strongly dependent on aeration conditions. It has been reported that changes in the availability of NAD(H/+) cofactors can improve fermentation in some microorganisms. In this work genome-scale metabolic modeling and phenotypic phase plane analysis were used to characterize metabolic response on a range of uptake rates. Sensitivity analysis was used to assess the effect of ARC on ethanol production indicating that modifying ARC by inhibiting the respiratory chain ethanol production can be improved. It was shown experimentally in batch culture using Rotenone as an inhibitor of the mitochondrial NADH dehydrogenase complex I (CINADH), increasing ethanol yield by 18%. Furthermore, trajectories for uptakes rates, specific productivity and specific growth rate were determined by modeling the batch culture, to calculate ARC associated to the addition of CINADH inhibitor. Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC.

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In this work, in silico flux balance analysis is used for predicting the metabolic behavior of Streptomyces clavuligerus during clavulanic acid production. To choose the best objective function for use in the analysis, three different optimization problems are evaluated inside the flux balance analysis formulation: (i) maximization of the specific growth rate, (ii) maximization of the ATP yield, and (iii) maximization of clavulanic acid production. Maximization of ATP yield showed the best predictions for the cellular behavior. Therefore, flux balance analysis using ATP as objective function was used for analyzing different scenarios of nutrient limitations toward establishing the effect of limiting the carbon, nitrogen, phosphorous, and oxygen sources on the growth and clavulanic acid production rates. Obtained results showed that ammonia and phosphate limitations are the ones most strongly affecting clavulanic acid biosynthesis. Furthermore, it was possible to identify the ornithine flux from the urea cycle and the α-ketoglutarate flux from the TCA cycle as the most determinant internal fluxes for promoting clavulanic acid production.

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We present a study of the metabolism of the Mycobacterium tuberculosis after exposure to antibiotics using proteomics data and flux balance analysis (FBA). The use of FBA to study prokaryotic organisms is well-established and allows insights into the metabolic pathways chosen by the organisms under different environmental conditions. To apply FBA a specific objective function must be selected that represents the metabolic goal of the organism. FBA estimates the metabolism of the cell by linear programming constrained by the stoichiometry of the reactions in an in silico metabolic model of the organism. It is assumed that the metabolism of the organism works towards the specified objective function. A common objective is the maximization of biomass. However, this goal is not suitable for situations when the bacterium is exposed to antibiotics, as the goal of organisms in these cases is survival and not necessarily optimal growth. In this paper we propose a new approach for defining the FBA objective function in studies when the bacterium is under stress. The function is defined based on protein expression data. The proposed methodology is applied to the case when the bacterium is exposed to the drug mefloquine, but can be easily extended to other organisms, conditions or drugs. We compare our method with an alternative method that uses experimental data for adjusting flux constraints. We perform comparisons in terms of essential enzymes and agreement using enzyme abundances. Results indicate that using proteomics data to define FBA objective functions yields less essential reactions with zero flux and lower error rates in prediction accuracy. With flux variability analysis we observe that overall variability due to alternate optima is reduced with the incorporation of proteomics data. We believe that incorporating proteomics data in the objective function used in FBA may help obtain metabolic flux representations that better support experimentally observed features.

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The oxidation process of sulfide minerals in natural environments is achieved by microbial communities from the Archaea and Bacteria domains. A metabolic reconstruction of two dominant species, Leptospirillum ferriphilum and Ferroplasma acidiphilum, which are always found together as a mixed culture in this natural environments, was made. The metabolic model, composed of 152 internal reactions and 29 transport reactions, describes the main interactions between these species, assuming that both use ferrous iron as energy source, and F. acidiphilum takes advantage of the organic compounds secreted by L. ferriphilum for chemomixotrophic growth. A first metabolic model for a mixed culture used in bacterial leaching is proposed in this article, which pretends to represent the characteristics of the mixed culture in a simplified manner. It was evaluated with experimental data through flux balance analysis (FBA) using as objective function the maximization of biomass. The growth yields on ferrous iron obtained for each microorganism are consistent with experimental data, and the flux distribution obtained allows understanding of the metabolic capabilities of both microorganisms growing together in a bioleaching process. The model was used to simulate the growth of F. acidiphilum on different substrates, to determine in silico which compounds maximize cell growth, and which are essential. Knockout simulations were carried out for L. ferriphilum and F. acidiphilum metabolic models, predicting key enzymes of central metabolism. The results of this analysis are consistent with experimental data from literature, showing a robust behavior of the metabolic model.

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Introducción: la medición de la excreción urinaria de sodio es importante en pacientes con litiasis urinaria, pues su excreción elevada predispone a hipercalciuria, el trastorno metabólico urinario más frecuente. Objetivo: determinar la ingestión (igual a excreción) de sodio e identificar su posible relación con variables demográficas y nutricionales, en pacientes con litiasis urinaria. Métodos: se desarrolló un estudio analítico, transversal, de los pacientes con litiasis urinaria que se hicieron estudio metabólico renal en el Instituto de Nefrología, entre enero 2011 y diciembre 2012. Se excluyeron los pacientes con factores que modifican la excreción de sodio. Las determinaciones de creatinina fueron realizadas por el método cinético de Jaffé, con espectrofotómetro Jenway®; las mediciones del sodio urinario, con analizador electrolítico marca Roche®. La información fue procesada de forma automatizada (SPSS versión 15.0). En cada categoría de las variables fueron calculadas media y desviación estándar de la excreción de sodio (mEq/d). Las comparaciones de los promedios se realizaron mediante la prueba t o mediante ANOVA. Resultados: de 1 985 pacientes estudiados, 1 363 fueron del sexo masculino (68,7 por ciento) y 622, del femenino (31,3 por ciento). La excreción urinaria media de sodio fue 235,29 mEq/d, globalmente, y resultó mayor en los hombres (252,69 mEq/d), al ser comparada con la de las mujeres (197,14 mEq/d) (p= 0,00). También se encontraron diferencias al comparar la excreción de sodio entre las categorías de valoración nutricional (p= 0,00) y de excreción de creatinina (p= 0,0). Conclusiones: la excreción urinaria de sodio es elevada en pacientes urolitiásicos, mayor en los hombres y en los sujetos con sobrepeso y obesidad(AU)

Introduction: measurement of urinary sodium excretion is important in patients with urolithiasis, for a high level of excretion leads to hypercalciuria, the most common urinary metabolic disorder. Objective: to determine sodium intake (equal to excretion) and identify its possible relationship to demographic and nutritional variables in patients with urinary lithiasis. Methods: an analytical cross-sectional study was conducted in patientes with urinary lithiasis undergoing metabolic renal study at the Institute of Nephrology from January 2011 to December 2012. Patients with factors modifying sodium excretion were excluded. Creatinine determinations were made with Jaffé's kinetic method using a Jenway™ spectrophotometer. Urinary sodium was measured with a Roche™ electrolytic analyzer. Data was processed with the statistical software SPSS version 15.0. Variables for each category were estimated as mean and standard deviation of sodium excretion (mEq/d). Comparisons of averages were made with the t test or ANOVA. Results: of the 1 985 patients studied, 1 363 were male (68.7 percent) and 622 were female (31.3 percent). Global mean sodium urinary excretion was 235.29 mEq/d, greater in men (252.69 mEq/d) than in women (197.14 mEq/d) (p= 0.00). Differences were also found when sodium excretion was compared by nutritional assessment (p= 0.00) and creatinine excretion (p= 0.0). Conclusions: urinary sodium excretion is high in patients with urolithiasis. Values are higher in men, and in overweight and obese individuals(AU)

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