Metabolic Flux and Compartmentation Analysis in the Brain In vivo.

Through significant developments and progresses in the last two decades, in vivo localized nuclear magnetic resonance spectroscopy (MRS) became a method of choice to probe brain metabolic pathways in a non-invasive way. Beside the measurement of the total concentration of more than 20 metabolites, (1)H MRS can be used to quantify the dynamics of substrate transport across the blood-brain barrier by varying the plasma substrate level. On the other hand, (13)C MRS with the infusion of (13)C-enriched substrates enables the characterization of brain oxidative metabolism and neurotransmission by incorporation of (13)C in the different carbon positions of amino acid neurotransmitters. The quantitative determination of the biochemical reactions involved in these processes requires the use of appropriate metabolic models, whose level of details is strongly related to the amount of data accessible with in vivo MRS. In the present work, we present the different steps involved in the elaboration of a mathematical model of a given brain metabolic process and its application to the experimental data in order to extract quantitative brain metabolic rates. We review the recent advances in the localized measurement of brain glucose transport and compartmentalized brain energy metabolism, and how these reveal mechanistic details on glial support to glutamatergic and GABAergic neurons.

Twenty-four-hour energy expenditure and basal metabolic rate measured in a whole-body indirect calorimeter in Gambian men.

By use of a respiration chamber, 24-hour energy expenditure (EE), diet-induced thermogenesis (DIT), and basal and sleeping EE were measured in 20 young rural Gambian men during the "hungry" season (weight, 60.8 +/- 1.4 kg) and in a group of 16 European men matched for body composition (weight, 66.9 +/- 1.9 kg). The 24-h EE was lower in Gambian than in European men (2047 +/- 46 vs 2635 +/- 74 kcal/d, p less than 0.001, respectively). Basal EE and sleeping EE were also lower in Gambian than in European men (1.05 +/- 0.02 vs 1.25 +/- 0.02 kcal/min and 1.0 +/- 0.02 vs 1.18 +/- 0.02 kcal/min, p less than 0.01, respectively). DIT was blunted in Gambian compared with European men (6.3 +/- 0.6% vs 12.1 +/- 0.5%, p less than 0.001 respectively). The net efficiency of walking was greater in Gambian than in European men (23.2 +/- 0.3% vs 20.1 +/- 0.4%, p less than 0.001, respectively). A low basal and sleeping EE, a reduced DIT, and a high work efficiency are important energy-sparing mechanisms in Gambian men, which allow them to cope with a marginal level of dietary intake during the hungry season.

Metabolic equivalent: one size does not fit all.

The metabolic equivalent (MET) is a widely used physiological concept that represents a simple procedure for expressing energy cost of physical activities as multiples of resting metabolic rate (RMR). The value equating 1 MET (3.5 ml O2 x kg(-1) x min(-1) or 1 kcal x kg(-1) x h(-1)) was first derived from the resting O2 consumption (VO2) of one person, a 70-kg, 40-yr-old man. Given the extensive use of MET levels to quantify physical activity level or work output, we investigated the adequacy of this scientific convention. Subjects consisted of 642 women and 127 men, 18-74 yr of age, 35-186 kg in weight, who were weight stable and healthy, albeit obese in some cases. RMR was measured by indirect calorimetry using a ventilated hood system, and the energy cost of walking on a treadmill at 5.6 km/h was measured in a subsample of 49 men and 49 women (26-45 kg/m2; 29-47 yr). Average VO2 and energy cost corresponding with rest (2.6 +/- 0.4 ml O2 x kg(-1) x min(-1) and 0.84 +/- 0.16 kcal x kg(-1) x h(-1), respectively) were significantly lower than the commonly accepted 1-MET values of 3.5 ml O2 x kg(-1) x min(-1) and 1 kcal x kg(-1) x h(-1), respectively. Body composition (fat mass and fat-free mass) accounted for 62% of the variance in resting VO2 compared with age, which accounted for only 14%. For a large heterogeneous sample, the 1-MET value of 3.5 ml O2 x kg(-1) x min(-1) overestimates the actual resting VO2 value on average by 35%, and the 1-MET of 1 kcal/h overestimates resting energy expenditure by 20%. Using measured or predicted RMR (ml O2 x kg(-1) x min(-1) or kcal x kg(-1) x h(-1)) as a correction factor can appropriately adjust for individual differences when estimating the energy cost of moderate intensity walking (5.6 km/h).

Effects of propranolol on resting metabolic rate after severe head injury.

Postabsorptive resting metabolic rate (RMR), measured by indirect calorimetry, and the effect of iv propranolol administration were studied in 12 nonseptic patients with severe head injury by means of indirect calorimetry. Before propranolol RMR was moderately increased (126 +/- 10.4% of predicted values) whereas urinary excretion of catecholamines was markedly elevated (p less than .01 vs. normal values). RMR was significantly correlated with both resting heart rate (HR) (r = .72, p less than .01) and 24-h urinary N excretion (r = .85, p less than .001). The administration of iv propranolol (0.1 mg/kg) produced a rapid decrease in HR (-10 +/- 4%, p less than .001) and in RMR (-6.1 +/- 2.3%, p less than .001). Further administration of propranolol produced no additional reduction in either HR or RMR. We conclude that severely head-injured patients are moderately hypermetabolic in resting and postabsorptive conditions, and that acute iv propranolol administration induces a reduction of about one quarter of the resting hypermetabolism.

Probable metabolic interaction between methadone and fluvoxamine in addict patients.

We report five cases where fluvoxamine (FLVX) was added to maintenance treatment with methadone (MTD) in addict patients with affective disorders. In view of the implication of FLVX in several metabolic drug interactions, MTD plasma levels were measured before and after treatment with FLVX. A slight increase (approximately 20% of the MTD plasma level/dose ratio) occurred in two cases. In the remaining three patients, the interaction was more pronounced (40-100% increase of the MTD plasma level/dose ratio), with clinical manifestations of opiate withdrawal after stopping FLVX therapy in one case. Caution is needed when starting or stopping treatment with FLVX in patients receiving maintenance treatment with methadone.

FGF21 signalling pathway and metabolic traits - genetic association analysis.

Fibroblast growth factor 21 (FGF21) is a novel master regulator of metabolic profile. The biological actions of FGF21 are elicited upon its klotho beta (KLB)-facilitated binding to FGF receptor 1 (FGFR1), FGFR2 and FGFR3. We hypothesised that common polymorphisms in the FGF21 signalling pathway may be associated with metabolic risk. At the screening stage, we examined associations between 63 common single-nucleotide polymorphisms (SNPs) in five genes of this pathway (FGF21, KLB, FGFR1, FGFR2, FGFR3) and four metabolic phenotypes (LDL cholesterol - LDL-C, HDL-cholesterol - HDL-C, triglycerides and body mass index) in 629 individuals from Silesian Hypertension Study (SHS). Replication analyses were performed in 5478 unrelated individuals of the Swiss CoLaus cohort (imputed genotypes) and in 3030 directly genotyped individuals of the German Myocardial Infarction Family Study (GerMIFS). Of 54 SNPs that met quality control criteria after genotyping in SHS, 4 (rs4733946 and rs7012413 in FGFR1; rs2071616 in FGFR2 and rs7670903 in KLB) showed suggestive association with LDL-C (P=0.0006, P=0.0013, P=0.0055, P=0.011, respectively) and 1 (rs2608819 in KLB) was associated with body mass index (P=0.011); all with false discovery rate q<0.5. Of these, only one FGFR2 polymorphism (rs2071616) showed replicated association with LDL-C in both CoLaus (P=0.009) and men from GerMIFS (P=0.017). The direction of allelic effect of rs2071616 upon LDL-C was consistent in all examined populations. These data show that common genetic variations in FGFR2 may be associated with LDL-C in subjects of white European ancestry.

Comparison of the metabolic and endocrine effects of 3,5,3'-triiodothyroacetic acid and thyroxine.

To test the hypothesis that 3,5,3'-triiodothyroacetic acid (Triac) is more active as a TSH suppressor than on peripheral parameters of thyroid hormone action, the following parameters were studied: basal metabolic rate, sleeping energy expenditure (SEE), sex hormone-binding globulin, and cholesterol. In a double blind trial, 14 subjects received during 3 weeks (phase 1) 180 micrograms T4 or 1700 micrograms Triac daily, divided into 3 doses, to suppress thyroidal secretion. The dosage was doubled for the next 3 weeks (phase 2). Under T4 treatment, TSH reached 0.11 mU/L during phase 1 and less than 0.03 mU/L during phase 2. With Triac, a marked TSH inhibition occurred after 1 week (0.17 mU/L), followed by an escape during the following 2 weeks (0.63 mU/L). During phase 2, an almost complete TSH suppression was obtained (0.03 mU/L). Both Triac doses suppressed endogenous thyroid hormone secretion, as evidenced by T4 and rT3 levels. Both substances induced a 2-fold stimulation of sex hormone-binding globulin during phase 2. Serum cholesterol decreased similarly, without affecting the high/low density lipoprotein ratio. T4 increased SEE by 4.1% and 8.5% during phases 1 and 2. Triac failed to induce the expected peripheral metabolic responses of the thyroid hormones, as demonstrated by an unchanged SEE and basal metabolic rate. These results clearly show a preferential action of Triac on TSH suppression.

A repeated GGA motif is critical for the activity and stability of the riboregulator RsmY of Pseudomonas fluorescens.

The riboregulator RsmY of Pseudomonas fluorescens strain CHA0 is an example of small regulatory RNAs belonging to the global Rsm/Csr regulatory systems controlling diverse cellular processes such as glycogen accumulation, motility, or formation of extracellular products in various bacteria. By binding multiple molecules of the small regulatory protein RsmA, RsmY relieves the negative effect of RsmA on the translation of several target genes involved in the biocontrol properties of strain CHA0. RsmY and functionally related riboregulators have repeated GGA motifs predicted to be exposed in single-stranded regions, notably in the loops of hairpins. The secondary structure of RsmY was corroborated by in vivo cleavage with lead acetate. RsmY mutants lacking three or five (out of six) of the GGA motifs showed reduced ability to derepress the expression of target genes in vivo and failed to bind the RsmA protein efficiently in vitro. The absence of GGA motifs in RsmY mutants resulted in reduced abundance of these transcripts and in a shorter half-life (< or = 6 min as compared with 27 min for wild type RsmY). These results suggest that both the interaction of RsmY with RsmA and the stability of RsmY strongly depend on the GGA repeats and that the ability of RsmY to interact with small regulatory proteins such as RsmA may protect this RNA from degradation.

An analysis of the metabolic patterns of two rural communities affected by soy expansion in the North of Argentina

The soy expansion model in Argentina generates structural changes in traditional lifestyles that can be associated with different biophysical and socioeconomic impacts. To explore this issue, we apply an innovative method for integrated assessment - the Multi Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) framework - to characterize two communities in the Chaco Region, Province of Formosa, North of Argentina. These communities have recently experienced the expansion of soy production, altering their economic activity, energy consumption patterns, land use, and human time allocation. The integrated characterization presented in the paper illustrates the differences (biophysical, socioeconomic, and historical) between the two communities that can be associated with different responses. The analysis of the factors behind these differences has important policy implications for the sustainable development of local communities in the area.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Background: Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment andinnate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results:Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection arefrequent on genes that are known to be at bifurcation points, and that are identified as beingin key position by a network-level analysis such as MGAT3 and GCS1.Conclusions: These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.