3,060 research outputs found
Impact of the solvent capacity constraint on E. coli metabolism
<p>Abstract</p> <p>Background</p> <p>Obtaining quantitative predictions for cellular metabolic activities requires the identification and modeling of the physicochemical constraints that are relevant at physiological growth conditions. Molecular crowding in a cell's cytoplasm is one such potential constraint, as it limits the solvent capacity available to metabolic enzymes.</p> <p>Results</p> <p>Using a recently introduced flux balance modeling framework (FBAwMC) here we demonstrate that this constraint determines a metabolic switch in <it>E. coli </it>cells when they are shifted from low to high growth rates. The switch is characterized by a change in effective optimization strategy, the excretion of acetate at high growth rates, and a global reorganization of <it>E. coli </it>metabolic fluxes, the latter being partially confirmed by flux measurements of central metabolic reactions.</p> <p>Conclusion</p> <p>These results implicate the solvent capacity as an important physiological constraint acting on <it>E. coli </it>cells operating at high metabolic rates and for the activation of a metabolic switch when they are shifted from low to high growth rates. The relevance of this constraint in the context of both the aerobic ethanol excretion seen in fast growing yeast cells (Crabtree effect) and the aerobic glycolysis observed in rapidly dividing cancer cells (Warburg effect) should be addressed in the future.</p
Impact of limited solvent capacity on metabolic rate, enzyme activities, and metabolite concentrations of S. cerevisiae glycolysis
The cell's cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic rate determined by the solvent capacity constraint is close to that measured in vivo. These results indicate that the limited solvent capacity is a relevant constraint acting on S. cerevisiae at physiological growth conditions, and that a full kinetic model together with the limited solvent capacity constraint can be used to predict both metabolite concentrations and enzyme activities in vivo. © 2008 Vazquez et al
Molecular crowding defines a common origin for the Warburg effect in proliferating cells and the lactate threshold in muscle physiology
Aerobic glycolysis is a seemingly wasteful mode of ATP production that is seen both in rapidly proliferating mammalian cells and highly active contracting muscles, but whether there is a common origin for its presence in these widely different systems is unknown. To study this issue, here we develop a model of human central metabolism that incorporates a solvent capacity constraint of metabolic enzymes and mitochondria, accounting for their occupied volume densities, while assuming glucose and/or fatty acid utilization. The model demonstrates that activation of aerobic glycolysis is favored above a threshold metabolic rate in both rapidly proliferating cells and heavily contracting muscles, because it provides higher ATP yield per volume density than mitochondrial oxidative phosphorylation. In the case of muscle physiology, the model also predicts that before the lactate switch, fatty acid oxidation increases, reaches a maximum, and then decreases to zero with concomitant increase in glucose utilization, in agreement with the empirical evidence. These results are further corroborated by a larger scale model, including biosynthesis of major cell biomass components. The larger scale model also predicts that in proliferating cells the lactate switch is accompanied by activation of glutaminolysis, another distinctive feature of the Warburg effect. In conclusion, intracellular molecular crowding is a fundamental constraint for cell metabolism in both rapidly proliferating- and non-proliferating cells with high metabolic demand. Addition of this constraint to metabolic flux balance models can explain several observations of mammalian cell metabolism under steady state conditions
Constrained Allocation Flux Balance Analysis
New experimental results on bacterial growth inspire a novel top-down
approach to study cell metabolism, combining mass balance and proteomic
constraints to extend and complement Flux Balance Analysis. We introduce here
Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic
costs associated to growth are accounted for in an effective way through a
single additional genome-wide constraint. Its roots lie in the experimentally
observed pattern of proteome allocation for metabolic functions, allowing to
bridge regulation and metabolism in a transparent way under the principle of
growth-rate maximization. We provide a simple method to solve CAFBA efficiently
and propose an "ensemble averaging" procedure to account for unknown protein
costs. Applying this approach to modeling E. coli metabolism, we find that, as
the growth rate increases, CAFBA solutions cross over from respiratory,
growth-yield maximizing states (preferred at slow growth) to fermentative
states with carbon overflow (preferred at fast growth). In addition, CAFBA
allows for quantitatively accurate predictions on the rate of acetate excretion
and growth yield based on only 3 parameters determined by empirical growth
laws.Comment: 21 pages, 6 figures (main) + 33 pages, various figures and tables
(supporting); for the supplementary MatLab code, see
http://tinyurl.com/h763es
Macromolecular crowding explains overflow metabolism in cells
Overflow metabolism is a metabolic phenotype of cells characterized by mixed oxidative phosphorylation (OxPhos) and fermentative glycolysis in the presence of oxygen. Recently, it was proposed that a combination of a protein allocation constraint and a higher proteome fraction cost of energy generation by OxPhos relative to fermentation form the basis of overflow metabolism in the bacterium, Escherichia coli. However, we argue that the existence of a maximum or optimal macromolecular density is another essential requirement. Here we re-evaluate our previous theory of overflow metabolism based on molecular crowding following the proteomic fractions formulation. We show that molecular crowding is a key factor in explaining the switch from OxPhos to overflow metabolism
Dynamic optimization of metabolic networks coupled with gene expression
The regulation of metabolic activity by tuning enzyme expression levels is
crucial to sustain cellular growth in changing environments. Metabolic networks
are often studied at steady state using constraint-based models and
optimization techniques. However, metabolic adaptations driven by changes in
gene expression cannot be analyzed by steady state models, as these do not
account for temporal changes in biomass composition. Here we present a dynamic
optimization framework that integrates the metabolic network with the dynamics
of biomass production and composition, explicitly taking into account enzyme
production costs and enzymatic capacity. In contrast to the established dynamic
flux balance analysis, our approach allows predicting dynamic changes in both
the metabolic fluxes and the biomass composition during metabolic adaptations.
We applied our algorithm in two case studies: a minimal nutrient uptake
network, and an abstraction of core metabolic processes in bacteria. In the
minimal model, we show that the optimized uptake rates reproduce the empirical
Monod growth for bacterial cultures. For the network of core metabolic
processes, the dynamic optimization algorithm predicted commonly observed
metabolic adaptations, such as a diauxic switch with a preference ranking for
different nutrients, re-utilization of waste products after depletion of the
original substrate, and metabolic adaptation to an impending nutrient
depletion. These examples illustrate how dynamic adaptations of enzyme
expression can be predicted solely from an optimization principle
A physical model of cell metabolism
Cell metabolism is characterized by three fundamental energy demands: to sustain cell maintenance, to trigger aerobic fermentation and to achieve maximum metabolic rate. The transition to aerobic fermentation and the maximum metabolic rate are currently understood based on enzymatic cost constraints. Yet, we are lacking a theory explaining the maintenance energy demand. Here we report a physical model of cell metabolism that explains the origin of these three energy scales. Our key hypothesis is that the maintenance energy demand is rooted on the energy expended by molecular motors to fluidize the cytoplasm and counteract molecular crowding. Using this model and independent parameter estimates we make predictions for the three energy scales that are in quantitative agreement with experimental values. The model also recapitulates the dependencies of cell growth with extracellular osmolarity and temperature. This theory brings together biophysics and cell biology in a tractable model that can be applied to understand key principles of cell metabolism
Serine biosynthesis with one carbon catabolism represents a novel pathway for ATP generation in cells using alternative glycolysis with zero net ATP production
Recent experimental evidence indicates that some cancer cells have an alternative glycolysis pathway with net zero ATP production, implying that upregulation of glycolysis in these cells may not be related to the generation of ATP. Here we use a genome-scale model of human cell metabolism to investigate the potential metabolic alterations in cells using net zero ATP glycolysis. We uncover a novel pathway for ATP generation that involves reactions from the serine biosynthesis and one-carbon metabolism pathways. This pathway has a predicted two-fold higher flux rate in cells using net zero ATP glycolysis than those using standard glycolysis and generates twice as much ATP with significantly lower rate of lactate- but higher rate of alanine secretion. Thus, in cells using the standard- or the net zero ATP glycolysis pathways a significant portion of the glycolysis flux is always associated with ATP generation, and the ratio between the flux rates of the two pathways determines the rate of ATP generation and lactate and alanine secretion during glycolysis
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