Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast

We studied the steady-state responses to changes in growth rate of yeast when ethanol is the sole source of carbon and energy. Analysis of these data, together with data from studies where glucose was the carbon source, allowed us to distinguish a "universal" growth rate response (GRR) common to all media studied from a GRR specific to the carbon source. Genes with positive universal GRR include ribosomal, translation, and mitochondrial genes, and those with negative GRR include autophagy, vacuolar, and stress response genes. The carbon source-specific GRR genes control mitochondrial function, peroxisomes, and synthesis of vitamins and cofactors, suggesting this response may reflect the intensity of oxidative metabolism. All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC). We propose that the universal GRR may be accounted for by changes in the relative durations of the YMC phases. This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h. We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.     

Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast

We studied the relationship between growth rate and genome-wide gene expression, cell cycle progression, and glucose metabolism in 36 steady-state continuous cultures limited by one of six different nutrients (glucose, ammonium, sulfate, phosphate, uracil, or leucine). The expression of more than one quarter of all yeast genes is linearly correlated with growth rate, independent of the limiting nutrient. The subset of negatively growth-correlated genes is most enriched for peroxisomal functions, whereas positively correlated genes mainly encode ribosomal functions. Many (not all) genes associated with stress response are strongly correlated with growth rate, as are genes that are periodically expressed under conditions of metabolic cycling. We confirmed a linear relationship between growth rate and the fraction of the cell population in the G0/G1 cell cycle phase, independent of limiting nutrient. Cultures limited by auxotrophic requirements wasted excess glucose, whereas those limited on phosphate, sulfate, or ammonia did not; this phenomenon (reminiscent of the "Warburg effect" in cancer cells) was confirmed in batch cultures. Using an aggregate of gene expression values, we predict (in both continuous and batch cultures) an "instantaneous growth rate." This concept is useful in interpreting the system-level connections among growth rate, metabolism, stress, and the cell cycle.     

Comparison of metabolic flux distributions for MDCK cell growth in glutamine- and pyruvate-containing media

In mammalian cell cultures, ammonia that is released into the medium as a result of glutamine metabolism and lactate that is excreted due to incomplete glucose oxidation are both known to essentially inhibit the growth of cells. For some cell lines, for example, hybridoma cells, excreted ammonia also has an effect on product formation. Although glutamine has been generally considered as the major energy source for mammalian cells, it was recently found that various adherent cell lines (MDCK, CHO-K1, and BHK21) can grow as well in glutamine-free medium, provided glutamine is substituted with pyruvate. In such a medium the level of both ammonia and lactate released was significantly reduced. In this study, metabolic flux analysis (MFA) was applied to Madin Darby Canine Kidney (MDCK) cells cultivated in glutamine-containing and glutamine-free medium. The results of the MFA allowed further investigation of the influence of glutamine substitution with pyruvate on the metabolism of MDCK cells during different growth stages of adherent cells, e.g., early exponential and late contact-inhibited phase. Pyruvate seemed to directly enter the TCA cycle, whereas most of the glucose consumed was excreted as lactate. Although the exact mechanisms are not clear so far, this resulted in a reduction of the glucose uptake necessary for cellular metabolism in glutamine-free medium. Furthermore, consumption of ATP by futile cycles seemed to be significantly reduced when substituting glutamine with pyruvate. These findings imply that glutamine-free medium favors a more efficient use of nutrients by cells. However, a number of metabolic fluxes were similar in the two cultivations considered, e.g., most of the amino acid uptake and degradation rates or fluxes through the branch of the TCA cycle converting alpha-ketoglutarate to malate, which is responsible for the mitochondrial ATP synthesis. Besides, the specific rate of cell growth was approximately the same in both cultivations. Thus, the switch from glutamine-containing to glutamine-free medium with pyruvate provided a series of benefits without dramatic changes of cellular metabolism.     

Mass spectrometry for metabolic flux analysis

Mass spectrometry in combination with tracer experiments based on 13C substrates can serve as a powerful tool for the modeling and analysis of intracellular fluxes and the investigation of biochemical networks. The theoretical background for the application of mass spectrometry to metabolic flux analysis is discussed. Mass spectrometry methods are especially useful to determine mass distribution of metabolites. Additional information gained from fragmentation of metabolites, e.g., by electron impact ionization, allows further localization of labeling positions, up to complete resolution of isotopomer pools. To effectively handle mass distributions in simulation experiments, a matrix based general methodology is formulated. The natural isotope distribution of carbon, oxygen, hydrogen and nitrogen in the target metabolites is considered by introduction of correction matrices. It is shown by simulation results for the central carbon metabolism that neglecting natural isotope distributions causes significant errors in intracellular flux distributions. By varying relative fluxes into pentosephosphate pathway and pyruvate carboxylation reaction, marked changes in the mass distributions of metabolites result, which are illustrated for pyruvate, oxaloacetate, and alpha-ketoglutarate. In addition mass distributions of metabolites are significantly influenced over a broad range by the degree of reversibility of transaldolase and transketolase reactions in the pentosephosphate pathway. The mass distribution of metabolites is very sensitive towards intracellular flux patterns and can be measured with high accuracy by routine mass spectrometry methods. Copyright 1999 John Wiley & Sons, Inc.     

A high standard metabolic rate constrains juvenile growth

The allocation of energy to various components of an individual's energy budget is often viewed as a competitive process. As such, a tradeoff may exist between production (growth) and maintenance metabolism. One view of a potential tradeoff, termed “the principle of allocation”, suggests that individuals with lower maintenance metabolic expenditures may have higher growth rates. To determine whether such a tradeoff exists, I analyzed the relationship between growth rate and maintenance metabolism of 225 juvenile snapping turtles housed in the laboratory. I measured growth from hatching to 6 months of age, and then measured oxygen consumption and calculated standard metabolic rate. Mean growth rate was 0.19 g d⁻ and mean standard metabolic rate (SMR) was 1.41 kJ d⁻. Maintenance metabolism and growth were negatively correlated after both were adjusted for body mass. The results support the “principle of allocation” theory: individuals with higher standard metabolic rates tended to have low growth rates.     

Age at first reproduction and growth rate are independent of basal metabolic rate in mammals

This study tested an emergent prediction from the Metabolic Theory of Ecology (MTE) that the age at first reproduction (α) of a mammal is proportional to the inverse of its mass-corrected basal metabolic rate: The hypothesis was tested with multiple regression models of conventional species data and phylogenetically independent contrasts of 121 mammal species. Since age at first reproduction is directly influenced by an individual’s growth rate, the hypothesis that growth rate is proportional to BMR was also tested. Although the overall multiple regression model was significant, age at first reproduction was not partially correlated with either body mass, growth rate or BMR. Similarly, growth rate was not correlated with BMR. Thus at least for mammals in general, there is no evidence to support the fundamental premise of the MTE that individual metabolism governs the rate at which energy is converted to growth and reproduction at the species level. The exponents of the BMR allometry calculated using phylogenetic generalized least squares regression models were significantly lower than the three-quarter value predicted by the MTE. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Development,growth and metabolic rate of Hermetia illucens larvae

The larvae of Hermetia illucens are known to successfully bio‐convert a vast range of organic substrates into high protein and fat biomass, but little is known about the larval instars. During this research, larval head capsules and biomass growth were measured daily and the specific metabolic rate of larger instars were considered. The head capsule measurements revealed that H. illucens pass through 6 actively feeding larval stadia before entering the last nonfeeding but migrating 7th stadium. Larval growth follows a sigmoid curve with slowly accelerating growth in the earlier stadia and decelerating growth in the latest stadia. In contrast, development was fast until reaching stadium 6 and then slowed down. Accordingly, the specific metabolic rate was high in instars 3, 4 and 5 and reduced in instars 6 and 7.     

Polyploidy in Xenopus lowers metabolic rate by decreasing total cell surface area

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Estimation of metabolic flux from dominant rate constants in vivo: application to brain and heart

In an earlier paper (Cohen and Bergman, Am. J. Physiol. 268 (1995) E397), we explored the relationship between the exponents in the exponential curve fit to isotopic enrichment versus time and the fractional turnover rate of the largest metabolic pool in the pathway. Here we present the analysis on a more rigorous footing and apply it to questions of cerebral and cardiac metabolism. Our emphasis in this paper is to describe and justify mathematically an approach for analysis of metabolic dynamics, not with the intention of replacing the use of numerical software for estimation of flux rates but for giving the scientist the opportunity to examine the system in an approximate manner, and thereby to check not only that the results of the numerical solution are the correct solutions to the equations but also that the equations portray the correct simplification of the metabolic pathway.We introduce the "dominant rate constant" as a tool for deriving algebraic formulas relating rates of metabolic flux, sizes of metabolic pools, and the dynamics of isotopic enrichment. Illustrations of such algebraic formulas are provided for the rates of the citric acid cycle (CAC), glycolysis and glutamine synthesis in brain, as well as the rate of the CAC in heart. In addition, we prove that formulas for estimation of rates of glycolysis and of the CAC depend critically on the fractional turnover rates of lactate and glutamate, respectively. The justification for analysis of simulated data is that we are studying the effects of simplifications of metabolic models on the accuracy of estimation of metabolic pathways. Our use of the dominant rate constant is an analytical convenience that allows us to assess proposed simplifications of metabolic pathways.     

Stoichiometric model and metabolic flux analysis for Leptospirillum ferrooxidans

A metabolic model for Leptospirillum ferrooxidans was developed based on the genomic information of an analogous iron oxidizing bacteria and on the pathways of ferrous iron oxidation, nitrogen and CO₂ assimilation based on experimental evidence for L. ferrooxidans found in the literature. From this metabolic reconstruction, a stoichiometric model was built, which includes 86 reactions describing the main catabolic and anabolic aspects of its metabolism. The model obtained has 2 degrees of freedom, so two external fluxes were estimated to achieve a determined and observable system. By using the external oxygen consumption rate and the generation flux biomass as input data, a metabolic flux map with a distribution of internal fluxes was obtained. The results obtained were verified with experimental data from the literature, achieving a very good prediction of the metabolic behavior of this bacterium at steady state. Biotechnol. Bioeng. 2010;107:696–706. © 2010 Wiley Periodicals, Inc.     

Understanding flux in plant metabolic networks

The revolutionary growth in our ability to identify the 'parts list' of cellular infrastructure in plants in detail, and to alter it with precision, challenges us to develop methods to quantify how these parts function. For components of metabolism, this means mapping fluxes at the level of metabolic networks. Advances in experimental, analytical and software tools for metabolic flux analysis now allow maps of the fluxes through central metabolism to be obtained from the results of stable-isotope-labeling experiments. Such maps have led to notable successes in understanding and engineering metabolic function in microorganisms. Recent studies in plants are giving insight into particular fluxes, such as those of the pentose phosphate pathway, and into general phenomena, such as substrate- or futile-cycles and compartmentation. The importance of experimental design and statistical analysis have been illustrated, and analyses of fluxes in heterotrophic plant tissues have been carried out recently.     

Identification of optimal measurement sets for complete flux elucidation in metabolic flux analysis experiments

Metabolic flux analysis (MFA) methods use external flux and isotopic measurements to quantify the magnitude of metabolic flows in metabolic networks. A key question in this analysis is choosing a set of measurements that is capable of yielding a unique flux distribution (identifiability). In this article, we introduce an optimization-based framework that uses incidence structure analysis to determine the smallest (or most cost-effective) set of measurements leading to complete flux elucidation. This approach relies on an integer linear programming formulation OptMeas that allows for the measurement of external fluxes and the complete (or partial) enumeration of the isotope forms of metabolites without requiring any of these to be chosen in advance. We subsequently query and refine the measurement sets suggested by OptMeas for identifiability and optimality. OptMeas is first tested on small to medium-size demonstration examples. It is subsequently applied to a large-scale E. coli isotopomer mapping model with more than 17,000 isotopomers. A number of additional measurements are identified leading to maximum flux elucidation in an amorphadiene producing E. coli strain.     

293SF metabolic flux analysis during cell growth and infection with an adenoviral vector

Metabolic flux quantification of cell culture is becoming a crucial means to improve cell growth as well as protein and vector productions. The technique allows rapid determination of cell culture status, thus providing a tool for further feeding improvements. Herein, we report on key results of a metabolic investigation using 293 cells adapted to suspension and serum-free medium (293SF) during growth and infection with an adenoviral vector encoding the green fluorescence protein (GFP). The model developed contains 35 fluxes, which include the main fluxes of glycolysis, glutaminolysis, and amino acids pathways. It requires specific consumption and production rate measurements of amino acids, glucose, lactate, NH(3), and O(2), as well as DNA and total proteins biosynthesis rate measurements. Also, it was found that extracellular protein concentration measurement is important for flux calculation accuracy. With this model, we are able to describe the 293SF cell metabolism, grown under different culture conditions in a 3-L controlled bioreactor for batch and fed-batch with low glucose. The metabolism is also investigated during infection under two different feeding strategies: a fed-batch starting at the end of the growth phase and extending during infection without medium change and a fed-batch after infection following medium renewal. Differences in metabolism are observed between growth and infection, as well as between the different feeding strategies, thus providing a better understanding of the general metabolism.     

Isoenzyme expression changes in response to high temperature determine the metabolic regulation of increased glycolytic flux in yeast

Qualitative phenotypic changes are the integrated result of quantitative changes at multiple regulatory levels. To explain the temperature-induced increase of glycolytic flux in fermenting cultures of Saccharomyces cerevisiae, we quantified the contributions of changes in activity at many regulatory levels. We previously showed that a similar temperature increase in glucose-limited cultivations lead to a qualitative change from respiratory to fermentative metabolism, and this change was mainly regulated at the metabolic level. In contrast, in fermenting cells, a combination of different modes of regulation was observed. Regulation by changes in expression and the effect of temperature on enzyme activities contributed much to the increase in flux. Mass spectrometric quantification of glycolytic enzymes revealed that increased enzyme activity did not correlate with increased protein abundance, suggesting a large contribution of post-translational regulation to activity. Interestingly, the differences in the direct effect of temperature on enzyme kinetics can be explained by changes in the expression of the isoenzymes. Therefore, both the interaction of enzyme with its metabolic environment and the temperature dependence of activity are in turn regulated at the hierarchical level.     

A possibilistic framework for constraint-based metabolic flux analysis

Background  

Constraint-based models allow the calculation of the metabolic flux states that can be exhibited by cells, standing out as a powerful analytical tool, but they do not determine which of these are likely to be existing under given circumstances. Typical methods to perform these predictions are (a) flux balance analysis, which is based on the assumption that cell behaviour is optimal, and (b) metabolic flux analysis, which combines the model with experimental measurements.