Revealing metabolic mechanisms of interaction in the anaerobic digestion microbiome by flux balance analysis

Anaerobic digestion is a key biological process for renewable energy, yet the mechanistic knowledge on its hidden microbial dynamics is still limited. The present work charted the interaction network in the anaerobic digestion microbiome via the full characterization of pairwise interactions and the associated metabolite exchanges. To this goal, a novel collection of 836 genome-scale metabolic models was built to represent the functional capabilities of bacteria and archaea species derived from genome-centric metagenomics. Dominant microbes were shown to prefer mutualistic, parasitic and commensalistic interactions over neutralism, amensalism and competition, and are more likely to behave as metabolite importers and profiteers of the coexistence. Additionally, external hydrogen injection positively influences microbiome dynamics by promoting commensalism over amensalism. Finally, exchanges of glucogenic amino acids were shown to overcome auxotrophies caused by an incomplete tricarboxylic acid cycle. Our novel strategy predicted the most favourable growth conditions for the microbes, overall suggesting strategies to increasing the biogas production efficiency. In principle, this approach could also be applied to microbial populations of biomedical importance, such as the gut microbiome, to allow a broad inspection of the microbial interplays.     

渗透压调控对裂殖壶菌发酵产DHA的影响

考察了不同渗透胁迫(0、10、20、30和40 g/L NaCl)对裂殖壶菌HX-308发酵产DHA及脂肪酸构成的影响。结果表明:20 g/L NaCl最有利于裂殖壶菌生长和DHA积累,生物量、总脂肪酸含量、DHA产量及DHA占生物量的比值分别为73 g/L、10.7 g/L、5.0 g/L和68 mg/g,并且DHA在总脂肪酸中所占百分比最高,为45.2%。此外,在低渗透压(10 g/L NaCl)条件下,添加40 mmol/L甘氨酸甜菜碱,DHA产量与未添加相比提高了28.21%;在高渗透压(40 g/L NaCl)条件下添加40 mmol/L海藻糖,DHA产量提高了46.84%;表明添加适量的外源相容性溶质能有效地促进裂殖壶菌积累DHA。     

Comparison and analysis of objective functions in flux balance analysis

Flux balance analysis (FBA) is currently one of the most important and used techniques for estimation of metabolic reaction rates (fluxes). This mathematical approach utilizes an optimization criterion in order to select a distribution of fluxes from the feasible space delimited by the metabolic reactions and some restrictions imposed over them, assuming that cellular metabolism is in steady state. Therefore, the obtained flux distribution depends on the specific objective function used. Multiple studies have been aimed to compare distinct objective functions at given conditions, in order to determine which of those functions produces values of fluxes closer to real data when used as objective in the FBA; in other words, what is the best objective function for modeling cell metabolism at a determined environmental condition. However, these comparative studies have been designed in very dissimilar ways, and in general, several factors that can change the ideal objective function in a cellular condition have not been adequately considered. Additionally, most of them have used only one dataset for representing one condition of cell growth, and different measuring techniques have been used. For these reasons, a rigorous study on the effect of factors such as the quantity of used data, the number and type of fluxes utilized as input data, and the selected classification of growth conditions, are required in order to obtain useful conclusions for these comparative studies, allowing limiting clearly the application range on any of those results. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:985–991, 2014     

Quantifying the propagation of parametric uncertainty on flux balance analysis

Flux balance analysis (FBA) and associated techniques operating on stoichiometric genome-scale metabolic models play a central role in quantifying metabolic flows and constraining feasible phenotypes. At the heart of these methods lie two important assumptions: (i) the biomass precursors and energy requirements neither change in response to growth conditions nor environmental/genetic perturbations, and (ii) metabolite production and consumption rates are equal at all times (i.e., steady-state). Despite the stringency of these two assumptions, FBA has been shown to be surprisingly robust at predicting cellular phenotypes. In this paper, we formally assess the impact of these two assumptions on FBA results by quantifying how uncertainty in biomass reaction coefficients, and departures from steady-state due to temporal fluctuations could propagate to FBA results. In the first case, conditional sampling of parameter space is required to re-weigh the biomass reaction so as the molecular weight remains equal to 1 g mmol⁻¹, and in the second case, metabolite (and elemental) pool conservation must be imposed under temporally varying conditions. Results confirm the importance of enforcing the aforementioned constraints and explain the robustness of FBA biomass yield predictions.     

Metabolic flux analysis for succinic acid production by recombinant Escherichia coli with amplified malic enzyme activity

A pfl ldhA double mutant Escherichia coli strain NZN111 was used to produce succinic acid by overexpressing the E. coli malic enzyme. Escherichia coli strain NZN111 harboring pTrcML produced 6 and 8 g/L of succinic acid from 20 g/L of glucose in flask culture at 37 degrees C and 30 degrees C, respectively. When NZN111(pTrcML) was cultured at 30 degrees C with intermittent glucose feeding the final succinic acid concentration obtained was 9.5 g/L and the ratio of succinic acid to acetic acid was 13:1. This system could not be analyzed by conventional metabolic flux analysis techniques, since some pyruvate and succinic acid were accumulated intracellularly. Therefore, a new flux analysis method was proposed by introducing intracellular pyruvate and succinic acid pools. By this new method the concentrations of intracellular metabolites were successfully predicted and the differences between the measured and calculated reaction rates could be considerably reduced.     

Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis

Flux balance analysis (FBA) has been widely used in calculating steady‐state flux distributions that provide important information for metabolic engineering. Several thermodynamics‐based methods, for example, quantitative assignment of reaction directionality and energy balance analysis have been developed to improve the prediction accuracy of FBA. However, these methods can only generate a thermodynamically feasible range, rather than the most thermodynamically favorable solution. We therefore developed a novel optimization method termed as thermodynamic optimum searching (TOS) to calculate the thermodynamically optimal solution, based on the second law of thermodynamics, the minimum magnitude of the Gibbs free energy change and the maximum entropy production principle (MEPP). Then, TOS was applied to five physiological conditions of Escherichia coli to evaluate its effectiveness. The resulting prediction accuracy was found significantly improved (10.7–48.5%) by comparing with the ¹³C‐fluxome data, indicating that TOS can be considered an advanced calculation and prediction tool in metabolic engineering. Biotechnol. Bioeng. 2013; 110: 914–923. © 2012 Wiley Periodicals, Inc.     

小球藻联产油脂和虾青素的基元模式分析

构建了包含虾青素合成途径的小球藻代谢网络模型,集成文献报道同位素标定的小球藻代谢通量数据,估算了胞内代谢通量分布。在正常和缺氮培养条件下,虾青素的代谢通量分别为0.38和0.35。计算得到基元模式共640条,通过最大熵原理算法求取了正常培养和缺氮培养条件下的基元模式概率。存在4条关键基元模式,在2种培养条件下,其基元模式概率之和分别为60.95%和77.53%。虾青素的最大理论合成产率为11.27%,但是这4条关键基元模式并不包括虾青素的合成反应。     

Enhancement of docosahexaenoic acid production by Schizochytrium sp. using a two-stage oxygen supply control strategy based on oxygen transfer coefficient

Aims: To improve the yield and productivity of docosahexaenoic acid (DHA) by Schizochytrium sp. in terms of the analysis of microbial physiology. Methods and Results: A two‐stage oxygen supply control strategy, aimed at achieving high concentration and high productivity of DHA, was proposed. At the first 40 h, K_La was controlled at 150·1 h^?1 to obtain high μ for cell growth, subsequently K_La was controlled at 88·5 h^?1 to maintain high q_p for high DHA accumulation. Finally, the maximum lipid, DHA content and DHA productivity reached 46·6, 17·7 g l^?1 and 111 mg l^?1 h^?1, which were 43·83%, 63·88% and 32·14% over the best results controlled by constant K_La. Conclusions: This paper described a two‐stage oxygen supply control strategy based on the kinetic analysis for efficient DHA fermentation by Schizochytrium sp. Significance and Impact of the study: This study showed the advantage of two‐stage control strategy in terms of microbial physiology. As K_La is a scaling‐up parameter, the idea developed in this paper could be scaled‐up to industrial process and applied to other industrial biotechnological processes to achieve both high product concentration and high productivity.     

Flux balance analysis of CHO cells before and after a metabolic switch from lactate production to consumption

Mammalian cell cultures typically exhibit an energy inefficient phenotype characterized by the consumption of large quantities of glucose and the concomitant production of large quantities of lactate. Under certain conditions, mammalian cells can switch to a more energy efficient state during which lactate is consumed. Using a metabolic model derived from a mouse genome scale model we performed flux balance analysis of Chinese hamster ovary cells before and after a metabolic switch from lactate production (in the presence of glucose) to lactate consumption (after glucose depletion). Despite a residual degree of freedom after accounting for measurements, the calculated flux ranges and associated errors were narrow enough to enable investigation of metabolic changes across the metabolic switch. Surprisingly, the fluxes through the lower part of the TCA cycle from oxoglutarate to malate were very similar (around 60 µmol/gDW/h) for both phases. A detailed analysis of the energy metabolism showed that cells consuming lactate have an energy efficiency (total ATP produced per total C‐mol substrate consumed) six times greater than lactate producing cells. Biotechnol. Bioeng. 2013; 110: 660–666. © 2012 Wiley Periodicals, Inc.     

基于Methylovorus sp.J1-1基因组尺度代谢网络优化吡咯喹啉醌合成

通过构建Methylovorus sp.J1-1基因组尺度代谢网络模型(genome scale of metabolic network model,GSMM),发掘能够提升吡咯喹啉醌(pyrroloquinoline quinone,PQQ)产量的发酵策略和相关靶基因.基于其注释的基因组和生化信息,构建J1-1的G...     

Fundamental Escherichia coli biochemical pathways for biomass and energy production: creation of overall flux states

We have previously shown that the metabolism for most efficient cell growth can be realized by a combination of two types of elementary modes. One mode produces biomass while the second mode generates only energy. The identity of the four most efficient biomass and energy pathway pairs changes, depending on the degree of oxygen limitation. The identification of such pathway pairs for different growth conditions offers a pathway-based explanation of maintenance energy generation. For a given growth rate, experimental aerobic glucose consumption rates can be used to estimate the contribution of each pathway type to the overall metabolic flux pattern. All metabolic fluxes are then completely determined by the stoichiometries of involved pathways defining all nutrient consumption and metabolite secretion rates. We present here equations that permit computation of network fluxes on the basis of unique pathways for the case of optimal, glucose-limited Escherichia coli growth under varying levels of oxygen stress. Predicted glucose and oxygen uptake rates and some metabolite secretion rates are in remarkable agreement with experimental observations supporting the validity of the presented approach. The entire most efficient, steady-state, metabolic rate structure is explicitly defined by the developed equations without need for additional computer simulations. The approach should be generally useful for analyzing and interpreting genomic data by predicting concise, pathway-based metabolic rate structures.     

Flux balance analysis in the production of clavulanic acid by Streptomyces clavuligerus

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. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1226–1236, 2015     

A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions

Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade‐off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper‐osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper‐osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance.     

Metabolic flux analysis of lactic acid fermentation: effects of pH and lactate ion concentration

A detailed metabolic flux analysis for lactic acid production by Streptococcus lactis has been carried out. A metabolic reaction set was constructed for the metabolism of S. lactis. Fluxes through these reactions were estimated by using accumulation rates of biomass, product and consumption rates of the substrate, which were obtained through experiments. The changes in the flux movement are shown for different pHs and initial lactate concentrations of the medium. The analysis indicated that pH only affected the uptake rates of lactose, whereas lactate ion concentration influenced the movement of flux through the network.     

Segregated flux balance analysis constrained by population structure/function data: The case of PHA production by mixed microbial cultures

In this study we developed a segregated flux balance analysis (FBA) method to calculate metabolic flux distributions of the individual populations present in a mixed microbial culture (MMC). Population specific flux data constraints were derived from the raw data typically obtained by the fluorescence in situ hybridization (FISH) and microautoradiography (MAR)‐FISH techniques. This method was applied to study the metabolic heterogeneity of a MMC that produces polyhydroxyalkanoates (PHA) from fermented sugar cane molasses. Three populations were identified by FISH, namely Paracoccus sp., Thauera sp., and Azoarcus sp. The segregated FBA method predicts a flux distribution for each of the identified populations. The method is shown to predict with high accuracy the average PHA storage flux and the respective monomeric composition for 16 independent experiments. Moreover, flux predictions by segregated FBA were slightly better than those obtained by nonsegregated FBA, and also highly concordant with metabolic flux analysis (MFA) estimated fluxes. The segregated FBA method can be of high value to assess metabolic heterogeneity in MMC systems and to derive more efficient eco‐engineering strategies. For the case of PHA‐producing MMC considered in this work, it becomes apparent that the PHA average monomeric composition might be controlled not only by the volatile fatty acids (VFA) feeding profile but also by the population composition present in the MMC. Biotechnol. Bioeng. 2013; 110: 2267–2276. © 2013 Wiley Periodicals, Inc.