Stoichiometric model and flux balance analysis for a mixed culture of Leptospirillum ferriphilum and Ferroplasma acidiphilum

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. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 31:307–315, 2015     

A stoichiometric model of Acidithiobacillus ferrooxidans ATCC 23270 for metabolic flux analysis

A stoichiometric model of Acidithiobacillus ferrooxidans based on the sequenced genome from strain ATCC 23270 is derived and parameterized using genome/pathway databases. The model describes the main aspects of catabolism and anabolism. By the construction and utilization of the mathematical determination of the network, metabolic flux analysis is performed for such a bacterium for the first time and results are successfully verified by comparison to literature values. This first metabolic model of A. ferrooxidans is able to simulate the main aspects of metabolism and will be useful for further investigation and improvement of bioleaching procedures. Biotechnol. Bioeng. 2009;102: 1448–1459. © 2008 Wiley Periodicals, Inc.     

The effect of CO2 availability on the growth, iron oxidation and CO2-fixation rates of pure cultures of Leptospirillum ferriphilum and Acidithiobacillus ferrooxidans

Understanding how bioleaching systems respond to the availability of CO(2) is essential to developing operating conditions that select for optimum microbial performance. Therefore, the effect of inlet gas and associated dissolved CO(2) concentration on the growth, iron oxidation and CO(2) -fixation rates of pure cultures of Acidithiobacillus ferrooxidans and Leptospirillum ferriphilum was investigated in a batch stirred tank system. The minimum inlet CO(2) concentrations required to promote the growth of At. ferrooxidans and L. ferriphilum were 25 and 70 ppm, respectively, and corresponded to dissolved CO(2) concentrations of 0.71 and 1.57 μM (at 30°C and 37°C, respectively). An actively growing culture of L. ferriphilum was able to maintain growth at inlet CO(2) concentrations less than 30 ppm (0.31-0.45 μM in solution). The highest total new cell production and maximum specific growth rates from the stationary phase inocula were observed with CO(2) inlet concentrations less than that of air. In contrast, the amount of CO(2) fixed per new cell produced increased with increasing inlet CO(2) concentrations above 100 ppm. Where inlet gas CO(2) concentrations were increased above that of air the additional CO(2) was consumed by the organisms but did not lead to increased cell production or significantly increase performance in terms of iron oxidation. It is proposed that At. ferrooxidans has two CO(2) uptake mechanisms, a high affinity system operating at low available CO(2) concentrations, which is subject to substrate inhibition and a low affinity system operating at higher available CO(2) concentrations. L. ferriphilum has a single uptake system characterised by a moderate CO(2) affinity. At. ferrooxidans performed better than L. ferriphilum at lower CO(2) availabilities, and was less affected by CO(2) starvation. Finally, the results demonstrate the limitations of using CO(2) uptake or ferrous iron oxidation data as indirect measures of cell growth and performance across varying physiological conditions.     

Characterization of Ferroplasma acidiphilum growing in pure and mixed culture with Leptospirillum ferriphilum

Biomining is defined as biotechnology for metal recovery from minerals, and is promoted by the concerted effort of a consortium of acidophile prokaryotes, comprised of members of the Bacteria and Archaea domains. Ferroplasma acidiphilum and Leptospirillum ferriphilum are the dominant species in extremely acid environments and have great use in bioleaching applications; however, the role of each species in this consortia is still a subject of research. The hypothesis of this work is that F. acidiphilum uses the organic matter secreted by L. ferriphilum for growth, maintaining low levels of organic compounds in the culture medium, preventing their toxic effects on L. ferriphilum. To test this hypothesis, a characterization of Ferroplasma acidiphilum strain BRL‐115 was made with the objective of determining its optimal growth conditions. Subsequently, under the optimal conditions, L. ferriphilum and F. acidiphilum were tested growing in each other's supernatant, in order to define if there was exchange of metabolites between the species. With these results, a mixed culture in batch cyclic operation was performed to obtain main specific growth rates, which were used to evaluate a mixed metabolic model previously developed by our group. It was observed that F. acidiphilum, strain BRL‐115 is a chemomixotrophic organism, and its growth is maximized with yeast extract at a concentration of 0.04% wt/vol. From the experiments of L. ferriphilum growing on F. acidiphilum supernatant and vice versa, it was observed that in both cases cell growth is favorably affected by the presence of the filtered medium of the other microorganism, proving a synergistic interaction between these species. Specific growth rates were obtained in cyclic batch operation of the mixed culture and were used as input data for a Flux Balance Analysis of the mixed metabolic model, obtaining a reasonable behavior of the metabolic fluxes and the system as a whole, therefore consolidating the model previously developed. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1390–1396, 2016     

代谢流量比率分析及其在代谢工程中的应用

细胞内代谢反应流量在系统理解细胞代谢特性和指导代谢工程改造等方面都起着重要的作用。由于代谢流量难以直接测量得到,在很多情况下通过跟踪稳定同位素在代谢网络中的转移并进行相应的模型计算能有效地定量代谢流量。代谢流量比率分析法能够高度体现系统的生物化学真实性、辨别细胞代谢网络的拓扑结构,并且能够相对简单快速地定量反应速率等,因此受到代谢工程研究者越来越多的重视。以下着重介绍并讨论了利用代谢物同位体分布信息分析关键代谢节点合成途径的流量比率、基于流量比率的代谢流量解析、以及应用于代谢工程等的相关原理、实验测量、数据分析、使用条件等,以期充分发挥代谢流量比率分析法的优势,并将其拓展推广至更多细胞体系的代谢特性阐明和代谢工程改造中去。     

Mass flux balance-based model and metabolic pathway engineering analysis for serine alkaline protease synthesis by Bacillus licheniformis

A mass flux balance-based stoichiometric model of Bacillus licheniformis for the serine alkaline protease (SAP) fermentation process has been established. The model considers 147 reaction fluxes, and there are 105 metabolites that are assumed to be in pseudo-steady state. Metabolic flux distributions were obtained from the solution of the model based on the minimum SAP accumulation rate assumption in B. licheniformis in combination with the off-line extracellular analyses of the metabolites that were the sole carbon source citrate, dry cell, organic acids, amino acids, and SAP; variations in the intracellular fluxes were demonstrated for the three periods of the batch bioprocess. The flux distribution maps showed that the cells completed the TCA cycle and utilized the gluconeogenesis pathway, pentose phosphate pathway, and anaplerotic reactions throughout the fermentation; however, the glycolysis pathway was inactive in all the periods of the fermentation. The flux values toward SAP increased throughout the bioprocess and slightly decreased in the last period; however, SAP selectivity values were almost the same in Periods II and III and higher than Period I. The diversions in the pathways and certain metabolic reactions depending on the bioprocess periods are also presented and the results indicated that the intracellular amino acid fluxes played an important role in the SAP fermentation process.     

Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria

Metabolite balancing has turned out to be a powerful computational tool in metabolic engineering. However, the linear equation systems occurring in this analysis are often underdetermined. If it is difficult or impossible to find the missing constraints, it is nevertheless feasible in some cases to determine the values of a subset of the unknown rates. Here, a procedure for finding out which reaction rates can be uniquely calculated in underdetermined metabolic networks and computing these rates is given. The method is based on the null space to the stoichiometry matrix corresponding to the reactions with unknown rates. It is shown that this method is considerably easier to handle than an algorithm given previously (Van der Heijden et al., 1994a). Furthermore, a useful elementary representation of the null space is presented which is closely related with the elementary flux modes. This unique representation is central to a more general approach to observability/calculability analysis. In particular, it allows one to find, in an easy way, those sets of measurable rates that enable a calculation of a certain unknown rate. Besides, rates which are never calculable by metabolite balancing may be easily detected by this method. The applicability of these methods is illustrated by a model of the central metabolism in purple nonsulfur bacteria. The photoheterotrophic growth of these representatives of anoxygenic photosynthetic bacteria is stoichiometrically analyzed. Interesting metabolic constraints caused by the necessary balancing of NADPH can be detected in a highly underdetermined system. This is, to our knowledge, the first application of stoichiometric analysis to the metabolic network in this bacteria group using metabolite balancing techniques. A new software tool, the FluxAnalyzer, is introduced. It allows quantitative and structural analysis of metabolic networks in a graphical user interface.     

Selection of Leptospirillum ferrooxidans SRPCBL and development for enhanced ferric regeneration in stirred tank and airlift column reactor

Presence of Leptospirillum ferrooxidans plays significant role in ferric sulphate generation during bioleaching process. Thus, an attempt was made to select L. ferrooxidans from the polymetallic concentrate leachate and further developed it for enhanced ferric iron regeneration from the leachate in shake flask, stirred tank and column reactor. When ferric to ferrous iron ratio in the shake flask reached to 20:1, L. ferrooxidans out competed Acidithiobacillus ferrooxidans and accounted for more than 99% of the total population. The isolate was confirmed by 16S rRNA genes sequence analysis and named as L. ferrooxidans SRPCBL. When the culture was exposure to UV dose and the oxidation-reduction potential of the inoculation medium was adjusted to 40 0mV by ferrous:ferric iron ratio, the IOR reached to as high as 1.2 g/L/h in shake flask, even with initial ferrous iron concentration of 200 g/L. The chalcopyrite concentrate leachate containing 12.8, 15.7, and 42.0 g/L ferrous iron, ferric iron and copper, respectively was studied for ferric iron regeneration with the developed polymetallic resistant L. ferrooxidans SRPCBL in stirred tank and a developed biofilm airlift column, the highest IOR achieved were 2.20 g/L/h and 3.1 g/L/h, respectively, with ferrous oxidation efficiency of 98%. The ferric regeneration ability of the developed isolate from the leachate proves useful for a two-stage metal extraction process.     

Interpretation of metabolic flux maps by limitation potentials and constrained limitation sensitivities

Two new concepts, "Limitation Potential" and "Constraint Limitation Sensitivity" are introduced that use definitions derived from metabolic flux analysis (MFA) and metabolic network analysis (MNA). They are applied to interpret a measured flux distribution in the context of all possible flux distributions and thus combine MFA with MNA. The proposed measures are used to quantify and compare the influence of intracellular fluxes on the production yield. The methods are purely based on the stoichiometry of the network and constraints that are given from irreversible fluxes. In contrast to metabolic control analysis (MCA), within this approach no information about the kinetic mechanisms are needed. A limitation potential (LP) is defined as the reduction of the reachable (theoretical) maximum by a measured flux. Measured fluxes that strongly narrow the reachable maximum are assumed to be limiting as the network has no ability to counterbalance the restriction due to the observed flux. In a second step, the sensitivity of the reduced maximum is regarded. This measure provides information about the necessitated changes to reach higher yields. The methods are applied to interpret the capabilities of a network based on measured fluxes for a L-phenylalanine producer. The strain was examined by a series of experiments and three flux maps of the production phase are analyzed. It can be shown that the reachable yield is drastically reduced by the measured efflux into the TCA cycle, while the oxidative pentose-phosphate pathway only plays a secondary role on the reachable maximum.     

13C代谢流量分析发展30年

13C代谢流量分析(13C metabolic flux analysis,13C-MFA),是通过标记实验分析蛋白氨基酸或胞内代谢物同位素标记异构体的分布情况,从而准确定量胞内反应速率.该技术在系统理解细胞代谢特性、指导代谢工程改造和揭示病理生理学等方面起着重要作用,引起研究者的广泛重视.文中重点综述了代谢流分析30...     

A dynamic metabolic flux balance based model of fed‐batch fermentation of bordetella pertussis

A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed‐batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by‐products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 520–531, 2013     

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.     

代谢网络定量分析研究进展

综述了代谢工程中代谢控制分析、代谢通量分析、生化系统理论、途径分析、控制论模型等定量分析方法的基本理论,以实例说明了这些方法的应用,并对代谢分析方法的发展进行了展望。     

Metabolic flux model for an anchorage-dependent MDCK cell line: characteristic growth phases and minimum substrate consumption flux distribution

Up to now cell-culture based vaccine production processes only reach low productivities. The reasons are: (i) slow cell growth and (ii) low cell concentrations. To address these shortcomings, a quantitative analysis of the process conditions, especially the cell growth and the metabolic capabilities of the host cell line is required. For this purpose a MDCK cell based influenza vaccine production process was investigated. With a segregated growth model four distinct cell growth phases are distinguished in the batch process. In the first phase the cells attach to the surface of the microcarriers and show low metabolic activity. The second phase is characterized by exponential cell growth. In the third phase, preceded by a change in oxygen consumption, contact inhibition leads to a decrease in cell growth. Finally, the last phase before infection shows no further increase in cell numbers. To gain insight into the metabolic activity during these phases, a detailed metabolic model of MDCK cell was developed based on genome information and experimental analysis. The MDCK model was also used to calculate a theoretical flux distribution representing an optimized cell that only consumes a minimum of carbon sources. Comparing this minimum substrate consumption flux distribution to the fluxes estimated from experiments unveiled high overflow metabolism under the applied process conditions.     

Metabolic flux analysis with a comprehensive isotopomer model in Bacillus subtilis

Fluxes in central carbon metabolism of a genetically engineered, riboflavin-producing Bacillus subtilis strain were investigated in glucose-limited chemostat cultures at low (0.11 h(-1)) and high (0.44 h(-1)) dilution rates. Using a mixture of 10% [U-(13)C] and 90% glucose labeled at natural abundance, (13)C-labeling experiments were carried out to provide additional information for metabolic flux balancing. The resulting labeling pattern in the proteinogenic amino acids were analyzed by two-dimensional [(13)C, (1)H] nuclear magnetic resonance (NMR) spectroscopy. To account rigorously for all available data from these experiments, we developed a comprehensive isotopomer model of B. subtilis central metabolism. Using this model, intracellular carbon net and exchange fluxes were estimated on the basis of validated physiological data and biomass composition in combination with 2D NMR data from 45 individual carbon atom spectra in the amino acids. Glucose catabolism proceeded primarily via glycolysis but pentose phosphate pathway fluxes increased with increasing growth rate. Moreover, significant back fluxes from the TCA cycle to the lower part of glycolysis via the gluconeogenic PEP carboxykinase were detected. The malic enzyme reaction, in contrast, was found to be inactive. A thorough statistical analysis was performed to prove the reliability of the isotopomer balance model and the obtained results. Specifically, a chi(2) test was applied to validate the model and the chi-square criterion was used to explore the sensitivity of model predictions to the experimental data.     

Dynamic metabolic flux analysis (DMFA): a framework for determining fluxes at metabolic non-steady state

Metabolic flux analysis (MFA) is a key tool for measuring in vivo metabolic fluxes in systems at metabolic steady state. Here, we present a new method for dynamic metabolic flux analysis (DMFA) of systems that are not at metabolic steady state. The advantages of our DMFA method are: (1) time-series of metabolite concentration data can be applied directly for estimating dynamic fluxes, making data smoothing and estimation of average extracellular rates unnecessary; (2) flux estimation is achieved without integration of ODEs, or iterations; (3) characteristic metabolic phases in the fermentation data are identified automatically by the algorithm, rather than selected manually/arbitrarily. We demonstrate the application of the new DMFA framework in three example systems. First, we evaluated the performance of DMFA in a simple three-reaction model in terms of accuracy, precision and flux observability. Next, we analyzed a commercial glucose-limited fed-batch process for 1,3-propanediol production. The DMFA method accurately captured the dynamic behavior of the fed-batch fermentation and identified characteristic metabolic phases. Lastly, we demonstrate that DMFA can be used without any assumed metabolic network model for data reconciliation and detection of gross measurement errors using carbon and electron balances as constraints.