Equations and calculations of product yields and preferred pathways for butanediol and mixed-acid fermentations

Butyric acid: fermentation production using organic waste as low-cost feedstocks

Butyric acid is an important chemical which has many applications in the chemical, food, and pharmaceutical industries. Butyraldehyde, which is derived from propylene, is now converted into butyrate by petrochemical processes known as oxo synthesis. Because of its poor productivity and low butyrate concentration in the fermentation broth, biotechnological production of butyric acid is not economically viable. Typically, a sizable amount of the overall production expenses goes toward the cost of the fermentation substrate. If the fermentation process can use minimal biomass as the feedstock, a cost-competitive production of butyric acid from the fermentation technique would be generated with a strong market prospect. Organic wastes are recommended as a source of butyric acid fermentation feedstock because they are inexpensive, can be generated in huge numbers, and are biodegradable. With a focus on the low-cost feedstock, the many uses of butyric acid are discussed, with its present production status. As a result, this paper explores several butyric acid fermentation-related problems and offers ideas for potential solutions.

Addressing uncertainty in genome-scale metabolic model reconstruction and analysis

The reconstruction and analysis of genome-scale metabolic models constitutes a powerful systems biology approach, with applications ranging from basic understanding of genotype-phenotype mapping to solving biomedical and environmental problems. However, the biological insight obtained from these models is limited by multiple heterogeneous sources of uncertainty, which are often difficult to quantify. Here we review the major sources of uncertainty and survey existing approaches developed for representing and addressing them. A unified formal characterization of these uncertainties through probabilistic approaches and ensemble modeling will facilitate convergence towards consistent reconstruction pipelines, improved data integration algorithms, and more accurate assessment of predictive capacity.

Production of butanol from biomass: recent advances and future prospects

At present, diminishing oil resources and increasing environmental concerns have led to a shift toward the production of alternative biofuels. In the last few decades, butanol, as liquid biofuel, has received considerable research attention due to its advantages over ethanol. Several studies have focused on the production of butanol through the fermentation from raw renewable biomass, such as lignocellulosic materials. However, the low concentration and productivity of butanol production and the price of raw materials are limitations for butanol fermentation. Moreover, these limitations are the main causes of industrial decline in butanol production. This study reviews butanol fermentation, including the metabolism and characteristics of acetone-butanol-ethanol (ABE) producing clostridia. Furthermore, types of butanol production from biomass feedstock are detailed in this study. Specifically, this study introduces the recent progress on the efficient butanol production of "designed" and modified biomass. Additionally, the recent advances in the butanol fermentation process, such as multistage continuous fermentation, metabolic flow change of the electron carrier supplement, continuous fermentation with immobilization and recycling of cell, and the recent technical separation of the products from the fermentation broth, are described in this study.

Direct cell-to-cell exchange of matter in a synthetic Clostridium syntrophy enables CO2 fixation, superior metabolite yields, and an expanded metabolic space

In microbial fermentations at least 33% of the sugar-substrate carbon is lost as CO₂ during pyruvate decarboxylation to acetyl-CoA, with the corresponding electrons lost in the form of H₂. Previous attempts to reduce this carbon and electron loss focused on engineering of a single organism. In nature, most microorganisms live in complex communities where syntrophic interactions result in superior resource utilization. Here, we show that a synthetic syntrophy consisting of the solventogen Clostridium acetobutylicum, which converts simple and complex carbohydrates into a variety of chemicals, and the acetogen C. ljungdahlii which fixes CO₂, achieved carbon recoveries into C2-C4 alcohols almost to the limit of substrate-electron availability, with minimal H₂ and CO₂ release. The syntrophic co-culture produced robust metabolic outcomes over a broad range of starting population ratios of the two organisms. We show that direct cell-to-cell interactions and material exchange among the two microbes enabled unforeseen rearrangements in the metabolism of the individual species that resulted in the production of non-native metabolites, namely isopropanol and 2,3-butanediol. This was accomplished by pathway-specific alterations of gene expression brought about by one organism on the other, and vice versa. While some of these gene-expression alterations can be explained by the exchange of metabolites that induce specific gene expression patterns, others, as demonstrated by co-culture setup in a transwell system, cannot. The latter, for now, would be attributed to complex direct physical interactions among the two organisms, thus providing a glimpse of the potential microbial complexity of simple or multicomponent microbiomes. Such direct material-transfer phenomena have not been documented in the literature. Furthermore, our study shows that syntrophic cultures offer a flexible platform for metabolite production with superior carbon recovery that can also be applied to electron-enhanced fermentations enabling even higher carbon recoveries.

Recent trends in biobutanol production

Finite availability of conventional fossil carbonaceous fuels coupled with increasing pollution due to their overexploitation has necessitated the quest for renewable fuels. Consequently, biomass-derived fuels are gaining importance due to their economic viability and environment-friendly nature. Among various liquid biofuels, biobutanol is being considered as a suitable and sustainable alternative to gasoline. This paper reviews the present state of the preprocessing of the feedstock, biobutanol production through fermentation and separation processes. Low butanol yield and its toxicity are the major bottlenecks. The use of metabolic engineering and integrated fermentation and product recovery techniques has the potential to overcome these challenges. The application of different nanocatalysts to overcome the existing challenges in the biobutanol field is gaining much interest. For the sustainable production of biobutanol, algae, a third-generation feedstock has also been evaluated.

Biosynthesis of butyric acid by Clostridium tyrobutyricum

Butyric acid (C₃H₇COOH) is an important chemical that is widely used in foodstuffs along with in the chemical and pharmaceutical industries. The bioproduction of butyric acid through large-scale fermentation has the potential to be more economical and efficient than petrochemical synthesis. In this paper, the metabolic pathways involved in the production of butyric acid from Clostridium tyrobutyricum using hexose and pentose as substrates are investigated, and approaches to enhance butyric acid production through genetic modification are discussed. Finally, bioreactor modifications (including fibrous bed bioreactor, inner disk-shaped matrix bioreactor, fibrous matrix packed in porous levitated sphere carriers), low-cost feedstocks, and special treatments (including continuous fermentation with cell recycling, extractive fermentation with solvent, using different artificial electron carriers) intended to improve the feasibility of commercial butyric acid bioproduction are summarized.

Evidence of mixotrophic carbon-capture by n-butanol-producer Clostridium beijerinckii

Recent efforts to combat increasing greenhouse gas emissions include their capture into advanced biofuels, such as butanol. Traditionally, biobutanol research has been centered solely on its generation from sugars. Our results show partial re-assimilation of CO₂ and H₂ by n-butanol-producer C. beijerinckii. This was detected as synchronous CO₂/H₂ oscillations by direct (real-time) monitoring of their fermentation gasses. Additional functional analysis demonstrated increased total carbon recovery above heterotrophic values associated to mixotrophic assimilation of synthesis gas (H₂, CO₂ and CO). This was further confirmed using ¹³C-Tracer experiments feeding ¹³CO₂ and measuring the resulting labeled products. Genome- and transcriptome-wide analysis revealed transcription of key C-1 capture and additional energy conservation genes, including partial Wood-Ljungdahl and complete reversed pyruvate ferredoxin oxidoreductase / pyruvate-formate-lyase-dependent (rPFOR/Pfl) pathways. Therefore, this report provides direct genetic and physiological evidences of mixotrophic inorganic carbon-capture by C. beijerinckii.

Automated genome annotation and metabolic model reconstruction in the SEED and Model SEED

Over the past decade, genome-scale metabolic models have proven to be a crucial resource for predicting organism phenotypes from genotypes. These models provide a means of rapidly translating detailed knowledge of thousands of enzymatic processes into quantitative predictions of whole-cell behavior. Until recently, the pace of new metabolic model development was eclipsed by the pace at which new genomes were being sequenced. To address this problem, the RAST and the Model SEED framework were developed as a means of automatically producing annotations and draft genome-scale metabolic models. In this chapter, we describe the automated model reconstruction process in detail, starting from a new genome sequence and finishing on a functioning genome-scale metabolic model. We break down the model reconstruction process into eight steps: submitting a genome sequence to RAST, annotating the genome, curating the annotation, submitting the annotation to Model SEED, reconstructing the core model, generating the draft biomass reaction, auto-completing the model, and curating the model. Each of these eight steps is documented in detail.

Mathematical models of ABE fermentation: review and analysis

Among different liquid biofuels that have emerged in the recent past, biobutanol produced via fermentation processes is of special interest due to very similar properties to that of gasoline. For an effective design, scale-up, and optimization of the acetone-butanol-ethanol (ABE) fermentation process, it is necessary to have insight into the micro- and macro-mechanisms of the process. The mathematical models for ABE fermentation are efficient tools for this purpose, which have evolved from simple stoichiometric fermentation equations in the 1980s to the recent sophisticated and elaborate kinetic models based on metabolic pathways. In this article, we have reviewed the literature published in the area of mathematical modeling of the ABE fermentation. We have tried to present an analysis of these models in terms of their potency in describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results. In addition, we have also highlighted important facets of these models such as metabolic pathways, basic kinetics of different metabolites, biomass growth, inhibition modeling and other additional features such as cell retention and immobilized cultures. Our review also covers the mathematical modeling of the downstream processing of ABE fermentation, i.e. recovery and purification of solvents through flash distillation, liquid-liquid extraction, and pervaporation. We believe that this review will be a useful source of information and analysis on mathematical models for ABE fermentation for both the appropriate scientific and engineering communities.

Determination of the fluxes in the central metabolism of Corynebacterium glutamicum by nuclear magnetic resonance spectroscopy combined with metabolite balancing

To determine the in vivo fluxes of the central metabolism we have developed a comprehensive approach exclusively based on the fundamental enzyme reactions known to be present, the fate of the carbon atoms of individual reactions, and the metabolite balance of the culture. No information on the energy balance is required, nor information on enzyme activities, or the directionalities of reactions. Our approach combines the power of (1)H-detected (13)C nuclear magnetic resonance spectroscopy to follow individual carbons with the simplicity of establishing carbon balances of bacterial cultures. We grew a lysine-producing strain of Corynebacterium glutamicum to the metabolic and isotopic steady state with [1-(13)C]glucose and determined the fractional enrichments in 27 carbon atoms of 11 amino acids isolated from the cell. Since precursor metabolites of the central metabolism are incorporated in an exactly defined manner in the carbon skeleton of amino acids, the fractional enrichments in carbons of precursor metabolites (oxaloacetate, glyceraldehyde 3-phosphate, erythrose 4-phosphate, etc.) became directly accessible. A concise and generally applicable mathematical model was established using matrix calculus to express all metabolite mass and carbon labeling balances. An appropriate all-purpose software for the iterative solution of the equations is supplied. Applying this comprehensive methodology to C. glutamicum, all major fluxes within the central metabolism were determined. The result is that the flux through the pentose phosphate pathway is 66.4% (relative to the glucose input flux of 1.49 mmol/g dry weight h), that of entry into the tricarboxylic acid cycle 62.2%, and the contribution of the succinylase pathway of lysine synthesis 13.7%. Due to the large amount and high quality of measured data in vivo exchange reactions could also be quantitated with particularly high exchange rates within the pentose phosphate pathway for the ribose 5-phosphate transketolase reaction. Moreover, the total net flux of the anaplerotic reactions was quantitated as 38.0%. Most importantly, we found that in vivo one component within these anaplerotic reactions is a back flux from the carbon 4 units of the tricarboxylic acid cycle to the carbon 3 units of glycolysis of 30.6%. (c) 1996 John Wiley & Sons, Inc.

Energy metabolism and ATP balance in animal cell cultivation using a stoichiometrically based reaction network

A metabolic reaction network is developed for the estimation of the stoichiometric production of adenosine triphosphate (ATP) in animal cell culture. By using the material balance data from fed-batch and batch cultures of hybridoma cells, the stoichiometric ATP productions are determined with estimated effective P/O ratios of 2 for NADH and 1.2 for FADH(2). A significant percentage of the ATP requirement (16-41%) in hybridoma cells is generated directly from free energy release without the participation of oxygen. The oxidative phosphorylation of NADH accounts for about 60% of the total ATP production in the fed-batch cultures and about 47% in the batch culture. The oxidative phosphorylation of FADH(2) accounts for less then 20% of the total ATP production in all cases.A fractional model is devised to analyze the contribution of each nutrient to the ATP production. Results show that a majority of the ATP is produced from glucose metabolism (60-76%). Less than 30% of the ATP is derived from glutamine, and less than 11% is derived from other essential amino acids. The analysis also shows that the glycolytic pathway generates more ATP in the batch (41%) than in the fed-batch (<27%) cultures. The TCA cycle provides 51-68% of the total ATP production. The calculated stoichiometric oxygen consumption differs among the batch and fed-batch cultures, depending on the glucose concentration. This result suggests that the relationship between the oxygen uptake rate (OUR) and cell growth may change with the culture conditions. However, the calculated respiratory quotient (RQ) is relatively constant in all cases.A linear relationship is obtained between the specific ATP production rate and the specific cell growth rate. The maximum ATP yield and the maintenance ATP requirement are determined based on this linear relationship. The biosynthetic ATP demand estimated from the dry cell weight and cell composition is significantly lower than that calculated from the maximum ATP yield, indicating that the non-growth-associated ATP demand may contain other factors than what is considered in the estimation of the biosynthetic ATP demand.

Network approaches to the functional analysis of microbial proteins

Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes.

The single-domain globin of Vitreoscilla: augmentation of aerobic metabolism for biotechnological applications

Extensive studies have revealed that large-scale, high-cell density bioreactor cultivations have significant impact on metabolic networks of oxygen-requiring production organisms. Oxygen transfer problems associated with fluid dynamics and inefficient mixing efficiencies result in oxygen gradients, which lead to reduced performance of the bioprocess, decreased product yields, and increased production costs. These problems can be partially alleviated by improving bioreactor configuration and setting, but significant improvements have been achieved by metabolic engineering methods, especially by heterologously expressing Vitreoscilla hemoglobin (VHb). Vast numbers of studies have been accumulating during the past 20 years showing the applicability of VHb to improve growth and product yields in a variety of industrially significant prokaryotic and eukaryotic hosts. The global view on the metabolism of globin-expressing Escherichia coli cells depicts increased energy generation, higher oxygen uptake rates, and a decrease in fermentative by-product excretion. Transcriptome and metabolic flux analysis clearly demonstrate the multidimensional influence of heterologous VHb on the expression of stationary phase-specific genes and on the regulation of cellular metabolic networks. The exact biochemical mechanisms by which VHb is able to improve the oxygen-limited growth remain poorly understood. The suggested mechanisms propose either the delivery of oxygen to the respiratory chain or the detoxification of reactive nitrogen species for the protection of cytochrome activity. The expression of VHb in E. coli bioreactor cultures is likely to assist bacterial growth through providing an increase in available intracellular oxygen, although to fully understand the exact role of VHb in vivo, further analysis will be required.

Fermentation equations for propionic-acid bacteria and production of assorted oxychemicals from various sugars

Fermentation (stoichiometric) equations are derived for anaerobic fermentations of propionic-acid bacteria (of both the Propionibacterium and acrylate pathways) and for production of various oxychemicals (butanol, acetone, isopropanol, butanediol, butyrate, acetate, propionate, succinate, lactate, and acrylate) from pentoses, hexoses, and cellobiose. The derivations of the equations are based on the fermentation biochemistries of the various bacterial classes. The validity of the equations is tested using fermentation data from the literature. The equations are shown to be valuable, among other uses, for calculating maximal yields and selectivities of the various fermentation products, as "gateway sensors" for monitoring of the fermentations, and for calculating the extents of the various intracellular reactions of the fermentation biochemistry.

Current progress on butyric acid production by fermentation

Several issues of butyric acid production with bacteria through fermentation are presented in this review. The current progress including the utilization of butyric acid, the production strains, the metabolic pathway, and regulation are presented in the paper. Process operation modes such as batch, fed-batch, and continuous fermentation are being discussed. Genetic engineering technologies for microbial strain improvement are also being discussed and fermentation systems have been recommended.

iBsu1103: a new genome-scale metabolic model of Bacillus subtilis based on SEED annotations

BACKGROUND

Bacillus subtilis is an organism of interest because of its extensive industrial applications, its similarity to pathogenic organisms, and its role as the model organism for Gram-positive, sporulating bacteria. In this work, we introduce a new genome-scale metabolic model of B. subtilis 168 called iBsu1103. This new model is based on the annotated B. subtilis 168 genome generated by the SEED, one of the most up-to-date and accurate annotations of B. subtilis 168 available.

RESULTS

The iBsu1103 model includes 1,437 reactions associated with 1,103 genes, making it the most complete model of B. subtilis available. The model also includes Gibbs free energy change (DeltarG' degrees ) values for 1,403 (97%) of the model reactions estimated by using the group contribution method. These data were used with an improved reaction reversibility prediction method to identify 653 (45%) irreversible reactions in the model. The model was validated against an experimental dataset consisting of 1,500 distinct conditions and was optimized by using an improved model optimization method to increase model accuracy from 89.7% to 93.1%.

CONCLUSIONS

Basing the iBsu1103 model on the annotations generated by the SEED significantly improved the model completeness and accuracy compared with the most recent previously published model. The enhanced accuracy of the iBsu1103 model also demonstrates the efficacy of the improved reaction directionality prediction method in accurately identifying irreversible reactions in the B. subtilis metabolism. The proposed improved model optimization methodology was also demonstrated to be effective in minimally adjusting model content to improve model accuracy.

Reconstruction of biochemical networks in microorganisms

Systems analysis of metabolic and growth functions in microbial organisms is rapidly developing and maturing. Such studies are enabled by reconstruction, at the genomic scale, of the biochemical reaction networks that underlie cellular processes. The network reconstruction process is organism specific and is based on an annotated genome sequence, high-throughput network-wide data sets and bibliomic data on the detailed properties of individual network components. Here we describe the process that is currently used to achieve comprehensive network reconstructions and discuss how these reconstructions are curated and validated. This review should aid the growing number of researchers who are carrying out reconstructions for particular target organisms.

Genome-scale model for Clostridium acetobutylicum: Part II. Development of specific proton flux states and numerically determined sub-systems

A regulated genome-scale model for Clostridium acetobutylicum ATCC 824 was developed based on its metabolic network reconstruction. To aid model convergence and limit the number of flux-vector possible solutions (the size of the phenotypic solution space), modeling strategies were developed to impose a new type of constraint at the endo-exo-metabolome interface. This constraint is termed the specific proton flux state, and its use enabled accurate prediction of the extracellular medium pH during vegetative growth of batch cultures. The specific proton flux refers to the influx or efflux of free protons (per unit biomass) across the cell membrane. A specific proton flux state encompasses a defined range of specific proton fluxes and includes all metabolic flux distributions resulting in a specific proton flux within this range. Effective simulation of time-course batch fermentation required the use of independent flux balance solutions from an optimum set of specific proton flux states. Using a real-coded genetic algorithm to optimize temporal bounds of specific proton flux states, we show that six separate specific proton flux states are required to model vegetative-growth metabolism and accurately predict the extracellular medium pH. Further, we define the apparent proton flux stoichiometry per weak acids efflux and show that this value decreases from approximately 3.5 mol of protons secreted per mole of weak acids at the start of the culture to approximately 0 at the end of vegetative growth. Calculations revealed that when specific weak acids production is maximized in vegetative growth, the net proton exchange between the cell and environment occurs primarily through weak acids efflux (apparent proton flux stoichiometry is 1). However, proton efflux through cation channels during the early stages of acidogenesis was found to be significant. We have also developed the concept of numerically determined sub-systems of genome-scale metabolic networks here as a sub-network with a one-dimensional null space basis set. A numerically determined sub-system was constructed in the genome-scale metabolic network to study the flux magnitudes and directions of acetylornithine transaminase, alanine racemase, and D-alanine transaminase. These results were then used to establish additional constraints for the genome-scale model.

Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis

A genome-scale metabolic network reconstruction for Clostridium acetobutylicum (ATCC 824) was carried out using a new semi-automated reverse engineering algorithm. The network consists of 422 intracellular metabolites involved in 552 reactions and includes 80 membrane transport reactions. The metabolic network illustrates the reliance of clostridia on the urea cycle, intracellular L-glutamate solute pools, and the acetylornithine transaminase for amino acid biosynthesis from the 2-oxoglutarate precursor. The semi-automated reverse engineering algorithm identified discrepancies in reaction network databases that are major obstacles for fully automated network-building algorithms. The proposed semi-automated approach allowed for the conservation of unique clostridial metabolic pathways, such as an incomplete TCA cycle. A thermodynamic analysis was used to determine the physiological conditions under which proposed pathways (e.g., reverse partial TCA cycle and reverse arginine biosynthesis pathway) are feasible. The reconstructed metabolic network was used to create a genome-scale model that correctly characterized the butyrate kinase knock-out and the asolventogenic M5 pSOL1 megaplasmid degenerate strains. Systematic gene knock-out simulations were performed to identify a set of genes encoding clostridial enzymes essential for growth in silico.

Construction and characterization of ack deleted mutant of Clostridium tyrobutyricum for enhanced butyric acid and hydrogen production

Clostridium tyrobutyricum produces butyrate, acetate, H(2), and CO(2) as its main fermentation products from glucose and xylose. To improve butyric acid and hydrogen production, integrational mutagenesis was used to create a metabolically engineered mutant with inactivated ack gene, encoding acetate kinase (AK) associated with the acetate formation pathway. A non-replicative plasmid containing the acetate kinase gene (ack) fragment was constructed and introduced into C. tyrobutyricum by electroporation. Integration of the plasmid into the homologous region on the chromosome should inactivate the target ack gene and produce ack-deleted mutant, PAK-Em. Enzyme activity assays showed that the AK activity in PAK-Em decreased by approximately 50%; meanwhile, phosphotransacetylase (PTA) and hydrogenase activities each increased by approximately 40%. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) results showed that the expression of protein with approximately 32 kDa molecular mass was reduced significantly in the mutant. Compared to the wild type, the mutant grew more slowly at pH 6.0 and 37 degrees C, with a lower specific growth rate of 0.14 h(-1) (vs 0.21 h(-1) for the wild type), likely due to the partially impaired PTA-AK pathway. However, the mutant produced 23.5% more butyrate (0.42 vs 0.34 g/g glucose) at a higher final concentration of 41.7 g/L (vs 19.98 g/L) as a result of its higher butyrate tolerance as indicated in the growth kinetics study using various intial concentrations of butyrate in the media. The mutant also produced 50% more hydrogen (0.024 g/g) from glucose than the wild type. Immobilized-cell fermentation of PAK-Em in a fibrous-bed bioreactor (FBB) further increased the final butyric acid concentration (50.1 g/L) and the butyrate yield (0.45 g/g glucose). Furthermore, in the FBB fermentation at pH 5.0 with xylose as the substrate, only butyric acid was produced by the mutant, whereas the wild type produced large amounts of acetate (0.43 g/g xylose) and lactate (0.61 g/g xylose) and little butyrate (0.05 g/g xylose), indicating a dramatic metabolic pathway shift caused by the ack deletion in the mutant.

Thermodynamics-based metabolic flux analysis

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.

Genome-scale thermodynamic analysis of Escherichia coli metabolism

Genome-scale metabolic models are an invaluable tool for analyzing metabolic systems as they provide a more complete picture of the processes of metabolism. We have constructed a genome-scale metabolic model of Escherichia coli based on the iJR904 model developed by the Palsson Laboratory at the University of California at San Diego. Group contribution methods were utilized to estimate the standard Gibbs free energy change of every reaction in the constructed model. Reactions in the model were classified based on the activity of the reactions during optimal growth on glucose in aerobic media. The most thermodynamically unfavorable reactions involved in the production of biomass in E. coli were identified as ATP phosphoribosyltransferase, ATP synthase, methylene-tetra-hydrofolate dehydrogenase, and tryptophanase. The effect of a knockout of these reactions on the production of biomass and the production of individual biomass precursors was analyzed. Changes in the distribution of fluxes in the cell after knockout of these unfavorable reactions were also studied. The methodologies and results discussed can be used to facilitate the refinement of the feasible ranges for cellular parameters such as species concentrations and reaction rate constants.

Construction and characterization of pta gene-deleted mutant of Clostridium tyrobutyricum for enhanced butyric acid fermentation

Clostridium tyrobutyricum ATCC 25755 is an acidogenic bacterium, producing butyrate and acetate as its main fermentation products. In order to decrease acetate and increase butyrate production, integrational mutagenesis was used to disrupt the gene associated with the acetate formation pathway in C. tyrobutyricum. A nonreplicative integrational plasmid containing the phosphotransacetylase gene (pta) fragment cloned from C. tyrobutyricum by using degenerate primers and an erythromycin resistance cassette were constructed and introduced into C. tyrobutyricum by electroporation. Integration of the plasmid into the homologous region on the chromosome inactivated the target pta gene and produced the pta-deleted mutant (PTA-Em), which was confirmed by Southern hybridization. SDS-PAGE and two-dimensional protein electrophoresis results indicated that protein expression was changed in the mutant. Enzyme activity assays using the cell lysate showed that the activities of PTA and acetate kinase (AK) in the mutant were reduced by more than 60% for PTA and 80% for AK. The mutant grew more slowly in batch fermentation with glucose as the substrate but produced 15% more butyrate and 14% less acetate as compared to the wild-type strain. Its butyrate productivity was approximately 2-fold higher than the wild-type strain. Moreover, the mutant showed much higher tolerance to butyrate inhibition, and the final butyrate concentration was improved by 68%. However, inactivation of pta gene did not completely eliminate acetate production in the fermentation, suggesting the existence of other enzymes (or pathways) also leading to acetate formation. This is the first-reported genetic engineering study demonstrating the feasibility of using a gene-inactivation technique to manipulate the acetic acid formation pathway in C. tyrobutyricum in order to improve butyric acid production from glucose.

OptStrain: a computational framework for redesign of microbial production systems

This paper introduces the hierarchical computational framework OptStrain aimed at guiding pathway modifications, through reaction additions and deletions, of microbial networks for the overproduction of targeted compounds. These compounds may range from electrons or hydrogen in biofuel cell and environmental applications to complex drug precursor molecules. A comprehensive database of biotransformations, referred to as the Universal database (with >5700 reactions), is compiled and regularly updated by downloading and curating reactions from multiple biopathway database sources. Combinatorial optimization is then used to elucidate the set(s) of non-native functionalities, extracted from this Universal database, to add to the examined production host for enabling the desired product formation. Subsequently, competing functionalities that divert flux away from the targeted product are identified and removed to ensure higher product yields coupled with growth. This work represents an advancement over earlier efforts by establishing an integrated computational framework capable of constructing stoichiometrically balanced pathways, imposing maximum product yield requirements, pinpointing the optimal substrate(s), and evaluating different microbial hosts. The range and utility of OptStrain are demonstrated by addressing two very different product molecules. The hydrogen case study pinpoints reaction elimination strategies for improving hydrogen yields using two different substrates for three separate production hosts. In contrast, the vanillin study primarily showcases which non-native pathways need to be added into Escherichia coli. In summary, OptStrain provides a useful tool to aid microbial strain design and, more importantly, it establishes an integrated framework to accommodate future modeling developments.

Data reconciliation and parameter estimation in flux-balance analysis

Flux blance analysis (FBA) has been shown to be a very effective tool to interpret and predict the metabolism of various microorganisms when the set of available measurements is not sufficient to determine the fluxes within the cell. In this methodology, an underdetermined stoichiometric model is solved using a linear programming (LP) approach. The predictions of FBA models can be improved if noisy measurements are checked for consistency, and these in turn are used to estimate model parameters. In this work, a formal methodology for data reconciliation and parameter estimation with underdetermined stoichiometric models is developed and assessed. The procedure is formulated as a nonlinear optimization problem, where the LP is transformed into a set of nonlinear constraints. However, some of these constraints violate standard regularity conditions, making the direct numerical solution very difficult. Hence, a barrier formulation is used to represent these constraints, and an iterative procedure is defined that allows solving the problem to the desired degree of convergence. This methodology is assessed using a stoichiometric yeast model. The procedure is used for data reconciliation where more reliable estimations of noisy measurements are computed. On the other hand, assuming unknown biomass composition, the procedure is applied for simultaneous data reconciliation and biomass composition estimation. In both cases it is verified that the f measurements required to get unbiased and reliable estimations is reduced if the LP approach is included as additional constraints in the optimization.

A computational model for the identification of biochemical pathways in the krebs cycle

We have applied an algorithmic methodology which provably decomposes any complex network into a complete family of principal subcircuits to study the minimal circuits that describe the Krebs cycle. Every operational behavior that the network is capable of exhibiting can be represented by some combination of these principal subcircuits and this computational decomposition is linearly efficient. We have developed a computational model that can be applied to biochemical reaction systems which accurately renders pathways of such reactions via directed hypergraphs (Petri nets). We have applied the model to the citric acid cycle (Krebs cycle). The Krebs cycle, which oxidizes the acetyl group of acetyl CoA to CO(2) and reduces NAD and FAD to NADH and FADH(2), is a complex interacting set of nine subreaction networks. The Krebs cycle was selected because of its familiarity to the biological community and because it exhibits enough complexity to be interesting in order to introduce this novel analytic approach. This study validates the algorithmic methodology for the identification of significant biochemical signaling subcircuits, based solely upon the mathematical model and not upon prior biological knowledge. The utility of the algebraic-combinatorial model for identifying the complete set of biochemical subcircuits as a data set is demonstrated for this important metabolic process.

Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions

An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.

Carbon flux distribution and kinetics of cellulose fermentation in steady-state continuous cultures of Clostridium cellulolyticum on a chemically defined medium

The metabolic characteristics of Clostridium cellulolyticum, a mesophilic cellulolytic nonruminal bacterium, were investigated and characterized kinetically for the fermentation of cellulose by using chemostat culture analysis. Since with C. cellulolyticum (i) the ATP/ADP ratio is lower than 1, (ii) the production of lactate at low specific growth rate (mu) is low, and (iii) there is a decrease of the NADH/NAD(+) ratio and q(NADH produced)/ q(NADH used) ratio as the dilution rate (D) increases in carbon-limited conditions, the chemostats used were cellulose-limited continuously fed cultures. Under all conditions, ethanol and acetate were the main end products of catabolism. There was no shift from an acetate-ethanol fermentation to a lactate-ethanol fermentation as previously observed on cellobiose as mu increased (E. Guedon, S. Payot, M. Desvaux, and H. Petitdemange, J. Bacteriol. 181:3262-3269, 1999). The acetate/ethanol ratio was always higher than 1 but decreased with D. On cellulose, glucose 6-phosphate and glucose 1-phosphate are important branch points since the longer the soluble beta-glucan uptake is, the more glucose 1-phosphate will be generated. The proportion of carbon flowing toward phosphoglucomutase remained constant (around 59.0%), while the carbon surplus was dissipated through exopolysaccharide and glycogen synthesis. The percentage of carbon metabolized via pyruvate-ferredoxin oxidoreductase decreased with D. Acetyl coenzyme A was mainly directed toward the acetate formation pathway, which represented a minimum of 27.1% of the carbon substrate. Yet the proportion of carbon directed through biosynthesis (i.e., biomass, extracellular proteins, and free amino acids) and ethanol increased with D, reaching 27.3 and 16.8%, respectively, at 0.083 h(-1). Lactate and extracellular pyruvate remained low, representing up to 1.5 and 0.2%, respectively, of the original carbon uptake. The true growth yield obtained on cellulose was higher, [50.5 g of cells (mol of hexose eq)(-1)] than on cellobiose, a soluble cellodextrin [36.2 g of cells (mol of hexose eq)(-1)]. The rate of cellulose utilization depended on the solid retention time and was first order, with a rate constant of 0.05 h(-1). Compared to cellobiose, substrate hydrolysis by cellulosome when bacteria are grown on cellulose fibers introduces an extra means for regulation of the entering carbon flow. This led to a lower mu, and so metabolism was not as distorted as previously observed with a soluble substrate. From these results, C. cellulolyticum appeared well adapted and even restricted to a cellulolytic lifestyle.

Mass flux balance-based model and metabolic flux analysis for collagen synthesis in the fibrogenesis process of human liver

A mass flux balance-based stoichiometric model for human liver metabolism has been set up. The model considers 125 reaction fluxes, and there are 83 metabolites that are assumed to be in pseudo-steady state. Theoretical metabolic flux distributions in the fibrotic and healthy liver cells were determined by maximizing respectively the collagen and palmitate synthesis in the objective function for the solution of the model. The flux distribution maps of the analysis for the collagen synthesis showed that the glycolysis pathway was active down to fructose-6-phosphate and the gluconeogenesis pathway was active up to glyceraldehyde 3-phosphate synthesis. However, the flux distribution maps for the palmitate synthesis revealed that both the glycolysis pathway and the gluconeogenesis pathway were active towards 3-phospho glycerate. The TCA cycle operated from citrate towards oxalacetate, and the anaplerotic reactions that connect the TCA cycle to the gluconeogenesis pathway were active in both analyses. Metabolic flux analysis shows that the amino acid fluxes are indeed important in the collagen synthesis. The results of the comparative analyses for the occurrence of the collagen synthesis in the fibrotic liver cells reveal that among the non-essential amino acids three, namely glycine, proline and aspartic acid, and among the essential amino acids one, methionine, are respectively the potential metabolic bottlenecks and the limiting amino acid. The diversions in the pathways and certain metabolic reactions are also presented, and potential strategies for controlling the collagen synthesis and consequently the fibrosis are also discussed.

Metabolic analysis of Escherichia coli in the presence and absence of the carboxylating enzymes phosphoenolpyruvate carboxylase and pyruvate carboxylase

Fermentation patterns of Escherichia coli with and without the phosphoenolpyruvate carboxylase (PPC) and pyruvate carboxylase (PYC) enzymes were compared under anaerobic conditions with glucose as a carbon source. Time profiles of glucose and fermentation product concentrations were determined and used to calculate metabolic fluxes through central carbon pathways during exponential cell growth. The presence of the Rhizobium etli pyc gene in E. coli (JCL1242/pTrc99A-pyc) restored the succinate producing ability of E. coli ppc null mutants (JCL1242), with PYC competing favorably with both pyruvate formate lyase and lactate dehydrogenase. Succinate formation was slightly greater by JCL1242/pTrc99A-pyc than by cells which overproduced PPC (JCL1242/pPC201, ppc(+)), even though PPC activity in cell extracts of JCL1242/pPC201 (ppc(+)) was 40-fold greater than PYC activity in extracts of JCL1242/pTrc99a-pyc. Flux calculations indicate that during anaerobic metabolism the pyc(+) strain had a 34% greater specific glucose consumption rate, a 37% greater specific rate of ATP formation, and a 6% greater specific growth rate compared to the ppc(+) strain. In light of the important position of pyruvate at the juncture of NADH-generating pathways and NADH-dissimilating branches, the results show that when PPC or PYC is expressed, the metabolic network adapts by altering the flux to lactate and the molar ratio of ethanol to acetate formation.

Metabolic flux analysis for serine alkaline protease fermentation by Bacillus licheniformis in a defined medium: effects of the oxygen transfer rate

The metabolic fluxes through the central carbon pathways in the bioprocess for serine alkaline protease (SAP) production by Bacillus licheniformis were calculated by the metabolic flux-based stoichiometric model based on the proposed metabolic network that contains 102 metabolites and 133 reaction fluxes using the time profiles of citrate, dry cell, organic acids, amino acids, and SAP as the constraints. The model was solved by minimizing the SAP accumulation rate in the cell. The effects of the oxygen-transfer rate (OTR) on the metabolic fluxes were investigated in a defined medium where citrate was used as the sole carbon source. The central pathways were active for the growth and the SAP synthesis in all the periods of the bioprocess at low (LOT), medium (MOT), and high (HOT) oxygen-transfer conditions. The flux partitioning in the TCA cycle at alpha-ketoglutarate towards glutamate group and at oxalacetate (OA) toward aspartic acid group amino acids were dependent on the OTR. The flux of the anaplerotic reaction that connects the TCA cycle either from malate or OA to the gluconeogenesis pathway via the main branch point pyruvate (Pyr) was also influenced by the OTR. With the decrease in the OTR, the intracellular flux values after glycerate 3-phosphate (PG3) in the gluconeogenesis pathway and the specific growth rate decreased. The total ATP-generation rate increased with the increase in OTR. The pathway towards the aspartic acid family amino acids which is important for sporulation that precedes the SAP synthesis were all active throughout the bioprocess. Metabolic flux analysis results at LOT, MOT, and HOT conditions encourage the design of an oxygen-transfer strategy in the bioreactor; moreover, asparagine synthetase or aspartate kinase could be the potential metabolic engineering sites due to the low value of the flux from the branch point aspartate toward asparagine.

Stoichiometric modeling of Clostridium acetobutylicum fermentations with non-linear constraints

A stoichiometric model of Clostridium acetobutylicum and related strains has been previously derived. The stoichiometric matrix of the model contains a singularity which has prevented the calculation of a unique set of fluxes which describe the primary metabolic activity. To resolve the singularity, we have developed a non-linear constraint relating the acetate and butyrate uptake fluxes. Subsequently, we developed a software package utilizing a model independent heuristic global optimization approach to solve the resultant non-linear problem. We have validated the use of the non-linear constraint by correlating calculated butyrate production pathway flux profiles with measured intracellular pH profiles. Finally, we examined a controlled batch fermentation to determine that the acid formation pathways play critical roles throughout solventogenesis. The broader usefulness of reformulating the stoichiometric model as a constrained minimization problem is discussed.

Carbon and electron flow in Clostridium cellulolyticum grown in chemostat culture on synthetic medium

Previous results indicated poor sugar consumption and early inhibition of metabolism and growth when Clostridium cellulolyticum was cultured on medium containing cellobiose and yeast extract. Changing from complex medium to a synthetic medium had a strong effect on (i) the specific cellobiose consumption, which was increased threefold; and (ii) the electron flow, since the NADH/NAD+ ratios ranged from 0.29 to 2.08 on synthetic medium whereas ratios as high as 42 to 57 on complex medium were observed. These data indicate a better control of the carbon flow on mineral salts medium than on complex medium. By continuous culture, it was shown that the electron flow from glycolysis was balanced by the production of hydrogen gas, ethanol, and lactate. At low levels of carbon flow, pyruvate was preferentially cleaved to acetate and ethanol, enabling the bacteria to maximize ATP formation. A high catabolic rate led to pyruvate overflow and to increased ethanol and lactate production. In vitro, glyceraldehyde-3-phosphate dehydrogenase, lactate dehydrogenase, and ethanol dehydrogenase levels were higher under conditions giving higher in vivo specific production rates. Redox balance is essentially maintained by NADH-ferredoxin reductase-hydrogenase at low levels of carbon flow and by ethanol dehydrogenase and lactate dehydrogenase at high levels of carbon flow. The same maximum growth rate (0.150 h-1) was found in both mineral salts and complex media, proving that the uptake of nutrients or the generation of biosynthetic precursors occurred faster than their utilization. On synthetic medium, cellobiose carbon was converted into cell mass and catabolized to produce ATP, while on complex medium, it served mainly as an energy supply and, if present in excess, led to an accumulation of intracellular metabolites as demonstrated for NADH. Cells grown on synthetic medium and at high levels of carbon flow were able to induce regulatory responses such as the production of ethanol and lactate dehydrogenase.

Mathematical models of metabolic pathways

There have been recent advances in metabolic flux analysis. In particular, the marriage of traditional flux balancing with NMR isotopomer distribution analysis holds great promise for the detailed quantification of physiology. Nevertheless, flux analysis yields only static snap-shots of metabolism. To robustly predict the time evolution of metabolic networks, dynamic mathematical models, especially those that contain a description of both gene expression as well as enzyme activity, must be utilized. When mechanistic control and regulatory information is not available, heuristic-based methods, such as the cybernetic framework, can be employed to describe the action of these control mechanisms. In the 'high-information' future, as more biological information becomes available, such heuristic-based approaches can be replaced by mechanistic mass-action representations of physiology that stem directly from genetic sequence.

Metabolism analysis and on-line physiological state diagnosis of acetone-butanol fermentation

Fermentation equations for acetone-butanol (AB) were applied in a metabolic analysis of the reaction network under various conditions; that is, at different pHs and a high NADH2 turnover rate using methyl viologen, in a Clostridium acetobutylicum culture. The results disclosed variations in the pattern of rate changes that reflected changes in the physiological state. A linear relationship was found to exist between NADH2 generation and butanol production rate. By coupling an automated measurement system with the fermentation model, on-line estimation of the culture state was accomplished. Based on the AB fermentation model, new parameters were defined for on-line diagnosis of the physiological state and determination of the best timing for amplifying NADH2 generation by the addition of methyl viologen to obtain a high level of butanol productivity. A potential means of achieving optimal control for a high level of solvent production, involving the correlation of certain rates, is proposed.