Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C(3) and C(4) metabolism

State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs

Methanotrophy is the ability of an organism to capture and utilize the greenhouse gas, methane, as a source of energy-rich carbon. Over the years, significant progress has been made in understanding of mechanisms for methane utilization, mostly in bacterial systems, including the key metabolic pathways, regulation and the impact of various factors (iron, copper, calcium, lanthanum, and tungsten) on cell growth and methane bioconversion. The implementation of -omics approaches provided vast amount of heterogeneous data that require the adaptation or development of computational tools for a system-wide interrogative analysis of methanotrophy. The genome-scale mathematical modeling of its metabolism has been envisioned as one of the most productive strategies for the integration of muti-scale data to better understand methane metabolism and enable its biotechnological implementation. Herein, we provide an overview of various computational strategies implemented for methanotrophic systems. We highlight functional capabilities as well as limitations of the most popular web resources for the reconstruction, modification and optimization of the genome-scale metabolic models for methane-utilizing bacteria.

Sodium formate redirects carbon flux and enhances heterologous mevalonate production in Methylobacterium extorquens AM1

Methylobacterium extorquens AM1 (AM1), a model strain of methylotrophic cell factories (MeCFs) could be used to produce fine chemicals from methanol. Synthesis of heterologous products usually needs reducing cofactors, but AM1 growing on methanol lack reducing power. Formate could be used as a reducing agent. In this study, mevalonic acid (MEV) yield of 0.067 gMEV/g methanol was reached by adding 10 mmol L^-1 sodium formate in MEV accumulating stage (at 72 h). The yield was improved by 64.57%, and represented the highest yield reported to date. ¹³ C-labeling experiments revealed global effects of sodium formate on metabolic pathways in engineered Methylobacterium extorquens AM1. Sodium formate significantly increased the ratios of reducing equivalents, enhanced the metabolic rate of pathways demanding reducing cofactors and redirected the carbon flux to MEV synthesis. As a result, coupling formate to methanol-based production provide a promising way for converting C1 substances to useful chemical products.

Developing methylotrophic microbial platforms for a methanol-based bioindustry

Methanol, a relatively cheap and renewable single-carbon feedstock, has gained considerable attention as a substrate for the bio-production of commodity chemicals. Conventionally produced from syngas, along with emerging possibilities of generation from methane and CO2, this C1 substrate can serve as a pool for sequestering greenhouse gases while supporting a sustainable bio-economy. Methylotrophic organisms, with the inherent ability to use methanol as the sole carbon and energy source, are competent candidates as platform organisms. Accordingly, methanol bioconversion pathways have been an attractive target for biotechnological and bioengineering interventions in developing microbial cell factories. This review summarizes the recent advances in methanol-based production of various bulk and value-added chemicals exploiting the native and synthetic methylotrophic organisms. Finally, the current challenges and prospects of streamlining these methylotrophic platforms are discussed.

A shortcut to carbon-neutral bioplastic production: Recent advances in microbial production of polyhydroxyalkanoates from C1 resources

Since the 20th century, plastics that are widely being used in general life and industries are causing enormous plastic waste problems since improperly discarded plastics barely degrade and decompose. Thus, the demand for polyhydroxyalkanoates (PHAs), biodegradable polymers with material properties similar to conventional petroleum-based plastics, has been increased so far. The microbial production of PHAs is an environment-friendly solution for the current plastic crisis, however, the carbon sources for the microbial PHA production is a crucial factor to be considered in terms of carbon-neutrality. One‑carbon (C1) resources, such as methane, carbon monoxide, and carbon dioxide, are greenhouse gases and are abundantly found in nature and industry. C1 resources as the carbon sources for PHA production have a completely closed carbon loop with much advances; i) fast carbon circulation with direct bioconversion process and ii) simple fermentation procedure without sterilization as non-preferable nutrients. This review discusses the biosynthesis of PHAs based on C1 resource utilization by wild-type and metabolically engineered microbial host strains via biorefinery processes.

Comparison of the Wild-Type Obligate Methylotrophic Bacterium Methylophilus quaylei and its Isogenic Streptomycin-Resistant Mutant via Metal Nanoparticle Generation

Metal nanoparticles synthesized by green methods with the use of microorganisms are currently one of the most closely studied types of nanomaterials. It has accurately been shown that the characteristics of metal nanoparticles generated in the presence of different bacteria vary. For the two isogenic strains of obligate methylotrophic bacteria of the wild type (M. quaylei MT^T) and its streptomycin-resistant mutant (M. quaylei SM^R), the pleiotropic character of streptomycin resistance mutation in the SM^R cells has been revealed. It has been shown that both cultures can generate silver nanoparticles. There is a dramatic difference in the formation of palladium nanoparticles, which are formed only in the presence of cells of the streptomycin-resistant mutant M. quaylei SM^R. This study shows that closely related isogenic strains of obligate methylotrophic bacteria can be distinguished by the spectra of biogenic nanoparticles of two noble metals. While palladium nanoparticles are only generated by the cells of the streptomycin-resistant mutant M. quaylei SM^R, biogenic silver nanoparticles can be generated from both cultures. Thus, the assessment of the ability of microorganisms to form biogenic nanoparticles of different metals allows the revelation of subtle metabolic differences of even close cultures.

Basics of genome-scale metabolic modeling and applications on C1-utilization

It is fundamental to understand the relationship between genotype and phenotype in biology. This requires comprehensive knowledge of metabolic pathways, genetic information and well-defined mathematic modeling. Integration of knowledge on metabolism with mathematical modeling results in genome-scale metabolic models which have proven useful to investigate bacterial metabolism and to engineer bacterial strains capable of producing value-added biochemical. Single carbon substrates such as methane and carbon monoxide have drawn interests and they assumed one of next-generation feedstocks because of their high abundance and low price. The methylotroph and acetogen-based biorefineries hold promises for bioconversion of C1 substrates into biofuels and high value compounds. As an effort on expanding our knowledge on C1 utilization approaches, in silico computational framework of C1-metabolism in methylotrophic and acetogenic bacteria has been developed. In this review, genome-scale metabolic models for C1-utilizing bacteria and well-established analysis tools are presented for potential uses for study of C1 metabolism at the genome scale and its application in metabolic engineering.

Dynamical modelling of secondary metabolism and metabolic switches in Streptomyces xiamenensis 318

The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increase the metabolic fitness of the organism via stabilizing the underlying metabolic network. And the fluxes directing to NADH, NADPH, acetyl-CoA and glutamate provide the key switches for the overall and secondary metabolism. The information may be helpful for improving the xiamenmycin production on the strain.

Production of 3-hydroxypropionic acid in engineered Methylobacterium extorquens AM1 and its reassimilation through a reductive route

Background

3-Hydroxypropionic acid (3-HP) is an important platform chemical, serving as a precursor for a wide range of industrial applications such as the production of acrylic acid and 1,3-propanediol. Although Escherichia coli or Saccharomyces cerevisiae are the primary industrial microbes for the production of 3-HP, alternative engineered hosts have the potential to generate 3-HP from other carbon feedstocks. Methylobacterium extorquens AM1, a facultative methylotrophic α-proteobacterium, is a model system for assessing the possibility of generating 3-HP from one-carbon feedstock methanol.

Results

Here we constructed a malonyl-CoA pathway by heterologously overexpressing the mcr gene to convert methanol into 3-HP in M. extorquens AM1. The engineered strains demonstrated 3-HP production with initial titer of 6.8 mg/l in shake flask cultivation, which was further improved to 69.8 mg/l by increasing the strength of promoter and mcr gene copy number. In vivo metabolic analysis showed a significant decrease of the acetyl-CoA pool size in the strain with the highest 3-HP titer, suggesting the supply of acetyl-CoA is a potential bottleneck for further improvement. Notably, 3-HP was rapidly degraded after the transition from exponential phase to stationary phase. Metabolomics analysis showed the accumulation of intracellular 3-hydroxypropionyl-CoA at stationary phase with the addition of 3-HP into the cultured medium, indicating 3-HP was first converted to its CoA derivatives. In vitro enzymatic assay and β-alanine pathway dependent ¹³C-labeling further demonstrated that a reductive route sequentially converted 3-HP-CoA to acrylyl-CoA and propionyl-CoA, with the latter being reassimilated into the ethylmalonyl-CoA pathway. The deletion of the gene META1_4251 encoding a putative acrylyl-CoA reductase led to reduced degradation rate of 3-HP in late stationary phase.

Conclusions

We demonstrated the feasibility of constructing the malonyl-CoA pathway in M. extorquens AM1 to generate 3-HP. Furthermore, we showed that a reductive route coupled with the ethylmalonyl-CoA pathway was the major channel responsible for degradation of the 3-HP during the growth transition. Engineered M. extorquens AM1 represents a good platform for 3-HP production from methanol.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0798-2) contains supplementary material, which is available to authorized users.

Kinetic model of metabolic network for xiamenmycin biosynthetic optimisation

Xiamenmycins, a series of prenylated benzopyran compounds with anti‐fibrotic bioactivities, were isolated from a mangrove‐derived Streptomyces xiamenensis. To fulfil the requirements of pharmaceutical investigations, a high production of xiamenmycin is needed. In this study,, the authors present a kinetic metabolic model to evaluate fluxes in an engineered Streptomyces lividans with xiamenmycin‐oriented genetic modification based on generic enzymatic rate equations and stability constraints. Lyapunov function was used for a viability optimisation. From their kinetic model, the flux distributions for the engineered S. lividans fed on glucose and glycerol as carbon sources were calculated. They found that if the bacterium can utilise glucose simultaneously with glycerol, xiamenmycin production can be enhanced by 40% theoretically, while maintaining the same growth rate. Glycerol may increase the flux for phosphoenolpyruvate synthesis without interfering citric acid cycle. They therefore believe this study demonstrates a possible new direction for bioengineering of S. lividans.

Selection Maintains Apparently Degenerate Metabolic Pathways due to Tradeoffs in Using Methylamine for Carbon versus Nitrogen

Microorganisms often encode multiple non-orthologous metabolic modules that catalyze the same reaction. However, little experimental evidence actually demonstrates a selective basis for metabolic degeneracy. Many methylotrophs-microorganisms that grow on reduced single-carbon compounds-like Methylobacterium extorquens AM1 encode two routes for methylamine oxidation: the periplasmic methylamine dehydrogenase (MaDH) and the cytoplasmic N-methylglutamate (NMG) pathway. In Methylobacterium extorquens AM1, MaDH is essential for methylamine growth, but the NMG pathway has no known physiological role. Here, we use experimental evolution of two isolates lacking (or incapable of using) MaDH to uncover the physiological challenges that need to be overcome in order to use the NMG pathway for growth on methylamine as a carbon and energy source. Physiological characterization of the evolved isolates revealed regulatory rewiring to increase expression of the NMG pathway and novel mechanisms to mitigate cytoplasmic ammonia buildup. These adaptations led us to infer and validate environmental conditions under which the NMG pathway is advantageous compared to MaDH. The highly expressed MaDH enables rapid growth on high concentrations of methylamine as the primary carbon and energy substrate, whereas the energetically expensive NMG pathway plays a pivotal role during growth with methylamine as the sole nitrogen source, which we demonstrate is especially true under limiting concentrations (<1 mM). Tradeoffs between cellular localization and ammonium toxicity lead to selection for this apparent degeneracy as it is beneficial to facultative methylotrophs that have to switch between using methylamine as a carbon and energy source or just a nitrogen source.

Genome-scale metabolic reconstructions and theoretical investigation of methane conversion in Methylomicrobium buryatense strain 5G(B1)

BACKGROUND

Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration.

RESULTS

A stoichiometric flux balance model of Methylomicrobium buryatense strain 5G(B1) was constructed and used for evaluating metabolic engineering strategies for biofuels and chemical production with a methanotrophic bacterium as the catalytic platform. The initial metabolic reconstruction was based on whole-genome predictions. Each metabolic step was manually verified, gapfilled, and modified in accordance with genome-wide expression data. The final model incorporates a total of 841 reactions (in 167 metabolic pathways). Of these, up to 400 reactions were recruited to produce 118 intracellular metabolites. The flux balance simulations suggest that only the transfer of electrons from methanol oxidation to methane oxidation steps can support measured growth and methane/oxygen consumption parameters, while the scenario employing NADH as a possible source of electrons for particulate methane monooxygenase cannot. Direct coupling between methane oxidation and methanol oxidation accounts for most of the membrane-associated methane monooxygenase activity. However the best fit to experimental results is achieved only after assuming that the efficiency of direct coupling depends on growth conditions and additional NADH input (about 0.1-0.2 mol of incremental NADH per one mol of methane oxidized). The additional input is proposed to cover loss of electrons through inefficiency and to sustain methane oxidation at perturbations or support uphill electron transfer. Finally, the model was used for testing the carbon conversion efficiency of different pathways for C1-utilization, including different variants of the ribulose monophosphate pathway and the serine cycle.

CONCLUSION

We demonstrate that the metabolic model can provide an effective tool for predicting metabolic parameters for different nutrients and genetic perturbations, and as such, should be valuable for metabolic engineering of the central metabolism of M. buryatense strains.

Parallel and Divergent Evolutionary Solutions for the Optimization of an Engineered Central Metabolism in Methylobacterium extorquens AM1

Bioengineering holds great promise to provide fast and efficient biocatalysts for methanol-based biotechnology, but necessitates proven methods to optimize physiology in engineered strains. Here, we highlight experimental evolution as an effective means for optimizing an engineered Methylobacterium extorquens AM1. Replacement of the native formaldehyde oxidation pathway with a functional analog substantially decreased growth in an engineered Methylobacterium, but growth rapidly recovered after six hundred generations of evolution on methanol. We used whole-genome sequencing to identify the basis of adaptation in eight replicate evolved strains, and examined genomic changes in light of other growth and physiological data. We observed great variety in the numbers and types of mutations that occurred, including instances of parallel mutations at targets that may have been "rationalized" by the bioengineer, plus other "illogical" mutations that demonstrate the ability of evolution to expose unforeseen optimization solutions. Notably, we investigated mutations to RNA polymerase, which provided a massive growth benefit but are linked to highly aberrant transcriptional profiles. Overall, we highlight the power of experimental evolution to present genetic and physiological solutions for strain optimization, particularly in systems where the challenges of engineering are too many or too difficult to overcome via traditional engineering methods.

Methenyl-Dephosphotetrahydromethanopterin Is a Regulatory Signal for Acclimation to Changes in Substrate Availability in Methylobacterium extorquens AM1

During an environmental perturbation, the survival of a cell and its response to the perturbation depend on both the robustness and functionality of the metabolic network. The regulatory mechanisms that allow the facultative methylotrophic bacterium Methylobacterium extorquens AM1 to effect the metabolic transition from succinate to methanol growth are not well understood. Methenyl-dephosphotetrahydromethanopterin (methenyl-dH4MPT), an early intermediate during methanol metabolism, transiently accumulated 7- to 11-fold after addition of methanol to a succinate-limited culture. This accumulation partially inhibited the activity of the methylene-H4MPT dehydrogenase, MtdA, restricting carbon flux to the assimilation cycles. A strain overexpressing the gene (mch) encoding the enzyme that consumes methenyl-dH4MPT did not accumulate methenyl-dH4MPT and had a growth rate that was 2.7-fold lower than that of the wild type. This growth defect demonstrates the physiological relevance of this enzymatic regulatory mechanism during the acclimation period. Changes in metabolites and enzymatic activities were analyzed in the strain overexpressing mch. Under these conditions, the activity of the enzyme coupling formaldehyde with dH4MPT (Fae) remained constant, with concomitant formaldehyde accumulation. Release of methenyl-dH4MPT regulation did not affect the induction of the serine cycle enzyme activities immediately after methanol addition, but after 1 h, the activity of these enzymes decreased, likely due to the toxicity of formaldehyde accumulation. Our results support the hypothesis that in a changing environment, the transient accumulation of methenyl-dH4MPT and inhibition of MtdA activity are strategies that permit flexibility and acclimation of the metabolic network while preventing the accumulation of the toxic compound formaldehyde.

IMPORTANCE

The identification and characterization of regulatory mechanisms for methylotrophy are in the early stages. We report a nontranscriptional regulatory mechanism that was found to operate as an immediate response for acclimation during changes in substrate availability. Methenyl-dH4MPT, an early intermediate during methanol oxidation, reversibly inhibits the methylene-H4MPT dehydrogenase, MtdA, when Methylobacterium extorquens is challenged to switch from succinate to methanol growth. Bypassing this regulatory mechanism causes formaldehyde to accumulate. Fae, the enzyme catalyzing the conversion of formaldehyde to methylene-dH4MPT, was also identified as another potential regulatory target using this strategy. The results herein further our understanding of the complex regulatory network in methylotrophy and will allow us to improve metabolic engineering strategies of methylotrophs for the production of value-added products.

Metabolic engineering in methanotrophic bacteria

Methane, as natural gas or biogas, is the least expensive source of carbon for (bio)chemical synthesis. Scalable biological upgrading of this simple alkane to chemicals and fuels can bring new sustainable solutions to a number of industries with large environmental footprints, such as natural gas/petroleum production, landfills, wastewater treatment, and livestock. Microbial biocatalysis with methane as a feedstock has been pursued off and on for almost a half century, with little enduring success. Today, biological engineering and systems biology provide new opportunities for metabolic system modulation and give new optimism to the concept of a methane-based bio-industry. Here we present an overview of the most recent advances pertaining to metabolic engineering of microbial methane utilization. Some ideas concerning metabolic improvements for production of acetyl-CoA and pyruvate, two main precursors for bioconversion, are presented. We also discuss main gaps in the current knowledge of aerobic methane utilization, which must be solved in order to release the full potential of methane-based biosystems.

Methylamine utilization via the N-methylglutamate pathway in Methylobacterium extorquens PA1 involves a novel flow of carbon through C1 assimilation and dissimilation pathways

Methylotrophs grow on reduced single-carbon compounds like methylamine as the sole source of carbon and energy. In Methylobacterium extorquens AM1, the best-studied aerobic methylotroph, a periplasmic methylamine dehydrogenase that catalyzes the primary oxidation of methylamine to formaldehyde has been examined in great detail. However, recent metagenomic data from natural ecosystems are revealing the abundance and importance of lesser-known routes, such as the N-methylglutamate pathway, for methylamine oxidation. In this study, we used M. extorquens PA1, a strain that is closely related to M. extorquens AM1 but is lacking methylamine dehydrogenase, to dissect the genetics and physiology of the ecologically relevant N-methylglutamate pathway for methylamine oxidation. Phenotypic analyses of mutants with null mutations in genes encoding enzymes of the N-methylglutamate pathway suggested that γ-glutamylmethylamide synthetase is essential for growth on methylamine as a carbon source but not as a nitrogen source. Furthermore, analysis of M. extorquens PA1 mutants with defects in methylotrophy-specific dissimilatory and assimilatory modules suggested that methylamine use via the N-methylglutamate pathway requires the tetrahydromethanopterin (H4MPT)-dependent formaldehyde oxidation pathway but not a complete tetrahydrofolate (H4F)-dependent formate assimilation pathway. Additionally, we present genetic evidence that formaldehyde-activating enzyme (FAE) homologs might be involved in methylotrophy. Null mutants of FAE and homologs revealed that FAE and FAE2 influence the growth rate and FAE3 influences the yield during the growth of M. extorquens PA1 on methylamine.

Differential Bees Flux Balance Analysis with OptKnock for in silico microbial strains optimization

Microbial strains optimization for the overproduction of desired phenotype has been a popular topic in recent years. The strains can be optimized through several techniques in the field of genetic engineering. Gene knockout is a genetic engineering technique that can engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, the complexities of the metabolic networks have made the process to identify the effects of genetic modification on the desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to the combinatorial problem in obtaining optimal gene deletion strategy. Basically, the size of a genome-scale metabolic model is usually large. As the size of the problem increases, the computation time increases exponentially. In this paper, we propose Differential Bees Flux Balance Analysis (DBFBA) with OptKnock to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by improving the performance of a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) by hybridizing Differential Evolution (DE) algorithm into neighborhood searching strategy of BAFBA. In addition, DBFBA is integrated with OptKnock to validate the results for improving the reliability the work. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as the model organisms, DBFBA has shown a better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes compared to the methods used in previous works.

Emergent biosynthetic capacity in simple microbial communities

Microbes have an astonishing capacity to transform their environments. Yet, the metabolic capacity of a single species is limited and the vast majority of microorganisms form complex communities and join forces to exhibit capabilities far exceeding those achieved by any single species. Such enhanced metabolic capacities represent a promising route to many medical, environmental, and industrial applications and call for the development of a predictive, systems-level understanding of synergistic microbial capacity. Here we present a comprehensive computational framework, integrating high-quality metabolic models of multiple species, temporal dynamics, and flux variability analysis, to study the metabolic capacity and dynamics of simple two-species microbial ecosystems. We specifically focus on detecting emergent biosynthetic capacity--instances in which a community growing on some medium produces and secretes metabolites that are not secreted by any member species when growing in isolation on that same medium. Using this framework to model a large collection of two-species communities on multiple media, we demonstrate that emergent biosynthetic capacity is highly prevalent. We identify commonly observed emergent metabolites and metabolic reprogramming patterns, characterizing typical mechanisms of emergent capacity. We further find that emergent secretion tends to occur in two waves, the first as soon as the two organisms are introduced, and the second when the medium is depleted and nutrients become limited. Finally, aiming to identify global community determinants of emergent capacity, we find a marked association between the level of emergent biosynthetic capacity and the functional/phylogenetic distance between community members. Specifically, we demonstrate a "Goldilocks" principle, where high levels of emergent capacity are observed when the species comprising the community are functionally neither too close, nor too distant. Taken together, our results demonstrate the potential to design and engineer synthetic communities capable of novel metabolic activities and point to promising future directions in environmental and clinical bioengineering.

Impact of non-storing biomass on PHA production: an enrichment culture on acetate and methanol

The use of enrichment cultures for polyhydroxyalkanoate (PHA) production from substrate mixtures such as wastewater inevitably results in the establishment of a non-PHA-storing population besides the PHA-producing bacteria. This reduces the maximum PHA content that can be established, and increases downstream-processing costs. The aim of this study was to investigate the impact of non-storing biomass on the PHA production process. A microbial culture was enriched in a sequencing batch reactor fed with acetate and methanol. Methanol served as model substrate for compounds unsuitable for PHA production. The enrichment was dominated by Plasticicumulans acidivorans, a known PHA producer, and Methylobacillus flagellatus, an obligate methylotroph that cannot store PHA. As expected, the presence of the non-storing population lowered the maximum PHA content of the culture, from more than 80 to 66wt.%. To mimic a nitrogen-rich waste stream, additional accumulation experiments were performed with continuous supply of carbon and ammonium. In these experiments P. acidivorans still accumulated large amounts of PHA, but unrestricted growth of the non-storing, methylotrophic population reduced the maximum overall PHA content to 52wt.%. Besides ammonium limitation, other strategies to restrict the fraction of non-storing biomass should be developed. The mixture of acetate and methanol is a useful model substrate for the development of such strategies.

Comparison on extreme pathways reveals nature of different biological processes

Background

Constraint-based reconstruction and analysis (COBRA) is used for modeling genome-scale metabolic networks (MNs). In a COBRA model, extreme pathways (ExPas) are the edges of its conical solution space, which is formed by all viable steady-state flux distributions. ExPa analysis has been successfully applied to MNs to reveal their phenotypic capabilities and properties. Recently, the COBRA framework has been extended to transcriptional regulatory networks (TRNs) and transcriptional and translational networks (TTNs), so efforts are needed to determine whether ExPa analysis is also effective on these two types of networks.

Results

In this paper, the ExPas resulting from the COBRA models of E.coli's MN, TRN and TTN were horizontally compared from 5 aspects: (1) Total number and the ratio of their amount to reaction amount; (2) Length distribution; (3) Reaction participation; (4) Correlated reaction sets (CoSets); (5) interconnectivity degree. Significant discrepancies in above properties were observed during the comparison, which reveals the biological natures of different biological processes. Besides, by demonstrating the application of ExPa analysis on E.coli, we provide a practical guidance of an improved approach to compute ExPas on COBRA models of TRNs.

Conclusions

ExPas of E.coli's MN, TRN and TTN have different properties, which are strongly connected with various biological natures of biochemical networks, such as topological structure, specificity and redundancy. Our study shows that ExPas are biologically meaningful on the newborn models and suggests the effectiveness of ExPa analysis on them.

Metabolic engineering of Methylobacterium extorquens AM1 for 1-butanol production

BACKGROUND

Butanol is a promising next generation fuel and a bulk chemical precursor. Although clostridia are the primary industrial microbes for the fermentative production of 1-butanol, alternative engineered hosts have the potential to generate 1-butanol from alternative carbon feedstocks via synthetic metabolic pathways. Methylobacterium extorquens AM1, a facultative methylotrophic α-proteobacterium, is a model system for assessing the possibility of generating products such as 1-butanol from one-carbon and two-carbon feedstocks. Moreover, the core methylotrophic pathways in M. extorquens AM1 involve unusual coenzyme A (CoA)-derivative metabolites, such as crotonyl-CoA, which is a precursor for the production of 1-butanol.

RESULTS

In this work, we engineered a modified CoA-dependent pathway in Methylobacterium extorquens AM1 to produce 1-butanol. Engineered strains displayed different 1-butanol titers using ethylamine as a substrate. A strain overexpressing Treponema denticola trans-enoyl-CoA reductase, Clostridium acetobutylicum alcohol dehydrogenase, and native crotonase was able to generate the highest 1-butanol titer (15.2 mg l(-1)). In vitro isotopic tracing of metabolic flux and in vivo metabolite analysis showed the accumulation of butyryl-CoA, demonstrating the functionality of the synthetic pathway and identifying targets for future improvement.

CONCLUSIONS

We demonstrated the feasibility of using metabolic intermediates of the ethylmalonyl-CoA pathway in M. extorquens AM1 to generate value-added chemicals, with 1-butanol as the test case. This will not only establish the biotechnological potential of the ethylmalonyl-CoA pathway, but will also introduce M. extorquens AM1 as a potential platform to produce value-added chemicals.

Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load

Steady-state metabolite concentrations in a microorganism typically span several orders of magnitude. The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. Our approach, based strictly on first thermodynamic principles, is the first method that successfully predicts high-throughput metabolite concentration data in bacteria across conditions.

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.

Microbial production of poly(hydroxybutyrate) from C₁ carbon sources

Polyhydroxybutyrate (PHB) is an attractive substitute for petrochemical plastic due to its similar properties, biocompatibility, and biodegradability. The cost of scaled-up PHB production inhibits its widespread usage. Intensive researches are growing to reduce costs and improve thermomechanical, physical, and processing properties of this green biopolymer. Among cheap substrates which are used for reducing total cost of PHB production, some C₁ carbon sources, e.g., methane, methanol, and CO₂ have received a great deal of attention due to their serious role in greenhouse problem. This article reviews the fundamentals of strategies for reducing PHA production and moves on to the applications of several cheap substrates with a special emphasis on methane, methanol, and CO₂. Also, some explanation for involved microorganisms including the hydrogen-oxidizing bacteria and methanotrophs, their history, culture condition, and nutritional requirements are given. After description of some important strains among the hydrogen-oxidizing and methanotrophic producers of PHB, the article is focused on limitations, threats, and opportunities for application and their future trends.

GENERIC ENZYMATIC RATE EQUATION UNDER LIVING CONDITIONS

Based on our experience in kinetic modeling of coupled multiple metabolic pathways, we propose a generic rate equation for the dynamical modeling of metabolic kinetics. It is symmetric for forward and backward reactions. Its Michaelis-Menten-King-Altman form makes the kinetic parameters (or functions) easy to relate to experimental values in the database and to use in computation. In addition, such a uniform form is ready to arbitrary number of substrates and products with different stiochiometry. We explicitly show how to obtain such rate equations rigorously for three well-known binding mechanisms. Hence, the proposed rate equation is formally exact under the quasi-steady state condition. Various features of this generic rate equation are discussed. In particular, for irreversible reactions, the product inhibition which directly arises from enzymatic reaction is eliminated in a natural way. We also discuss how to include the effects of modifiers and cooperativity.

Genome-scale reconstruction and system level investigation of the metabolic network of Methylobacterium extorquens AM1

Background

Methylotrophic microorganisms are playing a key role in biogeochemical processes - especially the global carbon cycle - and have gained interest for biotechnological purposes. Significant progress was made in the recent years in the biochemistry, genetics, genomics, and physiology of methylotrophic bacteria, showing that methylotrophy is much more widespread and versatile than initially assumed. Despite such progress, system-level description of the methylotrophic metabolism is currently lacking, and much remains to understand regarding the network-scale organization and properties of methylotrophy, and how the methylotrophic capacity emerges from this organization, especially in facultative organisms.

Results

In this work, we report on the integrated, system-level investigation of the metabolic network of the facultative methylotroph Methylobacterium extorquens AM1, a valuable model of methylotrophic bacteria. The genome-scale metabolic network of the bacterium was reconstructed and contains 1139 reactions and 977 metabolites. The sub-network operating upon methylotrophic growth was identified from both in silico and experimental investigations, and ¹³C-fluxomics was applied to measure the distribution of metabolic fluxes under such conditions. The core metabolism has a highly unusual topology, in which the unique enzymes that catalyse the key steps of C1 assimilation are tightly connected by several, large metabolic cycles (serine cycle, ethylmalonyl-CoA pathway, TCA cycle, anaplerotic processes). The entire set of reactions must operate as a unique process to achieve C1 assimilation, but was shown to be structurally fragile based on network analysis. This observation suggests that in nature a strong pressure of selection must exist to maintain the methylotrophic capability. Nevertheless, substantial substrate cycling could be measured within C2/C3/C4 inter-conversions, indicating that the metabolic network is highly versatile around a flexible backbone of central reactions that allows rapid switching to multi-carbon sources.

Conclusions

This work emphasizes that the metabolism of M. extorquens AM1 is adapted to its lifestyle not only in terms of enzymatic equipment, but also in terms of network-level structure and regulation. It suggests that the metabolism of the bacterium has evolved both structurally and functionally to an efficient but transitory utilization of methanol. Besides, this work provides a basis for metabolic engineering to convert methanol into value-added products.

Computational design of auxotrophy-dependent microbial biosensors for combinatorial metabolic engineering experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools).

A systems biology approach uncovers cellular strategies used by Methylobacterium extorquens AM1 during the switch from multi- to single-carbon growth

Background

When organisms experience environmental change, how does their metabolic network reset and adapt to the new condition? Methylobacterium extorquens is a bacterium capable of growth on both multi- and single-carbon compounds. These different modes of growth utilize dramatically different central metabolic pathways with limited pathway overlap.

Methodology/Principal Findings

This study focused on the mechanisms of metabolic adaptation occurring during the transition from succinate growth (predicted to be energy-limited) to methanol growth (predicted to be reducing-power-limited), analyzing changes in carbon flux, gene expression, metabolites and enzymatic activities over time. Initially, cells experienced metabolic imbalance with excretion of metabolites, changes in nucleotide levels and cessation of cell growth. Though assimilatory pathways were induced rapidly, a transient block in carbon flow to biomass synthesis occurred, and enzymatic assays suggested methylene tetrahydrofolate dehydrogenase as one control point. This “downstream priming” mechanism ensures that significant carbon flux through these pathways does not occur until they are fully induced, precluding the buildup of toxic intermediates. Most metabolites that are required for growth on both carbon sources did not change significantly, even though transcripts and enzymatic activities required for their production changed radically, underscoring the concept of metabolic setpoints.

Conclusions/Significance

This multi-level approach has resulted in new insights into the metabolic strategies carried out to effect this shift between two dramatically different modes of growth and identified a number of potential flux control and regulatory check points as a further step toward understanding metabolic adaptation and the cellular strategies employed to maintain metabolic setpoints.

Environments that induce synthetic microbial ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.

Methanol assimilation in Methylobacterium extorquens AM1: demonstration of all enzymes and their regulation

Background

Methylobacterium extorquens AM1 is an aerobic facultative methylotrophic α-proteobacterium that can use reduced one-carbon compounds such as methanol, but also multi-carbon substrates like acetate (C₂) or succinate (C₄) as sole carbon and energy source. The organism has gained interest as future biotechnological production platform based on methanol as feedstock.

Methodology/Principal Findings

We present a comprehensive study of all postulated enzymes for the assimilation of methanol and their regulation in response to the carbon source. Formaldehyde, which is derived from methanol oxidation, is assimilated via the serine cycle, which starts with glyoxylate and forms acetyl-CoA. Acetyl-CoA is assimilated via the proposed ethylmalonyl-CoA pathway, which thereby regenerates glyoxylate. To further the understanding of the central carbon metabolism we identified and quantified all enzymes of the pathways involved in methanol assimilation. We observed a strict differential regulation of their activity level depending on whether C₁, C₂ or C₄ compounds are used. The enzymes, which are specifically required for the utilization of the individual substrates, were several-fold up-regulated and those not required were down-regulated. The enzymes of the ethylmalonyl-CoA pathway showed specific activities, which were higher than the calculated minimal values that can account for the observed growth rate. Yet, some enzymes of the serine cycle, notably its first and last enzymes serine hydroxymethyl transferase and malate thiokinase, exhibit much lower values and probably are rate limiting during methylotrophic growth. We identified the natural C₁ carrying coenzyme as tetrahydropteroyl-tetraglutamate rather than tetrahydrofolate.

Conclusion/Significance

This study provides the first complete picture of the enzymes required for methanol assimilation, the regulation of their activity levels in response to the growth substrate, and the identification of potential growth limiting steps.

Expressed genome of Methylobacillus flagellatus as defined through comprehensive proteomics and new insights into methylotrophy

In recent years, techniques have been developed and perfected for high-throughput identification of proteins and their accurate partial sequencing by shotgun nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS), making it feasible to assess global protein expression profiles in organisms with sequenced genomes. We implemented comprehensive proteomics to assess the expressed portion of the genome of Methylobacillus flagellatus during methylotrophic growth. We detected a total of 1,671 proteins (64% of the inferred proteome), including all the predicted essential proteins. Nonrandom patterns observed with the nondetectable proteins appeared to correspond to silent genomic islands, as inferred through functional profiling and genome localization. The protein contents in methylamine- and methanol-grown cells showed a significant overlap, confirming the commonality of methylotrophic metabolism downstream of the primary oxidation reactions. The new insights into methylotrophy include detection of proteins for the N-methylglutamate methylamine oxidation pathway that appears to be auxiliary and detection of two alternative enzymes for both the 6-phosphogluconate dehydrogenase reaction (GndA and GndB) and the formate dehydrogenase reaction (FDH1 and FDH4). Mutant analysis revealed that GndA and FDH4 are crucial for the organism's fitness, while GndB and FDH1 are auxiliary.

Metabolic analysis of the removal of formic acid by unacclimated activated sludge

This paper investigates the removal of formic acid by unacclimated biomass from a municipal activated sludge wastewater treatment plant. The biomass was initially able to remove formic acid, but its removal rate and Oxygen Uptake Rate (OUR) decreased with time, until formic acid removal stopped before the formic acid had been exhausted. Formaldehyde was removed in a similar way, whereas the same biomass was simultaneously able to grow and store PHAs when acetic acid was used as substrate. Batch tests with glycine and (13)C NMR analysis were performed, showing that unacclimated biomass was not able to synthesize all the metabolic intermediates from formic acid alone. At least glycine needed to be externally supplemented, in order to activate the serine synthesis pathway. A small amount of formic acid removal in the absence of growth was also possible through formaldehyde formation and its further conversion to formalin (1,2-formaldehyde dimer), whereas no PHAs were formed.

Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators

Important efforts are being done to systematically identify the relevant pathways in a metabolic network. Unsurprisingly, there is not a unique set of network-based pathways to be tagged as relevant, and at least four related concepts have been proposed: extreme currents, elementary modes, extreme pathways, and minimal generators. Basically, there are two properties that these sets of pathways can hold: they can generate the flux space--if every feasible flux distribution can be represented as a nonnegative combination of flux through them--or they can comprise all the nondecomposable pathways in the network. The four concepts fulfill the first property, but only the elementary modes fulfill the second one. This subtle difference has been a source of errors and misunderstandings. This paper attempts to clarify the intricate relationship between the network-based pathways performing a comparison among them.

Alternative route for glyoxylate consumption during growth on two-carbon compounds by Methylobacterium extorquens AM1

Methylobacterium extorquens AM1 is a facultative methylotroph capable of growth on both single-carbon and multicarbon compounds. Mutants defective in a pathway involved in converting acetyl-coenzyme A (CoA) to glyoxylate (the ethylmalonyl-CoA pathway) are unable to grow on both C(1) and C(2) compounds, showing that both modes of growth have this pathway in common. However, growth on C(2) compounds via the ethylmalonyl-CoA pathway should require glyoxylate consumption via malate synthase, but a mutant lacking malyl-CoA/beta-methylmalyl-CoA lyase activity (MclA1) that is assumed to be responsible for malate synthase activity still grows on C(2) compounds. Since glyoxylate is toxic to this bacterium, it seemed likely that a system is in place to keep it from accumulating. In this study, we have addressed this question and have shown by microarray analysis, mutant analysis, metabolite measurements, and (13)C-labeling experiments that M. extorquens AM1 contains an additional malyl-CoA/beta-methylmalyl-CoA lyase (MclA2) that appears to take part in glyoxylate metabolism during growth on C(2) compounds. In addition, an alternative pathway appears to be responsible for consuming part of the glyoxylate, converting it to glycine, methylene-H(4)F, and serine. Mutants lacking either pathway have a partial defect for growth on ethylamine, while mutants lacking both pathways are unable to grow appreciably on ethylamine. Our results suggest that the malate synthase reaction is a bottleneck for growth on C(2) compounds by this bacterium, which is partially alleviated by this alternative route for glyoxylate consumption. This strategy of multiple enzymes/pathways for the consumption of a toxic intermediate reflects the metabolic versatility of this facultative methylotroph and is a model for other metabolic networks involving high flux through toxic intermediates.

In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'

MOTIVATION

In their article entitled 'Can sugars be produced from fatty acids? A test case for pathway analysis tools' de Figueiredo and co-authors assess the performance of three pathway prediction tools (METATOOL, PathFinding and Pathway Hunter Tool) using the synthesis of glucose-6-phosphate (G6P) from acetyl-CoA in humans as a test case. We think that this article is biased for three reasons: (i) the metabolic networks used as input for the respective tools were of very different sizes; (ii) the 'assessment' is restricted to two study cases; (iii) developers are inherently more skilled to use their own tools than those developed by other people. We extended the analyses led by de Figueiredo and clearly show that the apparent superior performance of their tool (METATOOL) is partly due to the differences in input network sizes. We also see a conceptual problem in the comparison of tools that serve different purposes. In our opinion, metabolic path finding and elementary mode analysis are answering different biological questions, and should be considered as complementary rather than competitive approaches.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Increasing the accuracy of mass isotopomer analysis through calibration curves constructed using biologically synthesized compounds

Mass isotopomer analysis is an important technique to measure the production and flow of metabolites in living cells, tissues, and organisms. This technique depends on accurate quantifications of different mass isotopomers using mass spectrometry. Constructing calibration curves using standard samples is the most universal approach to convert raw mass spectrometry measurements into quantitative distributions of mass isotopomers. Calibration curve approach has been, however, of very limited use in comprehensive analyses of biological systems, mainly suffering from the lack of extensive range of standard samples with accurately known isotopic enrichment. Here, we present a biological method capable of synthesizing specifically labeled amino acids. These amino acids have well-determined and estimable mass isotopomer distributions and thus can serve as standard samples. In this method, the bacterium strain Methylobacterium salsuginis sp. nov. was cultivated with partially 13C-labeled methanol as the only carbon source to produce 13C-enriched compounds. We show that the mass isotopomer distributions of the various biosynthesized amino acids are well determined and can be reasonably estimated based on proposed binomial approximation if the labeling state of the biomass reached an isotopic steady state. The interference of intramolecular inhomogeneity of 13C isotope abundances caused by biological isotope fractionation was eliminated by estimating average 13C isotope abundance. Further, the predictions are tested experimentally by mass spectrometry (MS) spectra of the labeled glycine, alanine, and aspartic acid. Most of the error in mass spectrometry measurements was less than 0.74 mol% in the test case, significantly reduced as compared with uncalibrated results, and this error is expected to be less than 0.4 mol% in real experiment as revealed by theoretical analysis.

Asymmetric, bimodal trade-offs during adaptation of Methylobacterium to distinct growth substrates

Trade-offs between selected and nonselected environments are often assumed to exist during adaptation. This phenomenon is prevalent in microbial metabolism, where many organisms have come to specialize on a narrow breadth of substrates. One well-studied example is methylotrophic bacteria that can use single-carbon (C(1)) compounds as their sole source of carbon and energy, but generally use few, if any, multi-C compounds. Here, we use adaptation of experimental populations of the model methylotroph, Methylobacterium extorquens AM1, to C(1) (methanol) or multi-C (succinate) compounds to investigate specialization and trade-offs between these two metabolic lifestyles. We found a general trend toward trade-offs during adaptation to succinate, but this was neither universal nor showed a quantitative relationship with the extent of adaptation. After 1500 generations, succinate-evolved strains had a remarkably bimodal distribution of fitness values on methanol: either an improvement comparable to the strains adapted on methanol or the complete loss of the ability to grow on C(1) compounds. In contrast, adaptation to methanol resulted in no such trade-offs. Based on the substantial, asymmetric loss of C(1) growth during growth on succinate, we suggest that the long-term maintenance of C(1) metabolism across the genus Methylobacterium requires relatively frequent use of C(1) compounds to prevent rapid loss.

Population heterogeneity in Methylobacterium extorquens AM1

Heterogeneity of cells within exponentially growing populations was addressed in a bacterium, the facultative methylotroph Methylobacterium extorquens AM1. A transcriptional fusion between a well-characterized methanol-inducible promoter (P(mxaF)) and gfp(uv) was used with flow cytometry to analyse the distribution of gene expression in populations grown on either succinate or methanol, correlated with forward scatter as a measure of cell size. These cell populations were found to consist of three major subpopulations defined by cells that were actively growing and dividing, newly divided, and non-dividing. Through the use of flow cytometry, it was demonstrated that a significant percentage of the total population did not respond to carbon shift. In addition, these experiments demonstrated that a small subset of the total population was significantly brighter than the rest of the population and dominated fluorimetry data. These results were corroborated with a continuous flow-through system and laser scanning microscopy, confirming that subpopulations, not discernible in the population average, dominate population response. These results demonstrate that the combination of flow cytometry and microscopic single-cell analysis can be effectively used to determine the dynamics of subpopulations in population response. In addition, they support the concept that physiological diversity in isogenic populations can poise some proportion of the population to respond appropriately to changing conditions.

Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction

BACKGROUND

Infections with Salmonella cause significant morbidity and mortality worldwide. Replication of Salmonella typhimurium inside its host cell is a model system for studying the pathogenesis of intracellular bacterial infections. Genome-scale modeling of bacterial metabolic networks provides a powerful tool to identify and analyze pathways required for successful intracellular replication during host-pathogen interaction.

RESULTS

We have developed and validated a genome-scale metabolic network of Salmonella typhimurium LT2 (iRR1083). This model accounts for 1,083 genes that encode proteins catalyzing 1,087 unique metabolic and transport reactions in the bacterium. We employed flux balance analysis and in silico gene essentiality analysis to investigate growth under a wide range of conditions that mimic in vitro and host cell environments. Gene expression profiling of S. typhimurium isolated from macrophage cell lines was used to constrain the model to predict metabolic pathways that are likely to be operational during infection.

CONCLUSION

Our analysis suggests that there is a robust minimal set of metabolic pathways that is required for successful replication of Salmonella inside the host cell. This model also serves as platform for the integration of high-throughput data. Its computational power allows identification of networked metabolic pathways and generation of hypotheses about metabolism during infection, which might be used for the rational design of novel antibiotics or vaccine strains.

Demonstration of the ethylmalonyl-CoA pathway by using 13C metabolomics

The assimilation of one-carbon (C1) compounds, such as methanol, by serine cycle methylotrophs requires the continuous regeneration of glyoxylate. Instead of the glyoxylate cycle, this process is achieved by a not yet established pathway where CoA thioesters are known to play a key role. We applied state-of-the-art metabolomics and (13)C metabolomics strategies to demonstrate how glyoxylate is generated during methylotrophic growth in the isocitrate lyase-negative methylotroph Methylobacterium extorquens AM1. High-resolution mass spectrometry showed the presence of CoA thioesters specific to the recently proposed ethylmalonyl-CoA pathway. The operation of this pathway was demonstrated by short-term (13)C-labeling experiments, which allowed determination of the sequence of reactions from the order of label incorporation into the different CoA derivatives. Analysis of (13)C positional enrichment in glycine by NMR was consistent with the predicted labeling pattern as a result of the operation of the ethylmalonyl-CoA pathway and the unique operation of the latter for glyoxylate generation during growth on methanol. The results also revealed that 2 molecules of glyoxylate were regenerated in this process. This work provides a complete pathway for methanol assimilation in the model methylotroph M. extorquens AM1 and represents an important step toward the determination of the overall topology of its metabolic network. The operation of the ethylmalonyl-CoA pathway in M. extorquens AM1 has major implications for the physiology of these methylotrophs and their role in nature, and it also provides a common ground for C1 and C2 compound assimilation in isocitrate lyase-negative bacteria.

Genome-scale models of bacterial metabolism: reconstruction and applications

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.

Flux balance analysis of barley seeds: a computational approach to study systemic properties of central metabolism

The accumulation of storage compounds is an important aspect of cereal seed metabolism. Due to the agronomical importance of the storage reserves of starch, protein, and oil, the understanding of storage metabolism is of scientific interest, with practical applications in agronomy and plant breeding. To get insight into storage patterning in developing cereal seed in response to environmental and genetic perturbation, a computational analysis of seed metabolism was performed. A metabolic network of primary metabolism in the developing endosperm of barley (Hordeum vulgare), a model plant for temperate cereals, was constructed that includes 257 biochemical and transport reactions across four different compartments. The model was subjected to flux balance analysis to study grain yield and metabolic flux distributions in response to oxygen depletion and enzyme deletion. In general, the simulation results were found to be in good agreement with the main biochemical properties of barley seed storage metabolism. The predicted growth rate and the active metabolic pathway patterns under anoxic, hypoxic, and aerobic conditions predicted by the model were in accordance with published experimental results. In addition, the model predictions gave insight into the potential role of inorganic pyrophosphate metabolism to maintain seed metabolism under oxygen deprivation.

Methanol-based industrial biotechnology: current status and future perspectives of methylotrophic bacteria

Methanol is one of the building blocks in the chemical industry and can be synthesized either from petrochemical or renewable resources, such as biogas. Bioprocess technology with methylotrophic bacteria is well established, as illustrated by large-scale single-cell protein production in the past. During recent years, the first genomes of methylotrophs have been sequenced and significant progress in elucidating their metabolism has been made. In addition, the tool set for genetic engineering of methylotrophic bacteria has expanded greatly and strategies to produce fine and bulk chemicals with methylotrophs have been described. This review highlights the potential of these bacteria for the development of economically competitive bioprocesses based on methanol as an alternative carbon source, bringing together biological, technical and economic considerations.

Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism

Elementary mode analysis is a useful metabolic pathway analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering.

Comprehensive proteomics of Methylobacterium extorquens AM1 metabolism under single carbon and nonmethylotrophic conditions

In order to validate a gel free quantitative proteomics assay for the model methylotrophic bacterium Methylobacterium extorquens AM1, we examined the M. extorquens AM1 proteome under single carbon (methanol) and multicarbon (succinate) growth, conditions that have been studied for decades and for which extensive corroborative data have been compiled. In total, 4447 proteins from a database containing 7556 putative ORFs from M. extorquens AM1 could be identified with two or more peptide sequences, corresponding to a qualitative proteome coverage of 58%. Statistically significant nonzero (log(2) scale) differential abundance ratios of methanol/succinate could be detected for 317 proteins using summed ion intensity measurements and 585 proteins using spectral counting, at a q-value cut-off of 0.01, a measure of false discovery rate. The results were compared to recent microarray studies performed under equivalent chemostat conditions. The M. extorquens AM1 studies demonstrated the feasibility of scaling up the multidimensional capillary HPLC MS/MS approach to a prokaryotic organism with a proteome more than three times the size of microbes we have investigated previously, while maintaining a high degree of proteome coverage and reliable quantitative abundance ratios.

Enhanced PHB production and scale up studies using cheese whey in fed batch culture of Methylobacterium sp. ZP24

Methylobacterium sp. ZP24 produced polyhydroxybutyrate (PHB) from disaccharides like lactose and sucrose. As Methylobacterium sp. ZP24 showed growth associated PHB production, an intermittent feeding strategy having lactose and ammonium sulfate at varying concentration was used towards reaching higher yield of the polymer. About 1.5-fold increase in PHB production was obtained by this intermittent feeding strategy. Further increase in PHB production by 0.8-fold could be achieved by limiting the dissolved oxygen (DO) levels in the fermenter. The decreased DO is thought to increase flux of acetyl CO-A towards PHB accumulation over TCA cycle. Cheese whey, a dairy waste product and being a rich source of utilizable sugar and other nutrients, when used in the bioreactor as a main substrate replacing the lactose, led to further increase in the PHB production by 2.5-fold. A total of 4.58-fold increase in the PHB production was obtained using limiting DO conditions with processed cheese whey supplemented with ammonium sulfate in fed batch culture of Methylobacterium sp. ZP24. The present investigation therefore reflects on the possibility of developing a cheap biological route for production of green thermoplastics.

Production of an insecticidal crystal protein from Bacillus thuringiensis by the methylotroph Methylobacterium extorquens

The Cry1Aa protein from Bacillus thuringiensis is an insecticidal protein that is highly active against several species of Lepidoptera. We cloned and expressed the cry1Aa gene in a plant-colonizing methylotroph, Methylobacterium extorquens, under the control of the strong M. extorquens AM1 methanol dehydrogenase promoter, P(mxaF). Transmission electron microscopy revealed characteristic bipyramidal intracellular delta-endotoxin crystals similar to the crystalline inclusions formed by B. thuringiensis. Both the protoxin protein and the activated toxin were visualized by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western analysis. In single-dose assays of the recombinant against the silkworm, Bombyx mori, both whole cells and cell lysates caused rapid feeding inhibition followed by mortality. The biomass and growth rate of recombinant cells in shake flask culture were similar to those of the wild-type strain, indicating a lack of fitness cost to the recombinant under controlled culture conditions. Recombinant Cry1Aa was expressed at a level of 4.5% of total M. extorquens cell protein. The potential benefits of modifying M. extorquens to deliver insecticidal Cry proteins for crop and forest protection are discussed.

Formate as the main branch point for methylotrophic metabolism in Methylobacterium extorquens AM1

In serine cycle methylotrophs, methylene tetrahydrofolate (H4F) is the entry point of reduced one-carbon compounds into the serine cycle for carbon assimilation during methylotrophic metabolism. In these bacteria, two routes are possible for generating methylene H4F from formaldehyde during methylotrophic growth: one involving the reaction of formaldehyde with H4F to generate methylene H4F and the other involving conversion of formaldehyde to formate via methylene tetrahydromethanopterin-dependent enzymes and conversion of formate to methylene H4F via H4F-dependent enzymes. Evidence has suggested that the direct condensation reaction is the main source of methylene H4F during methylotrophic metabolism. However, mutants lacking enzymes that interconvert methylene H4F and formate are unable to grow on methanol, suggesting that this route for methylene H4F synthesis should have a significant role in biomass production during methylotrophic metabolism. This problem was investigated in Methylobacterium extorquens AM1. Evidence was obtained suggesting that the existing deuterium assay might overestimate the flux through the direct condensation reaction. To test this possibility, it was shown that only minor assimilation into biomass occurred in mutants lacking the methylene H4F synthesis pathway through formate. These results suggested that the methylene H4F synthesis pathway through formate dominates assimilatory flux. A revised kinetic model was used to validate this possibility, showing that physiologically plausible parameters in this model can account for the metabolic fluxes observed in vivo. These results all support the suggestion that formate, not formaldehyde, is the main branch point for methylotrophic metabolism in M. extorquens AM1.