Complete genome sequence,metabolic model construction and phenotypic characterization of Geobacillus LC300, an extremely thermophilic,fast growing,xylose-utilizing bacterium

We have isolated a new extremely thermophilic fast-growing Geobacillus strain that can efficiently utilize xylose, glucose, mannose and galactose for cell growth. When grown aerobically at 72 °C, Geobacillus LC300 has a growth rate of 2.15 h⁻¹ on glucose and 1.52 h⁻¹ on xylose (doubling time less than 30 min). The corresponding specific glucose and xylose utilization rates are 5.55 g/g/h and 5.24 g/g/h, respectively. As such, Geobacillus LC300 grows 3-times faster than E. coli on glucose and xylose, and has a specific xylose utilization rate that is 3-times higher than the best metabolically engineered organism to date. To gain more insight into the metabolism of Geobacillus LC300 its genome was sequenced using PacBio׳s RS II single-molecule real-time (SMRT) sequencing platform and annotated using the RAST server. Based on the genome annotation and the measured biomass composition a core metabolic network model was constructed. To further demonstrate the biotechnological potential of this organism, Geobacillus LC300 was grown to high cell-densities in a fed-batch culture, where cells maintained a high xylose utilization rate under low dissolved oxygen concentrations. All of these characteristics make Geobacillus LC300 an attractive host for future metabolic engineering and biotechnology applications.     

13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252

Thermophilic organisms are being increasingly investigated and applied in metabolic engineering and biotechnology. The distinct metabolic and physiological characteristics of thermophiles, including broad substrate range and high uptake rates, coupled with recent advances in genetic tool development, present unique opportunities for strain engineering. However, poor understanding of the cellular physiology and metabolism of thermophiles has limited the application of systems biology and metabolic engineering tools to these organisms. To address this concern, we applied high resolution ¹³C metabolic flux analysis to quantify fluxes for three divergent extremely thermophilic bacteria from separate phyla: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252. We performed 18 parallel labeling experiments, using all singly labeled glucose tracers for each strain, reconstructed and validated metabolic network models, measured biomass composition, and quantified precise metabolic fluxes for each organism. In the process, we resolved many uncertainties regarding gaps in pathway reconstructions and elucidated how these organisms maintain redox balance and generate energy. Overall, we found that the metabolisms of the three thermophiles were highly distinct, suggesting that adaptation to growth at high temperatures did not favor any particular set of metabolic pathways. All three strains relied heavily on glycolysis and TCA cycle to generate key cellular precursors and cofactors. None of the investigated organisms utilized the Entner-Doudoroff pathway and only one strain had an active oxidative pentose phosphate pathway. Taken together, the results from this study provide a solid foundation for future model building and engineering efforts with these and related thermophiles.     

Co-utilization of glucose and xylose by evolved Thermus thermophilus LC113 strain elucidated by 13C metabolic flux analysis and whole genome sequencing

We evolved Thermus thermophilus to efficiently co-utilize glucose and xylose, the two most abundant sugars in lignocellulosic biomass, at high temperatures without carbon catabolite repression. To generate the strain, T. thermophilus HB8 was first evolved on glucose to improve its growth characteristics, followed by evolution on xylose. The resulting strain, T. thermophilus LC113, was characterized in growth studies, by whole genome sequencing, and ¹³C-metabolic flux analysis (¹³C-MFA) with [1,6-¹³C]glucose, [5-¹³C]xylose, and [1,6-¹³C]glucose+[5-¹³C]xylose as isotopic tracers. Compared to the starting strain, the evolved strain had an increased growth rate (~2-fold), increased biomass yield, increased tolerance to high temperatures up to 90 °C, and gained the ability to grow on xylose in minimal medium. At the optimal growth temperature of 81 °C, the maximum growth rate on glucose and xylose was 0.44 and 0.46 h⁻¹, respectively. In medium containing glucose and xylose the strain efficiently co-utilized the two sugars. ¹³C-MFA results provided insights into the metabolism of T. thermophilus LC113 that allows efficient co-utilization of glucose and xylose. Specifically, ¹³C-MFA revealed that metabolic fluxes in the upper part of metabolism adjust flexibly to sugar availability, while fluxes in the lower part of metabolism remain relatively constant. Whole genome sequence analysis revealed two large structural changes that can help explain the physiology of the evolved strain: a duplication of a chromosome region that contains many sugar transporters, and a 5x multiplication of a region on the pVV8 plasmid that contains xylose isomerase and xylulokinase genes, the first two enzymes of xylose catabolism. Taken together, ¹³C-MFA and genome sequence analysis provided complementary insights into the physiology of the evolved strain.     

COMPLETE-MFA: Complementary parallel labeling experiments technique for metabolic flux analysis

We have developed a novel approach for measuring highly accurate and precise metabolic fluxes in living cells, termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. The COMPLETE-MFA method is based on combined analysis of multiple isotopic labeling experiments, where the synergy of using complementary tracers greatly improves the precision of estimated fluxes. In this work, we demonstrate the COMPLETE-MFA approach using all singly labeled glucose tracers, [1-¹³C], [2-¹³C], [3-¹³C], [4-¹³C], [5-¹³C], and [6-¹³C]glucose to determine precise metabolic fluxes for wild-type Escherichia coli. Cells were grown in six parallel cultures on defined medium with glucose as the only carbon source. Mass isotopomers of biomass amino acids were measured by gas chromatography–mass spectrometry (GC–MS). The data from all six experiments were then fitted simultaneously to a single flux model to determine accurate intracellular fluxes. We obtained a statistically acceptable fit with more than 300 redundant measurements. The estimated flux map is the most precise flux result obtained thus far for E. coli cells. To our knowledge, this is the first time that six isotopic labeling experiments have been successfully integrated for high-resolution ¹³C-flux analysis.     

Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis

Glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass. While aerobic glucose metabolism is relatively well understood in E. coli, until now there have been only a handful of studies focused on anaerobic glucose metabolism and no ¹³C-flux studies on xylose metabolism. In the absence of experimentally validated flux maps, constraint-based approaches such as MOMA and RELATCH cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap in current understanding by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, using recent state-of-the-art techniques in ¹³C metabolic flux analysis (¹³C-MFA). Specifically, we quantified precise metabolic fluxes for each condition by performing parallel labeling experiments and analyzing the data through integrated ¹³C-MFA using the optimal tracers [1,2-¹³C]glucose, [1,6-¹³C]glucose, [1,2-¹³C]xylose and [5-¹³C]xylose. We also quantified changes in biomass composition and confirmed turnover of macromolecules by applying [U-¹³C]glucose and [U-¹³C]xylose tracers. We demonstrated that under anaerobic growth conditions there is significant turnover of lipids and that a significant portion of CO₂ originates from biomass turnover. Using knockout strains, we also demonstrated that β-oxidation is critical for anaerobic growth on xylose. Quantitative analysis of co-factor balances (NADH/FADH₂, NADPH, and ATP) for different growth conditions provided new insights regarding the interplay of energy and redox metabolism and the impact on E. coli cell physiology.     

Metabolic flux ratio analysis by parallel 13C labeling of isoprenoid biosynthesis in Rhodobacter sphaeroides

Metabolic engineering for increased isoprenoid production often benefits from the simultaneous expression of the two naturally available isoprenoid metabolic routes, namely the 2-methyl-D-erythritol 4-phosphate (MEP) pathway and the mevalonate (MVA) pathway. Quantification of the contribution of these pathways to the overall isoprenoid production can help to obtain a better understanding of the metabolism within a microbial cell factory. Such type of investigation can benefit from ¹³C metabolic flux ratio studies. Here, we designed a method based on parallel labeling experiments (PLEs), using [1-¹³C]- and [4-¹³C]glucose as tracers to quantify the metabolic flux ratios in the glycolytic and isoprenoid pathways. By just analyzing a reporter isoprenoid molecule and employing only four equations, we could describe the metabolism involved from substrate catabolism to product formation. These equations infer ¹³C atom incorporation into the universal isoprenoid building blocks, isopentenyl-pyrophosphate (IPP) and dimethylallyl-pyrophosphate (DMAPP). Therefore, this renders the method applicable to the study of any of isoprenoid of interest. As proof of principle, we applied it to study amorpha-4,11-diene biosynthesis in the bacterium Rhodobacter sphaeroides. We confirmed that in this species the Entner-Doudoroff pathway is the major pathway for glucose catabolism, while the Embden-Meyerhof-Parnas pathway contributes to a lesser extent. Additionally, we demonstrated that co-expression of the MEP and MVA pathways caused a mutual enhancement of their metabolic flux capacity. Surprisingly, we also observed that the isoprenoid flux ratio remains constant under exponential growth conditions, independently from the expression level of the MVA pathway. Apart from proposing and applying a tool for studying isoprenoid biosynthesis within a microbial cell factory, our work reveals important insights from the co-expression of MEP and MVA pathways, including the existence of a yet unclear interaction between them.     

Metabolism of the fast-growing bacterium Vibrio natriegens elucidated by 13C metabolic flux analysis

Vibrio natriegens is a fast-growing, non-pathogenic bacterium that is being considered as the next-generation workhorse for the biotechnology industry. However, little is known about the metabolism of this organism which is limiting our ability to apply rational metabolic engineering strategies. To address this critical gap in current knowledge, here we have performed a comprehensive analysis of V. natriegens metabolism. We constructed a detailed model of V. natriegens core metabolism, measured the biomass composition, and performed high-resolution ¹³C metabolic flux analysis (¹³C-MFA) to estimate intracellular fluxes using parallel labeling experiments with the optimal tracers [1,2−¹³C]glucose and [1,6−¹³C]glucose. During exponential growth in glucose minimal medium, V. natriegens had a growth rate of 1.70 1/h (doubling time of 24 min) and a glucose uptake rate of 3.90 g/g/h, which is more than two 2-fold faster than E. coli, although slower than the fast-growing thermophile Geobacillus LC300. ¹³C-MFA revealed that the core metabolism of V. natriegens is similar to that of E. coli, with the main difference being a 33% lower normalized flux through the oxidative pentose phosphate pathway. Quantitative analysis of co-factor balances provided additional insights into the energy and redox metabolism of V. natriegens. Taken together, the results presented in this study provide valuable new information about the physiology of V. natriegens and establish a solid foundation for future metabolic engineering efforts with this promising microorganism.     

Metabolic network reconstruction,growth characterization and 13C-metabolic flux analysis of the extremophile Thermus thermophilus HB8

Thermus thermophilus is an extremely thermophilic bacterium with significant biotechnological potential. In this work, we have characterized aerobic growth characteristics of T. thermophilus HB8 at temperatures between 50 and 85 °C, constructed a metabolic network model of its central carbon metabolism and validated the model using ¹³C-metabolic flux analysis (¹³C–MFA). First, cells were grown in batch cultures in custom constructed mini-bioreactors at different temperatures to determine optimal growth conditions. The optimal temperature for T. thermophilus grown on defined medium with glucose was 81 °C. The maximum growth rate was 0.25 h⁻¹. Between 50 and 81 °C the growth rate increased by 7-fold and the temperature dependence was described well by an Arrhenius model with an activation energy of 47 kJ/mol. Next, we performed a ¹³C-labeling experiment with [1,2-¹³C] glucose as the tracer and calculated intracellular metabolic fluxes using ¹³C–MFA. The results provided support for the constructed network model and highlighted several interesting characteristics of T. thermophilus metabolism. We found that T. thermophilus largely uses glycolysis and TCA cycle to produce biosynthetic precursors, ATP and reducing equivalents needed for cells growth. Consistent with its proposed metabolic network model, we did not detect any oxidative pentose phosphate pathway flux or Entner-Doudoroff pathway activity. The biomass precursors erythrose-4-phosphate and ribose-5-phosphate were produced via the non-oxidative pentose phosphate pathway, and largely via transketolase, with little contribution from transaldolase. The high biomass yield on glucose that was measured experimentally was also confirmed independently by ¹³C–MFA. The results presented here provide a solid foundation for future studies of T. thermophilus and its metabolic engineering applications.     

A guide to metabolic flux analysis in metabolic engineering: Methods,tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, “Metabolic fluxes and metabolic engineering” (Metabolic Engineering, 1: 1–11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.     

Evaluating (13)C enrichment data of free amino acids for precise metabolic flux analysis

Metabolic flux analysis using (13)C enrichment data of intracellular free amino acids (FAAs) can improve the time resolution of flux estimation compared to analysis of proteinogenic amino acid data owing to the faster turnover times of FAAs. The nature of the (13)C enrichment dynamics of FAAs remains obscure, however, especially with regard to its dependence on culture conditions, even though an understanding of dynamic behavior is important for precise metabolic flux estimation. In this study, we analyzed the (13)C enrichment dynamics of free and proteinogenic amino acids in a series of continuous culture experiments with Escherichia coli. The results indicated that the effect of protein degradation on the (13)C enrichment of FAAs was negligible under cellular growth conditions. Furthermore, they showed that the time scale necessary for (13)C enrichment dynamics of FAAs to reach a steady state depends on culture conditions such as oxygen uptake rate, which was likely due to different pool sizes of intracellular metabolites. The results demonstrate the importance of analyzing (13)C enrichment dynamics for the precise estimation of metabolic fluxes using FAA data.     

A priori analysis of metabolic flux identifiability from (13)C-labeling data

The (13)C-labeling technique was introduced in the field of metabolic engineering as a tool for determining fluxes that could not be found using the 'classical' method of flux balancing. An a priori flux identifiability analysis is required in order to determine whether a (13)C-labeling experiment allows the identification of all the fluxes. In this article, we propose a method for identifiability analysis that is based on the recently introduced 'cumomer' concept. The method improves upon previous identifiability methods in that it provides a way of systematically reducing the metabolic network on the basis of structural elements that constitute a network and to use the implicit function theorem to analytically determine whether the fluxes in the reduced network are theoretically identifiable for various types of real measurement data. Application of the method to a realistic flux identification problem shows both the potential of the method in yielding new, interesting conclusions regarding the identifiability and its practical limitations that are caused by the fact that symbolic calculations grow fast with the dimension of the studied system.     

13C metabolic flux analysis clarifies distinct metabolic phenotypes of cancer cell spheroid mimicking tumor hypoxia

Cancer cells adapt their intracellular energy metabolism to the oxygen-deprived tumor microenvironment (TME) to ensure tumor progression. This adaptive mechanism has focused attention on the metabolic phenotypes of tumor cells under hypoxic TME for developing novel cancer therapies. Although widely used monolayer (2D) culture does not fully reflect in vivo hypoxic TME, spheroid (3D) culture can produce a milieu similar to the TME in vivo. However, how different metabolic phenotypes are expressed in 3D cultures mimicking tumor hypoxia compared with 2D cultures under hypoxia remains unclear. To address this issue, we investigated the metabolic phenotypes of 2D- and 3D-cultured cancer cells by ¹³C-metabolic flux analysis (¹³C-MFA). Principal component analysis of ¹³C mass isotopomer distributions clearly demonstrated distinct metabolic phenotypes of 3D-cultured cells. ¹³C-MFA clarified that 3D culture significantly upregulated pyruvate carboxylase flux in line with the pyruvate carboxylase protein expression level. On the other hand, 3D culture downregulated glutaminolytic flux. Consistent with our findings, 3D-cultured cells are more resistant to a glutaminase inhibitor than 2D-cultured cells. This study suggests the importance of considering the metabolic characteristics of the particular in vitro model used for research on cancer metabolism.     

Bio-based succinate from sucrose: High-resolution 13C metabolic flux analysis and metabolic engineering of the rumen bacterium Basfia succiniciproducens

Succinic acid is a platform chemical of recognized industrial value and accordingly faces a continuous challenge to enable manufacturing from most attractive raw materials. It is mainly produced from glucose, using microbial fermentation. Here, we explore and optimize succinate production from sucrose, a globally applied substrate in biotechnology, using the rumen bacterium Basfia succiniciproducens DD1. As basis of the strain optimization, the yet unknown sucrose metabolism of the microbe was studied, using ¹³C metabolic flux analyses. When grown in batch culture on sucrose, the bacterium exhibited a high succinate yield of 1 mol mol⁻¹ and a by-product spectrum, which did not match the expected PTS-mediated sucrose catabolism. This led to the discovery of a fructokinase, involved in sucrose catabolism. The flux approach unraveled that the fructokinase and the fructose PTS both contribute to phosphorylation of the fructose part of sucrose. The contribution of the fructokinase reduces the undesired loss of the succinate precursor PEP into pyruvate and into pyruvate-derived by-products and enables increased succinate production, exclusively via the reductive TCA cycle branch. These findings were used to design superior producers. Mutants, which (i) overexpress the beneficial fructokinase, (II) lack the competing fructose PTS, and (iii) combine both traits, produce significantly more succinate. In a fed-batch process, B. succiniciproducens ΔfruA achieved a titer of 71 g L⁻¹ succinate and a yield of 2.5 mol mol⁻¹ from sucrose.     

Metabolic flux and metabolic network analysis of Penicillium chrysogenum using 2D [13C, 1H] COSY NMR measurements and cumulative bondomer simulation

At present two alternative methods are available for analyzing the fluxes in a metabolic network: (1) combining measurements of net conversion rates with a set of metabolite balances including the cofactor balances, or (2) leaving out the cofactor balances and fitting the resulting free fluxes to measured (13)C-labeling data. In this study these two approaches are applied to the fluxes in the glycolysis and pentose phosphate pathway of Penicillium chrysogenum growing on either ammonia or nitrate as the nitrogen source, which is expected to give different pentose phosphate pathway fluxes. The presented flux analyses are based on extensive sets of 2D [(13)C, (1)H] COSY data. A new concept is applied for simulation of this type of (13)C-labeling data: cumulative bondomer modeling. The outcomes of the (13)C-labeling based flux analysis substantially differ from those of the pure metabolite balancing approach. The fluxes that are determined using (13)C-labeling data are shown to be highly dependent on the chosen metabolic network. Extending the traditional nonoxidative pentose phosphate pathway with additional transketolase and transaldolase reactions, extending the glycolysis with a fructose 6-phosphate aldolase/dihydroxyacetone kinase reaction sequence or adding a phosphoenolpyruvate carboxykinase reaction to the model considerably improves the fit of the measured and the simulated NMR data. The results obtained using the extended version of the nonoxidative pentose phosphate pathway model show that the transketolase and transaldolase reactions need not be assumed reversible to get a good fit of the (13)C-labeling data. Strict statistical testing of the outcomes of (13)C-labeling based flux analysis using realistic measurement errors is demonstrated to be of prime importance for verifying the assumed metabolic model.     

13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling

¹³C metabolic flux analysis (¹³C-MFA) is a widely used tool for quantitative analysis of microbial and mammalian metabolism. Until now, ¹³C-MFA was based mainly on measurements of isotopic labeling of amino acids derived from hydrolyzed biomass proteins and isotopic labeling of extracted intracellular metabolites. Here, we demonstrate that isotopic labeling of glycogen and RNA, measured with gas chromatography-mass spectrometry (GC-MS), provides valuable additional information for ¹³C-MFA. Specifically, we demonstrate that isotopic labeling of glucose moiety of glycogen and ribose moiety of RNA greatly enhances resolution of metabolic fluxes in the upper part of metabolism; importantly, these measurements allow precise quantification of net and exchange fluxes in the pentose phosphate pathway. To demonstrate the practical importance of these measurements for ¹³C-MFA, we have used Escherichia coli as a model microbial system and CHO cells as a model mammalian system. Additionally, we have applied this approach to determine metabolic fluxes of glucose and xylose co-utilization in the E. coli ΔptsG mutant. The convenience of measuring glycogen and RNA, which are stable and abundant in microbial and mammalian cells, offers the following key advantages: reduced sample size, no quenching required, no extractions required, and GC-MS can be used instead of more costly LC-MS/MS techniques. Overall, the presented approach for ¹³C-MFA will have widespread applicability in metabolic engineering and biomedical research.     

A metabolic flux analysis to study the role of sucrose synthase in the regulation of the carbon partitioning in central metabolism in maize root tips

In order to understand the role of sucrose synthase (SuSy) in carbon partitioning, metabolic fluxes were analyzed in maize root tips of a double mutant of SuSy genes, sh1 sus1 and the corresponding wild type, W22. [U-¹⁴C]-glucose pulse labeling experiments permitted the quantification of unidirectional fluxes into sucrose, starch and cell wall polysaccharides. Isotopic steady-state labeling with [1-¹³C]-, [2-¹³C]- or [U-¹³C]-glucose followed by the quantification by ¹H-NMR and ¹³C-NMR of enrichments in carbohydrates and amino acids was also performed to determine 29 fluxes through central metabolism using computer-aided modeling. As a consequence of the suppression of SUS1 and SH1 isozymes, maize root tips diameter was significantly decreased and respiratory metabolism reduced by 30%. Our result clearly established that, in maize root tips, starch is produced from ADP-Glc synthesized in the plastid and not in the cytosol by sucrose synthase. Unexpectedly, the flux of cell wall synthesis was increased in the double mutant. This observation indicates that, in maize root tips, SH1 and SUS1 are not specific providers for cellulose biosynthesis.