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

Growth characteristics, redox potential changes and proton motive force generation in Thermus scotoductus K1 during growth on various carbon sources

The extremophile microorganism Thermus scotoductus primarily exhibits aerobic metabolism, though some strains are capable of anaerobic growth, utilizing diverse electron acceptors. We focused on the T. scotoductus K1 strain, exploring its aerobic growth and metabolism, responses to various carbon sources, and characterization of its bioenergetic and physiological properties. The strain grew on different carbon sources, depending on their concentration and the medium's pH, demonstrating adaptability to acidic environments (pH 6.0). It was shown that 4 g L-1 glucose inhibited the specific growth rate by approximately 4.8-fold and 5.6-fold compared to 1 g L-1 glucose at pH 8.5 and pH 6.0, respectively. However, this inhibition was not observed in the presence of fructose, galactose, lactose, and starch. Extracellular and intracellular pH variations were mainly alkalifying during growth. At pH 6.0, the membrane potential (ΔΨ) was lower for all carbon sources compared to pH 8.5. The proton motive force (Δp) was lower only during growth on lactose due to the difference in the transmembrane proton gradient (ΔpH). Moreover, at pH 6.0 during growth on lactose, a positive Δp was detected, indicating the cells' ability to employ a unique energy-conserving strategy. Taken together, these findings concluded that Thermus scotoductus K1 exhibits different growth and bioenergetic properties depending on the carbon source, which can be useful for biotechnological applications. These findings offer valuable insights into how bacterial cells function under high-temperature conditions, which is essential for applying bioenergetics knowledge in future biotechnological advancements.

Diversity and function of viral AMGs associated with DNA biosynthesis in the Napahai plateau wetland

Viruses play an important role in microbial community structure and biodiversity by lysing host cells, and can also affect host metabolic pathways by expressing auxiliary metabolic genes (AMGs). As a unique low-latitude, high-altitude seasonal plateau wetland in China, Napahai has high research value. However, studies on the genetic diversity of AMGs and viruses associated with DNA biosynthesis have not been reported. Based on metagenomics, with the phylogenetic tree, PCoA, and α diversity analysis, we found that three DNA biosynthesis-related viral AMGs (cobS, mazG, and purM) in the Napahai plateau wetland were rich in genetic diversity, uniqueness, and differences compared with other habitats and host sources. Through the KEGG metabolic pathway and metabolic flow analysis of Pseudomonas mandelii (SW-3) and phage (VSW-3), the AMGs (cobS, mazG, and purM) genes of the three related viruses involved in DNA biosynthesis were upregulated and their expression increased significantly. In general, we systematically described the genetic diversity of AMGs associated with DNA biosynthesis in plateau wetland ecosystems and clarified the contribution of viral AMGs in the Napahai plateau wetland to DNA biosynthesis, as well as the changes of metabolites and genes. It further expands the understanding of phage-host interactions, which is of great significance for further revealing the role of viral AMGs in the biological evolution and biogeochemical cycle of wetland ecosystems.

Insights into the rapid metabolism of Geobacillus sp. LC300: unraveling metabolic requirements and optimal growth conditions

This study investigated the metabolism of Geobacillus sp. LC300, a promising biorefinery host organism with high substrate utilization rates. A new defined medium was designed and tested that allows for exponential growth to elevated cell densities suitable for quantitative physiological studies. Screening of the metabolic requirements of G. sp. LC300 revealed prototrophy for all essential amino acids and most vitamins and only showed auxotrophy for vitamin B12 and biotin. The effect of temperature and pH on growth rate was investigated, adjusting the optimal growth temperature to several degrees lower than previously reported. Lastly, studies on carbon source utilization revealed a capability for fast growth on several common carbon sources, including monosaccharides, oligosaccharides, and polysaccharides, and the highest ever reported growth rate in defined medium on glucose (2.20 h-1) or glycerol (1.95 h-1). These findings provide a foundation for further exploration of G. sp. LC300's physiology and metabolic regulation, and its potential use in bioproduction processes.

Model-driven insights into the effects of temperature on metabolism

Temperature affects cellular processes at different spatiotemporal scales, and identifying the genetic and molecular mechanisms underlying temperature responses paves the way to develop approaches for mitigating the effects of future climate scenarios. A systems view of the effects of temperature on cellular physiology can be obtained by focusing on metabolism since: (i) its functions depend on transcription and translation and (ii) its outcomes support organisms' development, growth, and reproduction. Here we provide a systematic review of modelling efforts directed at investigating temperature effects on properties of single biochemical reactions, system-level traits, metabolic subsystems, and whole-cell metabolism across different prokaryotes and eukaryotes. We compare and contrast computational approaches and theories that facilitate modelling of temperature effects on key properties of enzymes and their consideration in constraint-based as well as kinetic models of metabolism. In addition, we provide a summary of insights from computational approaches, facilitating integration of omics data from temperature-modulated experiments with models of metabolic networks, and review the resulting biotechnological applications. Lastly, we provide a perspective on how different types of metabolic modelling can profit from developments in machine learning and models of different cellular layers to improve model-driven insights into the effects of temperature relevant for biotechnological applications.

Comprehensive Analysis of 13C6 Glucose Fate in the Hypoxia-Tolerant Blind Mole Rat Skin Fibroblasts

The bioenergetics of the vast majority of terrestrial mammals evolved to consuming glucose (Glc) for energy production under regular atmosphere (about 21% oxygen). However, some vertebrate species, such as aquatic turtles, seals, naked mole rat, and blind mole rat, Spalax, have adjusted their homeostasis to continuous function under severe hypoxic environment. The exploration of hypoxia-tolerant species metabolic strategies provides a better understanding of the adaptation to hypoxia. In this study, we compared Glc homeostasis in primary Spalax and rat skin cells under normoxic and hypoxic conditions. We used the targeted-metabolomics approach, utilizing liquid chromatography and mass spectrometry (LC-MS) to track the fate of heavy Glc carbons (¹³C₆ Glc), as well as other methodologies to assist the interpretation of the metabolic landscape, such as bioenergetics profiling, Western blotting, and gene expression analysis. The metabolic profile was recorded under steady-state (after 24 h) of the experiment. Glc-originated carbons were unequally distributed between the cytosolic and mitochondrial domains in Spalax cells compared to the rat. The cytosolic domain is dominant apparently due to the hypoxia-inducible factor-1 alpha (HIF-1α) mastering, since its level is higher under normoxia and hypoxia in Spalax cells. Consumed Glc in Spalax cells is utilized for the pentose phosphate pathway maintaining the NADPH pool, and is finally harbored as glutathione (GSH) and UDP-GlcNAc. The cytosolic domain in Spalax cells works in the semi-uncoupled mode that limits the consumed Glc-derived carbons flux to the tricarboxylic acid (TCA) cycle and reduces pyruvate delivery; however, it maintains the NAD⁺ pool via lactate dehydrogenase upregulation. Both normoxic and hypoxic mitochondrial homeostasis of Glc-originated carbons in Spalax are characterized by their massive cataplerotic flux along with the axis αKG→Glu→Pro→hydroxyproline (HPro). The product of collagen degradation, HPro, as well as free Pro are apparently involved in the bioenergetics of Spalax under both normoxia and hypoxia. The upregulation of 2-hydroxyglutarate production detected in Spalax cells may be involved in modulating the levels of HIF-1α. Collectively, these data suggest that Spalax cells utilize similar metabolic frame for both normoxia and hypoxia, where glucose metabolism is switched from oxidative pathways (conversion of pyruvate to Acetyl-CoA and further TCA cycle processes) to (i) pentose phosphate pathway, (ii) lactate production, and (iii) cataplerotic pathways leading to hexosamine, GSH, and HPro production.

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content

In this study, six bacterial isolates with variable GC, including Escherichia coli as mesophilic reference strain, were selected to compare hybrid assembly strategies based on next-generation sequencing (NGS) of short reads, single-tube long-fragment reads (stLFR) sequencing, and Oxford Nanopore Technologies (ONT) sequencing platforms. We obtained the complete genomes using the hybrid assembler Unicycler based on the NGS and ONT reads; others were de novo assembled using NGS, stLFR, and ONT reads by using different strategies. The contiguity, accuracy, completeness, sequencing costs, and DNA material requirements of the investigated strategies were compared systematically. Although all sequencing data could be assembled into accurate whole-genome sequences, the stLFR sequencing data yield a scaffold with more contiguity with more completeness of gene function than NGS sequencing assemblies. Our research provides a low-cost chromosome-level genome assembly strategy for large-scale sequencing of extremophile genomes with different GC contents.

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.

Hyperthermophilic composting reduces nitrogen loss via inhibiting ammonifiers and enhancing nitrogenous humic substance formation

Composting is an efficient and economic approach used to convert organic waste into organic fertilizers. However, the substantial nitrogen loss during the composting process is one of the major disadvantages of conventional thermophilic composting (cTC). Here, we demonstrated for the first time that hyperthermophilic composting (hTC) was able to mitigate nitrogen loss by 40.9% compared to cTC after 44 days of composting in a full-scale plant. Results demonstrate a decrease in NH₃ volatilization (52.4%), together with an inhibitory effect on protease (19.4-87.5%) and urease (9.1-75.2%) enzyme activities and the ammonification rate (5.2-80.1%) for hTC. Additionally, this study found that hTC could accelerate the humification process, thereby enhancing the formation of the recalcitrant nitrogen reservoir (mainly in the form of nitrogenous humic substances) and reducing the substrate for ammonification reactions. These findings suggest that hTC can significantly reduce nitrogen loss and provide insights into the role of humic substances in nitrogen retention in composting systems.

High-resolution 13C metabolic flux analysis

Precise quantification of metabolic pathway fluxes in biological systems is of major importance in guiding efforts in metabolic engineering, biotechnology, microbiology, human health, and cell culture. ¹³C metabolic flux analysis (¹³C-MFA) is the predominant technique used for determining intracellular fluxes. Here, we present a protocol for ¹³C-MFA that incorporates recent advances in parallel labeling experiments, isotopic labeling measurements, and statistical analysis, as well as best practices developed through decades of experience. Experimental design to ensure that fluxes are estimated with the highest precision is an integral part of the protocol. The protocol is based on growing microbes in two (or more) parallel cultures with ¹³C-labeled glucose tracers, followed by gas chromatography-mass spectrometry (GC-MS) measurements of isotopic labeling of protein-bound amino acids, glycogen-bound glucose, and RNA-bound ribose. Fluxes are then estimated using software for ¹³C-MFA, such as Metran, followed by comprehensive statistical analysis to determine the goodness of fit and calculate confidence intervals of fluxes. The presented protocol can be completed in 4 d and quantifies metabolic fluxes with a standard deviation of ≤2%, a substantial improvement over previous implementations. The presented protocol is exemplified using an Escherichia coli ΔtpiA case study with full supporting data, providing a hands-on opportunity to step through a complex troubleshooting scenario. Although applications to prokaryotic microbial systems are emphasized, this protocol can be easily adjusted for application to eukaryotic organisms.

Synthetic methylotrophy: Strategies to assimilate methanol for growth and chemicals production

Methanol is an attractive and broadly available substrate for large-scale bioproduction of fuels and chemicals. It contains more energy and electrons per carbon than carbohydrates and can be cheaply produced from natural gas. Synthetic methylotrophy refers to the development of non-native methylotrophs such as Escherichia coli and Corynebacterium glutamicum to utilize methanol as a carbon source. Here, we discuss recent advances in engineering these industrial hosts to assimilate methanol for growth and chemicals production through the introduction of the ribulose monophosphate (RuMP) cycle. In addition, we present novel strategies based on flux coupling and adaptive laboratory evolution to engineer new strains that can grow exclusively on methanol.

Correlating enzyme annotations with a large set of microbial growth temperatures reveals metabolic adaptations to growth at diverse temperatures

Background

The ambient temperature of all habitats is a key physical property that shapes the biology of microbes inhabiting them. The optimal growth temperature (OGT) of a microbe, is therefore a key piece of data needed to understand evolutionary adaptations manifested in their genome sequence. Unfortunately there is no growth temperature database or easily downloadable dataset encompassing the majority of cultured microorganisms. We are thus limited in interpreting genomic data to identify temperature adaptations in microbes.

Results

In this work I significantly contribute to closing this gap by mining data from major culture collection centres to obtain growth temperature data for a nonredundant set of 21,498 microbes. The dataset (10.5281/zenodo.1175608) contains mainly bacteria and archaea and spans psychrophiles, mesophiles, thermophiles and hyperthermophiles. Using this data a full 43% of all protein entries in the UniProt database can be annotated with the growth temperature of the species from which they originate. I validate the dataset by showing a Pearson correlation of up to 0.89 between growth temperature and mean enzyme optima, a physiological property directly influenced by the growth temperature. Using the temperature dataset I correlate the genomic occurance of enzyme functional annotations with growth temperature. I identify 319 enzyme functions that either increase or decrease in occurrence with temperature. Eight metabolic pathways were statistically enriched for these enzyme functions. Furthermore, I establish a correlation between 33 domains of unknown function (DUFs) with growth temperature in microbes, four of which (DUF438, DUF1524, DUF1957 and DUF3458_C) were significant in both archaea and bacteria.

Conclusions

The growth temperature dataset enables large-scale correlation analysis with enzyme function- and domain-level annotations. Growth-temperature dependent changes in their occurrence highlight potential evolutionary adaptations. A few of the identified changes are previously known, such as the preference for menaquinone biosynthesis through the futalosine pathway in bacteria growing at high temperatures. Others represent important starting points for future studies, such as DUFs where their occurrence change with temperature. The growth temperature dataset should become a valuable community resource and will find additional, important, uses in correlating genomic, transcriptomic, proteomic, metabolomic, phenotypic or taxonomic properties with temperature in future studies.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1320-7) contains supplementary material, which is available to authorized users.

Metabolism in dense microbial colonies: 13C metabolic flux analysis of E. coli grown on agar identifies two distinct cell populations with acetate cross-feeding

In this study, we have investigated for the first time the metabolism of E. coli grown on agar using ¹³C metabolic flux analysis (¹³C-MFA). To date, all ¹³C-MFA studies on microbes have been performed with cells grown in liquid culture. Here, we extend the scope of ¹³C-MFA to biological systems where cells are grown in dense microbial colonies. First, we identified new optimal ¹³C tracers to quantify fluxes in systems where the acetate yield cannot be easily measured. We determined that three parallel labeling experiments with the tracers [1,2-¹³C]glucose, [1,6-¹³C]glucose, and [4,5,6-¹³C]glucose permit precise estimation of not only intracellular fluxes, but also of the amount of acetate produced from glucose. Parallel labeling experiments were then performed with wild-type E. coli and E. coli ΔackA grown in liquid culture and on agar plates. Initial attempts to fit the labeling data from wild-type E. coli grown on agar did not produce a statistically acceptable fit. To resolve this issue, we employed the recently developed co-culture ¹³C-MFA approach, where two E. coli subpopulations were defined in the model that engaged in metabolite cross-feeding. The flux results identified two distinct E. coli cell populations, a dominant cell population (92% of cells) that metabolized glucose via conventional metabolic pathways and secreted a large amount of acetate (~40% of maximum theoretical yield), and a second smaller cell population (8% of cells) that consumed the secreted acetate without any glucose influx. These experimental results are in good agreement with recent theoretical simulations. Importantly, this study provides a solid foundation for future investigations of a wide range of problems involving microbial biofilms that are of great interest in biotechnology, ecology and medicine, where metabolite cross-feeding between cell populations is a core feature of the communities.

Establishment of a five-enzyme cell-free cascade for the synthesis of uridine diphosphate N-acetylglucosamine

In spite of huge endeavors in cell line engineering to produce glycoproteins with desired and uniform glycoforms, it is still not possible in vivo. Alternatively, in vitro glycoengineering can be used for the modification of glycans. However, in vitro glycoengineering relies on expensive nucleotide sugars, such as uridine 5'-diphospho-N-acetylglucosamine (UDP-GlcNAc) which serves as GlcNAc donor for the synthesis of various glycans. In this work, we present a systematic study for the cell-free de novo synthesis and regeneration of UDP-GlcNAc from polyphosphate, UMP and GlcNAc by a cascade of five enzymes (N-acetylhexosamine kinase (NahK), Glc-1P uridyltransferase (GalU), uridine monophosphate kinase (URA6), polyphosphate kinase (PPK3), and inorganic diphosphatase (PmPpA). All enzymes were expressed in E. coli BL21 Gold (DE3) and purified using immobilized metal affinity chromatography (IMAC). Results from one-pot experiments demonstrate the successful production of UDP-GlcNAc with a yield approaching 100%. The highest volumetric productivity of the cascade was about 0.81 g L^-1  h^-1 of UDP-GlcNAc. A simple model based on mass action kinetics was sufficient to capture the dynamic behavior of the multienzyme pathway. Moreover, a design equation based on metabolic control analysis was established to investigate the effect of enzyme concentration on the UDP-GlcNAc flux and to demonstrate that the flux of UDP-GlcNAc can be controlled by means of the enzyme concentrations. The effect of temperature on the UDP-GlcNAc flux followed an Arrhenius equation and the optimal co-factor concentration (Mg²⁺) for high UDP-GlcNAc synthesis rates depended on the working temperature. In conclusion, the study covers the entire engineering process of a multienzyme cascade, i.e. pathway design, enzyme expression, enzyme purification, reaction kinetics and investigation of the influence of basic parameters (temperature, co-factor concentration, enzyme concentration) on the synthesis rate. Thus, the study lays the foundation for future cascade optimization, preparative scale UDP-GlcNAc synthesis and for in situ coupling of the network with UDP-GlcNAc transferases to efficiently regenerate UDP-GlcNAc. Hence, this study provides a further step towards cost-effective in vitro glycoengineering of antibodies and other glycosylated proteins.

A guide to 13C metabolic flux analysis for the cancer biologist

Cancer metabolism is significantly altered from normal cellular metabolism allowing cancer cells to adapt to changing microenvironments and maintain high rates of proliferation. In the past decade, stable-isotope tracing and network analysis have become powerful tools for uncovering metabolic pathways that are differentially activated in cancer cells. In particular, ¹³C metabolic flux analysis (¹³C-MFA) has emerged as the primary technique for quantifying intracellular fluxes in cancer cells. In this review, we provide a practical guide for investigators interested in getting started with ¹³C-MFA. We describe best practices in ¹³C-MFA, highlight potential pitfalls and alternative approaches, and conclude with new developments that can further enhance our understanding of cancer metabolism.

Tracing tagged molecules can help researchers understand the altered metabolism of cancer cells. The abilities of cancer cells to multiply rapidly and invade new tissues are supported by metabolic alterations, which can be investigated by feeding tagged molecules to cells and tracing how they are metabolized. These techniques, such as ¹³C metabolic flux analysis (¹³C-MFA), have been perceived as difficult to use, but recent advances are making them more accessible. Maciek Antoniewicz, University of Delaware, Newark, USA, has published a practical guide for researchers wanting to use 13C-MFA. The review includes best practices, pitfalls, alternative approaches, and new developments, especially new user-friendly software that allows researchers without extensive training in mathematics, statistics, or coding to perform 13C-MFA. Broadening access to tools for investigating altered metabolic pathways may spur development of new cancer therapies targeting these pathways.

Optimization of the production of an extracellular and thermostable amylolytic enzyme by Thermus thermophilus HB8 and basic characterization

The objective of this study was to determine the potential of Thermus thermophilus HB8 for accumulating a high level of extracellular, thermostable amylolytic enzyme. Initial production tests indicated clearly that only very low levels of amylolytic activity could be detected, solely from cells after extraction using the mild, non-ionic detergent Triton X-100. A sequential optimization strategy, based on statistical designs, was used to enhance greatly the production of extracellular amylolytic activity to achieve industrially attractive enzyme titers. Focus was placed on the optimal level of initial biomass concentration, culture medium composition and temperature for maximizing extracellular amylolytic enzyme accumulation. Empirical models were then developed describing the effects of the experimental parameters and their interactions on extracellular amylolytic enzyme production. Following such efforts, extracellular amylolytic enzyme accumulation was increased more than 70-fold, with enzyme titers in the 76 U/mL range. The crude extracellular enzyme was thereafter partially characterized. The optimal temperature and pH values were found to be 80 °C and 9.0, respectively. 100% of the initial enzyme activity could be recovered after incubation for 24 h at 80 °C, therefore, proving the very high thermostability of the enzyme preparation.

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.

Physiological, metabolic and biotechnological features of extremely thermophilic microorganisms

The current upper thermal limit for life as we know it is approximately 120°C. Microorganisms that grow optimally at temperatures of 75°C and above are usually referred to as 'extreme thermophiles' and include both bacteria and archaea. For over a century, there has been great scientific curiosity in the basic tenets that support life in thermal biotopes on earth and potentially on other solar bodies. Extreme thermophiles can be aerobes, anaerobes, autotrophs, heterotrophs, or chemolithotrophs, and are found in diverse environments including shallow marine fissures, deep sea hydrothermal vents, terrestrial hot springs-basically, anywhere there is hot water. Initial efforts to study extreme thermophiles faced challenges with their isolation from difficult to access locales, problems with their cultivation in laboratories, and lack of molecular tools. Fortunately, because of their relatively small genomes, many extreme thermophiles were among the first organisms to be sequenced, thereby opening up the application of systems biology-based methods to probe their unique physiological, metabolic and biotechnological features. The bacterial genera Caldicellulosiruptor, Thermotoga and Thermus, and the archaea belonging to the orders Thermococcales and Sulfolobales, are among the most studied extreme thermophiles to date. The recent emergence of genetic tools for many of these organisms provides the opportunity to move beyond basic discovery and manipulation to biotechnologically relevant applications of metabolic engineering. WIREs Syst Biol Med 2017, 9:e1377. doi: 10.1002/wsbm.1377 For further resources related to this article, please visit the WIREs website.

Recent applications of metabolomics to advance microbial biofuel production

Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers.

Recent advances in high-throughput 13C-fluxomics

The rise of high throughput (HT) strain engineering tools accompanying the area of synthetic biology is supporting the generation of a large number of microbial cell factories. A current bottleneck in process development is our limited capacity to rapidly analyze the metabolic state of the engineered strains, and in particular their intracellular fluxes. HT ¹³C-fluxomics workflows have not yet become commonplace, despite the existence of several HT tools at each of the required stages. This includes cultivation and sampling systems, analytics for isotopic analysis, and software for data processing and flux calculation. Here, we review recent advances in the field and highlight bottlenecks that must be overcome to allow the emergence of true HT ¹³C-fluxomics workflows.

Comprehensive metabolic modeling of multiple 13C-isotopomer data sets to study metabolism in perfused working hearts

In many forms of cardiomyopathy, alterations in energy substrate metabolism play a key role in disease pathogenesis. Stable isotope tracing in rodent heart perfusion systems can be used to determine cardiac metabolic fluxes, namely those relative fluxes that contribute to pyruvate, the acetyl-CoA pool, and pyruvate anaplerosis, which are critical to cardiac homeostasis. Methods have previously been developed to interrogate these relative fluxes using isotopomer enrichments of measured metabolites and algebraic equations to determine a predefined metabolic flux model. However, this approach is exquisitely sensitive to measurement error, thus precluding accurate relative flux parameter determination. In this study, we applied a novel mathematical approach to determine relative cardiac metabolic fluxes using ¹³C-metabolic flux analysis (¹³C-MFA) aided by multiple tracer experiments and integrated data analysis. Using ¹³C-MFA, we validated a metabolic network model to explain myocardial energy substrate metabolism. Four different ¹³C-labeled substrates were queried (i.e., glucose, lactate, pyruvate, and oleate) based on a previously published study. We integrated the analysis of the complete set of isotopomer data gathered from these mouse heart perfusion experiments into a single comprehensive network model that delineates substrate contributions to both pyruvate and acetyl-CoA pools at a greater resolution than that offered by traditional methods using algebraic equations. To our knowledge, this is the first rigorous application of ¹³C-MFA to interrogate data from multiple tracer experiments in the perfused heart. We anticipate that this approach can be used widely to study energy substrate metabolism in this and other similar biological systems.

Identification of Preferred DNA-Binding Sites for the Thermus thermophilus Transcriptional Regulator SbtR by the Combinatorial Approach REPSA

One of the first steps towards elucidating the biological function of a putative transcriptional regulator is to ascertain its preferred DNA-binding sequences. This may be rapidly and effectively achieved through the application of a combinatorial approach, one involving very large numbers of randomized oligonucleotides and reiterative selection and amplification steps to enrich for high-affinity nucleic acid-binding sequences. Previously, we had developed the novel combinatorial approach Restriction Endonuclease Protection, Selection and Amplification (REPSA), which relies not on the physical separation of ligand-nucleic acid complexes but instead selects on the basis of ligand-dependent inhibition of enzymatic template inactivation, specifically cleavage by type IIS restriction endonucleases. Thus, no prior knowledge of the ligand is required for REPSA, making it more amenable for discovery purposes. Here we describe using REPSA, massively parallel sequencing, and bioinformatics to identify the preferred DNA-binding sites for the transcriptional regulator SbtR, encoded by the TTHA0167 gene from the model extreme thermophile Thermus thermophilus HB8. From the resulting position weight matrix, we can identify multiple operons potentially regulated by SbtR and postulate a biological role for this protein in regulating extracellular transport processes. Our study provides a proof-of-concept for the application of REPSA for the identification of preferred DNA-binding sites for orphan transcriptional regulators and a first step towards determining their possible biological roles.

Co-utilization of glucose and xylose by evolved Thermus thermophilus LC113 strain elucidated by (13)C 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 (13)C-metabolic flux analysis ((13)C-MFA) with [1,6-(13)C]glucose, [5-(13)C]xylose, and [1,6-(13)C]glucose+[5-(13)C]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 0.46h(-1), respectively. In medium containing glucose and xylose the strain efficiently co-utilized the two sugars. (13)C-MFA results provided insights into the metabolism of T. thermophilus LC113 that allows efficient co-utilization of glucose and xylose. Specifically, (13)C-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, (13)C-MFA and genome sequence analysis provided complementary insights into the physiology of the evolved strain.

Extremely thermophilic microorganisms as metabolic engineering platforms for production of fuels and industrial chemicals

Enzymes from extremely thermophilic microorganisms have been of technological interest for some time because of their ability to catalyze reactions of industrial significance at elevated temperatures. Thermophilic enzymes are now routinely produced in recombinant mesophilic hosts for use as discrete biocatalysts. Genome and metagenome sequence data for extreme thermophiles provide useful information for putative biocatalysts for a wide range of biotransformations, albeit involving at most a few enzymatic steps. However, in the past several years, unprecedented progress has been made in establishing molecular genetics tools for extreme thermophiles to the point that the use of these microorganisms as metabolic engineering platforms has become possible. While in its early days, complex metabolic pathways have been altered or engineered into recombinant extreme thermophiles, such that the production of fuels and chemicals at elevated temperatures has become possible. Not only does this expand the thermal range for industrial biotechnology, it also potentially provides biodiverse options for specific biotransformations unique to these microorganisms. The list of extreme thermophiles growing optimally between 70 and 100°C with genetic toolkits currently available includes archaea and bacteria, aerobes and anaerobes, coming from genera such as Caldicellulosiruptor, Sulfolobus, Thermotoga, Thermococcus, and Pyrococcus. These organisms exhibit unusual and potentially useful native metabolic capabilities, including cellulose degradation, metal solubilization, and RuBisCO-free carbon fixation. Those looking to design a thermal bioprocess now have a host of potential candidates to choose from, each with its own advantages and challenges that will influence its appropriateness for specific applications. Here, the issues and opportunities for extremely thermophilic metabolic engineering platforms are considered with an eye toward potential technological advantages for high temperature industrial biotechnology.

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.

Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis

Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine.

(13)C metabolic flux analysis of the extremely thermophilic, fast growing, xylose-utilizing Geobacillus strain LC300

Thermophiles are increasingly used as versatile hosts in the biotechnology industry. One of the key advantages of thermophiles is the potential to achieve high rates of feedstock conversion at elevated temperatures. The recently isolated Geobacillus strain LC300 grows extremely fast on xylose, with a doubling time of less than 30 min. In the accompanying paper, the genome of Geobacillus LC300 was sequenced and annotated. In this work, we have experimentally validated the metabolic network model using parallel (13)C-labeling experiments and applied (13)C-metabolic flux analysis to quantify precise metabolic fluxes. Specifically, the complete set of singly labeled xylose tracers, [1-(13)C], [2-(13)C], [3-(13)C], [4-(13)C], and [5-(13)C]xylose, was used for the first time. Isotopic labeling of biomass amino acids was measured by gas chromatography mass spectrometry (GC-MS). Isotopic labeling of carbon dioxide in the off-gas was also measured by an on-line mass spectrometer. The (13)C-labeling data was then rigorously integrated for flux elucidation using the COMPLETE-MFA approach. The results provided important new insights into the metabolism of Geobacillus LC300, its efficient xylose utilization pathways, and the balance between carbon, redox and energy fluxes. The pentose phosphate pathway, glycolysis and TCA cycle were found to be highly active in Geobacillus LC300. The oxidative pentose phosphate pathway was also active and contributed significantly to NADPH production. No transhydrogenase activity was detected. Results from this work provide a solid foundation for future studies of this strain and its metabolic engineering and biotechnological applications.

Methods and advances in metabolic flux analysis: a mini-review

Metabolic flux analysis (MFA) is one of the pillars of metabolic engineering. Over the past three decades, it has been widely used to quantify intracellular metabolic fluxes in both native (wild type) and engineered biological systems. Through MFA, changes in metabolic pathway fluxes are quantified that result from genetic and/or environmental interventions. This information, in turn, provides insights into the regulation of metabolic pathways and may suggest new targets for further metabolic engineering of the strains. In this mini-review, we discuss and classify the various methods of MFA that have been developed, which include stoichiometric MFA, (13)C metabolic flux analysis, isotopic non-stationary (13)C metabolic flux analysis, dynamic metabolic flux analysis, and (13)C dynamic metabolic flux analysis. For each method, we discuss key advantages and limitations and conclude by highlighting important recent advances in flux analysis approaches.

Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for (13)C metabolic flux analysis ((13)C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-(13)C]glucose and mixtures of [1-(13)C]glucose and [U-(13)C]glucose, four novel tracers were applied in this study: [2,3-(13)C]glucose, [4,5,6-(13)C]glucose, [2,3,4,5,6-(13)C]glucose and a mixture of [1-(13)C]glucose and [4,5,6-(13)C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-(13)C]glucose+20% [U-(13)C]glucose, while [4,5,6-(13)C]glucose and [5-(13)C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.

How to measure metabolic fluxes: a taxonomic guide for (13)C fluxomics

Metabolic reaction rates (fluxes) contribute fundamentally to our understanding of metabolic phenotypes and mechanisms of cellular regulation. Stable isotope-based fluxomics integrates experimental data with biochemical networks and mathematical modeling to 'measure' the in vivo fluxes within an organism that are not directly observable. In recent years, (13)C fluxomics has evolved into a technology with great experimental, analytical, and mathematical diversity. This review aims at establishing a unified taxonomy by means of which the various fluxomics methods can be compared to each other. By linking the developed modeling approaches to recent studies, their challenges and opportunities are put into perspective. The proposed classification serves as a guide for scientific 'travelers' who are striving to resolve research questions with the currently available (13)C fluxomics toolset.

Quantifying biomass composition by gas chromatography/mass spectrometry

We developed a set of methods for the quantification of four major components of microbial biomass using gas chromatography/mass spectrometry (GC/MS). Specifically, methods are described to quantify amino acids, RNA, fatty acids, and glycogen, which comprise an estimated 88% of the dry weight of Escherichia coli. Quantification is performed by isotope ratio analysis with fully (13)C-labeled biomass as internal standard, which is generated by growing E. coli on [U-(13)C]glucose. This convenient, reliable, and accurate single-platform (GC/MS) workflow for measuring biomass composition offers significant advantages over existing methods. We demonstrate the consistency, accuracy, precision, and utility of this procedure by applying it to three metabolically unique E. coli strains. The presented methods will have widespread applicability in systems microbiology and bioengineering.

Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for (13)C metabolic flux analysis

In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and (13)C-metabolic flux analysis ((13)C-MFA). Here, cells were grown in parallel cultures with [1-(13)C]glucose and [U-(13)C]glucose as tracers and (13)C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of (13)C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for (13)C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased (13)C-flux measurements in C. acetobutylicum.

Metabolic flux pattern of glucose utilization by Xanthomonas campestris pv. campestris: prevalent role of the Entner–Doudoroff pathway and minor fluxes through the pentose phosphate pathway and glycolysis

Complex metabolic flux pattern ofX. campestris.