Recent advances in mapping environmental microbial metabolisms through 13C isotopic fingerprints

An isotopic labeling approach linking natural products with biosynthetic gene clusters

Major advances in genome sequencing and large-scale biosynthetic gene cluster (BGC) analysis have prompted an age of natural product discovery driven by genome mining. Still, connecting molecules to their cognate BGCs is a substantial bottleneck for this approach. We have developed a mass-spectrometry-based parallel stable isotope labeling platform, termed IsoAnalyst, which assists in associating metabolite stable isotope labeling patterns with BGC structure prediction to connect natural products to their corresponding BGCs. Here we show that IsoAnalyst can quickly associate both known metabolites and unknown analytes with BGCs to elucidate the complex chemical phenotypes of these biosynthetic systems. We validate this approach for a range of compound classes, using both the type strain Saccharopolyspora erythraea and an environmentally isolated Micromonospora sp. We further demonstrate the utility of this tool with the discovery of lobosamide D, a new and structurally unique member of the family of lobosamide macrolactams.

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.

Selfish, sharing and scavenging bacteria in the Atlantic Ocean: a biogeographical study of bacterial substrate utilisation

Identifying the roles played by individual heterotrophic bacteria in the degradation of high molecular weight (HMW) substrates is critical to understanding the constraints on carbon cycling in the ocean. At five sites in the Atlantic Ocean, we investigated the processing of organic matter by tracking changes in microbial community composition as HMW polysaccharides were enzymatically hydrolysed over time. During this investigation, we discovered that a considerable fraction of heterotrophic bacteria uses a newly-identified ‘selfish’ mode of substrate processing. We therefore additionally examined the balance of individual substrate utilisation mechanisms at different locations by linking individual microorganisms to distinct substrate utilisation mechanisms. Through FISH and uptake of fluorescently-labelled polysaccharides, ‘selfish’ organisms were identified as belonging to the Bacteroidetes, Planctomycetes and Gammaproteobacteria. ‘Sharing’ (extracellular enzyme producing) and ‘scavenging’ (non-enzyme producing) organisms predominantly belonged to the Alteromonadaceae and SAR11 clades, respectively. The extent to which individual mechanisms prevail depended on the initial population structure of the bacterial community at a given location and time, as well as the growth rate of specific bacteria. Furthermore, the same substrate was processed in different ways by different members of a pelagic microbial community, pointing to significant follow-on effects for carbon cycling.

Model metabolic strategy for heterotrophic bacteria in the cold ocean based on Colwellia psychrerythraea 34H

Colwellia psychrerythraea 34H is a model psychrophilic bacterium found in the cold ocean-polar sediments, sea ice, and the deep sea. Although the genomes of such psychrophiles have been sequenced, their metabolic strategies at low temperature have not been quantified. We measured the metabolic fluxes and gene expression of 34H at 4 °C (the mean global-ocean temperature and a normal-growth temperature for 34H), making comparative analyses at room temperature (above its upper-growth temperature of 18 °C) and with mesophilic Escherichia coli When grown at 4 °C, 34H utilized multiple carbon substrates without catabolite repression or overflow byproducts; its anaplerotic pathways increased flux network flexibility and enabled CO₂ fixation. In glucose-only medium, the Entner-Doudoroff (ED) pathway was the primary glycolytic route; in lactate-only medium, gluconeogenesis and the glyoxylate shunt became active. In comparison, E. coli, cold stressed at 4 °C, had rapid glycolytic fluxes but no biomass synthesis. At their respective normal-growth temperatures, intracellular concentrations of TCA cycle metabolites (α-ketoglutarate, succinate, malate) were 4-17 times higher in 34H than in E. coli, while levels of energy molecules (ATP, NADH, NADPH) were 10- to 100-fold lower. Experiments with E. coli mutants supported the thermodynamic advantage of the ED pathway at cold temperature. Heat-stressed 34H at room temperature (2 hours) revealed significant down-regulation of genes associated with glycolytic enzymes and flagella, while 24 hours at room temperature caused irreversible cellular damage. We suggest that marine heterotrophic bacteria in general may rely upon simplified metabolic strategies to overcome thermodynamic constraints and thrive in the cold ocean.

Rerouting of Metabolism into Desired Cellular Products by Nutrient Stress: Fluxes Reveal the Selected Pathways in Cyanobacterial Photosynthesis

Boosting cellular growth rates while redirecting metabolism to make desired products are the preeminent goals of gene engineering of photoautotrophs, yet so far these goals have been hardly achieved owing to lack of understanding of the functional pathways and their choke points. Here we apply a ¹³C mass isotopic method (INST-MFA) to quantify instantaneous fluxes of metabolites during photoautotrophic growth. INST-MFA determines the globally most accurate set of absolute fluxes for each metabolite from a finite set of measured ¹³C-isotopomer fluxes by minimizing the sum of squared residuals between experimental and predicted mass isotopomers. We show that the widely observed shift in biomass composition in cyanobacteria, demonstrated here with Synechococcus sp. PCC 7002, favoring glycogen synthesis during nitrogen starvation is caused by (1) increased flux through a bottleneck step in gluconeogenesis (3PG → GAP/DHAP), and (2) flux overflow through a previously unrecognized hybrid gluconeogenesis-pentose phosphate (hGPP) pathway. Our data suggest the slower growth rate and biomass accumulation under N starvation is due to a reduced carbon fixation rate and a reduced flux of carbon into amino acid precursors. Additionally, ¹³C flux from α-ketoglutarate to succinate is demonstrated to occur via succinic semialdehyde, an alternative to the conventional TCA cycle, in Synechococcus 7002 under photoautotrophic conditions. We found that pyruvate and oxaloacetate are synthesized mainly by malate dehydrogenase with minimal flux into acetyl coenzyme-A via pyruvate dehydrogenase. Nutrient stress induces major shifts in fluxes into new pathways that deviate from historical metabolic pathways derived from model bacteria.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Bacterial Substrate Transformation Tracked by Stable-Isotope-Guided NMR Metabolomics: Application in a Natural Aquatic Microbial Community

The transformation of organic substrates by heterotrophic bacteria in aquatic environments constitutes one of the key processes in global material cycles. The development of procedures that would enable us to track the wide range of organic compounds transformed by aquatic bacteria would greatly improve our understanding of material cycles. In this study, we examined the applicability of nuclear magnetic resonance spectroscopy coupled with stable-isotope labeling to the investigation of metabolite transformation in a natural aquatic bacterial community. The addition of a model substrate (¹³C₆–glucose) to a coastal seawater sample and subsequent incubation resulted in the detection of >200 peaks and the assignment of 22 metabolites from various chemical classes, including amino acids, dipeptides, organic acids, nucleosides, nucleobases, and amino alcohols, which had been identified as transformed from the ¹³C₆–glucose. Additional experiments revealed large variability in metabolite transformation and the key compounds, showing the bacterial accumulation of glutamate over the incubation period, and that of 3-hydroxybutyrate with increasing concentrations of ¹³C₆–glucose added. These results suggest the potential ability of our approach to track substrate transformation in aquatic bacterial communities. Further applications of this procedure may provide substantial insights into the metabolite dynamics in aquatic environments.

Accurate and sensitive determination of molar fractions of 13C-Labeled intracellular metabolites in cell cultures grown in the presence of isotopically-labeled glucose

This work describes a methodology based on multiple linear regression and GC-MS for the determination of molar fractions of isotopically-labeled intracellular metabolites in cell cultures. Novel aspects of this work are: i) the calculation of theoretical isotopic distributions of the different isotopologues from an experimentally measured value of % 13C enrichment of the labeled precursor ii) the calculation of the contribution of lack of mass resolution of the mass spectrometer and different fragmentation mechanism such as the loss or gain of hydrogen atoms in the EI source to measure the purity of the selected cluster for each metabolite and iii) the validation of the methodology not only by the analysis of gravimetrically prepared mixtures of isotopologues but also by the comparison of the obtained molar fractions with experimental values obtained by GC-Combustion-IRMS based on ¹³C/¹²C isotope ratio measurements. The method is able to measure molar fractions for twenty-eight intracellular metabolites derived from glucose metabolism in cell cultures grown in the presence of ¹³C-labeled Glucose. The validation strategies demonstrate a satisfactory accuracy and precision of the proposed procedure. Also, our results show that the minimum value of ¹³C incorporation that can be accurately quantified is significantly influenced by the calculation of the spectral purity of the measured cluster and the number of ¹³C atoms of the labeled precursor. The proposed procedure was able to accurately quantify gravimetrically prepared mixtures of natural and labeled glucose molar fractions of 0.07% and mixtures of natural and labeled glycine at molar fractions down to 0.7%. The method was applied to initial studies of glucose metabolism of different prostate cancer cell lines.

Decoding how a soil bacterium extracts building blocks and metabolic energy from ligninolysis provides road map for lignin valorization

Sphingobium sp. SYK-6 is a soil bacterium boasting a well-studied ligninolytic pathway and the potential for development into a microbial chassis for lignin valorization. An improved understanding of its metabolism will help researchers in the engineering of SYK-6 for the production of value-added chemicals through lignin valorization. We used ¹³C-fingerprinting, ¹³C metabolic flux analysis (¹³C-MFA), and RNA-sequencing differential expression analysis to uncover the following metabolic traits: (i) SYK-6 prefers alkaline conditions, making it an efficient host for the consolidated bioprocessing of lignin, and it also lacks the ability to metabolize sugars or organic acids; (ii) the CO₂ release (i.e., carbon loss) from the ligninolysis-based metabolism of SYK-6 is significantly greater than the CO₂ release from the sugar-based metabolism of Escherichia coli; (iii) the vanillin catabolic pathway (which is the converging point of majority of the lignin catabolic pathways) is coupled with the tetrahydrofolate-dependent C1 pathway that is essential for the biosynthesis of serine, histidine, and methionine; (iv) catabolic end products of lignin (pyruvate and oxaloacetate) must enter the tricarboxylic acid (TCA) cycle first and then use phosphoenolpyruvate carboxykinase to initiate gluconeogenesis; and (v) ¹³C-MFA together with RNA-sequencing differential expression analysis establishes the vanillin catabolic pathway as the major contributor of NAD(P)H synthesis. Therefore, the vanillin catabolic pathway is essential for SYK-6 to obtain sufficient reducing equivalents for its healthy growth; cosubstrate experiments support this finding. This unique energy feature of SYK-6 is particularly interesting because most heterotrophs rely on the transhydrogenase, the TCA cycle, and the oxidative pentose phosphate pathway to obtain NADPH.

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species.

Recent highlights in biosynthesis research using stable isotopes

The long and successful history of isotopic labeling experiments within natural products research has both changed and deepened our understanding of biosynthesis. As demonstrated in this article, the usage of isotopes is not at all old-fashioned, but continues to give important insights into biosynthetic pathways of secondary metabolites. This review with 85 cited references is structured by separate discussions of compounds from different classes including polyketides, non-ribosomal peptides, their hybrids, terpenoids, and aromatic compounds formed via the shikimate pathway. The text does not aim at a comprehensive overview, but instead a selection of recent important examples of isotope usage within biosynthetic studies is presented, with a special emphasis on mechanistic surprises.

Two pathways for glutamate biosynthesis in the syntrophic bacterium Syntrophus aciditrophicus

The anaerobic metabolism of crotonate, benzoate, and cyclohexane carboxylate by Syntrophus aciditrophicus grown syntrophically with Methanospirillum hungatei provides a model to study syntrophic cooperation. Recent studies revealed that S. aciditrophicus contains Re-citrate synthase but lacks the common Si-citrate synthase. To establish whether the Re-citrate synthase is involved in glutamate synthesis via the oxidative branch of the Krebs cycle, we have used [1-(13)C]acetate and [1-(14)C]acetate as well as [(13)C]bicarbonate as additional carbon sources during axenic growth of S. aciditrophicus on crotonate. Our analyses showed that labeled carbons were detected in at least 14 amino acids, indicating the global utilization of acetate and bicarbonate. The labeling patterns of alanine and aspartate verified that pyruvate and oxaloacetate were synthesized by consecutive carboxylations of acetyl coenzyme A (acetyl-CoA). The isotopomer profile and (13)C nuclear magnetic resonance (NMR) spectroscopy of the obtained [(13)C]glutamate, as well as decarboxylation of [(14)C]glutamate, revealed that this amino acid was synthesized by two pathways. Unexpectedly, only the minor route used Re-citrate synthase (30 to 40%), whereas the majority of glutamate was synthesized via the reductive carboxylation of succinate. This symmetrical intermediate could have been formed from two acetates via hydration of crotonyl-CoA to 4-hydroxybutyryl-CoA. 4-Hydroxybutyrate was detected in the medium of S. aciditrophicus when grown on crotonate, but an active hydratase could not be measured in cell extracts, and the annotated 4-hydroxybutyryl-CoA dehydratase (SYN_02445) lacks key amino acids needed to catalyze the hydration of crotonyl-CoA. Besides Clostridium kluyveri, this study reveals the second example of a microbial species to employ two pathways for glutamate synthesis.

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.

Combining Stable Isotope Labeling and Molecular Networking for Biosynthetic Pathway Characterization

Filamentous fungi are a rich source of bioactive compounds, ranging from statins over immunosuppressants to antibiotics. The coupling of genes to metabolites is of large commercial interest for production of the bioactives of the future. To this end, we have investigated the use of stable isotope labeled amino acids (SILAAs). SILAAs were added to the cultivation media of the filamentous fungus Aspergillus nidulans for the study of the cyclic tetrapeptide nidulanin A. Analysis by UHPLC-TOFMS confirmed that the SILAAs were incorporated into produced nidulanin A, and the change in observed m/z could be used to determine whether a compound (known or unknown) incorporated any of the added amino acids. Samples were then analyzed using MS/MS and the data used to perform molecular networking. The molecular network revealed several known and unknown compounds that were also labeled. Assisted by the isotope labeling, it was possible to determine the sequence of several of the compounds, one of which was the known metabolite fungisporin, not previously described in A. nidulans. Several novel analogues of nidulanin A and fungisporin were detected and tentatively identified, and it was determined that these metabolites were all produced by the same nonribosomal peptide synthase. The combination of stable isotope labeling and molecular network generation was shown to very effective for the automated detection of structurally related nonribosomal peptides, while the labeling was effective for determination of the peptide sequence, which could be used to provide information on biosynthesis of bioactive compounds.

Large-Scale 13C flux profiling reveals conservation of the Entner-Doudoroff pathway as a glycolytic strategy among marine bacteria that use glucose

Marine bacteria form one of the largest living surfaces on Earth, and their metabolic activity is of fundamental importance for global nutrient cycling. Here, we explored the largely unknown intracellular pathways in 25 microbes representing different classes of marine bacteria that use glucose: Alphaproteobacteria, Gammaproteobacteria, and Flavobacteriia of the Bacteriodetes phylum. We used (13)C isotope experiments to infer metabolic fluxes through their carbon core pathways. Notably, 90% of all strains studied use the Entner-Doudoroff (ED) pathway for glucose catabolism, whereas only 10% rely on the Embden-Meyerhof-Parnas (EMP) pathway. This result differed dramatically from the terrestrial model strains studied, which preferentially used the EMP pathway yielding high levels of ATP. Strains using the ED pathway exhibited a more robust resistance against the oxidative stress typically found in this environment. An important feature contributing to the preferential use of the ED pathway in the oceans could therefore be enhanced supply of NADPH through this pathway. The marine bacteria studied did not specifically rely on a distinct anaplerotic route, but the carboxylation of phosphoenolpyruvate (PEP) or pyruvate for fueling of the tricarboxylic acid (TCA) cycle was evenly distributed. The marine isolates studied belong to clades that dominate the uptake of glucose, a major carbon source for bacteria in seawater. Therefore, the ED pathway may play a significant role in the cycling of mono- and polysaccharides by bacterial communities in marine ecosystems.

Characterization of the pivotal carbon metabolism of Streptococcus suis serotype 2 under ex vivo and chemically defined in vitro conditions by isotopologue profiling

Streptococcus suis is a neglected zoonotic pathogen that has to adapt to the nutritional requirements in the different host niches encountered during infection and establishment of invasive diseases. To dissect the central metabolic activity of S. suis under different conditions of nutrient availability, we performed labeling experiments starting from [(13)C]glucose specimens and analyzed the resulting isotopologue patterns in amino acids of S. suis grown under in vitro and ex vivo conditions. In combination with classical growth experiments, we found that S. suis is auxotrophic for Arg, Gln/Glu, His, Leu, and Trp in chemically defined medium. De novo biosynthesis was shown for Ala, Asp, Ser, and Thr at high rates and for Gly, Lys, Phe, Tyr, and Val at moderate or low rates, respectively. Glucose degradation occurred mainly by glycolysis and to a minor extent by the pentose phosphate pathway. Furthermore, the exclusive formation of oxaloacetate by phosphoenolpyruvate (PEP) carboxylation became evident from the patterns in de novo synthesized amino acids. Labeling experiments with S. suis grown ex vivo in blood or cerebrospinal fluid reflected the metabolic adaptation to these host niches with different nutrient availability; however, similar key metabolic activities were identified under these conditions. This points at the robustness of the core metabolic pathways in S. suis during the infection process. The crucial role of PEP carboxylation for growth of S. suis in the host was supported by experiments with a PEP carboxylase-deficient mutant strain in blood and cerebrospinal fluid.

Using photosystem I as a reporter protein for ¹³C analysis in a coculture containing cyanobacterium and a heterotrophic bacterium

(13)C metabolism analysis of a microbial community is often hindered by the time-consuming and complicated separation procedure for a single species. However, a "reporter protein," produced uniquely by one cell type, retains (13)C fingerprint information in microbial consortia. This study describes the use of photosystem I (PSI), a multi-subunit protein complex universally found in oxygenic phototrophs, as a reliable reporter protein to probe microalgal metabolism (i.e., cyanobacterium Synechocystis sp. PCC 6803) in a mixed culture with heterotrophic bacteria (i.e., Escherichia coli). We demonstrate that efficient purification of PSI and subsequent (13)C-based amino acid analyses may decipher photomixotrophic metabolism of Synechocystis 6803 in the coculture. This study also indicates that a supplement of NaHCO3 at high concentration could significantly improve the robustness of cyanobacterial growth against bacterial contamination.

The return of metabolism: biochemistry and physiology of the pentose phosphate pathway

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner–Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the ‘Warburg effect’ of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and parasite infections, neurons, stem cell potency and cancer metabolism.

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.

Application of stable isotope-assisted metabolomics for cell metabolism studies

The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other "omics" analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research.

Elucidation of intrinsic biosynthesis yields using 13C-based metabolism analysis

This paper discusses the use of 13C-based metabolism analysis for the assessment of intrinsic product yields - the actual carbon contribution from a single carbon substrate to the final product via a specific biosynthesis route - in the following four cases. First, undefined nutrients (such as yeast extract) in fermentation may contribute significantly to product synthesis, which can be quantified through an isotopic dilution method. Second, product and biomass synthesis may be dependent on the co-metabolism of multiple-carbon sources. 13C labeling experiments can track the fate of each carbon substrate in the cell metabolism and identify which substrate plays a main role in product synthesis. Third, 13C labeling can validate and quantify the contribution of the engineered pathway (versus the native pathway) to the product synthesis. Fourth, the loss of catabolic energy due to cell maintenance (energy used for functions other than production of new cell components) and low P/O ratio (Phosphate/Oxygen Ratio) significantly reduces product yields. Therefore, 13C-metabolic flux analysis is needed to assess the influence of suboptimal energy metabolism on microbial productivity, and determine how ATP/NAD(P)H are partitioned among various cellular functions. Since product yield is a major determining factor in the commercialization of a microbial cell factory, we foresee that 13C-isotopic labeling experiments, even without performing extensive flux calculations, can play a valuable role in the development and verification of microbial cell factories.

The use of functional genomics in conjunction with metabolomics for Mycobacterium tuberculosis research

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a fatal infectious disease, resulting in 1.4 million deaths globally per annum. Over the past three decades, genomic studies have been conducted in an attempt to elucidate the functionality of the genome of the pathogen. However, many aspects of this complex genome remain largely unexplored, as approaches like genomics, proteomics, and transcriptomics have failed to characterize them successfully. In turn, metabolomics, which is relatively new to the “omics” revolution, has shown great potential for investigating biological systems or their modifications. Furthermore, when these data are interpreted in combination with previously acquired genomics, proteomics and transcriptomics data, using what is termed a systems biology approach, a more holistic understanding of these systems can be achieved. In this review we discuss how metabolomics has contributed so far to characterizing TB, with emphasis on the resulting improved elucidation of M. tuberculosis in terms of (1) metabolism, (2) growth and replication, (3) pathogenicity, and (4) drug resistance, from the perspective of systems biology.

Experimental evidence and isotopomer analysis of mixotrophic glucose metabolism in the marine diatom Phaeodactylum tricornutum

BACKGROUND

Heterotrophic fermentation using simple sugars such as glucose is an established and cost-effective method for synthesizing bioproducts from bacteria, yeast and algae. Organisms incapable of metabolizing glucose have limited applications as cell factories, often despite many other advantageous characteristics. Therefore, there is a clear need to investigate glucose metabolism in potential cell factories. One such organism, with a unique metabolic network and a propensity to synthesize highly reduced compounds as a large fraction of its biomass, is the marine diatom Phaeodactylum tricornutum (Pt). Although Pt has been engineered to metabolize glucose, conflicting lines of evidence leave it unresolved whether Pt can natively consume glucose.

RESULTS

Isotope labeling experiments in which Pt was mixotrophically grown under light on 100% U-(13)C glucose and naturally abundant (~99% (12)C) dissolved inorganic carbon resulted in proteinogenic amino acids with an average 13C-enrichment of 88%, thus providing convincing evidence of glucose uptake and metabolism. The dissolved inorganic carbon was largely incorporated through anaplerotic rather than photosynthetic fixation. Furthermore, an isotope labeling experiment utilizing 1-(13)C glucose and subsequent metabolic pathway analysis indicated that (i) the alternative Entner-Doudoroff and Phosphoketolase glycolytic pathways are active during glucose metabolism, and (ii) during mixotrophic growth, serine and glycine are largely synthesized from glyoxylate through photorespiratory reactions rather than from 3-phosphoglycerate. We validated the latter result for mixotrophic growth on glycerol by performing a 2-(13)C glycerol isotope labeling experiment. Additionally, gene expression assays showed that known, native glucose transporters in Pt are largely insensitive to glucose or light, whereas the gene encoding cytosolic fructose bisphosphate aldolase 3, an important glycolytic enzyme, is overexpressed in light but insensitive to glucose.

CONCLUSION

We have shown that Pt can use glucose as a primary carbon source when grown in light, but cannot use glucose to sustain growth in the dark. We further analyzed the metabolic mechanisms underlying the mixotrophic metabolism of glucose and found isotopic evidence for unusual pathways active in Pt. These insights expand the envelope of Pt cultivation methods using organic substrates. We anticipate that they will guide further engineering of Pt towards sustainable production of fuels, pharmaceuticals, and platform chemicals.

Metabolic flux analysis of Cyanothece sp. ATCC 51142 under mixotrophic conditions

Cyanobacteria are a group of photosynthetic prokaryotes capable of utilizing solar energy to fix atmospheric carbon dioxide to biomass. Despite several "proof of principle" studies, low product yield is an impediment in commercialization of cyanobacteria-derived biofuels. Estimation of intracellular reaction rates by (13)C metabolic flux analysis ((13)C-MFA) would be a step toward enhancing biofuel yield via metabolic engineering. We report (13)C-MFA for Cyanothece sp. ATCC 51142, a unicellular nitrogen-fixing cyanobacterium, known for enhanced hydrogen yield under mixotrophic conditions. Rates of reactions in the central carbon metabolism under nitrogen-fixing and -non-fixing conditions were estimated by monitoring the competitive incorporation of (12)C and (13)C from unlabeled CO2 and uniformly labeled glycerol, respectively, into terminal metabolites such as amino acids. The observed labeling patterns suggest mixotrophic growth under both the conditions, with a larger fraction of unlabeled carbon in nitrate-sufficient cultures asserting a greater contribution of carbon fixation by photosynthesis and an anaplerotic pathway. Indeed, flux analysis complements the higher growth observed under nitrate-sufficient conditions. On the other hand, the flux through the oxidative pentose phosphate pathway and tricarboxylic acid cycle was greater in nitrate-deficient conditions, possibly to supply the precursors and reducing equivalents needed for nitrogen fixation. In addition, an enhanced flux through fructose-6-phosphate phosphoketolase possibly suggests the organism's preferred mode under nitrogen-fixing conditions. The (13)C-MFA results complement the reported predictions by flux balance analysis and provide quantitative insight into the organism's distinct metabolic features under nitrogen-fixing and -non-fixing conditions.

An integrated computational approach for metabolic flux analysis coupled with inference of tandem-MS collisional fragments

MOTIVATION

Metabolic flux analysis (MFA) is a commonly used approach for quantifying metabolic fluxes based on tracking isotope labeling of metabolite within cells. Tandem mass-spectrometry (MS/MS) has been recently shown to be especially useful for MFA by providing rich information on metabolite positional labeling, measuring isotopic labeling patterns of collisional fragments. However, a major limitation in this approach is the requirement that the positional origin of atoms in a collisional fragment would be known a priori, which in many cases is difficult to determine.

RESULTS

Here we show that MS/MS data could also be used to improve flux inference even when the positional origin of fragments is unknown. We develop a novel method, metabolic flux analysis/unknown fragments, that extends on standard MFA and jointly searches for the most likely metabolic fluxes together with the most plausible position of collisional fragments that would optimally match measured MS/MS data. MFA/UF is shown to markedly improve flux prediction accuracy in a simulation model of gluconeogenesis and using experimental MS/MS data in Bacillus subtilis.

Development of Synechocystis sp. PCC 6803 as a phototrophic cell factory

Cyanobacteria (blue-green algae) play profound roles in ecology and biogeochemistry. One model cyanobacterial species is the unicellular cyanobacterium Synechocystis sp. PCC 6803. This species is highly amenable to genetic modification. Its genome has been sequenced and many systems biology and molecular biology tools are available to study this bacterium. Recently, researchers have put significant efforts into understanding and engineering this bacterium to produce chemicals and biofuels from sunlight and CO₂. To demonstrate our perspective on the application of this cyanobacterium as a photosynthesis-based chassis, we summarize the recent research on Synechocystis 6803 by focusing on five topics: rate-limiting factors for cell cultivation; molecular tools for genetic modifications; high-throughput system biology for genome wide analysis; metabolic modeling for physiological prediction and rational metabolic engineering; and applications in producing diverse chemicals. We also discuss the particular challenges for systems analysis and engineering applications of this microorganism, including precise characterization of versatile cell metabolism, improvement of product rates and titers, bioprocess scale-up, and product recovery. Although much progress has been achieved in the development of Synechocystis 6803 as a phototrophic cell factory, the biotechnology for “Compounds from Synechocystis” is still significantly lagging behind those for heterotrophic microbes (e.g., Escherichia coli).