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13C-metabolic flux analysis (13C-MFA) allows metabolic fluxes to be quantified in living organisms and is a major tool in biotechnology and systems biology. Current 13C-MFA approaches model label propagation starting from the extracellular 13C-labeled nutrient(s), which limits their applicability to the analysis of pathways close to this metabolic entry point. Here, we propose a new approach to quantify fluxes through any metabolic subnetwork of interest by modeling label propagation directly from the metabolic precursor(s) of this subnetwork. The flux calculations are thus purely based on information from within the subnetwork of interest, and no additional knowledge about the surrounding network (such as atom transitions in upstream reactions or the labeling of the extracellular nutrient) is required. This approach, termed ScalaFlux for SCALAble metabolic FLUX analysis, can be scaled up from individual reactions to pathways to sets of pathways. ScalaFlux has several benefits compared with current 13C-MFA approaches: greater network coverage, lower data requirements, independence from cell physiology, robustness to gaps in data and network information, better computational efficiency, applicability to rich media, and enhanced flux identifiability. We validated ScalaFlux using a theoretical network and simulated data. We also used the approach to quantify fluxes through the prenyl pyrophosphate pathway of Saccharomyces cerevisiae mutants engineered to produce phytoene, using a dataset for which fluxes could not be calculated using existing approaches. A broad range of metabolic systems can be targeted with minimal cost and effort, making ScalaFlux a valuable tool for the analysis of metabolic fluxes., Author summary Metabolism is a fundamental biochemical process that enables all organisms to operate and grow by converting nutrients into energy and ‘building blocks’. Metabolic flux analysis allows the quantification of metabolic fluxes in vivo, i.e. the actual rates of biochemical conversions in biological systems, and is increasingly used to probe metabolic activity in biology, biotechnology and medicine. Isotope labeling experiments coupled with mathematical models of large metabolic networks are the most commonly used approaches to quantify fluxes within cells. However, many biological questions only require flux information from a subset of reactions, not the full network. Here, we propose a new approach with three main advantages over existing methods: better scalability (fluxes can be measured through a single reaction, a metabolic pathway or a set of pathways of interest), better robustness to missing data and information gaps, and lower requirements in terms of measurements and computational resources. We validate our method both theoretically and experimentally. ScalaFlux can be used for high-throughput flux measurements in virtually any metabolic system and paves the way to the analysis of dynamic fluxome rearrangements.

The phyllosphere, which is defined as the parts of terrestrial plants above the ground, is a large habitat for different microorganisms that show a high extent of adaption to their environment. A number of hypotheses were generated by culture-independent functional genomics studies to explain the competitiveness of specialized bacteria in the phyllosphere. In contrast, in situ data at the metabolome level as a function of bacterial colonization are lacking. Here, we aimed to obtain new insights into the metabolic interplay between host and epiphytes upon colonization of Arabidopsis thaliana leaves in a controlled laboratory setting using environmental metabolomics approaches. Quantitative nuclear magnetic resonance (NMR) and imaging high-resolution mass spectrometry (IMS) methods were used to identify Arabidopsis leaf surface compounds and their possible involvement in the epiphytic lifestyle by relative changes in compound pools. The dominant carbohydrates on the leaf surfaces were sucrose, fructose and glucose. These sugars were significantly and specifically altered after epiphytic leaf colonization by the organoheterotroph Sphingomonas melonis or the phytopathogen Pseudomonas syringae pv. tomato, but only to a minor extent by the methylotroph Methylobacterium extorquens. In addition to carbohydrates, IMS revealed surprising alterations in arginine metabolism and phytoalexin biosynthesis that were dependent on the presence of bacteria, which might reflect the consequences of bacterial activity and the recognition of not only pathogens but also commensals by the plant. These results highlight the power of environmental metabolomics to aid in elucidating the molecular basis underlying plant-epiphyte interactions in situ.

International audience; Methylobacterium extorquens AM1 uses dedicated cofactors for one-carbon unit conversion. Based on the sequence identities of enzymes and activity determinations, a methanofuran analog was proposed to be involved in formaldehyde oxidation in Alphaproteobacteria. Here, we report the structure of the cofactor, which we termed methylofuran. Using an in vitro enzyme assay and LC-MS, methylofuran was identified in cell extracts and further purified. From the exact mass and MS-MS fragmentation pattern, the structure of the cofactor was determined to consist of a polyglutamic acid side chain linked to a core structure similar to the one present in archaeal methanofuran variants. NMR analyses showed that the core structure contains a furan ring. However, instead of the tyramine moiety that is present in methanofuran cofactors, a tyrosine residue is present in methylofuran, which was further confirmed by MS through the incorporation of a C-13-labeled precursor. Methylofuran was present as a mixture of different species with varying numbers of glutamic acid residues in the side chain ranging from 12 to 24. Notably, the glutamic acid residues were not solely gamma-linked, as is the case for all known methanofurans, but were identified by NMR as a mixture of alpha- and gamma-linked amino acids. Considering the unusual peptide chain, the elucidation of the structure presented here sets the basis for further research on this cofactor, which is probably the largest cofactor known so far.

International audience; Acetyl-CoA assimilation was extensively studied in organisms harboring the glyoxylate cycle. In this study, we analyzed the metabolism of the facultative methylotroph Methylobacterium extorquens AM1, which lacks isocitrate lyase, the key enzyme in the glyoxylate cycle, during growth on acetate. MS/MS-based proteomic analysis revealed that the protein repertoire of M. extorquens AM1 grown on acetate is similar to that of cells grown on methanol and includes enzymes of the ethylmalonyl-CoA (EMC) pathway that were recently shown to operate during growth on methanol. Dynamic C-13 labeling experiments indicate the presence of distinct entry points for acetate: the EMC pathway and the TCA cycle. C-13 steady-state metabolic flux analysis showed that oxidation of acetyl-CoA occurs predominantly via the TCA cycle and that assimilation occurs via the EMC pathway. Furthermore, acetyl-CoA condenses with the EMC pathway product glyoxylate, resulting in malate formation. The latter, also formed by the TCA cycle, is converted to phosphoglycerate by a reaction sequence that is reversed with respect to the serine cycle. Thus, the results obtained in this study reveal the utilization of common pathways during the growth of M. extorquens AM1 on C1 and C2 compounds, but with a major redirection of flux within the central metabolism. Furthermore, our results indicate that the metabolic flux distribution is highly complex in this model methylotroph during growth on acetate and is fundamentally different from organisms using the glyoxylate cycle.

Background Methylotrophic microorganisms are playing a key role in biogeochemical processes - especially the global carbon cycle - and have gained interest for biotechnological purposes. Significant progress was made in the recent years in the biochemistry, genetics, genomics, and physiology of methylotrophic bacteria, showing that methylotrophy is much more widespread and versatile than initially assumed. Despite such progress, system-level description of the methylotrophic metabolism is currently lacking, and much remains to understand regarding the network-scale organization and properties of methylotrophy, and how the methylotrophic capacity emerges from this organization, especially in facultative organisms. Results In this work, we report on the integrated, system-level investigation of the metabolic network of the facultative methylotroph Methylobacterium extorquens AM1, a valuable model of methylotrophic bacteria. The genome-scale metabolic network of the bacterium was reconstructed and contains 1139 reactions and 977 metabolites. The sub-network operating upon methylotrophic growth was identified from both in silico and experimental investigations, and 13C-fluxomics was applied to measure the distribution of metabolic fluxes under such conditions. The core metabolism has a highly unusual topology, in which the unique enzymes that catalyse the key steps of C1 assimilation are tightly connected by several, large metabolic cycles (serine cycle, ethylmalonyl-CoA pathway, TCA cycle, anaplerotic processes). The entire set of reactions must operate as a unique process to achieve C1 assimilation, but was shown to be structurally fragile based on network analysis. This observation suggests that in nature a strong pressure of selection must exist to maintain the methylotrophic capability. Nevertheless, substantial substrate cycling could be measured within C2/C3/C4 inter-conversions, indicating that the metabolic network is highly versatile around a flexible backbone of central reactions that allows rapid switching to multi-carbon sources. Conclusions This work emphasizes that the metabolism of M. extorquens AM1 is adapted to its lifestyle not only in terms of enzymatic equipment, but also in terms of network-level structure and regulation. It suggests that the metabolism of the bacterium has evolved both structurally and functionally to an efficient but transitory utilization of methanol. Besides, this work provides a basis for metabolic engineering to convert methanol into value-added products., BMC Systems Biology, 5, ISSN:1752-0509

International audience; The deletion of thezwfgene encoding G6PDH activ-ity led to restructuring of the carbon flux through central metab-olism inEscherichia coli, though over-expression of this gene hadonly minor consequences for overall carbon flux. The modifiedcarbon flux seen in thezwfdeletion mutant enabled alternativeroutes of anabolic precursor formation and an adequate supplyof NADPH synthesis via a modified TCA cycle to be generatedso as to sustain growth rates comparable to the WT.Ó2007 Federation of European Biochemical Societies.Published by Elsevier B.V. All rights reserved.

International audience; In the present work we investigated the most commonly applied methods used for sampling of microorganisms in the field of metabolomics in order to unravel potential sources of error previously ignored but of utmost importance for accurate metabolome analysis. To broaden the significance of our study, we investigated different Gram-negative and Gram-positive bacteria, i.e., Bacillus subtilis, Corynebacterium glutamicum, Escherichia coli, Gluconobacter oxydans, Pseudomonas putida, and Zymononas mobilis, and analyzed metabolites from different catabolic and anabolic intracellular pathways. Quenching of cells with cold methanol prior to cell separation and extraction led to drastic loss (>60%) of all metabolites tested due to unspecific leakage. Using fast filtration, Gram-negative bacteria also revealed a significant loss (>80%) when inappropriate washing solutions with low ionic strength were applied. Adapting the ionic strength of the washing solution to that of the cultivation medium could almost completely avoid this problem. Gram-positive strains did not show significant leakage independent of the washing solution. Fast filtration with sampling times of several seconds prior to extraction appears to be a suitable approach for metabolites with relatively high intracellular level and low turnover such as amino acids or TCA cycle intermediates. Comparison of metabolite levels in the culture supernatant and the cell interior revealed that the common assumption of whole broth quenching protocols attributing the metabolites found exclusively to the intracellular pools may not be valid in many cases. In such cases a differential approach correcting for medium-contained metabolites is required.

International audience; Liquid chromatography tandem mass spectrometry coupling is a highly sensitive and specific technique allowing molecule detection in the femtomolar range. This article introduces a straightforward approach to apply this technique in 13C metabolic flux analysis. Based on a theoretical analysis of the correlation between molecule ions and corresponding fragments, a method was developed to determine the carbon labeling of intracellular metabolites without increasing the number of measurements per metabolite compared with direct molecule ion analysis. The method was applied to phosphorylated metabolites because their fragmentation results in high yields of [PO3]− and/or [H2PO4]− ions. Comparing the accuracy of the carbon labeling determination of phosphorylated metabolites between direct analysis of the molecule ions with that of corresponding phosphate fragment ions, it could be demonstrated that the introduced approach resulted in significantly higher accuracy and sensitivity for all tested metabolites. When applying the techniques to Escherichia coli cell extracts, 2 μg cell dry weight per injection was sufficient to determine the natural abundances of the carbon fractions m and m + 1 from six phosphorylated metabolites with high accuracy, predestining the approach for very small cultivation volumes in the microliter range.