Acetate is a beneficial nutrient for E. coli at low glycolytic flux.

Acetate, a major by-product of glycolytic metabolism in Escherichia coli and many other microorganisms, has long been considered a toxic waste compound that inhibits microbial growth. This counterproductive auto-inhibition represents a major problem in biotechnology and has puzzled the scientific community for decades. Recent studies have however revealed that acetate is also a co-substrate of glycolytic nutrients and a global regulator of E. coli metabolism and physiology. Here, we used a systems biology strategy to investigate the mutual regulation of glycolytic and acetate metabolism in E. coli. Computational and experimental analyses demonstrate that decreasing the glycolytic flux enhances co-utilization of acetate with glucose. Acetate metabolism thus compensates for the reduction in glycolytic flux and eventually buffers carbon uptake so that acetate, rather than being toxic, actually enhances E. coli growth under these conditions. We validated this mechanism using three orthogonal strategies: chemical inhibition of glucose uptake, glycolytic mutant strains, and alternative substrates with a natively low glycolytic flux. In summary, acetate makes E. coli more robust to glycolytic perturbations and is a valuable nutrient, with a beneficial effect on microbial growth.

Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control.

For engineered microorganisms, the production of heterologous proteins that are often useless to host cells represents a burden on resources, which have to be shared with normal cellular processes. Within a certain metabolic leeway, this competitive process has no impact on growth. However, once this leeway, or free capacity, is fully utilized, the extra load becomes a metabolic burden that inhibits cellular processes and triggers a broad cellular response, reducing cell growth and often hindering the production of heterologous proteins. In this study, we sought to characterize the metabolic rearrangements occurring in the central metabolism of Pseudomonas putida at different levels of metabolic load. To this end, we constructed a P. putida KT2440 strain that expressed two genes encoding fluorescent proteins, one in the genome under constitutive expression to monitor the free capacity, and the other on an inducible plasmid to probe heterologous protein production. We found that metabolic fluxes are considerably reshuffled, especially at the level of periplasmic pathways, as soon as the metabolic load exceeds the free capacity. Heterologous protein production leads to the decoupling of anabolism and catabolism, resulting in large excess energy production relative to the requirements of protein biosynthesis. Finally, heterologous protein production was found to exert a stronger control on carbon fluxes than on energy fluxes, indicating that the flexible nature of P. putida's central metabolic network is solicited to sustain energy production.

Microplastic-Free Microcapsules Using Supramolecular Self-Assembly of Bis-Urea Molecules at an Emulsion Interface.

Encapsulation technology is well established for entrapping active ingredients within an outer shell for their protection and controlled release. However, many solutions employed industrially use nondegradable cross-linked synthetic polymers for shell formation. To curb rising microplastic pollution, regulatory policies are forcing industries to substitute the use of such intentionally added microplastics with environmentally friendly alternatives. This work demonstrates a one-pot process to make microplastic-free microcapsules using supramolecular self-assembly of bis-ureas. Molecular bis-urea species generated in-situ spontaneously self-assemble at the interface of an oil-in-water emulsion via hydrogen bonding to form a shell held together by noncovalent bonds. In addition, Laponite nanodiscs were introduced in the formulation to restrict aggregation observed during the self-assembly and to reduce the porosity of the shell, leading to well-dispersed microcapsules (mean Sauter diameter d [3,2] ∼ 5 µm) with high encapsulation efficiency (∼99%). Accelerated release tests revealed an increase in characteristic release time of the active by more than an order of magnitude after encapsulation. The mechanical strength parameters of these capsules were comparable to some of the commercial, nondegradable melamine-formaldehyde microcapsules. With mild operating conditions in an aqueous environment, this technology has real potential to offer an industrially viable method for producing microplastic-free microcapsules.

High throughput 13C-metabolic flux analysis of 3-hydroxypropionic acid producing Pichia pastoris reveals limited availability of acetyl-CoA and ATP due to tight control of the glycolytic flux.

BACKGROUND: Production of 3-hydroxypropionic acid (3-HP) through the malonyl-CoA pathway has yielded promising results in Pichia pastoris (Komagataella phaffii), demonstrating the potential of this cell factory to produce this platform chemical and other acetyl-CoA-derived products using glycerol as a carbon source. However, further metabolic engineering of the original P. pastoris 3-HP-producing strains resulted in unexpected outcomes, e.g., significantly lower product yield and/or growth rate. To gain an understanding on the metabolic constraints underlying these observations, the fluxome (metabolic flux phenotype) of ten 3-HP-producing P. pastoris strains has been characterized using a high throughput 13C-metabolic flux analysis platform. Such platform enabled the operation of an optimised workflow to obtain comprehensive maps of the carbon flux distribution in the central carbon metabolism in a parallel-automated manner, thereby accelerating the time-consuming strain characterization step in the design-build-test-learn cycle for metabolic engineering of P. pastoris. RESULTS: We generated detailed maps of the carbon fluxes in the central carbon metabolism of the 3-HP producing strain series, revealing the metabolic consequences of different metabolic engineering strategies aimed at improving NADPH regeneration, enhancing conversion of pyruvate into cytosolic acetyl-CoA, or eliminating by-product (arabitol) formation. Results indicate that the expression of the POS5 NADH kinase leads to a reduction in the fluxes of the pentose phosphate pathway reactions, whereas an increase in the pentose phosphate pathway fluxes was observed when the cytosolic acetyl-CoA synthesis pathway was overexpressed. Results also show that the tight control of the glycolytic flux hampers cell growth due to limited acetyl-CoA biosynthesis. When the cytosolic acetyl-CoA synthesis pathway was overexpressed, the cell growth increased, but the product yield decreased due to higher growth-associated ATP costs. Finally, the six most relevant strains were also cultured at pH 3.5 to assess the effect of a lower pH on their fluxome. Notably, similar metabolic fluxes were observed at pH 3.5 compared to the reference condition at pH 5. CONCLUSIONS: This study shows that existing fluoxomics workflows for high-throughput analyses of metabolic phenotypes can be adapted to investigate P. pastoris, providing valuable information on the impact of genetic manipulations on the metabolic phenotype of this yeast. Specifically, our results highlight the metabolic robustness of P. pastoris's central carbon metabolism when genetic modifications are made to increase the availability of NADPH and cytosolic acetyl-CoA. Such knowledge can guide further metabolic engineering of these strains. Moreover, insights into the metabolic adaptation of P. pastoris to an acidic pH have also been obtained, showing the capability of the fluoxomics workflow to assess the metabolic impact of environmental changes.

Microencapsulation of High-Content Actives Using Biodegradable Silk Materials.

There is a compelling need across several industries to substitute non-degradable, intentionally added microplastics with biodegradable alternatives. Nonetheless, stringent performance criteria in actives' controlled release and manufacturing at scale of emerging materials hinder the replacement of polymers used for microplastics fabrication with circular ones. Here, the authors demonstrate that active microencapsulation in a structural protein such as silk fibroin can be achieved by modulating protein protonation and chain relaxation at the point of material assembly. Silk fibroin micelles' size is tuned from several to hundreds of nanometers, enabling the manufacturing-by retrofitting spray drying and spray freeze drying techniques-of microcapsules with tunable morphology and structure, that is, hollow-spongy, hollow-smooth, hollow crumpled matrices, and hollow crumpled multi-domain. Microcapsules degradation kinetics and sustained release of soluble and insoluble payloads typically used in cosmetic and agriculture applications are controlled by modulating fibroin's beta-sheet content from 20% to near 40%. Ultraviolet-visible studies indicate that burst release of a commonly used herbicide (i.e., saflufenacil) significantly decreases from 25% to 0.8% via silk fibroin microencapsulation. As a proof-of-concept for agrochemicals applications, a 6-day greenhouse trial demonstrates that saflufenacil delivered on corn plants via silk microcapsules reduces crop injury when compared to the non-encapsulated version.

Improved NMR Detection of Phospho-Metabolites in a Complex Mixture.

Phosphorylated metabolites are omnipresent in cells, but their analytical characterization faces several technical hurdles. Here, we detail an improved NMR workflow aimed at assigning the high-resolution subspectrum of the phospho-metabolites in a complex mixture. Combining a pure absorption J-resolved spectrum (Pell, A. J.; J. Magn. Reson. 2007, 189 (2), 293-299) with alternate on- and off-switching of the 31P coupling interaction during the t1 evolution with a pure in-phase (PIP) HSQMBC experiment (Castañar, L.; Angew. Chem., Int. Ed. 2014, 53 (32), 8379-8382) without or with total correlation spectroscopy (TOCSY) transfer during the insensitive nuclei enhancement by polarization transfer (INEPT) gives access to selective identification of the individual subspectra of the phosphorylated metabolites. Returning to the initial J-res spectra, we can extract with optimal resolution the full trace for the individual phospho-metabolites, which can then be transposed on the high-resolution quantitative one dimensional spectrum.

IsoSolve: An Integrative Framework to Improve Isotopic Coverage and Consolidate Isotopic Measurements by Mass Spectrometry and/or Nuclear Magnetic Resonance.

Stable-isotope labeling experiments are widely used to investigate the topology and functioning of metabolic networks. Label incorporation into metabolites can be quantified using a broad range of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy methods, but in general, no single approach can completely cover isotopic space, even for small metabolites. The number of quantifiable isotopic species could be increased and the coverage of isotopic space improved by integrating measurements obtained by different methods; however, this approach has remained largely unexplored because no framework able to deal with partial, heterogeneous isotopic measurements has yet been developed. Here, we present a generic computational framework based on symbolic calculus that can integrate any isotopic data set by connecting measurements to the chemical structure of the molecules. As a test case, we apply this framework to isotopic analyses of amino acids, which are ubiquitous to life, central to many biological questions, and can be analyzed by a broad range of MS and NMR methods. We demonstrate how this integrative framework helps to (i) clarify and improve the coverage of isotopic space, (ii) evaluate the complementarity and redundancy of different techniques, (iii) consolidate isotopic data sets, (iv) design experiments, and (v) guide future analytical developments. This framework, which can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform, has been implemented in IsoSolve (available at https://github.com/MetaSys-LISBP/IsoSolve and https://pypi.org/project/IsoSolve), an open-source software that can be readily integrated into data analysis pipelines.

Functional Analysis of Deoxyhexose Sugar Utilization in Escherichia coli Reveals Fermentative Metabolism under Aerobic Conditions.

l-Rhamnose and l-fucose are the two main 6-deoxyhexoses Escherichia coli can use as carbon and energy sources. Deoxyhexose metabolism leads to the formation of lactaldehyde, whose fate depends on oxygen availability. Under anaerobic conditions, lactaldehyde is reduced to 1,2-propanediol, whereas under aerobic conditions, it should be oxidized into lactate and then channeled into the central metabolism. However, although this all-or-nothing view is accepted in the literature, it seems overly simplistic since propanediol is also reported to be present in the culture medium during aerobic growth on l-fucose. To clarify the functioning of 6-deoxyhexose sugar metabolism, a quantitative metabolic analysis was performed to determine extra- and intracellular fluxes in E. coli K-12 MG1655 (a laboratory strain) and in E. coli Nissle 1917 (a human commensal strain) during anaerobic and aerobic growth on l-rhamnose and l-fucose. As expected, lactaldehyde is fully reduced to 1,2-propanediol under anoxic conditions, allowing complete reoxidation of the NADH produced by glyceraldehyde-3-phosphate-dehydrogenase. We also found that net ATP synthesis is ensured by acetate production. More surprisingly, lactaldehyde is also primarily reduced into 1,2-propanediol under aerobic conditions. For growth on l-fucose, 13C-metabolic flux analysis revealed a large excess of available energy, highlighting the need to better characterize ATP utilization processes. The probiotic E. coli Nissle 1917 strain exhibits similar metabolic traits, indicating that they are not the result of the K-12 strain's prolonged laboratory use. IMPORTANCE E. coli's ability to survive in, grow in, and colonize the gastrointestinal tract stems from its use of partially digested food and hydrolyzed glycosylated proteins (mucins) from the intestinal mucus layer as substrates. These include l-fucose and l-rhamnose, two 6-deoxyhexose sugars, whose catabolic pathways have been established by genetic and biochemical studies. However, the functioning of these pathways has only partially been elucidated. Our quantitative metabolic analysis provides a comprehensive picture of 6-deoxyhexose sugar metabolism in E. coli under anaerobic and aerobic conditions. We found that 1,2-propanediol is a major by-product under both conditions, revealing the key role of fermentative pathways in 6-deoxyhexose sugar metabolism. This metabolic trait is shared by both E. coli strains studied here, a laboratory strain and a probiotic strain. Our findings add to our understanding of E. coli's metabolism and of its functioning in the bacterium's natural environment.

ScalaFlux: A scalable approach to quantify fluxes in metabolic subnetworks.

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.

Simultaneous Measurement of Metabolite Concentration and Isotope Incorporation by Mass Spectrometry.

Studies of the topology, functioning, and regulation of metabolic systems are based on two main types of information that can be measured by mass spectrometry: the (absolute or relative) concentration of metabolites and their isotope incorporation in 13C-labeling experiments. These data are currently obtained from two independent experiments because the 13C-labeled internal standard (IS) used to determine the concentration of a given metabolite overlaps the 13C-mass fractions from which its 13C-isotopologue distribution (CID) is quantified. Here, we developed a generic method with a dedicated processing workflow to obtain these two sets of information simultaneously in a unique sample collected from a single cultivation, thereby reducing by a factor of 2 both the number of cultivations to perform and the number of samples to collect, prepare, and analyze. The proposed approach is based on an IS labeled with other isotope(s) that can be resolved from the 13C-mass fractions of interest. As proof-of-principle, we analyzed amino acids using a doubly labeled 15N13C-cell extract as IS. Extensive evaluation of the proposed approach shows a similar accuracy and precision compared to state-of-the-art approaches. We demonstrate the value of this approach by investigating the dynamic response of amino acids metabolism in mammalian cells upon activation of the protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK), a key component of the unfolded protein response. Integration of metabolite concentrations and isotopic profiles reveals a reduced de novo biosynthesis of amino acids upon PERK activation. The proposed approach is generic and can be applied to other (micro)organisms, analytical platforms, isotopic tracers, or classes of metabolites.

IsoCor: isotope correction for high-resolution MS labeling experiments.

SUMMARY: Mass spectrometry (MS) is widely used for isotopic studies of metabolism and other (bio)chemical processes. Quantitative applications in systems and synthetic biology require to correct the raw MS data for the contribution of naturally occurring isotopes. Several tools are available to correct low-resolution MS data, and recent developments made substantial improvements by introducing resolution-dependent correction methods, hence opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless, current HRMS correction methods partly fail to determine which isotopic species are resolved from the tracer isotopologues and should thus be corrected. We present an updated version of our isotope correction software (IsoCor) with a novel correction algorithm which ensures to accurately exploit any chemical species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes a novel graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. AVAILABILITY AND IMPLEMENTATION: IsoCor v2 is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/ and https://isocor.readthedocs.io/.

Increasing field strength versus advanced isotope labeling for NMR-based fluxomics.

Nuclear magnetic resonance (NMR)-based fluxomics seeks to measure the incorporation of isotope labels in selected metabolites to follow kinetically the synthesis of the latter. It can however equally be used to understand the biosynthetic origin of the same metabolites. We investigate here different NMR approaches to optimize such experiments in terms of resolution and time requirement. Using the isoleucine biosynthesis as an example, we explore the use of different field strengths ranging from 500 MHz to 1.1 GHz. Because of the different field dependence of chemical shift and heteronuclear J couplings, the spectra change at different field strengths. We equally explore the approach to silence the leucine/valine methyl signals through the use of a suitable deuterated precursor, thereby allowing selective observation of the Ile 13 C labeling pattern. Combining both approaches, we arrive at an efficient procedure for the NMR-based exploration of Ile biosynthesis.

Integrated pH Measurement during Reaction Monitoring with Dual-Reception 1H-31P NMR Spectroscopy.

Simultaneous detection of 1H and 31P NMR signals through a dual-detection scheme with two receivers allows monitoring of both the signals of a molecule and the pH of the solution through the resonance of the inorganic phosphate. We evaluate here the method in terms of sensitivity and ease of implementation and show that the additional information obtained without any loss of information or increase in measuring time can be of practical importance in a number of biochemical systems.

Chemical and Metabolic Controls on Dihydroxyacetone Metabolism Lead to Suboptimal Growth of Escherichia coli.

In this work, we shed light on the metabolism of dihydroxyacetone (DHA), a versatile, ubiquitous, and important intermediate for various chemicals in industry, by analyzing its metabolism at the system level in Escherichia coli Using constraint-based modeling, we show that the growth of E. coli on DHA is suboptimal and identify the potential causes. Nuclear magnetic resonance analysis shows that DHA is degraded nonenzymatically into substrates known to be unfavorable to high growth rates. Transcriptomic analysis reveals that DHA promotes genes involved in biofilm formation, which may reduce the bacterial growth rate. Functional analysis of the genes involved in DHA metabolism proves that under the aerobic conditions used in this study, DHA is mainly assimilated via the dihydroxyacetone kinase pathway. In addition, these results show that the alternative routes of DHA assimilation (i.e., the glycerol and fructose-6-phosphate aldolase pathways) are not fully activated under our conditions because of anaerobically mediated hierarchical control. These pathways are therefore certainly unable to sustain fluxes as high as the ones predicted in silico for optimal aerobic growth on DHA. Overexpressing some of the genes in these pathways releases these constraints and restores the predicted optimal growth on DHA.IMPORTANCE DHA is an attractive triose molecule with a wide range of applications, notably in cosmetics and the food and pharmaceutical industries. DHA is found in many species, from microorganisms to humans, and can be used by Escherichia coli as a growth substrate. However, knowledge about the mechanisms and regulation of this process is currently lacking, motivating our investigation of DHA metabolism in E. coli We show that under aerobic conditions, E. coli growth on DHA is far from optimal and is hindered by chemical, hierarchical, and possibly allosteric constraints. We show that optimal growth on DHA can be restored by releasing the hierarchical constraint. These results improve our understanding of DHA metabolism and are likely to help unlock biotechnological applications involving DHA as an intermediate, such as the bioconversion of glycerol or C1 substrates into value-added chemicals.

Functional analysis of isoprenoid precursors biosynthesis by quantitative metabolomics and isotopologue profiling.

INTRODUCTION: Isoprenoids are amongst the most abundant and diverse biological molecules and are involved in a broad range of biological functions. Functional understanding of their biosynthesis is thus key in many fundamental and applicative fields, including systems biology, medicine and biotechnology. However, available methods do not yet allow accurate quantification and tracing of stable isotopes incorporation for all the isoprenoids precursors. OBJECTIVES: We developed and validated a complete methodology for quantitative metabolomics and isotopologue profiling of isoprenoid precursors in the yeast Saccharomyces cerevisiae. METHODS: This workflow covers all the experimental and computational steps from sample collection and preparation to data acquisition and processing. It also includes a novel quantification method based on liquid chromatography coupled to high-resolution mass spectrometry. Method validation followed the Metabolomics Standards Initiative guidelines. RESULTS: This workflow ensures accurate absolute quantification (RSD < 20%) of all mevalonate and prenyl pyrophosphates intermediates with a high sensitivity over a large linear range (from 0.1 to 50 pmol). In addition, we demonstrate that this workflow brings crucial information to design more efficient phytoene producers. Results indicate stable turnover rates of prenyl pyrophosphate intermediates in the constructed strains and provide quantitative information on the change of the biosynthetic flux of phytoene precursors. CONCLUSION: This methodology fills one of the last technical gaps for functional studies of isoprenoids biosynthesis and should be applicable to other eukaryotic and prokaryotic (micro)organisms after adaptation of some organism-dependent steps. This methodology also opens the way to 13C-metabolic flux analysis of isoprenoid biosynthesis.

Improved Isotopic Profiling by Pure Shift Heteronuclear 2D J-Resolved NMR Spectroscopy.

Quantitative information on the carbon isotope content of metabolites is essential for flux analysis. Whereas this information is in principle present in proton NMR spectra through both direct and long-range heteronuclear coupling constants, spectral overlap and homonuclear coupling constants both hinder its extraction. We demonstrate here how pure shift 2D J-resolved NMR spectroscopy can simultaneously remove the homonuclear couplings and separate the chemical shift information from the heteronuclear coupling patterns. We demonstrate the power of this method on cell lysates from different bacterial cultures and investigate in detail the branched chain amino acid biosynthesis.

Methodology for the Validation of Isotopic Analyses by Mass Spectrometry in Stable-Isotope Labeling Experiments.

Stable-isotope labeling experiments (ILEs) are widely used to investigate the topology and operation of metabolic networks. The quality of isotopic data collected in ILEs is of utmost importance to ensure reliable biological interpretations, but current evaluation approaches are limited due to a lack of suitable reference material and relevant evaluation criteria. In this work, we present a complete methodology to evaluate mass spectrometry (MS) methods used for quantitative isotopic studies of metabolic systems. This methodology, based on a biological sample containing metabolites with controlled labeling patterns, exploits different quality metrics specific to isotopic analyses (accuracy and precision of isotopologue masses, abundances, and mass shifts and isotopic working range). We applied this methodology to evaluate a novel LC-MS method for the analysis of amino acids, which was tested on high resolution (Orbitrap operating in full scan mode) and low resolution (triple quadrupole operating in multiple reaction monitoring mode) mass spectrometers. Results show excellent accuracy and precision over a large working range and revealed matrix-specific as well as mode-specific characteristics. The proposed methodology can identify reliable (and unreliable) isotopic data in an easy and straightforward way and efficiently supports the identification of sources of systematic biases as well as of the main factors that influence the overall accuracy and precision of measurements. This approach is generic and can be used to validate isotopic analyses on different matrices, analytical platforms, labeled elements, or classes of metabolites. It is expected to strengthen the reliability of isotopic measurements and thereby the biological value of ILEs.

Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli.

The metabolism of microorganisms is regulated through two main mechanisms: changes of enzyme capacities as a consequence of gene expression modulation ("hierarchical control") and changes of enzyme activities through metabolite-enzyme interactions. An increasing body of evidence indicates that hierarchical control is insufficient to explain metabolic behaviors, but the system-wide impact of metabolic regulation remains largely uncharacterized. To clarify its role, we developed and validated a detailed kinetic model of Escherichia coli central metabolism that links growth to environment. Metabolic control analyses confirm that the control is widely distributed across the network and highlight strong interconnections between all the pathways. Exploration of the model solution space reveals that several robust properties emerge from metabolic regulation, from the molecular level (e.g. homeostasis of total metabolite pool) to the overall cellular physiology (e.g. coordination of carbon uptake, catabolism, energy and redox production, and growth), while allowing a large degree of flexibility at most individual metabolic steps. These properties have important physiological implications for E. coli and significantly expand the self-regulating capacities of its metabolism.

Stable Isotope Labeling Highlights Enhanced Fatty Acid and Lipid Metabolism in Human Acute Myeloid Leukemia.

Background: In Acute Myeloid Leukemia (AML), a complete response to chemotherapy is usually obtained after conventional chemotherapy but overall patient survival is poor due to highly frequent relapses. As opposed to chronic myeloid leukemia, B lymphoma or multiple myeloma, AML is one of the rare malignant hemopathies the therapy of which has not significantly improved during the past 30 years despite intense research efforts. One promising approach is to determine metabolic dependencies in AML cells. Moreover, two key metabolic enzymes, isocitrate dehydrogenases (IDH1/2), are mutated in more than 15% of AML patient, reinforcing the interest in studying metabolic reprogramming, in particular in this subgroup of patients. Methods: Using a multi-omics approach combining proteomics, lipidomics, and isotopic profiling of [U-13C] glucose and [U-13C] glutamine cultures with more classical biochemical analyses, we studied the impact of the IDH1 R132H mutation in AML cells on lipid biosynthesis. Results: Global proteomic and lipidomic approaches showed a dysregulation of lipid metabolism, especially an increase of phosphatidylinositol, sphingolipids (especially few species of ceramide, sphingosine, and sphinganine), free cholesterol and monounsaturated fatty acids in IDH1 mutant cells. Isotopic profiling of fatty acids revealed that higher lipid anabolism in IDH1 mutant cells corroborated with an increase in lipogenesis fluxes. Conclusions: This integrative approach was efficient to gain insight into metabolism and dynamics of lipid species in leukemic cells. Therefore, we have determined that lipid anabolism is strongly reprogrammed in IDH1 mutant AML cells with a crucial dysregulation of fatty acid metabolism and fluxes, both being mediated by 2-HG (2-Hydroxyglutarate) production.

15N-NMR-Based Approach for Amino Acids-Based 13C-Metabolic Flux Analysis of Metabolism.

NMR analysis of the isotope incorporation in amino acids can be used to derive information about the topology and operation of cellular metabolism. Although traditionally performed by 1H and/or 13C NMR, we present here novel experiments that exploit the 15N nucleus to derive the same information with increased efficiency. Combined with a novel Hα-13CO experiment, we increase the coverage of the isotopic space that can be probed by obtaining the complete distribution of isotopic species for the first two carbons of amino acids in cellular biomass hydrolysates. Our approach was evaluated using as reference material a biologically produced sample containing 15N-labeled metabolites with fully predictable 13C-labeling patterns. Results show excellent agreement between measured and expected isotopomer abundances for the different NMR experiments, with an accuracy and precision within 1%. We also demonstrate how these experiments can give detailed information about metabolic fluxes depending on the expression level of a critical enzyme. Hence, exploiting the 15N labeling of a cellular sample accelerates subsequent analysis of the hydrolyzed biomass and increases the coverage of isotopomers that can be quantified, making it a promising tool to increase the throughput and the resolution of 13C-fluxomics studies.