Exploring the Glucose Fluxotype of the E. coli y-ome Using High-Resolution Fluxomics.

We have developed a robust workflow to measure high-resolution fluxotypes (metabolic flux phenotypes) for large strain libraries under fully controlled growth conditions. This was achieved by optimizing and automating the whole high-throughput fluxomics process and integrating all relevant software tools. This workflow allowed us to obtain highly detailed maps of carbon fluxes in the central carbon metabolism in a fully automated manner. It was applied to investigate the glucose fluxotypes of 180 Escherichia coli strains deleted for y-genes. Since the products of these y-genes potentially play a role in a variety of metabolic processes, the experiments were designed to be agnostic as to their potential metabolic impact. The obtained data highlight the robustness of E. coli's central metabolism to y-gene deletion. For two y-genes, deletion resulted in significant changes in carbon and energy fluxes, demonstrating the involvement of the corresponding y-gene products in metabolic function or regulation. This work also introduces novel metrics to measure the actual scope and quality of high-throughput fluxomics investigations.

Targeting MDM2-dependent serine metabolism as a therapeutic strategy for liposarcoma.

Well-differentiated and dedifferentiated liposarcomas (LPSs) are characterized by a systematic amplification of the MDM2 oncogene, which encodes a key negative regulator of the p53 pathway. The molecular mechanisms underlying MDM2 overexpression while sparing wild-type p53 in LPS remain poorly understood. Here, we show that the p53-independent metabolic functions of chromatin-bound MDM2 are exacerbated in LPS and mediate an addiction to serine metabolism that sustains nucleotide synthesis and tumor growth. Treatment of LPS cells with Nutlin-3A, a pharmacological inhibitor of the MDM2-p53 interaction, stabilized p53 but unexpectedly enhanced MDM2-mediated control of serine metabolism by increasing its recruitment to chromatin, likely explaining the poor clinical efficacy of this class of MDM2 inhibitors. In contrast, genetic or pharmacological inhibition of chromatin-bound MDM2 by SP141, a distinct MDM2 inhibitor triggering its degradation, or interfering with de novo serine synthesis, impaired LPS growth both in vitro and in clinically relevant patient-derived xenograft models. Our data indicate that targeting MDM2 functions in serine metabolism represents a potential therapeutic strategy for LPS.

Sink/Source Balance of Leaves Influences Amino Acid Pools and Their Associated Metabolic Fluxes in Winter Oilseed Rape (Brassica napus L.).

Nitrogen remobilization processes from source to sink tissues in plants are determinant for seed yield and their implementation results in a complete reorganization of the primary metabolism during sink/source transition. Here, we decided to characterize the impact of the sink/source balance on amino acid metabolism in the leaves of winter oilseed rape grown at the vegetative stage. We combined a quantitative metabolomics approach with an instationary 15N-labeling experiment by using [15N]L-glycine as a metabolic probe on leaf ranks with a gradual increase in their source status. We showed that the acquisition of the source status by leaves was specifically accompanied by a decrease in asparagine, glutamine, proline and S-methyl-l-cysteine sulphoxide contents and an increase in valine and threonine contents. Dynamic analysis of 15N enrichment and concentration of amino acids revealed gradual changes in the dynamics of amino acid metabolism with respect to the sink/source status of leaf ranks. Notably, nitrogen assimilation into valine, threonine and proline were all decreased in source leaves compared to sink leaves. Overall, our results suggested a reduction in de novo amino acid biosynthesis during sink/source transition at the vegetative stage.

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/.

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.

Identification of an analgesic lipopeptide produced by the probiotic Escherichia coli strain Nissle 1917.

Administration of the probiotic Escherichia coli strain Nissle 1917 (EcN) decreases visceral pain associated with irritable bowel syndrome. Mutation of clbA, a gene involved in the biosynthesis of secondary metabolites, including colibactin, was previously shown to abrogate EcN probiotic activity. Here, we show that EcN, but not an isogenic clbA mutant, produces an analgesic lipopeptide. We characterize lipoamino acids and lipopeptides produced by EcN but not by the mutant by online liquid chromatography mass spectrometry. One of these lipopeptides, C12AsnGABAOH, is able to cross the epithelial barrier and to inhibit calcium flux induced by nociceptor activation in sensory neurons via the GABAB receptor. C12AsnGABAOH inhibits visceral hypersensitivity induced by nociceptor activation in mice. Thus, EcN produces a visceral analgesic, which could be the basis for the development of new visceral pain therapies.

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.

E4F1 controls a transcriptional program essential for pyruvate dehydrogenase activity.

The mitochondrial pyruvate dehydrogenase (PDH) complex (PDC) acts as a central metabolic node that mediates pyruvate oxidation and fuels the tricarboxylic acid cycle to meet energy demand. Here, we reveal another level of regulation of the pyruvate oxidation pathway in mammals implicating the E4 transcription factor 1 (E4F1). E4F1 controls a set of four genes [dihydrolipoamide acetlytransferase (Dlat), dihydrolipoyl dehydrogenase (Dld), mitochondrial pyruvate carrier 1 (Mpc1), and solute carrier family 25 member 19 (Slc25a19)] involved in pyruvate oxidation and reported to be individually mutated in human metabolic syndromes. E4F1 dysfunction results in 80% decrease of PDH activity and alterations of pyruvate metabolism. Genetic inactivation of murine E4f1 in striated muscles results in viable animals that show low muscle PDH activity, severe endurance defects, and chronic lactic acidemia, recapitulating some clinical symptoms described in PDC-deficient patients. These phenotypes were attenuated by pharmacological stimulation of PDH or by a ketogenic diet, two treatments used for PDH deficiencies. Taken together, these data identify E4F1 as a master regulator of the PDC.

Chromatin-Bound MDM2 Regulates Serine Metabolism and Redox Homeostasis Independently of p53.

The mouse double minute 2 (MDM2) oncoprotein is recognized as a major negative regulator of the p53 tumor suppressor, but growing evidence indicates that its oncogenic activities extend beyond p53. Here, we show that MDM2 is recruited to chromatin independently of p53 to regulate a transcriptional program implicated in amino acid metabolism and redox homeostasis. Identification of MDM2 target genes at the whole-genome level highlights an important role for ATF3/4 transcription factors in tethering MDM2 to chromatin. MDM2 recruitment to chromatin is a tightly regulated process that occurs during oxidative stress and serine/glycine deprivation and is modulated by the pyruvate kinase M2 (PKM2) metabolic enzyme. Depletion of endogenous MDM2 in p53-deficient cells impairs serine/glycine metabolism, the NAD(+)/NADH ratio, and glutathione (GSH) recycling, impacting their redox state and tumorigenic potential. Collectively, our data illustrate a previously unsuspected function of chromatin-bound MDM2 in cancer cell metabolism.

Validation of a reference method for total cholesterol measurement in human serum and assignation of reference values to proficiency testing samples.

OBJECTIVES: Our objective was to develop a reference method to measure total cholesterol in human serum, in order to assign values and assess the accuracy of field methods in French clinical laboratories. DESIGN AND METHODS: A reference method based on gas chromatography coupled with mass spectrometry and isotope dilution (GC-IDMS) was developed and validated. It was then used to assign reference values to five frozen serum samples from voluntary proficiency testing schemes gathering 170 French clinical laboratories. Three peer groups were defined and bias against the reference method target value was calculated. RESULTS: Accuracy of the reference method was assessed against NIST SRM 1951b. Bias of the reference method was less than 0.5% and imprecision was less than 1.0%. Our study indicated that field methods tended to overestimate total cholesterol concentration, mean bias being +5.02% ± 1.02%. The most popular methods (phenolic chromogen with spectrophotometric detection, 80% of participants) exhibited the highest bias (peer group mean bias: +5.51 ± 1.24%). Neither these methods nor those using a non-phenolic chromogen with reflectometric detection (10% of participants, peer group mean bias: +4.20 ± 1.44%) met NCEP recommendations according to which bias should be less than 3%. Only the methods using a non phenolic chromogen with a spectrophotometric detection met these recommendations (10% of participants, peer group mean bias: +1.39 ± 2.75%). CONCLUSIONS: As all three peer groups provided positively biased results, the consensus mean usually used to assess the trueness of routine methods is biased as well, which results in an erroneous estimation of method bias. Therefore, this study highlights the value added by reference method target values to assess trueness of field methods and monitor performance of clinical laboratories.