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.

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.

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/.

Biofilm microenvironment induces a widespread adaptive amino-acid fermentation pathway conferring strong fitness advantage in Escherichia coli.

Bacterial metabolism has been studied primarily in liquid cultures, and exploration of other natural growth conditions may reveal new aspects of bacterial biology. Here, we investigate metabolic changes occurring when Escherichia coli grows as surface-attached biofilms, a common but still poorly characterized bacterial lifestyle. We show that E. coli adapts to hypoxic conditions prevailing within biofilms by reducing the amino acid threonine into 1-propanol, an important industrial commodity not known to be naturally produced by Enterobacteriaceae. We demonstrate that threonine degradation corresponds to a fermentation process maintaining cellular redox balance, which confers a strong fitness advantage during anaerobic and biofilm growth but not in aerobic conditions. Whereas our study identifies a fermentation pathway known in Clostridia but previously undocumented in Enterobacteriaceae, it also provides novel insight into how growth in anaerobic biofilm microenvironments can trigger adaptive metabolic pathways edging out competition with in mixed bacterial communities.

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.

Absolute Quantification of ppGpp and pppGpp by Double-Spike Isotope Dilution Ion Chromatography-High-Resolution Mass Spectrometry.

Guanosine 5'-diphosphate 3'-diphosphate (ppGpp) and guanosine 5'-triphosphate 3'-diphosphate (pppGpp) play a central role in the adaptation of bacterial and plant cells to nutritional and environmental stresses and in bacterial resistance to antibiotics. These compounds have historically been detected and quantified by two-dimensional thin-layer chromatography of 32P-radiolabeled nucleotides. We report a new method to quantify ppGpp and pppGpp in complex biochemical matrix using ion chromatography coupled to high-resolution mass spectrometry. The method is based on isotopic dilution mass spectrometry (IDMS) using 13C to accurately quantify the nucleotides. However, the loss of a phosphate group from pppGpp during the sample preparation process results in the erroneous quantification of ppGpp. This bias was corrected by adding an extra 15N isotope dilution dimension. This double-spike IDMS method was applied to quantify the ppGpp and pppGpp in Escherichia coli and in a mutant strain deleted for gppA (encoding the ppGpp phosphohydrolase) before and after exposure of both strains to serine hydroxamate, known to trigger the accumulation of these nucleotides.

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.

The post-transcriptional regulatory system CSR controls the balance of metabolic pools in upper glycolysis of Escherichia coli.

Metabolic control in Escherichia coli is a complex process involving multilevel regulatory systems but the involvement of post-transcriptional regulation is uncertain. The post-transcriptional factor CsrA is stated as being the only regulator essential for the use of glycolytic substrates. A dozen enzymes in the central carbon metabolism (CCM) have been reported as potentially controlled by CsrA, but its impact on the CCM functioning has not been demonstrated. Here, a multiscale analysis was performed in a wild-type strain and its isogenic mutant attenuated for CsrA (including growth parameters, gene expression levels, metabolite pools, abundance of enzymes and fluxes). Data integration and regulation analysis showed a coordinated control of the expression of glycolytic enzymes. This also revealed the imbalance of metabolite pools in the csrA mutant upper glycolysis, before the phosphofructokinase PfkA step. This imbalance is associated with a glucose-phosphate stress. Restoring PfkA activity in the csrA mutant strain suppressed this stress and increased the mutant growth rate on glucose. Thus, the carbon storage regulator system is essential for the effective functioning of the upper glycolysis mainly through its control of PfkA. This work demonstrates the pivotal role of post-transcriptional regulation to shape the carbon metabolism.

Systems and synthetic biology perspective of the versatile plant-pathogenic and polysaccharide-producing bacterium Xanthomonas campestris.

Bacteria of the genus Xanthomonas are a major group of plant pathogens. They are hazardous to important crops and closely related to human pathogens. Being collectively a major focus of molecular phytopathology, an increasing number of diverse and intricate mechanisms are emerging by which they communicate, interfere with host signalling and keep competition at bay. Interestingly, they are also biotechnologically relevant polysaccharide producers. Systems biotechnology techniques have revealed their central metabolism and a growing number of remarkable features. Traditional analyses of Xanthomonas metabolism missed the Embden-Meyerhof-Parnas pathway (glycolysis) as being a route by which energy and molecular building blocks are derived from glucose. As a consequence of the emerging full picture of their metabolism process, xanthomonads were discovered to have three alternative catabolic pathways and they use an unusual and reversible phosphofructokinase as a key enzyme. In this review, we summarize the synthetic and systems biology methods and the bioinformatics tools applied to reconstruct their metabolic network and reveal the dynamic fluxes within their complex carbohydrate metabolism. This is based on insights from omics disciplines; in particular, genomics, transcriptomics, proteomics and metabolomics. Analysis of high-throughput omics data facilitates the reconstruction of organism-specific large- and genome-scale metabolic networks. Reconstructed metabolic networks are fundamental to the formulation of metabolic models that facilitate the simulation of actual metabolic activities under specific environmental conditions.

Plasmid-encoded biosynthetic genes alleviate metabolic disadvantages while increasing glucose conversion to shikimate in an engineered Escherichia coli strain.

Metabolic engineering strategies applied over the last two decades to produce shikimate (SA) in Escherichia coli have resulted in a battery of strains bearing many expression systems. However, the effects that these systems have on the host physiology and how they impact the production of SA are still not well understood. In this work we utilized an engineered E. coli strain to determine the consequences of carrying a vector that promotes SA production from glucose with a high-yield but that is also expected to impose a significant cellular burden. Kinetic comparisons in fermentors showed that instead of exerting a negative effect, the sole presence of the plasmid increased glucose consumption without diminishing the growth rate. By constitutively expressing a biosynthetic operon from this vector, the more active glycolytic metabolism was exploited to redirect intermediates toward the production of SA, which further increased the glucose consumption rate and avoided excess acetate production. Fluxomics and metabolomics experiments revealed a global remodeling of the carbon and energy metabolism in the production strain, where the increased SA production reduced the carbon available for oxidative and fermentative pathways. Moreover, the results showed that the production of SA relies on a specific setup of the pentose phosphate pathway, where both its oxidative and non-oxidative branches are strongly activated to supply erythrose-4-phosphate and balance the NADPH requirements. This work improves our understanding of the metabolic reorganization observed in E. coli in response to the plasmid-based expression of the SA biosynthetic pathway. Biotechnol. Bioeng. 2017;114: 1319-1330. © 2017 Wiley Periodicals, Inc.

Differential quantitative proteome analysis of Escherichia coli grown on acetate versus glucose.

Relative protein abundances of Escherichia coli MG1655 growing exponentially on minimal medium with acetate or glucose as the sole carbon source were investigated in a quantitative shotgun proteome analysis with TMT6-plex isobaric tags. Peptides were separated by high resolution high/low pH 2D-LC, using an optimized fraction pooling scheme followed by mass spectrometric analysis. Quantitative data were acquired for 2099 proteins covering 49% of the predicted E. coli proteins, showing system-wide effects of growth conditions. In total, 507 proteins showed a fold change of at least 1.5 and 205 proteins changed by more than twofold. Significant differences in abundance were observed for most of the proteins in the central carbon metabolism and in proteins relevant for amino acid and protein synthesis, processing of environmental information and scavenging of a variety of alternate carbon sources. Periplasmic-binding proteins were also more abundant on acetate, especially proteins involved in scavenging extracellular resources such as sugars. All MS data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (dataset identifier PXD003863).

Acetate Exposure Determines the Diauxic Behavior of Escherichia coli during the Glucose-Acetate Transition.

UNLABELLED: Growth of Escherichia coli on glucose in batch culture is accompanied by the excretion of acetate, which is consumed by the cells when glucose is exhausted. This glucose-acetate transition is classically described as a diauxie (two successive growth stages). Here, we investigated the physiological and metabolic properties of cells after glucose exhaustion through the analysis of growth parameters and gene expression. We found that E. coli cells grown on glucose in batch culture produce acetate and consume it after glucose exhaustion but do not grow on acetate. Acetate is catabolized, but key anabolic genes--such as the genes encoding enzymes of the glyoxylate shunt--are not upregulated, hence preventing growth. Both the induction of the latter anabolic genes and growth were observed only after prolonged exposure to low concentrations of acetate and could be accelerated by high acetate concentrations. We postulate that such decoupling between acetate catabolism and acetate anabolism might be an advantage for the survival of E. coli in the ever-changing environment of the intestine. IMPORTANCE: The glucose-acetate transition is a valuable experimental model for comprehensive investigations of metabolic adaptation and a current paradigm for developing modeling approaches in systems microbiology. Yet, the work reported in our paper demonstrates that the metabolic behavior of Escherichia coli during the glucose-acetate transition is much more complex than what has been reported so far. A decoupling between acetate catabolism and acetate anabolism was observed after glucose exhaustion, which has not been reported previously. This phenomenon could represent a strategy for optimal utilization of carbon resources during colonization and persistence of E. coli in the gut and is also of significant interest for biotechnological applications.

ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics.

We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions.

Developmental stage dependent metabolic regulation during meiotic differentiation in budding yeast.

BACKGROUND: The meiotic developmental pathway in yeast enables both differentiation of vegetative cells into haploid spores that ensure long-term survival, and recombination of the parental DNA to create genetic diversity. Despite the importance of proper metabolic regulation for the supply of building blocks and energy, little is known about the reprogramming of central metabolic pathways in meiotically differentiating cells during passage through successive developmental stages. RESULTS: Metabolic regulation during meiotic differentiation in budding yeast was analysed by integrating information on genome-wide transcriptional activity, 26 enzymatic activities in the central metabolism, the dynamics of 67 metabolites, and a metabolic flux analysis at mid-stage meiosis. Analyses of mutants arresting sporulation at defined stages demonstrated that metabolic reprogramming is tightly controlled by the progression through the developmental pathway. The correlation between transcript levels and enzymatic activities in the central metabolism varies significantly in a developmental-stage dependent manner. The complete loss of phosphofructokinase activity at mid-stage meiosis enables a unique setup of the glycolytic pathway which facilitates carbon flux repartitioning into synthesis of spore-wall precursors during the co-assimilation of glycogen and acetate. The need for correct homeostasis of purine nucleotides during the meiotic differentiation was demonstrated by the sporulation defect of the AMP deaminase mutant, amd1, which exhibited hyper-accumulation of ATP accompanied by depletion of guanosine nucleotides. CONCLUSIONS: Our systems-level analysis shows that reprogramming of the central metabolism during the meiotic differentiation is controlled at different hierarchical levels to meet the metabolic and energetic needs at successive developmental stages.

Isotopic studies of metabolic systems by mass spectrometry: using Pascal's triangle to produce biological standards with fully controlled labeling patterns.

Mass spectrometry (MS) is widely used for isotopic studies of metabolism in which detailed information about biochemical processes is obtained from the analysis of isotope incorporation into metabolites. The biological value of such experiments is dependent on the accuracy of the isotopic measurements. Using MS, isotopologue distributions are measured from the quantitative analysis of isotopic clusters. These measurements are prone to various biases, which can occur during the experimental workflow and/or MS analysis. The lack of relevant standards limits investigations of the quality of the measured isotopologue distributions. To meet that need, we developed a complete theoretical and experimental framework for the biological production of metabolites with fully controlled and predictable labeling patterns. This strategy is valid for different isotopes and different types of metabolisms and organisms, and was applied to two model microorganisms, Pichia augusta and Escherichia coli, cultivated on (13)C-labeled methanol and acetate as sole carbon source, respectively. The isotopic composition of the substrates was designed to obtain samples in which the isotopologue distribution of all the metabolites should give the binomial coefficients found in Pascal's triangle. The strategy was validated on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform by quantifying the complete isotopologue distributions of different intracellular metabolites, which were in close agreement with predictions. This strategy can be used to evaluate entire experimental workflows (from sampling to data processing) or different analytical platforms in the context of isotope labeling experiments.

Nucleotide degradation and ribose salvage in yeast.

Nucleotide degradation is a universal metabolic capability. Here we combine metabolomics, genetics and biochemistry to characterize the yeast pathway. Nutrient starvation, via PKA, AMPK/SNF1, and TOR, triggers autophagic breakdown of ribosomes into nucleotides. A protein not previously associated with nucleotide degradation, Phm8, converts nucleotide monophosphates into nucleosides. Downstream steps, which involve the purine nucleoside phosphorylase, Pnp1, and pyrimidine nucleoside hydrolase, Urh1, funnel ribose into the nonoxidative pentose phosphate pathway. During carbon starvation, the ribose-derived carbon accumulates as sedoheptulose-7-phosphate, whose consumption by transaldolase is impaired due to depletion of transaldolase's other substrate, glyceraldehyde-3-phosphate. Oxidative stress increases glyceraldehyde-3-phosphate, resulting in rapid consumption of sedoheptulose-7-phosphate to make NADPH for antioxidant defense. Ablation of Phm8 or double deletion of Pnp1 and Urh1 prevent effective nucleotide salvage, resulting in metabolite depletion and impaired survival of starving yeast. Thus, ribose salvage provides means of surviving nutrient starvation and oxidative stress.

Sampling of intracellular metabolites for stationary and non-stationary (13)C metabolic flux analysis in Escherichia coli.

The analysis of metabolic intermediates is a rich source of isotopic information for (13)C metabolic flux analysis ((13)C-MFA) and extends the range of its applications. The sampling of labeled metabolic intermediates is particularly important to obtain reliable isotopic information. The assessment of the different sampling procedures commonly used to generate such data, therefore, is crucial. In this work, we thoroughly evaluated several sampling procedures for stationary and non-stationary (13)C-MFA using Escherichia coli. We first analyzed the efficiency of these procedures for quenching metabolism and found that procedures based on cold or boiling solvents are reliable, in contrast to fast filtration, which is not. We also showed that separating the cells from the broth is not necessary in isotopic stationary state conditions. On the other hand, we demonstrated that the presence of metabolic intermediates outside the cells strongly affects the transient isotopic data monitored during non-stationary (13)C-labeling experiments. Meaningful isotopic data can be obtained by recovering intracellular labeled metabolites from pellets of cells centrifuged in cold solvent. We showed that if the intracellular pools are not separated from the extracellular ones, accurate flux maps can be established provided that the contribution of exogenous compounds is taken into account in the metabolic flux model.