Douglas McCloskey

Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli.

The genome‐scale model (GEM) of metabolism in the bacterium Escherichia coli K‐12 has been in development for over a decade and is now in wide use. GEM‐enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model‐driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome‐scale mechanistic understanding of genotype–phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large‐scale network models with sufficient accuracy.

Tracing Compartmentalized NADPH Metabolism in the Cytosol and Mitochondria of Mammalian Cells

Eukaryotic cells compartmentalize biochemical processes in different organelles, often relying on metabolic cycles to shuttle reducing equivalents across intracellular membranes. NADPH serves as the electron carrier for the maintenance of redox homeostasis and reductive biosynthesis, with separate cytosolic and mitochondrial pools providing reducing power in each respective location. This cellular organization is critical for numerous functions but complicates analysis of metabolic pathways using available methods. Here we develop an approach to resolve NADP(H)-dependent pathways present within both the cytosol and the mitochondria. By tracing hydrogen in compartmentalized reactions that use NADPH as a cofactor, including the production of 2-hydroxyglutarate by mutant isocitrate dehydrogenase enzymes, we can observe metabolic pathway activity in these distinct cellular compartments. Using this system we determine the direction of serine/glycine interconversion within the mitochondria and cytosol, highlighting the ability of this approach to resolve compartmentalized reactions in intact cells.

A model‐driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K‐12 MG1655 that is biochemically and thermodynamically consistent

The advent of model‐enabled workflows in systems biology allows for the integration of experimental data types with genome‐scale models to discover new features of biology. This work demonstrates such a workflow, aimed at establishing a metabolomics platform applied to study the differences in metabolomes between anaerobic and aerobic growth of Escherichia coli. Constraint‐based modeling was utilized to deduce a target list of compounds for downstream method development. An analytical and experimental methodology was developed and tailored to the compound chemistry and growth conditions of interest. This included the construction of a rapid sampling apparatus for use with anaerobic cultures. The resulting genome‐scale data sets for anaerobic and aerobic growth were validated by comparison to previous small‐scale studies comparing growth of E. coli under the same conditions. The metabolomics data were then integrated with the E. coli genome‐scale metabolic model (GEM) via a sensitivity analysis that utilized reaction thermodynamics to reconcile simulated growth rates and reaction directionalities. This analysis highlighted several optimal network usage inconsistencies, including the incorrect use of the beta‐oxidation pathway for synthesis of fatty acids. This analysis also identified enzyme promiscuity for the pykA gene, that is critical for anaerobic growth, and which has not been previously incorporated into metabolic models of E coli. Biotechnol. Bioeng. 2014;111: 803–815.

MID Max: LC-MS/MS Method for Measuring the Precursor and Product Mass Isotopomer Distributions of Metabolic Intermediates and Cofactors for Metabolic Flux Analysis Applications.

The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC-MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA that takes advantage of additional scan types that maximizes the number of mass isotopomer distributions (MIDs) that can be acquired in a given experiment. The analytical method was found to measure the MIDs of 97 metabolites, corresponding to 74 unique metabolite-fragment pairs (32 precursor spectra and 42 product spectra) with accuracy and precision. The compounds measured included metabolic intermediates in central carbohydrate metabolism and cofactors of peripheral metabolism (e.g., ATP). Using only a subset of the acquired MIDs, the method was found to improve the precision of flux estimations and number of resolved exchange fluxes for wild-type E. coli compared to traditional methods and previously published data sets.

Fast Swinnex filtration (FSF): a fast and robust sampling and extraction method suitable for metabolomics analysis of cultures grown in complex media

Liquid chromatography tandem mass spectrometry (LC–MS/MS) provides a powerful means to analyze intracellular metabolism. A prerequisite to accurate metabolomics analysis using LC–MS/MS is a robust sampling and extraction protocol. One unaddressed area in sampling is a detailed examination of a suitable method for anaerobic cultures grown in complex media. Given that a vast majority of bacteria are facultative or obligate anaerobes that grow to low biomass density and need to be cultured in complex media, a suitable sampling and extraction strategy for anaerobic cultures is needed. In this work, we develop a fast-filtration method using pressure-driven Swinnex® filters. We show that the method is fast enough to provide an accurate snapshot of intracellular metabolism, reduces matrix interference from the media to improve the number of compounds that can be detected, and is applicable to anaerobic and aerobic liquid cultures grown in a variety of culturing systems. Furthermore, we apply the fast filtration method to investigate differences in the absolute intracellular metabolite levels of anaerobic cultures grown in minimal and complex media.

Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale.

Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems. The majority of work using MFA has been limited to core models of metabolism due to challenges in implementing genome-scale MFA and the undesirable trade-off between increased scope and decreased precision in flux estimations. This work presents a tunable workflow for expanding the scope of MFA to the genome-scale without trade-offs in flux precision. The genome-scale MFA model presented here, iDM2014, accounts for 537 net reactions, which includes the core pathways of traditional MFA models and also covers the additional pathways of purine, pyrimidine, isoprenoid, methionine, riboflavin, coenzyme A, and folate, as well as other biosynthetic pathways. When evaluating the iDM2014 using a set of measured intracellular intermediate and cofactor mass isotopomer distributions (MIDs),1 it was found that a total of 232 net fluxes of central and peripheral metabolism could be resolved in the E. coli network. The increase in scope was shown to cover the full biosynthetic route to an expanded set of bioproduction pathways, which should facilitate applications such as the design of more complex bioprocessing strains and aid in identifying new antimicrobials. Importantly, it was found that there was no loss in precision of core fluxes when compared to a traditional core model, and additionally there was an overall increase in precision when considering all observable reactions.

A pH and solvent optimized reverse-phase ion-paring-LC–MS/MS method that leverages multiple scan-types for targeted absolute quantification of intracellular metabolites

Comprehensive knowledge of intracellular biochemistry is needed to accurately understand, model, and manipulate metabolism for industrial and therapeutic applications. Quantitative metabolomics has been driven by advances in analytical instrumentation and can add valuable knowledge to the understanding of intracellular metabolism. Liquid chromatography coupled to mass spectrometry (LC–MS and LC–MS/MS) has become a reliable means with which to quantify a multitude of intracellular metabolites in parallel with great specificity and accuracy. This work details a method that builds and extends upon existing reverse phase ion-paring liquid chromatography methods for separation and detection of polar and anionic compounds that comprise key nodes of intracellular metabolism by optimizing pH and solvent composition. In addition, the presented method utilizes multiple scan types provided by hybrid instrumentation to improve confidence in compound identification. The developed method was validated for a broad coverage of polar and anionic metabolites of intracellular metabolism.

Antibiotic-Induced Changes to the Host Metabolic Environment Inhibit Drug Efficacy and Alter Immune Function

Bactericidal antibiotics alter microbial metabolism as part of their lethality and can damage mitochondria in mammalian cells. In addition, antibiotic susceptibility is sensitive to extracellular metabolites, but it remains unknown whether metabolites present at an infection site can affect either treatment efficacy or immune function. Here, we quantify local metabolic changes in the host microenvironment following antibiotic treatment for a peritoneal Escherichia coli infection. Antibiotic treatment elicits microbiome-independent changes in local metabolites, but not those distal to the infection site, by acting directly on host cells. The metabolites induced during treatment, such as AMP, reduce antibiotic efficacy and enhance phagocytic killing. Moreover, antibiotic treatment impairs immune function by inhibiting respiratory activity in immune cells. Collectively, these results highlight the immunomodulatory potential of antibiotics and reveal the local metabolic microenvironment to be an important determinant of infection resolution.

Metabolic impact of an NADH-producing glucose-6-phosphate dehydrogenase in Escherichia coli

In Escherichia coli, the oxidative branch of the pentose phosphate pathway (oxPPP) is one of the major sources of NADPH when glucose is the sole carbon nutrient. However, unbalanced NADPH production causes growth impairment as observed in a strain lacking phosphoglucoisomerase (Δpgi). In this work, we studied the metabolic response of this bacterium to the replacement of its glucose-6-phosphate dehydrogenase (G6PDH) by an NADH-producing variant. The homologous enzyme from Leuconostoc mesenteroides was studied by molecular dynamics and site-directed mutagenesis to obtain the NAD-preferring LmG6PDH(R46E,Q47E). Through homologous recombination, the zwf loci (encoding G6PDH) in the chromosomes of WT and Δpgi E. coli strains were replaced by DNA encoding LmG6PDH(R46E,Q47E). Contrary to some predictions performed with flux balance analysis, the replacements caused a substantial effect on the growth rates, increasing 59 % in the Δpgi strain, while falling 44 % in the WT. Quantitative PCR (qPCR) analysis of the zwf locus showed that the expression level of the mutant enzyme was similar to the native enzyme and the expression of genes encoding key enzymes of the central pathways also showed moderate changes among the studied strains. The phenotypic and qPCR data were integrated into in silico modelling, showing an operative G6PDH flux contributing to the NADH pool. Our results indicated that, in vivo, the generation of NADH by G6PDH is beneficial or disadvantageous for growth depending on the operation of the upper Embden-Meyerhof pathway. Interestingly, a genomic database search suggested that in bacteria lacking phosphofructokinase, the G6PDHs tend to have similar preferences for NAD and NADP. The importance of the generation of NADPH in a pathway such as the oxPPP is discussed.

Adaptation to the coupling of glycolysis to toxic methylglyoxal production in tpiA deletion strains of Escherichia coli requires synchronized and counterintuitive genetic changes

Methylglyoxal is a highly toxic metabolite that can be produced in all living organisms. Methylglyoxal was artificially elevated by removal of the tpiA gene from a growth optimized Escherichia coli strain. The initial response to elevated methylglyoxal and its toxicity was characterized, and detoxification mechanisms were studied using adaptive laboratory evolution. We found that: 1) Multi-omics analysis revealed biological consequences of methylglyoxal toxicity, which included attack on macromolecules including DNA and RNA and perturbation of nucleotide levels; 2) Counter-intuitive cross-talk between carbon starvation and inorganic phosphate signalling was revealed in the tpiA deletion strain that required mutations in inorganic phosphate signalling mechanisms to alleviate; and 3) The split flux through lower glycolysis depleted glycolytic intermediates requiring a host of synchronized and coordinated mutations in non-intuitive network locations in order to re-adjust the metabolic flux map to achieve optimal growth. Such mutations included a systematic inactivation of the Phosphotransferase System (PTS) and alterations in cell wall biosynthesis enzyme activity. This study demonstrated that deletion of major metabolic genes followed by ALE was a productive approach to gain novel insight into the systems biology underlying optimal phenotypic states.