α -Ketoglutarate accumulation is not dependent on isocitrate dehydrogenase activity during tellurite detoxification in Escherichia coli

Impact of Tellurite on the Metabolism of Paenibacillus pabuli AL109b With Flagellin Production Explaining High Reduction Capacity

Tellurium (Te) is a metalloid with scarce and scattered abundance but with an increased interest in human activity for its uses in emerging technologies. As is seen for other metals and metalloids, the result of mining activity and improper disposal of high-tech devices will lead to niches with increased abundance of Te. This metalloid will be more available to bacteria and represent an increasing selective pressure. This environmental problem may constitute an opportunity to search for microorganisms with genetic and molecular mechanisms of microbial resistance to Te toxic anions. Organisms from Te-contaminated niches could provide tools for Te remediation and fabrication of Te-containing structures with added value. The objective of this study was to determine the ability of a high metal-resistant Paenibacillus pabuli strain ALJ109b, isolated from high metal content mining residues, to reduce tellurite ion, and to evaluate the formation of metallic tellurium by cellular reduction, isolate the protein responsible, and determine the metabolic response to tellurite during growth. P. pabuli ALJ109b demonstrated to be resistant to Te (IV) at concentrations higher than reported for its genus. It can efficiently remove soluble Te (IV) from solution, over 20% in 8 h of growth, and reduce it to elemental Te, forming monodisperse nanostructures, verified by scattering electron microscopy. Cultivation of P. pabuli ALJ109b in the presence of Te (IV) affected the general protein expression pattern, and hence the metabolism, as demonstrated by high-throughput proteomic analysis. The Te (IV)-induced metabolic shift is characterized by an activation of ROS response. Flagellin from P. pabuli ALJ109b demonstrates high Te (0) forming activity in neutral to basic conditions in a range of temperatures from 20°C to 37°C. In conclusion, the first metabolic characterization of a strain of P. pabuli response to Te (IV) reveals a highly resistant strain with a unique Te (IV) proteomic response. This strain, and its flagellin, display, all the features of potential tools for Te nanoparticle production.

LC-MS/MS-based metabolic profiling of Escherichia coli under heterologous gene expression stress

Escherichia coli is frequently exploited for genetic manipulations and heterologous gene expression studies. We have evaluated the metabolic profile of E. coli strain BL21 (DE3) RIL CodonPlus after genetic modifications and subjecting to the production of recombinant protein. Three genetically variable E. coli cell types were studied, normal cells (susceptible to antibiotics) cultured in simple LB medium, cells harboring ampicillin-resistant plasmid pET21a (+), grown under antibiotic stress, and cells having recombinant plasmid pET21a (+) ligated with bacterial lactate dehydrogenase gene grown under ampicillin and standard isopropyl thiogalactoside (IPTG)-induced gene expression conditions. A total of 592 metabolites were identified through liquid chromatography-mass spectrometry/mass spectrometry analysis, feature and peak detection using XCMS and CAMERA followed by precursor identification by METLIN-based procedures. Overall, 107 metabolites were found differentially regulated among genetically modified cells. Quantitative analysis has shown a significant modulation in DHNA-CoA, p-aminobenzoic acid, and citrulline levels, indicating an alteration in vitamin K, folic acid biosynthesis, and urea cycle of E. coli cells during heterologous gene expression. Modulations in energy metabolites including NADH, AMP, ADP, ATP, carbohydrate, terpenoids, fatty acid metabolites, diadenosine tetraphosphate (Ap4A), and l-carnitine advocate major metabolic rearrangements. Our study provides a broader insight into the metabolic adaptations of bacterial cells during gene manipulation experiments that can be prolonged to improve the yield of heterologous gene products and concomitant production of valuable biomolecules.

Escherichia coli 6-phosphogluconate dehydrogenase aids in tellurite resistance by reducing the toxicant in a NADPH-dependent manner

Exposure to the tellurium oxyanion tellurite (TeO3(2-)) results in the establishment of an oxidative stress status in most microorganisms. Usually, bacteria growing in the presence of the toxicant turn black because of the reduction of tellurite (Te(4+)) to the less-toxic elemental tellurium (Te(0)). In vitro, at least part of tellurite reduction occurs enzymatically in a nicotinamide dinucleotide-dependent reaction. In this work, we show that TeO3(2-) reduction by crude extracts of Escherichia coli overexpressing the zwf gene (encoding glucose-6-phosphate dehydrogenase) takes place preferentially in the presence of NADPH instead of NADH. The enzyme responsible for toxicant reduction was identified as 6-phosphogluconate dehydrogenase (Gnd). The gnd gene showed a subtle induction at short times after toxicant exposure while strains lacking gnd were more susceptible to the toxicant. These results suggest that both NADPH-generating enzymes from the pentose phosphate shunt may be involved in tellurite detoxification and resistance in E. coli.

Metabolic reconfigurations aimed at the detoxification of a multi-metal stress in Pseudomonas fluorescens: implications for the bioremediation of metal pollutants

Although the ability of microbial systems to adapt to the toxic challenge posed by numerous metal pollutants individually has been well documented, there is little detailed information on how bacteria survive in a multiple-metal environment. Here we describe the metabolic reconfiguration invoked by the soil microbe Pseudomonas fluorescens in a medium with millimolar amounts of aluminum (Al), iron (Fe), gallium (Ga), calcium (Ca), and zinc (Zn). While enzymes involved in the production of NADH were decreased, there was a marked increase in enzymatic activities dedicated to NADPH formation. A modified tricarboxylic acid (TCA) cycle coupled to an alternate glyoxylate shunt mediated the synthesis of adenosine triphosphate (ATP) with the concomitant generation of oxalate. This dicarboxylic acid was a key ingredient in the sequestration of the metals that were detoxified as a lipid complex. It appears that the microbe favors this strategy as opposed to a detoxification process aimed at each metal separately. These findings have interesting implications for bioremediation technologies.

Glutathione reductase-mediated synthesis of tellurium-containing nanostructures exhibiting antibacterial properties

Tellurium, a metalloid belonging to group 16 of the periodic table, displays very interesting physical and chemical properties and lately has attracted significant attention for its use in nanotechnology. In this context, the use of microorganisms for synthesizing nanostructures emerges as an eco-friendly and exciting approach compared to their chemical synthesis. To generate Te-containing nanostructures, bacteria enzymatically reduce tellurite to elemental tellurium. In this work, using a classic biochemical approach, we looked for a novel tellurite reductase from the Antarctic bacterium Pseudomonas sp. strain BNF22 and used it to generate tellurium-containing nanostructures. A new tellurite reductase was identified as glutathione reductase, which was subsequently overproduced in Escherichia coli. The characterization of this enzyme showed that it is an NADPH-dependent tellurite reductase, with optimum reducing activity at 30°C and pH 9.0. Finally, the enzyme was able to generate Te-containing nanostructures, about 68 nm in size, which exhibit interesting antibacterial properties against E. coli, with no apparent cytotoxicity against eukaryotic cells.

A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database

BACKGROUND

Constraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology.

RESULTS

We present EcoCyc-18.0-GEM, a genome-scale model of the E. coli K-12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc-18.0-GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc-18.0-GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model's derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc-18.0-GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization.

CONCLUSION

Significant advantages can be derived from the combination of model organism databases and flux balance modeling represented by MetaFlux. Interpretation of the EcoCyc database as a flux balance model results in a highly accurate metabolic model and provides a rigorous consistency check for information stored in the database.