Genome-scale metabolic models (GEMs) allow predicting metabolic phenotypes from limited data on uptake and secretion fluxes by defining the space of all the feasible solutions and excluding physio-chemically and biologically unfeasible behaviors. The integration of additional biological information in genome-scale models, e.g., transcriptomic or proteomic profiles, has the potential to improve phenotype prediction accuracy. This is particularly important for metabolic engineering applications where more accurate model predictions can translate to more reliable model-based strain design. Here we present a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO) model of Bacillus subtilis, which uses publicly available proteomic data and enzyme kinetic parameters for central carbon (CC) metabolic reactions to constrain the flux solution space. This model allows more accurate prediction of the flux distribution and growth rate of wild-type and single-gene/operon deletion strains compared to a standard genome-scale metabolic model. The flux prediction error decreased by 43% and 36% for wild-type and mutants respectively. The model additionally increased the number of correctly predicted essential genes in CC pathways by 2.5-fold and significantly decreased flux variability in more than 80% of the reactions with variable flux. Finally, the model was used to find new gene deletion targets to optimize the flux toward the biosynthesis of poly-γ-glutamic acid (γ-PGA) polymer in engineered B. subtilis. We implemented the single-reaction deletion targets identified by the model experimentally and showed that the new strains have a twofold higher γ-PGA concentration and production rate compared to the ancestral strain. This work confirms that integration of enzyme constraints is a powerful tool to improve existing genome-scale models, and demonstrates the successful use of enzyme-constrained models in B. subtilis metabolic engineering. We expect that the new model can be used to guide future metabolic engineering efforts in the important industrial production host B. subtilis.

Spinel phases, with unique and outstanding physical properties, are attracting a great deal of interest in many fields. In particular, MgFe₂O₄, a partially inverted spinel phase, could find applications in medicine thanks to the remarkable antibacterial properties attributed to the generation of reactive oxygen species. In this paper, undoped and Ag-doped MgFe_2-xAg_xO₄ (x = 0.1 and 0.3) nanoparticles were prepared using microwave-assisted combustion and sol–gel methods. X-ray powder diffraction, with Rietveld structural refinements combined with micro-Raman spectroscopy, allowed to determine sample purity and the inversion degree of the spinel, passing from about 0.4 to 0.7 when Ag was introduced as dopant. The results are discussed in view of the antibacterial activity towards Escherichia coli and Staphylococcus aureus, representative strains of Gram-negative and Gram-positive bacteria. The sol–gel particles were more efficient towards the chosen bacteria, possibly thanks to the nanometric sizes of metallic silver, which were well distributed in the powders and in the spinel phase, with respect to microwave ones, that, however, acquired antibacterial activity after thermal treatment, probably due to the nucleation of hematite, itself displaying well-known antibacterial properties and which could synergistically act with silver and spinel.

γ-Glutamyl derivatives of proteinogenic or modified amino acids raise considerable interest as flavor enhancers or biologically active compounds. However, their supply, on a large scale and at reasonable costs, remains challenging. Enzymatic synthesis has been recognized as a possible affordable alternative with respect to both isolation procedures from natural sources, burdened by low-yield and by the requirement of massive amount of starting material, and chemical synthesis, inconvenient because of the need of protection/deprotection steps. The E. coli γ-glutamyltransferase (Ec-GGT) has already been proposed as a biocatalyst for the synthesis of various γ-glutamyl derivatives. However, enzymatic syntheses using this enzyme usually provide the desired products in limited yield. Hydrolysis and autotranspeptidation of the donor substrate have been identified as the side reactions affecting the final yield of the catalytic process. In addition, experimental conditions need to be specifically adjusted for each acceptor substrate. Substrate specificity and the fine characterization of the activities exerted by the enzyme over time has so far escaped rationalization. In this work, reactions catalyzed by Ec-GGT between the γ-glutamyl donor glutamine and several representative acceptor amino acids have been finely analyzed with the identification of single reaction products over time. This approach allowed to rationalize the effect of donor/acceptor molar ratio on the outcome of the transpeptidation reaction and on the distribution of the different byproducts, inferring a general scheme for Ec-GGT-catalyzed reactions. The propensity to react of the different acceptor substrates is in agreement with recent findings obtained using model substrates and further supported by x-ray crystallography and will contribute to characterize the still elusive acceptor binding site of the enzyme.