Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

<div><p>Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in <em>Saccharomyces cerevisiae</em>.</p> </div

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Production of mannosylglycerate in Saccharomyces cerevisiae by metabolic engineering and bioprocess optimization

Mannosylglycerate (MG) is one of the most widespread compatible solutes among marine microorganisms adapted to hot environments. This ionic solute holds excellent ability to protect proteins against thermal denaturation, hence a large number of biotechnological and clinical applications have been put forward. However, the current prohibitive production costs impose severe constraints towards large-scale applications. All known microbial producers synthesize MG from GDP-mannose and 3-phosphoglycerate via a two-step pathway in which mannosyl-3-phosphoglycerate is the intermediate metabolite. In an early work, this pathway was expressed in Saccharomyces cerevisiae with the goal to confirm gene function (Empadinhas et al. in J Bacteriol 186:4075--4084, 2004), but the level of MG accumulation was low. Therefore, in view of the potential biotechnological value of this compound, we decided to invest further effort to convert S. cerevisiae into an efficient cell factory for MG production.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte and also by project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI). Cristiana Faria was supported by a Ph.D. Grant from FCT (Ref. SFRH/ BD/79552/2011).info:eu-repo/semantics/publishedVersio

Electroanalysis may be used in the Vanillin Biotechnological Production

This study shows that electroanalysis may be used in vanillin biotechnological production. As a matter of fact, vanillin and some molecules implicated in the process like eugenol, ferulic acid, and vanillic acid may be oxidized on electrodes made of different materials (gold, platinum, glassy carbon). By a judicious choice of the electrochemical method and the experimental conditions the current intensity is directly proportional to the molecule concentrations in a range suitable for the biotechnological process. So, it is possible to imagine some analytical strategies to control some steps in the vanillin biotechnological production: by sampling in the batch reactor during the process, it is possible to determine out of line the concentration of vanillin, eugenol, ferulic acid, and vanillic acid with a gold rotating disk electrode, and low concentration of vanillin with addition of hydrazine at an amalgamated electrode. Two other possibilities consist in the introduction of electrodes directly in the batch during the process; the first one with a gold rotating disk electrode using linear sweep voltammetry and the second one requires three gold rotating disk electrodes held at different potentials for chronoamperometry. The last proposal is the use of ultramicroelectrodes in the case when stirring is not possible

Identification of target genes to control acetate yield during aerobic fermentation with Saccharomyces cerevisiae

Background: Aerobic fermentation of grape must, leading to respiro-fermentative metabolism of sugars, has been proposed as way of reducing alcohol content in wines. Two factors limit the usefulness of Saccharomyces cerevisiae for this application, the Crabtree effect, and excess volatile acidity under aerobic conditions. This work aimed to explore the impact on ethanol acetate production of different S. cerevisiae strains deleted for genes previously related with the Crabtree phenotype. Results: Recombinant strains were constructed on a wine industrial genetic background, FX10. All yeast strains, including FX10, showed respiro-fermentative metabolism in natural grape must under aerobic conditions, as well as a concomitant reduction in ethanol yield. This indicates that the Crabtree effect is not a major constrain for reaching relevant respiration levels in grape must. Indeed, only minor differences in ethanol yield were observed between the original and some of the recombinant strains. In contrast, some yeast strains showed a relevant reduction of acetic acid production. This was identified as a positive feature for the feasibility of alcohol level reduction by respiration. Reduced acetic acid production was confirmed by a thorough analysis of these and some additional deletion strains (involving genes HXK2, PYK1, REG1, PDE2 and PDC1). Some recombinant yeasts showed altered production of glycerol and pyruvate derived metabolites. Conclusions:REG1 and PDC1 deletion strains showed a strong reduction of acetic acid yield in aerobic fermentations. Since REG1 defective strains may be obtained by non-GMO approaches, these gene modifications show good promise to help reducing ethanol content in wines. © 2016 The Author(s)