1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Metabolic Fluxes in Lactic Acid Bacteria—A Review

      , , ,

      Food Biotechnology

      Informa UK Limited

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references 123

          • Record: found
          • Abstract: found
          • Article: not found

          The effects of alternate optimal solutions in constraint-based genome-scale metabolic models.

          Genome-scale constraint-based models of several organisms have now been constructed and are being used for model driven research. A key issue that may arise in the use of such models is the existence of alternate optimal solutions wherein the same maximal objective (e.g., growth rate) can be achieved through different flux distributions. Herein, we investigate the effects that alternate optimal solutions may have on the predicted range of flux values calculated using currently practiced linear (LP) and quadratic programming (QP) methods. An efficient LP-based strategy is described to calculate the range of flux variability that can be present in order to achieve optimal as well as suboptimal objective states. Sample results are provided for growth predictions of E. coli using glucose, acetate, and lactate as carbon substrates. These results demonstrate the extent of flux variability to be highly dependent on environmental conditions and network composition. In addition we examined the impact of alternate optima for growth under gene knockout conditions as calculated using QP-based methods. It was observed that calculations using QP-based methods can show significant variation in growth rate if the flux variability among alternate optima is high. The underlying biological significance and general source of such flux variability is further investigated through the identification of redundancies in the network (equivalent reaction sets) that lead to alternate solutions. Collectively, these results illustrate the variability inherent in metabolic flux distributions and the possible implications of this heterogeneity for constraint-based modeling approaches. These methods also provide an efficient and robust method to calculate the range of flux distributions that can be derived from quantitative fermentation data.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.

            The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The genome sequence of Bifidobacterium longum subsp. infantis reveals adaptations for milk utilization within the infant microbiome.

              Following birth, the breast-fed infant gastrointestinal tract is rapidly colonized by a microbial consortium often dominated by bifidobacteria. Accordingly, the complete genome sequence of Bifidobacterium longum subsp. infantis ATCC15697 reflects a competitive nutrient-utilization strategy targeting milk-borne molecules which lack a nutritive value to the neonate. Several chromosomal loci reflect potential adaptation to the infant host including a 43 kbp cluster encoding catabolic genes, extracellular solute binding proteins and permeases predicted to be active on milk oligosaccharides. An examination of in vivo metabolism has detected the hallmarks of milk oligosaccharide utilization via the central fermentative pathway using metabolomic and proteomic approaches. Finally, conservation of gene clusters in multiple isolates corroborates the genomic mechanism underlying milk utilization for this infant-associated phylotype.
                Bookmark

                Author and article information

                Journal
                Food Biotechnology
                Food Biotechnology
                Informa UK Limited
                0890-5436
                1532-4249
                May 2015
                April 03 2015
                May 2015
                April 03 2015
                : 29
                : 2
                : 185-217
                Article
                10.1080/08905436.2015.1027913
                © 2015

                Comments

                Comment on this article