MOESM1 of Integrated intracellular metabolic profiling and pathway analysis approaches reveal complex metabolic regulation by Clostridium acetobutylicum

Additional file 1. All the metabolites detected in our study and the results of pathway analysis

MOESM2 of Metabolic network model guided engineering ethylmalonyl-CoA pathway to improve ascomycin production in Streptomyces hygroscopicus var. ascomyceticus

Additional file 2. Metabolic network model of S. hygroscopicus var. ascomyceticus FS35 and potential targets identified using this model

MOESM3 of Metabolic network model guided engineering ethylmalonyl-CoA pathway to improve ascomycin production in Streptomyces hygroscopicus var. ascomyceticus

Additional file 3: Table S1. Primers used in this section. Figure S1. Heat map illustrating the conservation of metabolic enzymes in different metabolic subsystems among 31 Streptomyces strains. Figure S2. Homology analysis of proteins related to the primary metabolism of S. coelicolor A3(2) and S16-shyl. Figure S3. Production profiles of the stain S. hygroscopicus var. ascomyceticus FS35 in batch fermentation. Table S2. Genetic targets chosen for experimental implementation. Table S3. The encoded enzymes involved in the ethylmalonyl-CoA pathways of the 31 Streptomyces strains

Comparative Metabolomic-Based Metabolic Mechanism Hypothesis for Microbial Mixed Cultures Utilizing Cane Molasses Wastewater for Higher 2‑Phenylethanol Production

The mixed microbes coculture method in cane molasses wastewater (CMW) was adopted to produce 2-phenylethanol (2-PE). Comparative metabolomics combined with multivariate statistical analysis was performed to profile the differences of overall intracellular metabolites concentration for the mixed microbes cocultured under two different fermentation conditions with low and high 2-PE production. In total 102 intracellular metabolites were identified, and 17 of them involved in six pathways were responsible for 2-PE biosynthesis. After further analysis of metabolites and verification by feeding experiment, an overall metabolic mechanism hypothesis for the microbial mixed cultures (MMC) utilizing CMW for higher 2-PE production was presented. The results demonstrated that the branches of intracellular pyruvate metabolic flux, as well as the flux of phenylalanine, tyrosine, tryptophan, glutamate, proline, leucine, threonine, and oleic acid, were closely related to 2-PE production and cell growth, which provided theoretical guidance for domestication and selection of species as well as medium optimization for MMC metabolizing CMW to enhance 2-PE yield

Model-Driven Redox Pathway Manipulation for Improved Isobutanol Production in <i>Bacillus subtilis</i> Complemented with Experimental Validation and Metabolic Profiling Analysis

<div><p>To rationally guide the improvement of isobutanol production, metabolic network and metabolic profiling analysis were performed to provide global and profound insights into cell metabolism of isobutanol-producing <i>Bacillus subtilis</i>. The metabolic flux distribution of strains with different isobutanol production capacity (BSUL03, BSUL04 and BSUL05) drops a hint of the importance of NADPH on isobutanol biosynthesis. Therefore, the redox pathways were redesigned in this study. To increase NADPH concentration, glucose-6-phosphate isomerase was inactivated (BSUL06) and glucose-6-phosphate dehydrogenase was overexpressed (BSUL07) successively. As expected, NADPH pool size in BSUL07 was 4.4-fold higher than that in parental strain BSUL05. However, cell growth, isobutanol yield and production were decreased by 46%, 22%, and 80%, respectively. Metabolic profiling analysis suggested that the severely imbalanced redox status might be the primary reason. To solve this problem, gene <i>udhA</i> of <i>Escherichia coli</i> encoding transhydrogenase was further overexpressed (BSUL08), which not only well balanced the cellular ratio of NAD(P)H/NAD(P)⁺, but also increased NADH and ATP concentration. In addition, a straightforward engineering approach for improving NADPH concentrations was employed in BSUL05 by overexpressing exogenous gene <i>pntAB</i> and obtained BSUL09. The performance for isobutanol production by BSUL09 was poorer than BSUL08 but better than other engineered strains. Furthermore, in fed-batch fermentation the isobutanol production and yield of BSUL08 increased by 11% and 19%, up to the value of 6.12 g/L and 0.37 C-mol isobutanol/C-mol glucose (63% of the theoretical value), respectively, compared with parental strain BSUL05. These results demonstrated that model-driven complemented with metabolic profiling analysis could serve as a useful approach in the strain improvement for higher bio-productivity in further application.</p></div

Fermentation properties of BSUL08 and BSUL05 in fed-batch fermentation.

<p>Data were expressed as average values and standard deviations (SD) of three parallel studies.</p

Fold changes of the major intracellular metabolites for different isobutanol-producing strains.

<p>The concentrations of different intracellular metabolites of reconstructed strains (BSUL06, BSUL07 and BSUL08) were normalized to that of BSUL05. Data presented in heat map were the average fold change values of each metabolite between the reconstructed strains and BSUL05.</p

Concentration of intracellular redox cofactors and energy for different isobutanol-producing <i>B. subtilis</i> strains.

<p>Data were expressed as average values and standard deviations (SD) of three parallel studies.</p

The metabolic flux distribution in isobutanol-producing strain <i>B. subtilis</i>.

<p>Data represented <i>in silico</i> flux distribution of different isobutanol-producing strains (top BSUL03, middle BSUL04, down BSUL05). Bold red and green lines represented the increased and decreased flux, respectively. The blue marks represented the targets for redox pathway engineering in this work. Abbreviations were listed in previous work <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093815#pone.0093815-Li2" target="_blank">[10]</a>. Part of the flux data in central metabolism were taken from previous work <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093815#pone.0093815-Li2" target="_blank">[10]</a>.</p

Strains and plasmids used in this work.

a<p>CGSC: Coli Gentic Stock Center.</p>b<p>BGSC: Bacillus Gentic Stock Center.</p