Metabolic regulation of Escherichia coli under phosphate limitation and the effect of phoB gene knockout on the metabolism

2009 ◽  
Vol 108 ◽  
pp. S170 ◽  
Author(s):  
Lolo Wal Marzan ◽  
Kazuyuki Shimizu
Keyword(s):  
Escherichia Coli ◽  
Metabolic Regulation ◽  
Gene Knockout ◽  
Phosphate Limitation

scholarly journals Omics analysis coupled with gene editing revealed potential transporters and regulators related to levoglucosan metabolism efficiency of the engineered Escherichia coli

2022 ◽  
Vol 15 (1) ◽  
Author(s):  
Dongdong Chang ◽  
Cong Wang ◽  
Zia Ul Islam ◽  
Zhisheng Yu
Keyword(s):  
Escherichia Coli ◽  
Metabolic Regulation ◽  
Raw Materials ◽  
Gene Knockout ◽  
Transcriptional Analysis ◽  
Cellular Transport ◽  
Protein Database ◽  
Kinase Gene ◽  
Microbial Utilization ◽  
Native Strains

Abstract Background Bioconversion of levoglucosan, a promising sugar derived from the pyrolysis of lignocellulose, into biofuels and chemicals can reduce our dependence on fossil-based raw materials. However, this bioconversion process in microbial strains is challenging due to the lack of catalytic enzyme relevant to levoglucosan metabolism, narrow production ranges of the native strains, poor cellular transport rate of levoglucosan, and inhibition of levoglucosan metabolism by other sugars co-existing in the lignocellulose pyrolysate. The heterologous expression of eukaryotic levoglucosan kinase gene in suitable microbial hosts like Escherichia coli could overcome the first two challenges to some extent; however, no research has been dedicated to resolving the last two issues till now. Results Aiming to resolve the two unsolved problems, we revealed that seven ABC transporters (XylF, MalE, UgpB, UgpC, YtfQ, YphF, and MglA), three MFS transporters (KgtP, GntT, and ActP), and seven regulatory proteins (GalS, MhpR, YkgD, Rsd, Ybl162, MalM, and IraP) in the previously engineered levoglucosan-utilizing and ethanol-producing E. coli LGE2 were induced upon exposure to levoglucosan using comparative proteomics technique, indicating these transporters and regulators were involved in the transport and metabolic regulation of levoglucosan. The proteomics results were further verified by transcriptional analysis of 16 randomly selected genes. Subsequent gene knockout and complementation tests revealed that ABC transporter XylF was likely to be a levoglucosan transporter. Molecular docking showed that levoglucosan can bind to the active pocket of XylF by seven H-bonds with relatively strong strength. Conclusion This study focusing on the omics discrepancies between the utilization of levoglucosan and non-levoglucosan sugar, could provide better understanding of levoglucosan transport and metabolism mechanisms by identifying the transporters and regulators related to the uptake and regulation of levoglucosan metabolism. The protein database generated from this study could be used for further screening and characterization of the transporter(s) and regulator(s) for downstream enzymatic/genetic engineering work, thereby facilitating more efficient microbial utilization of levoglucosan for biofuels and chemicals production in future.

scholarly journals Genome-Wide Screening Identifies Six Genes That Are Associated with Susceptibility to Escherichia coli Microcin PDI

2015 ◽  
Vol 81 (20) ◽  
pp. 6953-6963 ◽  
Author(s):  
Zhe Zhao ◽  
Lauren J. Eberhart ◽  
Lisa H. Orfe ◽  
Shao-Yeh Lu ◽  
Thomas E. Besser ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Atp Synthase ◽  
Disulfide Bonds ◽  
Gene Knockout ◽  
Single Gene ◽  
Site Directed Mutagenesis ◽  
Content Type ◽  
E Coli ◽  
Synthase Inhibitor ◽  
Loss Of Susceptibility

ABSTRACTThe microcin PDI inhibits a diverse group of pathogenicEscherichia colistrains. Coculture of a single-gene knockout library (BW25113;n= 3,985 mutants) against a microcin PDI-producing strain (E. coli25) identified six mutants that were not susceptible (ΔatpA, ΔatpF, ΔdsbA, ΔdsbB, ΔompF, and ΔompR). Complementation of these genes restored susceptibility in all cases, and the loss of susceptibility was confirmed through independent gene knockouts inE. coliO157:H7 Sakai. Heterologous expression ofE. coliompFconferred susceptibility toSalmonella entericaandYersinia enterocoliticastrains that are normally unaffected by microcin PDI. The expression of chimeric OmpF and site-directed mutagenesis revealed that the K47G48N49region within the first extracellular loop ofE. coliOmpF is a putative binding site for microcin PDI. OmpR is a transcriptional regulator forompF, and consequently loss of susceptibility by the ΔompRstrain most likely is related to this function. Deletion of AtpA and AtpF, as well as AtpE and AtpH (missed in the original library screen), resulted in the loss of susceptibility to microcin PDI and the loss of ATP synthase function. Coculture of a susceptible strain in the presence of an ATP synthase inhibitor resulted in a loss of susceptibility, confirming that a functional ATP synthase complex is required for microcin PDI activity. Intransexpression ofompFin the ΔdsbAand ΔdsbBstrains did not restore a susceptible phenotype, indicating that these proteins are probably involved with the formation of disulfide bonds for OmpF or microcin PDI.

scholarly journals Metabolic Engineering of Escherichia coli for Enhanced Production of Succinic Acid, Based on Genome Comparison and In Silico Gene Knockout Simulation

2005 ◽  
Vol 71 (12) ◽  
pp. 7880-7887 ◽  
Author(s):  
Sang Jun Lee ◽  
Dong-Yup Lee ◽  
Tae Yong Kim ◽  
Byung Hun Kim ◽  
Jinwon Lee ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Succinic Acid ◽  
In Silico ◽  
Acid Production ◽  
Gene Knockout ◽  
Fermentation Products ◽  
E Coli ◽  
Metabolic Analysis ◽  
Enhanced Production ◽  
Succinic Acid Production

ABSTRACT Comparative analysis of the genomes of mixed-acid-fermenting Escherichia coli and succinic acid-overproducing Mannheimia succiniciproducens was carried out to identify candidate genes to be manipulated for overproducing succinic acid in E. coli. This resulted in the identification of five genes or operons, including ptsG, pykF, sdhA, mqo, and aceBA, which may drive metabolic fluxes away from succinic acid formation in the central metabolic pathway of E. coli. However, combinatorial disruption of these rationally selected genes did not allow enhanced succinic acid production in E. coli. Therefore, in silico metabolic analysis based on linear programming was carried out to evaluate the correlation between the maximum biomass and succinic acid production for various combinatorial knockout strains. This in silico analysis predicted that disrupting the genes for three pyruvate forming enzymes, ptsG, pykF, and pykA, allows enhanced succinic acid production. Indeed, this triple mutation increased the succinic acid production by more than sevenfold and the ratio of succinic acid to fermentation products by ninefold. It could be concluded that reducing the metabolic flux to pyruvate is crucial to achieve efficient succinic acid production in E. coli. These results suggest that the comparative genome analysis combined with in silico metabolic analysis can be an efficient way of developing strategies for strain improvement.

scholarly journals A Cybernetic Approach to Modeling Lipid Metabolism in Mammalian Cells

Processes ◽  
2018 ◽  
Vol 6 (8) ◽  
pp. 126 ◽  
Author(s):  
Lina Aboulmouna ◽  
Shakti Gupta ◽  
Mano Maurya ◽  
Frank DeVilbiss ◽  
Shankar Subramaniam ◽  
...  
Keyword(s):  
Mammalian Cells ◽  
Metabolic Regulation ◽  
Metabolic Flux ◽  
Optimal Parameter ◽  
Gene Knockout ◽  
Model Parameters ◽  
Mouse Bone Marrow ◽  
Optimization Approach ◽  
Substrate Uptake ◽  
Data Set

The goal-oriented control policies of cybernetic models have been used to predict metabolic phenomena such as the behavior of gene knockout strains, complex substrate uptake patterns, and dynamic metabolic flux distributions. Cybernetic theory builds on the principle that metabolic regulation is driven towards attaining goals that correspond to an organism’s survival or displaying a specific phenotype in response to a stimulus. Here, we have modeled the prostaglandin (PG) metabolism in mouse bone marrow derived macrophage (BMDM) cells stimulated by Kdo2-Lipid A (KLA) and adenosine triphosphate (ATP), using cybernetic control variables. Prostaglandins are a well characterized set of inflammatory lipids derived from arachidonic acid. The transcriptomic and lipidomic data for prostaglandin biosynthesis and conversion were obtained from the LIPID MAPS database. The model parameters were estimated using a two-step hybrid optimization approach. A genetic algorithm was used to determine the population of near optimal parameter values, and a generalized constrained non-linear optimization employing a gradient search method was used to further refine the parameters. We validated our model by predicting an independent data set, the prostaglandin response of KLA primed ATP stimulated BMDM cells. We show that the cybernetic model captures the complex regulation of PG metabolism and provides a reliable description of PG formation.

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