Unknown

Dataset Information

0

A Genome-Scale Metabolic Model for Methylococcus capsulatus (Bath) Suggests Reduced Efficiency Electron Transfer to the Particulate Methane Monooxygenase.


ABSTRACT: Background: Genome-scale metabolic models allow researchers to calculate yields, to predict consumption and production rates, and to study the effect of genetic modifications in silico, without running resource-intensive experiments. While these models have become an invaluable tool for optimizing industrial production hosts like Escherichia coli and S. cerevisiae, few such models exist for one-carbon (C1) metabolizers. Results: Here, we present a genome-scale metabolic model for Methylococcus capsulatus (Bath), a well-studied obligate methanotroph, which has been used as a production strain of single cell protein (SCP). The model was manually curated, and spans a total of 879 metabolites connected via 913 reactions. The inclusion of 730 genes and comprehensive annotations, make this model not only a useful tool for modeling metabolic physiology, but also a centralized knowledge base for M. capsulatus (Bath). With it, we determined that oxidation of methane by the particulate methane monooxygenase could be driven both through direct coupling or uphill electron transfer, both operating at reduced efficiency, as either scenario matches well with experimental data and observations from literature. Conclusion: The metabolic model will serve the ongoing fundamental research of C1 metabolism, and pave the way for rational strain design strategies toward improved SCP production processes in M. capsulatus.

SUBMITTER: Lieven C 

PROVIDER: S-EPMC6288188 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

altmetric image

Publications

A Genome-Scale Metabolic Model for <i>Methylococcus capsulatus</i> (Bath) Suggests Reduced Efficiency Electron Transfer to the Particulate Methane Monooxygenase.

Lieven Christian C   Petersen Leander A H LAH   Jørgensen Sten Bay SB   Gernaey Krist V KV   Herrgard Markus J MJ   Sonnenschein Nikolaus N  

Frontiers in microbiology 20181204


<b>Background:</b> Genome-scale metabolic models allow researchers to calculate yields, to predict consumption and production rates, and to study the effect of genetic modifications <i>in silico</i>, without running resource-intensive experiments. While these models have become an invaluable tool for optimizing industrial production hosts like <i>Escherichia coli</i> and <i>S. cerevisiae</i>, few such models exist for one-carbon (C1) metabolizers. <b>Results:</b> Here, we present a genome-scale  ...[more]

Similar Datasets

| S-EPMC95072 | biostudies-literature
| S-EPMC2533734 | biostudies-literature
| S-EPMC4831470 | biostudies-literature
| S-EPMC3423442 | biostudies-literature
| S-EPMC6281684 | biostudies-literature
| S-EPMC107742 | biostudies-literature
| S-EPMC4257694 | biostudies-literature
| S-EPMC2707821 | biostudies-literature
| S-EPMC93468 | biostudies-literature
| S-EPMC1146800 | biostudies-other