Methane utilization in <i>Methylomicrobium alcaliphilum</i> 20Z<sup>R</sup> [electronic resource] : a systems approach

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Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 662.8 Other fuels

Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2018

Mô tả vật lý: Size: Article No. 2512 (2018) : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 263054

 Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, <
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 13<
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 C-labeling, and transcriptomic datasets make <
 i>
 Methylomicrobium alcaliphilum<
 /i>
  20Z<
 sup>
 R<
 /sup>
  an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in <
 i>
 M. alcaliphilum<
 /i>
  20Z<
 sup>
 R<
 /sup>
 . A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C<
 sub>
 1<
 /sub>
 -metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.
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