Next-Gen<sup>3</sup> [electronic resource] : Sequencing, Modeling, and Advanced Biofuels - Final Technical Report

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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 Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2017

Mô tả vật lý: Size: 46 p. : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 264407

 Successful, scalable implementation of biofuels is dependent on the efficient and near complete utilization of diverse biomass sources. One approach is to utilize the large recalcitrant biomass fraction (or any organic waste stream) through the thermochemical conversion of organic compounds to syngas, a mixture of carbon monoxide (CO), carbon dioxide (CO<
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 ), and hydrogen (H<
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 ), which can subsequently be metabolized by acetogenic microorganisms to produce next-gen biofuels. The goal of this proposal was to advance the development of the acetogen Clostridium ljungdahlii as a chassis organism for next-gen biofuel production from cheap, renewable sources and to detail the interconnectivity of metabolism, energy conservation, and regulation of acetogens using next-gen sequencing and next-gen modeling. To achieve this goal we determined optimization of carbon and energy utilization through differential translational efficiency in C. ljungdahlii. Furthermore, we reconstructed a next-generation model of all major cellular processes, such as macromolecular synthesis and transcriptional regulation and deployed this model to predicting proteome allocation, overflow metabolism, and metal requirements in this model acetogen. In addition we explored the evolutionary significance of tRNA operon structure using the next-gen model and determined the optimal operon structure for bioproduction. Our study substantially enhanced the knowledgebaase for chemolithoautotrophs and their potential for advanced biofuel production. It provides next-generation modeling capability, offer innovative tools for genome-scale engineering, and provide novel methods to utilize next-generation models for the design of tunable systems that produce commodity chemicals from inexpensive sources.
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