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Title: A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism

Abstract

Quantitative understanding of clostridial metabolism is of longstanding interest due to the importance of Clostridia as model anaerobes, biotechnology workhorses, and contributors to evolutionary history and ecosystem. Current computational methods such as flux balance analysis-based construction of clostridial metabolism in genome scale provide a fundamental framework for metabolic analysis. However, this method alone is inadequate to characterize cellular metabolic activity. Experiment-driven approaches including isotope tracer-based fluxomics in association with genetic and biochemical methods are needed to gain a more comprehensive understanding. Here we focus on typical examples where these integrated approaches have contributed to the identification of new metabolic pathways and quantification of metabolic fluxes in Clostridia. Here, we also highlight the opportunities and challenges of cutting-edge fluxomics approaches such as machine learning modeling, deuterium tracer approach, and high throughput flux phenotyping in exploring clostridial metabolism with respect to inorganic carbon utilization, redox cofactor interconversion, and other key metabolic features.

Authors:
 [1]; ORCiD logo [2];  [1];  [1];  [1];  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Colorado School of Mines, Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B); USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1573196
Report Number(s):
NREL/JA-2700-74431
Journal ID: ISSN 0958-1669
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Current Opinion in Biotechnology
Additional Journal Information:
Journal Volume: 64; Journal Issue: C; Journal ID: ISSN 0958-1669
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; Clostridium; fluxomics; metabolic analysis; systems microbiology

Citation Formats

Wu, Chao, Cano, Melissa, Gao, Xiang, Lo, Jonathan, Maness, PinChing, and Xiong, Wei. A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism. United States: N. p., 2019. Web. doi:10.1016/j.copbio.2019.09.012.
Wu, Chao, Cano, Melissa, Gao, Xiang, Lo, Jonathan, Maness, PinChing, & Xiong, Wei. A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism. United States. doi:10.1016/j.copbio.2019.09.012.
Wu, Chao, Cano, Melissa, Gao, Xiang, Lo, Jonathan, Maness, PinChing, and Xiong, Wei. Wed . "A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism". United States. doi:10.1016/j.copbio.2019.09.012.
@article{osti_1573196,
title = {A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism},
author = {Wu, Chao and Cano, Melissa and Gao, Xiang and Lo, Jonathan and Maness, PinChing and Xiong, Wei},
abstractNote = {Quantitative understanding of clostridial metabolism is of longstanding interest due to the importance of Clostridia as model anaerobes, biotechnology workhorses, and contributors to evolutionary history and ecosystem. Current computational methods such as flux balance analysis-based construction of clostridial metabolism in genome scale provide a fundamental framework for metabolic analysis. However, this method alone is inadequate to characterize cellular metabolic activity. Experiment-driven approaches including isotope tracer-based fluxomics in association with genetic and biochemical methods are needed to gain a more comprehensive understanding. Here we focus on typical examples where these integrated approaches have contributed to the identification of new metabolic pathways and quantification of metabolic fluxes in Clostridia. Here, we also highlight the opportunities and challenges of cutting-edge fluxomics approaches such as machine learning modeling, deuterium tracer approach, and high throughput flux phenotyping in exploring clostridial metabolism with respect to inorganic carbon utilization, redox cofactor interconversion, and other key metabolic features.},
doi = {10.1016/j.copbio.2019.09.012},
journal = {Current Opinion in Biotechnology},
issn = {0958-1669},
number = C,
volume = 64,
place = {United States},
year = {2019},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on October 23, 2020
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