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Title: EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix

Abstract

Stable isotope based metabolic flux analysis is currently the unique methodology that allows the experimental study of the integrated responses of metabolic networks. This method primarily relies on isotope labeling and modeling, which could be a challenge in both experimental and computational biology. Specifically, the algorithm implementation for isotope simulation is a critical step, limiting extensive usage of this powerful approach. In this work, we introduce EMUlator a Python-based isotope simulator which is developed on Elementary Metabolite Unit (EMU) algorithm, an efficient and powerful algorithm for isotope modeling. We propose a novel adjacency matrix method to implement EMU modeling and exemplify it stepwise. This method is intuitively straightforward and can be conveniently mastered for various customized purposes. We apply this arithmetic pipeline to understand the phosphoketolase flux in the metabolic network of an industrial microbe Clostridium acetobutylicum. The resulting design enables a high-throughput and non-invasive approach for estimating phosphoketolase flux in vivo. Our computational insights allow the systematic design and prediction of isotope-based metabolic models and yield a comprehensive understanding of their limitations and potentials.

Authors:
 [1];  [2];  [1];  [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Inst. of Nuclear Energy Research, Taoyuan (Taiwan)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)
OSTI Identifier:
1514834
Report Number(s):
NREL/JA-2700-73924
Journal ID: ISSN 1664-302X
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Microbiology
Additional Journal Information:
Journal Volume: 10; Journal ID: ISSN 1664-302X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; adjacency matrix; elementary metabolite unit; fractional labeling; Clostridium acetobutylicum; phosphoketolase

Citation Formats

Wu, Chao, Chen, Chia-hsin, Lo, Jonathan, Michener, William, Maness, PinChing, and Xiong, Wei. EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix. United States: N. p., 2019. Web. doi:10.3389/fmicb.2019.00922.
Wu, Chao, Chen, Chia-hsin, Lo, Jonathan, Michener, William, Maness, PinChing, & Xiong, Wei. EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix. United States. doi:10.3389/fmicb.2019.00922.
Wu, Chao, Chen, Chia-hsin, Lo, Jonathan, Michener, William, Maness, PinChing, and Xiong, Wei. Tue . "EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix". United States. doi:10.3389/fmicb.2019.00922. https://www.osti.gov/servlets/purl/1514834.
@article{osti_1514834,
title = {EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix},
author = {Wu, Chao and Chen, Chia-hsin and Lo, Jonathan and Michener, William and Maness, PinChing and Xiong, Wei},
abstractNote = {Stable isotope based metabolic flux analysis is currently the unique methodology that allows the experimental study of the integrated responses of metabolic networks. This method primarily relies on isotope labeling and modeling, which could be a challenge in both experimental and computational biology. Specifically, the algorithm implementation for isotope simulation is a critical step, limiting extensive usage of this powerful approach. In this work, we introduce EMUlator a Python-based isotope simulator which is developed on Elementary Metabolite Unit (EMU) algorithm, an efficient and powerful algorithm for isotope modeling. We propose a novel adjacency matrix method to implement EMU modeling and exemplify it stepwise. This method is intuitively straightforward and can be conveniently mastered for various customized purposes. We apply this arithmetic pipeline to understand the phosphoketolase flux in the metabolic network of an industrial microbe Clostridium acetobutylicum. The resulting design enables a high-throughput and non-invasive approach for estimating phosphoketolase flux in vivo. Our computational insights allow the systematic design and prediction of isotope-based metabolic models and yield a comprehensive understanding of their limitations and potentials.},
doi = {10.3389/fmicb.2019.00922},
journal = {Frontiers in Microbiology},
number = ,
volume = 10,
place = {United States},
year = {2019},
month = {4}
}

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