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:
-
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Inst. of Nuclear Energy Research, Taoyuan (Taiwan)
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (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), Sustainable Transportation Office. Bioenergy Technologies Office (BETO)
- 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. https://doi.org/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. https://doi.org/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 = {Tue Apr 30 00:00:00 EDT 2019},
month = {Tue Apr 30 00:00:00 EDT 2019}
}
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Cited by: 3 works
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Figures / Tables:
FIGURE 1: Simplified tricarboxylic acid (TCA) cycle to illustrate adjacency matrix-based EMU decomposition. Reactions involved in the metabolic model are listed on the right. Lowercase letters in brackets demonstrate atom transition in each reaction. Decimals indicate EMU equivalents due to rotation axis within molecule. AcCoA, acetyl coenzyme A; AKG, $a$-ketoglutarate;more »
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Cumulative bondomers: A new concept in flux analysis from 2D [13C,1H] COSY NMR data
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- Biotechnology and Bioengineering, Vol. 80, Issue 7
An elementary metabolite unit (EMU) based method of isotopically nonstationary flux analysis
journal, February 2008
- Young, Jamey D.; Walther, Jason L.; Antoniewicz, Maciek R.
- Biotechnology and Bioengineering, Vol. 99, Issue 3
Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells
journal, November 2009
- Metallo, Christian M.; Walther, Jason L.; Stephanopoulos, Gregory
- Journal of Biotechnology, Vol. 144, Issue 3
Transcriptional analysis of catabolite repression in Clostridium acetobutylicum growing on mixtures of d-glucose and d-xylose
journal, November 2010
- Grimmler, Christina; Held, Claudia; Liebl, Wolfgang
- Journal of Biotechnology, Vol. 150, Issue 3
Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements
journal, July 2006
- Antoniewicz, Maciek R.; Kelleher, Joanne K.; Stephanopoulos, Gregory
- Metabolic Engineering, Vol. 8, Issue 4
Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for 13C metabolic flux analysis
journal, November 2014
- Au, Jennifer; Choi, Jungik; Jones, Shawn W.
- Metabolic Engineering, Vol. 26
13C metabolic flux analysis at a genome-scale
journal, November 2015
- Gopalakrishnan, Saratram; Maranas, Costas D.
- Metabolic Engineering, Vol. 32
Metabolic networks in motion: 13 C‐based flux analysis
journal, January 2006
- Sauer, Uwe
- Molecular Systems Biology, Vol. 2, Issue 1
Synthetic non-oxidative glycolysis enables complete carbon conservation
journal, September 2013
- Bogorad, Igor W.; Lin, Tzu-Shyang; Liao, James C.
- Nature, Vol. 502, Issue 7473
influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments
journal, December 2011
- Sokol, S.; Millard, P.; Portais, J. -C.
- Bioinformatics, Vol. 28, Issue 5
13CFLUX2—high-performance software suite for 13C-metabolic flux analysis
journal, October 2012
- Weitzel, Michael; Nöh, Katharina; Dalman, Tolga
- Bioinformatics, Vol. 29, Issue 1
Transcriptional analysis of differential carbohydrate utilization by Clostridium acetobutylicum
journal, July 2010
- Servinsky, M. D.; Kiel, J. T.; Dupuy, N. F.
- Microbiology, Vol. 156, Issue 11
Genome-Scale Fluxome of Synechococcus elongatus UTEX 2973 Using Transient 13 C-Labeling Data
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- BioMed Research International, Vol. 2014
OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis
journal, January 2009
- Quek, Lake-Ee; Wittmann, Christoph; Nielsen, Lars K.
- Microbial Cell Factories, Vol. 8, Issue 1
OpenFLUX2: 13C-MFA modeling software package adjusted for the comprehensive analysis of single and parallel labeling experiments
journal, November 2014
- Shupletsov, Mikhail S.; Golubeva, Lyubov I.; Rubina, Svetlana S.
- Microbial Cell Factories, Vol. 13, Issue 1
Isotope-Assisted Metabolite Analysis Sheds Light on Central Carbon Metabolism of a Model Cellulolytic Bacterium Clostridium thermocellum
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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.