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Title: High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

Abstract

The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2∙L₋1∙h₋1. The productivity was further enhanced to 54 mmol H2∙L₋1∙h₋1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

Authors:
 [1];  [2];  [3];  [4];  [1];  [5];  [6];  [7];  [7];  [8];  [2];  [9]
  1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Biological Systems Engineering; Cell-Free Bioinnovations, Blacksburg, VA (United States)
  2. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Biological Systems Engineering
  3. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Biological Systems Engineering; Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Inst. for Critical Technology and Applied Science
  4. Cell-Free Bioinnovations, Blacksburg, VA (United States)
  5. Milwaukee School of Engineering, Milwaukee, WI (United States). Dept. of Physics and Chemistry
  6. Texas A&M Univ., Kingsville, TX (United States). Dept. of Chemical and Natural Gas Engineering
  7. Univ. of Georgia, Athens, GA (United States). Dept. of Biochemistry and Molecular Biology
  8. Univ. of Georgia, Athens, GA (United States). Dept. of Biochemistry and Molecular Biology; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). BioEnergy Science Center (BESC)
  9. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Biological Systems Engineering; Cell-Free Bioinnovations, Blacksburg, VA (United States); Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Inst. for Critical Technology and Applied Science; Chinese Academy of Sciences (CAS), Tianjin(China). Tianjin Inst. of Industrial Biotechnology
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1293980
Grant/Contract Number:  
FG05-95ER20175; IIP-1321528; IIP-1353266
Resource Type:
Accepted Manuscript
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 112; Journal Issue: 16; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 09 BIOMASS FUELS; 08 HYDROGEN; hydrogen; biomass; in vitro metabolic engineering; metabolic network modeling; global sensitivity analysis

Citation Formats

Rollin, Joseph A., Martin del Campo, Julia, Myung, Suwan, Sun, Fangfang, You, Chun, Bakovic, Allison, Castro, Roberto, Chandrayan, Sanjeev K., Wu, Chang-Hao, Adams, Michael W. W., Senger, Ryan S., and Zhang, Y. -H. Percival. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling. United States: N. p., 2015. Web. doi:10.1073/pnas.1417719112.
Rollin, Joseph A., Martin del Campo, Julia, Myung, Suwan, Sun, Fangfang, You, Chun, Bakovic, Allison, Castro, Roberto, Chandrayan, Sanjeev K., Wu, Chang-Hao, Adams, Michael W. W., Senger, Ryan S., & Zhang, Y. -H. Percival. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling. United States. https://doi.org/10.1073/pnas.1417719112
Rollin, Joseph A., Martin del Campo, Julia, Myung, Suwan, Sun, Fangfang, You, Chun, Bakovic, Allison, Castro, Roberto, Chandrayan, Sanjeev K., Wu, Chang-Hao, Adams, Michael W. W., Senger, Ryan S., and Zhang, Y. -H. Percival. Mon . "High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling". United States. https://doi.org/10.1073/pnas.1417719112. https://www.osti.gov/servlets/purl/1293980.
@article{osti_1293980,
title = {High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling},
author = {Rollin, Joseph A. and Martin del Campo, Julia and Myung, Suwan and Sun, Fangfang and You, Chun and Bakovic, Allison and Castro, Roberto and Chandrayan, Sanjeev K. and Wu, Chang-Hao and Adams, Michael W. W. and Senger, Ryan S. and Zhang, Y. -H. Percival},
abstractNote = {The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2∙L₋1∙h₋1. The productivity was further enhanced to 54 mmol H2∙L₋1∙h₋1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.},
doi = {10.1073/pnas.1417719112},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 16,
volume = 112,
place = {United States},
year = {Mon Apr 06 00:00:00 EDT 2015},
month = {Mon Apr 06 00:00:00 EDT 2015}
}

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