Award Abstract # 1511346
GOALI: Development of Spatiotemporal Metabolic Models for Syngas Fermentation in Industrial Bubble Column Reactors

NSF Org: CBET
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Recipient: UNIVERSITY OF MASSACHUSETTS
Initial Amendment Date: June 1, 2015
Latest Amendment Date: June 1, 2015
Award Number: 1511346
Award Instrument: Standard Grant
Program Manager: Robert McCabe
CBET
 Division of Chemical, Bioengineering, Environmental, and Transport Systems
ENG
 Directorate for Engineering
Start Date: June 1, 2015
End Date: May 31, 2019 (Estimated)
Total Intended Award Amount: $300,000.00
Total Awarded Amount to Date: $300,000.00
Funds Obligated to Date: FY 2015 = $300,000.00
History of Investigator:
  • Michael Henson (Principal Investigator)
    henson@ecs.umass.edu
  • Derek Griffin (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Massachusetts Amherst
101 COMMONWEALTH AVE
AMHERST
MA  US  01003-9252
(413)545-0698
Sponsor Congressional District: 02
Primary Place of Performance: University of Massachusetts Amherst
Amherst
MA  US  01003-9242
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): VGJHK59NMPK9
Parent UEI: VGJHK59NMPK9
NSF Program(s): Proc Sys, Reac Eng & Mol Therm,
GOALI-Grnt Opp Acad Lia wIndus
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 047E, 050E, 1504, 7752
Program Element Code(s): 140300, 150400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Henson - 1511346

One of the most promising routes to renewable liquid fuels and chemicals is the fermentation of waste carbon by specialized microbes. This can not only enable advanced biofuel and renewable chemical production but could also help reduce carbon emissions. Commercial development of gas fermentation technology is being led by emerging companies such as LanzaTech, but many fundamental research problems must be addressed to further advance the technology towards economic competitiveness. A particularly important challenge is to develop integrated metabolic and transport models that describe gas fermentation in industrially relevant bubble column reactors. The development of such spatiotemporal metabolic models is an emerging research problem with numerous potential applications in environmental science, biotechnology, bioenergy and human health. The objectives of this GOALI project are to develop general tools for spatiotemporal metabolic modeling and to evaluate the methods through application to gas fermentation in bubble column reactors.

The PIs plan to convert CO-rich waste streams as well as synthesis gas (syngas - mainly comprised of H2/CO/CO2) to liquid fuels and chemicals in bubble column reactors. His proposed modeling approach involves combining genome-scale reconstructions of species metabolism with transport equations that govern the relevant convective and/or diffusional processes within the spatially varying system. The resulting models consist of linear programs for intracellular metabolism embedded within partial different equations for spatial and dynamic variations within the extracellular environment. UMass will develop efficient model formulation and robust numerical solution techniques using gas fermentation and biofilm growth problems as in silico testbeds. The syngas fermentation models will be developed in collaboration with LanzaTech, an industrial leader in gas fermentation and bubble column reactor technology. These models will be formulated by combining a recently developed genome-scale metabolic reconstruction of the syngas fermenting bacterium Clostridium ljungdahlii with convective transport equations for the feed gas components and the major metabolic byproducts, ethanol and acetate. Following initial testing at UMass, the syngas fermentation models will be validated with data collected from a LanzaTech laboratory/pilot facility. Using these data, the spatiotemporal metabolic models will be refined as necessary to capture the key features of industrial bubble column reactors.

Broader Impacts: The proposed research will both advance fundamental research and impact industrial practice. While a few isolated papers have been published on spatiotemporal metabolic modeling, our research will produce a considerably more general treatment of this important problem. We expect the application work focused on syngas fermentation to produce new computational tools to simulate, design and optimize industrial bubble column reactors. The UMass graduate student supported by NSF funds will complete a four month internship at LanzaTech?s Skokie, IL research facility to participate in data collection and to perform model refinement and validation. The student will be co-advised by the two project investigators, with Prof. Henson (UMass, PI) leading the methods development work and Dr. Griffin (LanzaTech, co-PI) overseeing the bubble column model development work. While at LanzaTech, the student will work with a broad array of scientists and engineers in a highly multidisciplinary and team oriented environment. Tight integration of the UMass and LanzaTech efforts will be achieved through frequent email exchanges, biweekly videoconferences and biannual project meetings. At least two undergraduate students will participate in the research by having the funded Ph.D. student serve a partial advising role. These students will interact with other students funded through the Institute of Massachusetts Biofuels Research (TIMBR) and participate in ongoing TIMBR activities.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Chen, J. and M. A. Henson "In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation" Metabolic Engineering , v.38 , 2016 , p.389 10.1016/j.ymben.2016.10.002
Chen, J., D. Griffin, X. Li and M. A. Henson, "Experimental Testing of a Spatiotemporal Metabolic Model for Carbon Monoxide Fermentation with Clostridium autoethanogenum" Biochemical Engineering Journal , v.129 , 2018 , p.64 10.1016/j.bej.2017.10.018
Chen, J., J. A. Gomez, K. Hoffner, P. I. Barton and M. A. Henson "Metabolic Modeling of Synthesis Gas Fermentation in Bubble Column Reactors" Biotechnology for Biofuels , v.8 , 2015 , p.89 10.1186/s13068-015-0272-5
Chen, J., P. Phalak, J. A. Gomez, K. Hoffner, P. I. Barton and M. A. Henson "Spatiotemporal Modeling of Microbial Metabolism" BMC Systems Biology , v.10 , 2016 , p.21 10.1186/s12918-016-0259-2
Chen, J.,P. Phalak, J. A. Gomez, K. Hoffner, P. I. Barton and M. A. Henson "Spatiotemporal Modeling of Microbial Metabolism" BMC Systems Biology , v.10 , 2016 , p.21 10.1186/s12918-016-0259-2
Henson, M. A. "Genome-Scale Modeling of Microbial Metabolism with Temporal and Spatial Resolution" Biochemical Society Transactions , v.43 , 2015 , p.1164 10.1042/BST20150146
Henson, M. A. and P. Phalak "Byproduct Cross Feeding and Community Stability in an In Silico Biofilm Model of the Gut Microbiome" Processes , v.5 , 2017 , p.13 10.3390/pr5010013
Phalak, P., J. Chen, R. P. Carlson and M. A. Henson "Metabolic Modeling of a Chronic Wound Biofilm Consortium Predicts Spatial Partitioning of Bacterial Species" BMC Systems Biology , v.10 , 2016 , p.90 10.1186/s12918-016-0334-8

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The development of new technologies for conversion of cheap sources of carbon into useful fuels and chemicals is of paramount importance to the long-term security and economy of the United States. Gas mixtures containing carbon monoxide (CO) along with carbon dioxide and hydrogen constitute a particularly promising, but underutilized, class of carbon-containing feedstocks. The goal of this project was to develop and evaluate computer modeling technology for large-scale processes designed to convert these CO-rich gas streams into chemicals that have applications as liquid transportation fuels. The research focused on computer modeling of gas fermentation processes in which bacterial cells are used to metabolize the gas components into ethanol and other biochemicals. The modeling framework is based on combining detailed cellular models of bacterial metabolism with process models that capture the gas and liquid transport mechanisms relevant to industrial bubble column bioeactors. Using gas fermentation data collected from a laboratory-scale bioreactor, we demonstrated that the combined cellular-process model could satisfactorily predict key measures of fermentation performance including the concentrations of bacterial cells, the desired product ethanol and the undesired product acetate. Having established model credibility, we applied our modeling framework to several important problems in the gas fermentation field including optimization and control of bioreactor operating conditions and production of more valuable biochemicals such as butyrate. We believe that this project represents an important step to advancing gas fermentation technology towards reality.


Last Modified: 07/02/2019
Modified by: Michael A Henson

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