Dataset Information

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.

SUBMITTER: Rollin JA

PROVIDER: S-EPMC4413329 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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

Rollin Joseph A JA Martin del Campo Julia J Myung Suwan S Sun Fangfang F You Chun C Bakovic Allison A Castro Roberto R Chandrayan Sanjeev K SK Wu Chang-Hao CH Adams Michael W W MW Adams Michael W W MW Senger Ryan S RS Zhang Y-H Percival YH

Proceedings of the National Academy of Sciences of the United States of America 20150406 16

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 y ...[more]

PMID: 25848015

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Project description:Lignocellulosic biomass is recalcitrant toward deconstruction into simple sugars mainly due to the presence of lignin. By engineering plants to partially replace traditional lignin monomers with alternative ones, lignin degradability and extractability can be enhanced. Previously, the alternative monomer curcumin has been successfully produced and incorporated into lignified cell walls of Arabidopsis by the heterologous expression of DIKETIDE-CoA SYNTHASE (DCS) and CURCUMIN SYNTHASE2 (CURS2). The resulting transgenic plants did not suffer from yield penalties and had an increased saccharification yield after alkaline pretreatment. Here, we translated this strategy into the bio-energy crop poplar. Via the heterologous expression of DCS and CURS2 under the control of the secondary cell wall CELLULOSE SYNTHASE A8-B promoter (ProCesA8-B), curcumin was also produced and incorporated into the lignified cell walls of poplar. ProCesA8-B:DCS_CURS2 transgenic poplars, however, suffered from shoot-tip necrosis and yield penalties. Compared to that of the wild-type (WT), the wood of transgenic poplars had 21% less cellulose, 28% more matrix polysaccharides, 23% more lignin and a significantly altered lignin composition. More specifically, ProCesA8-B:DCS_CURS2 lignin had a reduced syringyl/guaiacyl unit (S/G) ratio, an increased frequency of p-hydroxyphenyl (H) units, a decreased frequency of p-hydroxybenzoates and a higher fraction of phenylcoumaran units. Without, or with alkaline or hot water pretreatment, the saccharification efficiency of the transgenic lines was equal to that of the WT. These differences in (growth) phenotype illustrate that translational research in crops is essential to assess the value of an engineering strategy for applications. Further fine-tuning of this research strategy (e.g., by using more specific promoters or by translating this strategy to other crops such as maize) might lead to transgenic bio-energy crops with cell walls more amenable to deconstruction without settling in yield.

Project description:BackgroundThe optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing.ResultsWe present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli.ConclusionsWe develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements.

Dataset Information

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

Publications

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

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