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Metabolic Flux Analysis Of Ethanol Type Fermentation Hydrogen Production Bacteria And Research On Regulation Mechanism

Posted on:2017-11-25Degree:MasterType:Thesis
Country:ChinaCandidate:S R JiaFull Text:PDF
GTID:2381330545998683Subject:Environmental engineering
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Biohydrogen fermentation has attracted great research interest with degradation of sewage and energy recovery.Currently improving hydrogen production efficiency is the bottleneck of industrial applications.Releasing hydrogen metabolism of microorganisms present in the product inhibition is an effective way.In this study the typical ethanol type fermentation bacteria E.harbinense B49 is the research object.Using metabolic flux analysis to explore the microbial hydrogen production mechanism.Exploring liquid end product inhibition effects on metabolic flux of hydrogen production.Bipolar membrane electrodialysis coupled with hydrogen production isolated major inhibitory product acetic acid.Different operating modes are used to metabolic flux analysis,and explicit hydrogen metabolism key points.Provide theoretical support for improving anaerobic metabolic flux of hydrogen production,hydrogen production efficiency enhancement type of ethanol fermentation.We established metabolic flux analysis method as theoretical foundation.Constructing and simplifying metabolic network of E.harbinense B49 include EMP,PPP and TCA.Obtained by screening and simplify finishing containing 14 equations(biochemical reactions)and 14 unknowns(metabolites)from the entire metabolic network.Wherein the ends of the substrate glucose and metabolites acetate,ethanol,butyrate,carbon dioxide and hydrogen through the experimentally measured,the mass balance is calculated intermediate metabolite intracellular metabolic flux,the experimental data is converted to normalized data analyzed and plotted metabolic flux distribution.Use E.Harbinense B49 metabolic flux analysis method has been established applied hydrogen metabolism in different concentrations of acetic acid and ethanol were analyzed.The network has two hydrogen precursors Fdred and NADH.Applied acetic acid make lactic acid flux increases,precursors hydrogen production NADH is consumed,resulting in hydrogen production decline.The addition of low concentrations of ethanol has little effect on the overall metabolic effect on hydrogen production is mainly to reduce AcCoA to PYR way lead to a reduction in the pathway flux generated hydrogen precursors Fdred,the high-concentration ethanol makes the overall metabolic rate decreases.Through the nodes at different concentrations on the percentage difference between the initial concentration and the initial concentration changes to determine the size of key nodes,the nodes determine the robustness of the linear relationship between these nodes generate and consumption rate.G6P belongs flexible node.PYR is rigid nodes.Acetyl coenzyme A is weak rigid joints,Then from the point of view of intracellular metabolism analysis of different product concentrations to suppress the influence of the amount of hydrogen production.Use E.Harbinense B49 metabolic flux analysis method has been established for the traditional fermentation hydrogen production,hydrogen fermentation and separation coupled intermittent operation mode,fed hydrogen metabolism in operation mode analysis.Three hydrogen flux modes are 208.3,210.4 and 238.5 mmol/g CDW h-1.It is mainly through the separation and increase the production of acetic acid pathway,thereby increasing the flux of pyruvate to acetyl coenzyme A,leading to two hydrogen precursors Fdred and NADH increased,which is greater than the traditional fermentation efficiency in hydrogen production mode and intermittent operation mode.In the comparative study of traditional fermentation and electrodialysis continuous separation of acetic acid coupled experiment found that continuous separation coupled continuous experiments and efficient separation of acetic acid,to obtain specific hydrogen production rate 1.65mol H2/mol glucose,compared with the traditional model increased by nearly 30%.According to continuously feeding the fermentation and product separation test hydrogen production continuous separation mode continuous operation,when the glucose degradation rate has remained at a high level,to achieve a continuous feeding continuous separation mode stable operation,and get more than hydrogen production was 2.2mol H2/mol glucose.Continuous feeding and continuously separating hydrogen production mode,acetic acid production and growth of cell separation compared with not continuous feeding mode were all improved.Supplementary continuous separation and substrate acid helps to improve hydrogen production capacity.Traditional fermentation,continuous separation,continuous separation and continuous feeding three different operating modes metabolic flux analysis.Experimental study found that continuous separation coupled continuous and efficient separation of acetic acid,to obtain specific hydrogen production rate 1.65mol H2/mol glucose,compared with the traditional model increased nearly 30%.Continuous feeding mode continuous separation of glucose degradation rate has remained at a high level,to achieve a continuous feeding continuous separation mode stable operation,and obtain specific hydrogen production rate of 2.2mol H2/mol glucose.Three different operating modes metabolic flux analysis showed that continuous operation separating acetic acid electrodialysis continuous feeding mode dramatically improves the process E.harbinese B49 metabolism of glucose to generate the amount of hydrogen production major precursor Fdred(the three modes are 211,248 and 281mmol/g CDW h-1).Resulting in a higher hydrogen production efficiency,the established method showed good explanation of the inherent regulatory mechanisms to lift the inhibition of the production of acetic acid hydrogen promote and provide theoretical guidance for the next step to take engineering to further increase the amount of hydrogen production.
Keywords/Search Tags:Ethanol-type fermentation, Biohydrogen, Metabolic Flux Analysis, Analysis of node
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