Biohydrogen production by bacteria using sago waste and its metabolic flux balancing
Hydrogen has been recognized as one of the potential alternative energy sources which can be used for many different purposes. It can be produced from microbial cultivation with waste organic materials. However, the amount of biohydrogen produced is still at an unsatisfactorily level. Besides, raw m...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/44634/ http://irep.iium.edu.my/44634/13/bio.pdf |
| Summary: | Hydrogen has been recognized as one of the potential alternative energy sources which can be used for many different purposes. It can be produced from microbial cultivation with waste organic materials. However, the amount of biohydrogen produced is still at an unsatisfactorily level. Besides, raw material cost is another concern for making the whole process economically feasible. This study aimed to use Flux Balance Analysis (FBA) to investigate and understand the production of biohydrogen using microbial cultures with sago waste as the substrate. FBA is a powerful quantitative approach to recognize and determine the specific pathways or branch reactions that influence the most in a specific metabolite formation. A stoichiometric balance metabolic model has been reconstructed based on the latest published articles, biochemistry books and online resources (Kyoto Encyclopedia of Genes and Genome (KEGG) and MetaCyc) using Escherichia coli (E.coli) as the model. This model consists of 206 metabolic reactions with 144 metabolites towards the production of biomass and biohydrogen. The carbon metabolic pathways include glycolysis/gluconeogenesis, pentose phosphate pathway (PPP), pyruvate metabolism, tricarboxylic acid (TCA) cycle and electron transport. A series of batch experiments involving E. coli and Enterobacter aerogenes (E. aerogenes) were carried out and the experimental data such as sugar uptake and specific growth rates as well as the biomass composition (proteins, RNA, DNA and lipids) were used as the constraints for the model. The objective function was set as the maximization of hydrogen yield in order to solve the unknown fluxes using Linear Programming (LP) method in General Algebraic Modelling System (GAMS) software. The FBA results showed the pathways that are involved in the biohydrogen production and the metabolites that will affect the most the yield of biohydrogen in both hydrogen-producing bacteria. In addition, further in silico analysis was done on the metabolic mdoel such as deletion of certain metabolites to investigate their effect on biohydrogen yield. |
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