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Flux Balance Analysis to Model Microbial Metabolism for Electricity Generation

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Flux Balance Analysis to Model Microbial Metabolism for Electricity Generation Lincoln University Digital Thesis Copyright Statement The digital copy of this thesis is protected by the Copyright Act 1994 (New Zealand). This thesis may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: you will use the copy only for the purposes of research or private study you will recognise the author's right to be identified as the author of the thesis and due acknowledgement will be made to the author where appropriate you will obtain the author's permission before publishing any material from the thesis. Flux balance analysis to model microbial metabolism for electricity generation A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy in Computational Biology and Bioengineering at Lincoln University by Longfei Mao Lincoln University 2013 Abstract of a thesis submitted in partial fulfilment of the requirements for the Degree of Philosophy Flux balance analysis to model microbial metabolism for electricity generation by Longfei Mao Abstract Microbial fuel cells (MFCs) are bioelectrochemcial devices that possess a similar design to a fuel cell, with an anode and a cathode connected through an electrical circuit. Unlike fuel cells, MFCs use microorganisms as biocatalysts to convert organic matter into electrons and protons, of which a portion can be transferred to electrode to generate electricity. Since all microorganisms transfer electrons during metabolism inside the cell, there could potentially be unlimited choices of biocatalyst candidates for MFCs for various applications. However, in reality, the application of MFCs is heavily restricted by their low current outputs. As the performance of an MFC is associated with various factors, MFC research devoted to improve energy output level is a very interdisciplinary field and demands knowledge from a diverse range of scientific areas including microbiology, environmental science and chemical engineering. Because the MFC current is fundamentally produced by the metabolic activity of the microorganisms, it would be desirable to elucidate the innate capacity of the microbial systems to sustain the energy extraction processes in MFCs, and pertinent metabolic pathways and burdens. However, due to the large number of cellular reactions (up to thousands for a eukaryote), no previous study has provided such information regarding the complete metabolic processes inside the cells during an MFC operation. Therefore, to understand the metabolic potential and behaviours at the whole-cell level and obviate the difficulties experienced in reductionist investigative methods, the present PhD thesis employed in silico metabolic engineering techniques to model the optimal metabolic states and flux adjustments of the four selected microbial species for electricity generation. ii The first part of this thesis is the development of a framework method based on existing constraint-based methods to analyse the impact of microbial electricity generation on the metabolisms of the selected microorganisms at genome-scale. To identify the alternative equivalent solutions and avoid the disturbance of futile cycle in a network mode, we developed a method, flux variability analysis with target flux minimization (FATMIN), which can characterize the metabolic strategies underlying a high current output compatible with reaction stoichiometry and realistic biological constraints. The second part of this thesis is the application of the constraint-based methods to model the four selected microorganisms for current production. The present study mainly considered NADH as the intracellular electron source for MET mode and c-type cytochrome for DET mode. In DET mode, charge is directly transferred from the microorganism to the electrode, and in MET mode a mediator molecule performs the transfer. The results have shown that that S. cerevisiae was the best candidate for MFC use based on its highest potential computed for current output (5.781 for aerobic and 6.193 A/gDW for anaerobic growths) and coulombic efficiency (over 85%). G. sulfurreducen had a potential to achieve the second highest current, up to 2.711 A/gDW for MET mode, 3.710 A/gDW for DET mode and 3.272 A/gDW for a putative mixed MET and DET mode. On the other hand, the maximum current values of 2.368 and 0.792 A/gDW were obtained from MET mode for C. reinhardtii under mixotrophic conditions and from DET mode for Synechocystis sp. PCC 6803 under autotrophic conditions respectively. Subsequently, the present study elucidated the impact of NADH, type-c cytochrome, ferredoxin and quinol-dependent current generation on the metabolisms and possible metabolic pathways that microorganisms can use to resolve the redox disruption arising from the energy extraction. It is expected that these referential data on the four pure cultures to be a good starting point for development of other experimental MFC research. The final part of the thesis is the employment of an optimization algorithm to test the suitability of reaction deletion strategy for improving the electron transfer rates for electricity generation. The results show that the reaction deletion strategy has improved the reducing equivalent regeneration capability for MFC current production in all the cases of G. sulfurreducens, C. reinhardtii and Synechocystis to different extents. Notably, the identified knockouts could effectively produce S. cerevisiae mutants that have elevated the lower limits of the current output to about two-third the theoretical maximum current. iii Overall, this thesis is the first report of using in silico modelling approach to study the capability and underlying metabolisms of microbial oxidation at the anode. It is expected the knowledge extended by this thesis in the microbial processes for electricity generation will integrate with advance in electrochemical engineering to increase performance of MFCs in future. Keywords: MFC; Microbial fuel cell; Geobacter sulfurreducens; Chlamydomonas reinhardtii; Synechocystis sp. PCC 6803; Sachoromyoces cerevisiae; bioelectricity; Flux balance analysis; Flux variability analysis; Flux minimization; FATMIN; Mathematical optimization; Metabolic model; Metabolic network analysis; Metabolic network redesign; Metabolic engineering; In silico simulation; Model-driven discovery. iv List of Publications Some parts of materials in this thesis have been published or accepted, and some have been submitted for publications Verwoerd, W. S., & Mao, L. (2014). The Problem of Futile Cycles in Metabolic Flux Modeling: Flux Space Characterisation and Practical Approaches to its Solution. In S. K. Basu & N. Kumar (Eds.), Simulation Foundations, Methods and Applications: Modeling and Simulation Methods and Applications: Springer (In press). Mao, L., & Verwoerd, W. S. (2013). Selection of organisms for systems biology study of microbial electricity generation: a review. International Journal of Energy and Environmental Engineering, 4(1), 17. Mao, L., & Verwoerd, W. S. (2013) Model-driven elucidation of the inherent capacity of Geobacter sulfurreducens for electricity generation. Journal of Biological Engineering, 7(1), 14. Mao, L., & Verwoerd, W. S. Computational comparison of mediated MFC current generation capacity of Chlamydomonas reinhardtii in photosynthetic and respiratory growth modes. Submitted to Molecular BioSystems Mao, L., & Verwoerd, W. S. (2013) Genome-scale stoichiometry analysis to elucidate the innate capability of the cyanobacterium Synechocystis for electricity generation. Journal of Industrial Microbiology & Biotechnology, 40(10), 1161-1180. Mao, L., & Verwoerd, W. S. (2013). Exploration and comparison of inborn microbial capacity of aerobic and anaerobic metabolisms of Saccharomyces cerevisiae for current production. Bioengineered, 4(6), 23-22. v Mao, L., & Verwoerd, W. S. (2013). MFCoT - a computational toolbox to study the metabolism of MFC biocatalysts. In 4th international microbial fuel cell conference; Cairns, Australia. 82-83. vi Acknowledgments The production of a doctoral thesis often involves uncertainty, sacrifice, failure and aloneness. However, in addition to those stressful feelings, my PhD experience contains enjoyableness, cooperativeness, effectiveness and success. All these are possible due to two key ingredients: one is my supervisor, Dr. Wynand Verwoerd, and the other is the passion for science that he has passed on to me. Perhaps, in the multi-disciplinary laboratory of the systems biology at Lincoln, I was the most ignorant and naive of my colleagues, but with the inspiration and expertise of Dr. Verwoerd, I could push myself to the limit and learn as much as possible. For the past years, Dr. Verwoerd has been a phenomenal mentor to me, and represents an exceptional scientist who is fast, inquisitive and explorative. I truly appreciate the valuable opportunity he gives me to pursue a PhD under his mentorship. I think I am fortunate enough to know him and to be his student in this life. I would also like to acknowledge Professor Don Kulasiri for all his good suggestions and insightful conversions about the life and philosophy during the Wednesday group meeting. As the head of Centre for Advanced Computational Solutions (C-fACS), he has provided unwavering supports over the course of this project. To the fellow students at C-fACS, I have to express my appreciation for sharing the knowledge. Besides, I am grateful to Caitriona Cameron for her useful advice in improving my acadmetic writting skills.
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