AN ABSTRACT OF THE THESIS OF

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2 AN ABSTRACT OF THE THESIS OF Robert G. Hall for the degree of Master of Science in Biological and Ecological Engineering presented on August 3, Title: Metabolic Engineering of Shewanella oneidensis MR-1 for Microbial Fuel Cell Application Abstract approved: Frank W.R. Chaplen Shewanella oneidensis MR-1 is a gram-negative, facultative anaerobic bacteria with the capability of dissimilatory metal reduction. The ability of the organism to reduce a wide range of solid metal-oxides during anaerobic respiration makes it an ideal candidate for the powering of microbial fuel cells (MFCs), which capture the electrons discharged by the organism as work energy. The transfer of electrons from S. oneidensis to an anode surface occurs either as the result of direct electron transfer from a proximal outer membrane (OM) surface, or via soluble shuttling compounds which ferry the electrons from distal OM surfaces. The concentration of these electron shuttling compounds in the media have a strong influence on the current produced in the MFC. The ability of S. oneidensis to produce soluble electron shuttling compounds de novo in the form of riboflavin and flavin mononucleotide (FMN) provides a metabolic target for the enhancement of current generation in an MFC. This study uses variable ion concentrations in

3 the growth media to deregulate the riboflavin synthesis pathway in S. oneidensis and induce the overproduction of electron shuttling compounds. The increase in electron shuttle production is demonstrated to increase the current produced in an MFC. Additionally, the metabolic relationship between the rates of growth, electron shuttle production, and anaerobic respiration are explored using flux balance analysis (FBA). Statistically designed screening experiments were used to quantify the influence of Mg 2+, Ca 2+, K +, NH + 4, PO 3 4, SeO 2 4, and Na + concentrations in the growth media on the metabolic production rate of riboflavin and FMN by S. oneidensis. Mg 2+ was the only compound identified to be a significant factor in influencing the production of these electron shuttling compounds. A 5.75 mm reduction in Mg 2+ concentration (0.25 mm vs mm) correlated to an increase of 0.55 µm gafdw 1 (grams ash-free dry cell weight) combined flavin concentration after 72 hours of anaerobic growth. The difference in electron shuttle concentration resulted from a 0.95 µm gafdw 1 increase in FMN concentration and a 0.40 µm gafdw 1 decrease in riboflavin concentration with the reduced Mg 2+ dose. The influence of Mg 2+ on electron shuttle production was highly sensitive to the presence of other compounds in the media. The addition of mineral and vitamin supplements to the media eliminated the significant influence of Mg 2+ on electron shuttle production rate. S. oneidensis current generation in an MFC was evaluated at different metabolic production rates of electron shuttling compounds. The concentration of Mg 2+ was used as the sole variable to influence these production rates. At three tested magni-

4 tudes of load resistances, the MFC receiving the low Mg 2+ treatment outperformed the high Mg 2+ treatment. The low Mg 2+ treatment produced 52% higher maximum current at 27800Ω resistance, 74% higher maximum current at 8250Ω, and 151% at 1100Ω. This corresponds to the highest observed current output of 260 ± 72 µa observed by the low Mg 2+ treatment at 1100Ω. The superior performance of MFCs containing the low treatment of Mg 2+ was observed both in single-chamber MFCs and in MFCs where direct anode contact by the bacteria was precluded. Low Mg 2+ concentration in MFCs where direct anode contact was precluded not only increased the maximum current generating potential, but significantly decreased the time necessary to utilize the avaiable substrate. A genome-scale, FBA model was used to evaluate the metabolic capabilities of S. oneidensis. The model, originally calibrated for aerobic conditions, was evaluated under anaerobic growth conditions using lactate and fumarate. The model correctly predicted the acetate secretion rate, however, was off by several factors in the prediction of succinate and the biomass growth rate. The difference between experimental and computer simulations was small enough to conclude qualitative validation of the model. FBA model simulations were used to evaluate the parameters of growth rate, electron shuttle production rate, and anaerobic respiration rate. A trade-off between electron shuttle production and biomass accumulation was predicted to be gafdw mm 1 for riboflavin production and gafdw mm 1 for FMN production. Similarly, a decrease in anaerobic respiration rate was predicted for rate increases to flavin compound synthesis at a ratio of mm e mm 1 and

5 mm e mm 1 for riboflavin and FMN, respectively. A comparison between extreme cases of FMN production indicated an increased demand for phosphorous and nitrogen under conditions of high FMN synthesis. Review of central carbon metabolism under these conditions demonstrates that this increased demand is due to the increased flow of material through the pentose phosphate pathway. The model was used to screen single reaction knockouts for potentially useful genetic modifications. Removal of acetate kinase resulted in an increase of the anaerobic respiration rate, however, this mutation has been previously identified as a fatal knockout. The knockout of cytochrome-c oxidase also indicated an increase to the anaerobic respiration rate and has previously been identified as a mutant with superior current generating performance in an MFC as compared to the wildtype strain. Several other potentially beneficial knockouts are identified, including non-intuitive knockouts such as homoserine kinase. The results of this study demonstrate that microbial metabolism significantly influences the performance of MFCs not only though respiration rates, but through the rate of electron shuttle production. Modification of electron shuttle production rates was successful by changing the availability of Mg 2+ to S. oneidensis, however, FBA simulations suggest that higher production rates are still possible. The results of this study provide a practical framework for the targeting of S. oneidensis flavin metabolism as a means of enhancing MFC current densities.

6 c Copyright by Robert G. Hall August 3, 2011 All Rights Reserved

7 Metabolic Engineering of Shewanella oneidensis MR-1 for Microbial Fuel Cell Application by Robert G. Hall A THESIS submitted to Oregon State University in partial fulfillment of the requirements for the degree of Master of Science Presented August 3, 2011 Commencement June 2012

8 Master of Science thesis of Robert G. Hall presented on August 3, APPROVED: Major Professor, representing Biological and Ecological Engineering Head of the Department of Biological and Ecological Engineering Dean of the Graduate School I understand that my thesis will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my thesis to any reader upon request. Robert G. Hall, Author

9 ACKNOWLEDGEMENTS I would like to thank my advisor, Dr. Frank W.R. Chaplen, and my committee members, Dr. Hong Liu and Dr. Ganti Murthy, for mentoring me during the course of this study. I would also like to thank my colleagues Shoutao Xu, Mark Luterra, Jed Eberly, Keaton Lesnik, Deepak Kumar and Abraham Mooney who were always willing to lend an ear. Finally, I would like to thank Jessica Yankovich for her amazing editing skills and unwavering support over the course of this project.

10 TABLE OF CONTENTS Page 1 Introduction 1 2 Deregulation of Flavin Compound Production in Shewanella oneidensis MR-1 by Media Modification Background Methods and Materials Bacterial Strains and Media Conditions Statistical Experiment Design and Analysis Metabolite Analysis Experimental Results Validation of HPLC Procedures M1 Media Main Effects Metal Ion Response Surface Role of Mg Discussion Analytical Methodology Mg 2+ Influence on Flavin Production Conclusions Modified Mg 2+ Concentration influence on Shewanella oneidensis MR-1 Current Generation in a Microbial Fuel Cell Background Method and Materials Bacterial Strains and Media Conditions MFC Specifications MFC Operation Dialysis Membrane Characterization Results Mediatorless MFC Operation Preclusion of Direct Anode Contact Discussion MFC Conclusions

11 TABLE OF CONTENTS (Continued) 4 Shewanella oneidensis MR-1 Flux Balance Analysis Using a Genome-scale Page Model Background Method and Materials Flux Balance Analysis Model Dynamic Flux Balance Analysis Model Results Model Validation with Experimental Data Metabolic Trade-off Analysis Implementation of Commericial Production Strategy Reaction Knockout Analysis Discussion Validity of Model Under Anaerobic Conditions Exploration of Shewanella oneidensis MR-1 Metabolism using FBA Model Conclusions Conclusion 79 Bibliography 80

12 Figure LIST OF FIGURES Page 1.1 Shewanella oneidensis MR-1 Flavin Synthesis Pathway µm FMN Standard Chromatograms HPLC standard degradation during 12 days at 4 o C Effect of storage on riboflavin chromatogram Effect of storage on FMN chromatogram Central Composite Design: Boxplot of Riboflavin response vs. K + Concentration Central Composite Design: Boxplot of FMN response vs. Mg 2+ Concentration Central Composite Design: Boxplot of FMN response vs. Ca 2+ Concentration Central Composite Design: Surface of FMN response vs. Mg 2+ and Ca 2+ Interaction Boxplot of Riboflavin Response vs. Mg 2+ Treatment Level Boxplot of FMN Response vs. Mg 2+ Treatment Level Boxplot of Total Flavin Response vs. Mg 2+ Treatment Level MFC Current Generation in Cells 205, 108, MFC Current Generation in Cells 104, 103, Maximum Current Generation in MFCs at Each Resistance Characterization Flavin Compound Diffusion through Dialysis Membrane MFC Start-up Performance with Membrane Precluding Anode Contact MFC Lifetime Performance with Membrane Precluding Anode Contact Moving Average of Current Output in MFC by Mg 2+ Treatment.. 51

13 Figure LIST OF FIGURES (Continued) Page 4.1 Observed Biomass Growth and Organic Acid Flux Under Anaerobic Growth Conditions Observed Flavin Flux Under Anaerobic Growth Conditions Modeled Anaerobic Growth Conditions using dynamic FBA Response of Biomass Growth Rate to Increased Electron Mediator Production Response of Outer Membrane Electron Flux to Increased Electron Mediator Production Exchange Flux Values Resulting from Extreme Flavin Production States Selected Internal Flux Values Resulting from Extreme Flavin Production States Simulated Growth Profile of Reaction Knockout Mutants Simulated Outer Membrane Electron Flux of Reaction Knockout Mutants Simulated Outer Membrane Electron Flux of Reaction Knockout Mutants

14 Table LIST OF TABLES Page 2.1 One-Eighth Factorial Design Setup and Results Categorical ANOVA Summary for M1 Media Component Influence on Riboflavin Concentration Categorical ANOVA Summary for M1 Media Component Influence on FMN Concentration Central Composite Design Setup and Results Riboflavin Coded Parameter Estimate and ANOVA Statistics for Central Composite Design FMN Coded Parameter Estimate and ANOVA Statistics for Central Composite Design Mean Flavin Concentration from Mg 2+ Treatments Summary of MFC Operating Parameters Comparison of Observed Flux to Model Output Under Anaerobic Growth Conditions Implementation of Commercial Riboflavin Production Strategy on S. oneidensis Model

15 Chapter 1 Introduction Securing alternative energy sources is one of society s top priorities as non-renewable energy reserves become depleted, and an increasing amount of data links the burning of fossil fuels to climate change [42], [37]. Emphasis on the development of renewable energy technologies has reignited interest in microbial fuel cells (MFCs). MFCs operate by converting fermentable sugars and other organic material directly to electrical current through the use of microbial metabolism. The ability of MFC technology to produce current from domestic and industrial wastewater has been successfully demonstrated and offers great potential to couple the treatment of wastewater directly to power generation [23], [14]. The demand for domestic wastewater treatment in 2000 was calculated to be 21 billion kilowatt hours per year in the United States alone and is expected to rise to 30 billion kilowatt hours by 2050 based on a projection of the data [1]. Thus, there is great potential to offset this high operational energy demand through the development and implementation of MFC technology to the treatment of domestic and industrial wastewater. This technology would have the added benefit of providing a localized, self-sustaining power source that is immune from reliability issues associated with central power generation and distribution. An additional application of MFCs is the powering of sensors and transmitters in remote locations that are both difficult and costly to reach, such as the bottom of the ocean. The operation of

16 2 mechanical sensors and transmitters with power derived solely from MFCs has been demonstrated successfully in previous studies [40]. The mechanical structure of an MFC is similar to that of a voltaic cell: redox reactions occurring within the anode compartment reduce a conductive anode and the electrons subsequently flow through a load-bearing circuit to the surface of a cathode where they are discharged by cathode oxidation reactions. However, in contrast to the chemical redox reactions taking place at the anode surface in a voltaic cell, MFC anode reduction is driven by the metabolic respiration of electrons from a microbial community [25]. Many species of microbial life have been identified that are capable of reducing anodes composed of solid metal-oxides. Shewanella oneidensis MR-1 is a model organism for the study of electron respiration to solid metal oxides due to its fully sequenced genome and is commonly used as a model organism in the study of MFCs [12]. S. oneidensis is a gram-negative, facultative anaerobe that has demonstrated the capacity to reduce a wide range of solid metal-oxides such as Mn(III), Mn(IV), Fe(III), Cr(IV), and U(VI), as well as organic compounds such as fumarate, nitrate, trimethylamine N-oxide, dimethyl sulfoxide, sulfite, thiosulfate, and elemental sulfur [12], [30], [33]. Research has identified a sequence of heme proteins, named the Mtr respiratory pathway, that is responsible for the transport of electrons from the inner membrane quinol:quinone pool, through the periplasmic space, to proteins located on the exterior surface of the outer membrane [41]. Three possible mechanisms of electron transfer from the outer membrane proteins to a proximal electron sink have been identified in S. oneidensis: direct

17 3 electron transfer via outer-membrane proteins, electron shuttling via soluble flavin compounds, and the self-assembly of long appendages named nanowires. The mechanism of direct electron transfer is made possible by the adhesion of the bacterial cell directly to the surface of the electron sink. A direct electron transfer strategy during biofilm formation becomes limited by both the free anode surface area and the density of Mtr proteins on the outer cell membranes which are in direct contact with the surface. The ability for S. oneidensis to transfer electrons via electron shuttles and appendages allows cells on the exterior of the biofilm and within planktonic growth a mechanism by which to transfer electrons to the anode surface. A study by Marsili et al. demonstrated that the role of electron shuttling by soluble flavin compounds may account for as much as 73% of the total electron transfer rate observed in a mature biofilm [28]. A study by Baron et al. further qualified this effect by demonstrating the role of soluble flavins in increasing electron transfer rates through the addition of exogenous soluble flavins to the media containing a metal reducing biofilm [3]. The large influence of soluble flavin compounds on the electron transfer rates makes the de novo synthesis and secretion of electron shuttling flavin compounds an attractive target for metabolic engineering practice. The compounds actively secreted and used as electron shuttles by S. oneidensis were isolated and identified to be predominantly flavin mononucleotide (FMN) and riboflavin [48]. These compounds are ideal electron carriers due to their stability in three different redox states: one electron, two electrons or no electrons. Riboflavin, vitamin B2, is the main precursor to FMN and flavin adenine dinu-

18 4 cleotide (FAD), which are both essential co-factors in cellular energy metabolism. S. oneidensis contains all necessary enzymes for de novo riboflavin synthesis. The precursors for riboflavin synthesis are ribulose 5-phosphate, originating from the pentose phosphate pathway, and guanosine 5-triphosphate (GTP), originating from the purine nucleotide synthesis pathway. Riboflavin is subsequently converted to FMN by riboflavin kinase, which can be subsequently converted to FAD by FMN adenylyltransferase. A diagram summarizing the riboflavin biosynthetic pathway is presented below in Figure 1.1. Figure 1.1: Shewanella oneidensis MR-1 Flavin Synthesis Pathway The identification of riboflavin and FMN secretion as a primary contributor to the electron transfer dynamics of S. oneidensis provides a point of great interest

19 5 in the engineering of MFCs with higher current outputs. As anode surface area becomes limiting, the proliferation of thicker biomass structures and a higher population of planktonic cells will become necessary to obtain higher current densities. Previous studies have demonstrated that MFCs containing external additions of flavins at concentrations of µm are able to produce current outputs at least four times higher than MFCs that contain flavin concentrations of only µm [45]. Although effective, MFC methods using externally added flavins are not ideal due to the higher costs associated with materials and maintenance; the ability of S. oneidensis to produce FMN and riboflavin de novo provides a natural alternative. This study explores the naturally occurring process of flavin synthesis in S. oneidensis and how this metabolic capability may be used for the enhancement of current density in MFCs.

20 6 Chapter 2 Deregulation of Flavin Compound Production in Shewanella oneidensis MR-1 by Media Modification 2.1 Background The identification of riboflavin and flavin mononucleotide (FMN) as the primary compounds synthesized and secreted by Shewanella oneidensis MR-1 provides an ideal target for metabolic engineering activity. Several methods to enhance the production of desirable secondary metabolites in microbial species have been developed and successfully implemented within the field of metabolic engineering. Methods used to alter the expressed phenotype of microbial species include a range of genetic and environmental tools. Genetic techniques involve modifying the DNA of a host organism by introducing a transformation vector containing a new genetic sequence to be spliced into the host genome. The spliced sequence can target specific gene expression levels by using various promoters, altering mrna stability, increasing or decreasing the gene copy number, or modifying ribosome binding strength [16]. Genetic modification strategies that have been successful in the past involve the overexpression of native enzymes, the introduction of non-native enzymes, and the elimination of competitive or toxic pathways [4], [50], [17], [29]. The susceptibility of a host organism to genetic perturbation varies greatly between species and is limited by the physiological and genetic sequence data available.

21 7 Metabolic engineering methods that use environmental factors to manipulate phenyotype, however, can be applied more broadly and without the prior knowledge necessary for genetic modifications. Some of the more common environmental conditions used to modify metabolism in bacteria include nutrient availability, oxygen conditions, incubation temperatures, and media ph. A compilation of metabolic engineering data from previous Escherichia coli work suggests that cultivation method, nutrient supplementation, and oxygen conditions are three of the most significant factors effecting microbial product yield [8]. This study focuses on elucidating the relationship between the availability of nutrients to S. oneidensis during growth and the secretion of electron shuttling compounds. Riboflavin is an important cellular metabolite because it serves as a dedicated precursor for FMN and flavin adenine dinucleotide (FAD), both of which are key prosthetic groups in critical cellular redox reactions. Given the high importance of this pathway in maintaining homeostasis within the cell, and the fact that the primary precursors, ribulose-5 -phosphate and guanosine-5 -triphosphate, are involved in numerous other metabolic pathways, riboflavin synthesis is a critical point for regulation of metabolic flux by the cell. Regulation of riboflavin synthesis in bacteria has been identified to be actuated through the activity of a FMN riboswitch (RFN element) [51]. The RFN element is a sequence of mrna found in the 5 -untranslated region (UTR) of riboflavin synthesis transcripts which undergoes conformational changes in secondary structure when FMN is present and bound. The conformational changes induced during FMN binding causes transcription termination by acting as an anti-antiterminator or by preventing

22 8 translation initiation through the suppression of the ribosome-binding site (Shine- Dalgarno) [46]. A genomic search of Shewanella oniendensis MR-1 identified a conserved RNA element upstream from the genes encoding 3,4-dihydroxy-2-butanone- 4-phosphate synthase (ribb) that is consistent with the mechanism of RFN induced translation attenuation [46]. The binding affinity of FMN, and thus the overall activity of the RFN element, was demonstrated to be dependent on the presence of the divalent cation Mg 2+ which is responsible for coordinating the phosphate oxygen of FMN to the binding pocket [39]. The activity of the riboswitch is dependent on the concentration of not only Mg 2+, but other metal cofactors that may modify the activity of FMN binding. Mn 2+ or Ca 2+, for example, can substitute for Mg 2+ with varying degrees of success, and monovalent cation concentrations such as K + modify the activity of the metal co-factor in bond coordination [39]. This study explores the feasibility of manipulating the nutrient and metal ion availability in the growth media of Shewanella oniendensis MR-1 to deregulate the metabolic production of flavin compounds, thereby promoting the overproduction of electron shuttles available for anaerobic respiration.

23 9 2.2 Methods and Materials Bacterial Strains and Media Conditions Shewanella oniendensis MR-1 (ATC ) was grown aerobically in shake flasks at 30 C and 150 r.p.m. overnight in LB medium. Cells were pelleted by centrifugation at 3000 r.p.m. for 8 minutes, washed twice in 20 mm phosphate buffer solution (ph 7.0), and resuspended in distilled water to serve as the inoculum for media experiments. M1 medium was used as a basis for developing media treatment conditions during the initial screening experiments. The media treatments included the following: 30 mm PIPES (piperazine-n,n -bis(2-ethanesulfonic acid)) buffer, 14 mm - 56 mm NH 4 Cl, mm NaH 2 PO 4 -H 2 O, mm NaCl, mm MgCl 2-6H 2 O, mm KCl, µm CaCl 2, µm Na 2 SeO 4, 0.4 ml vitamin solution, 0.4 ml mineral solution, 112 mm sodium D,L-lactate, and 50 mm sodium fumarate. Many media components unnecessary for growth were omitted in the central composite design (CCD) experiments to remove potentially confounding factors. The resulting media was composed of 30 mm PIPES buffer, 28 mm NH 4 Cl, 4.35 mm NaH 2 PO 4 -H 2 O, 0.25 mm MgSO 4-7H 2 O, 50 mm sodium D,L-lactate, 100 mm sodium fumarate, and experimental treatments of mm MgCl 2-6H2O, mm KCl, and mm CaCl 2, defined for each sample. The media used to isolate the role of Mg 2+ included 30 mm PIPES buffer, 28 mm NH 4 Cl, 4.35 mm NaH 2 PO 4 -H 2 O, 0.25 mm MgSO 4-7H 2 O, 1.34 mm KCl,

24 mm CaCl 2, 50 mm sodium D,L-lactate, 100 mm sodium fumarate, and experimental treatments of either 0 or 5.75 mm MgCl 2-6H2O. The contents of the vitamin solution per liter was 10 mg pyridoxine hydrochloride, 5 mg thiamine-hcl, 5 mg riboflavin, 5 mg nicotinic acid, 5 mg calcium D- (+)-pantothenate, 5 mg p-aminobenzoic acid, 5 mg thioctic acid, 2 mg biotin, 2 mg folic acid, and 0.1 mg vitamin B12. The contents of the mineral solution per liter were 3 g MgSO 4-7H 2 O, 0.5 g MnSO 4 -H 2 O, 1 g NaCl, 0.1 g FeSO 4-7H 2 O, 0.1 g CoCl 2-6H 2 O, 0.1 g CaCl 2, 0.1 g ZnSO 4-7H 2 O, 0.01 g CuSO 4-5H 2 O, 0.01 g AlK(SO) 4-12H 2 O, 0.01 g H 3 BO 3, 0.01 g Na 2 MoO 4-2H 2 O. Prepared media, except the inoculum and sodium fumarate, was placed in an anaerobic tube, plugged with a butyl rubber stopper and sealed shut with a crimped aluminum seal. The head space within the sealed anaerobic tube was purged with oxygen-free nitrogen gas to create an anoxic environment. The glass tubes were autoclaved for 20 minutes. Filter sterilized sodium fumarate and sample inoculum were added to the sterile anaerobic tubes for a final test volume of 25 ml during the screening experiments and 20 ml during the CCD and Mg 2+ experiments. The optical density of suspended cells was measured using a wavelength of 600 nm. The optical density measurements were converted to units of grams ashfree dry cell weight per liter (gafdw L 1) by multiplying the optical density measurements by a scalar of 0.69 [35].

25 Statistical Experiment Design and Analysis A two-level, one-eighth factorial screening experiment was designed to evaluate the influence of the seven major components of M1 minimal media on the production and secretion of riboflavin and FMN by S. oneidensis. The components NH 4 Cl, NaH 2 PO 4, NaCl, MgCl 2, KCl, CaCl 2, and Na 2 SeO 4 were evaluated at a high and low concentration. The resulting experimental design consisted of 16 unique treatments to provide a resolution of IV in the response data (all main effects and some interactions). R version (The R Foundation for Statistical Computing) was used in the analysis of the screening experiment. A central composite design (CCD) with uniform precision was used to evaluate the influence of Mg 2+, Ca 2+, and K + on the synthesis and secretion of flavins. Each of the three treatment factors (Mg 2+, Ca 2+, and K + ) were evaluated at concentrations corresponding to 5 coded levels: -1.68, -1, 0, 1, and This fully rotatable design included 20 total runs: 6 extreme points, 8 factorial points, and 6 center points [32]. The level of each factor in each treatment is defined in Table 2.4. The optical density of each sample was measured at 0 hours immediately after inoculation and at 72 hours when samples were pulled for metabolite analysis. The measured concentration of riboflavin and FMN, normalized to cell concentration, was used as the response variable. The data were fit to a linear regression model comprised of the main effect, second order contributions, and pairwise interactions from each factor. SAS version 9.2 (SAS Institute Inc.) was used in constructing the experimental design and R version (The R Foundation for Statistical

26 12 Computing) was used in the subsequent analysis. A two-level, one factor design was used to analyze the specific influence of Mg 2+ on the production of flavins. Seven replicates were run for each of the treatments, and R version (The R Foundation for Statistical Computing) was used in the analysis of the resulting data Metabolite Analysis Samples taken at 72 hours from the anaerobic tubes were centrifuged at 5000 r.p.m. for 5 minutes to pellet the cells. The supernatant was filtered using 0.22 µm sterile syringe filters and analyzed on an Agilent 1200 series HPLC equipped with a 4.6 mm x 250 mm Alltima C18-5µm column. The column was operated at 30 C with a mobile phase consisting of 30% methanol and 1% glacial acetic acid in water. Sample injection volumes were 25 µl. An inline fluorescence detector using an excitation wavelength of 440 nm and emission wavelength of 525 nm was used to identify riboflavin and FMN. The concentration of each compound was quantified by comparing peak areas to prepared standards ranging in concentrations from 5 µm to 0.05 µm.

27 Experimental Results Validation of HPLC Procedures Several HPLC parameters, including column specifications and mobile phase composition, were evaluated to identify the optimal method for the identification of flavin compounds. FMN has been identified as the dominate supernatant flavin compound in Shewanella oneidensis MR-1 cultures and was thus used as a reference peak to evaluate chromatograph resolution. The cleanest signal of the four test conditions was obtained with the use of the 4.6 mm x 250 mm Alltima C18-5µm column with 30% methanol and 1% glacial acetic acid in water. This chromatogram offered a clearly identifiable, dominate peak with a minimal amount of tailing and peak splitting. The other three methods exhibited a higher degree of either peak tailing or peak fractionation that made the identification of a single reference peak difficult and imprecise. Representative chromatograms used in the comparison of these methods are displayed in Figure 2.1. Freshly prepared FMN and riboflavin standards were used to develop calibration curves for the identification of compound retention time and to directly correlate the peak area to compound concentration. The retention time for riboflavin was found to be ± 0.06 minutes. A linear fit of riboflavin concentration data to peak area resulted in the relationship: µm ribof lavin = 0.004(peakarea) 0.011,

28 14 with a coefficient of determination, R 2, greater than The range of riboflavin concentrations used in the development of the calibration curve was from 0.05 to 5 µm thus providing good coverage of the sample response. Similarly, the retention time for FMN was found to be 8.52 ± 0.04 minutes, and a linear fit of FMN concentration data to peak area resulted in the relationship: µm F MN = (peakarea) , with a coefficient of determination greater than 0.99 for concentrations ranging from 0.05 to 5 µm. The sensitivity of the analytical method to light and to the lag time between sample preparation and analysis was also evaluated. Two sets of standards were prepared in the lab: one set under normal light conditions and the second set using precautions to prevent the irradiance of the standards (dark room, foil wrapped glassware). These standards were measured on the HPLC and compared. The effect of light had very little effect on FMN but reduced the peak intensity of riboflavin by 53%. The samples prepared under normal lab conditions were stored at 4 o C in the refrigerator for 12 days and then measured again. FMN concentration was reduced by 33% during the 12 day span and riboflavin was reduced by an additional 80% (Figure 2.2). Review of the riboflavin and FMN chromatograms (Figures 2.3 and 2.4, respectively) indicates that the degradation of both compounds are associated with a concomitant increase in the area of peaks with retention times of 11.2, 17.4, and 23.5 minuites.

29 M1 Media Main Effects A one-eight factorial design was used to evaluate the main effect of each media component on the synthesis and secretion of flavin compounds. The details of the experimental treatments along with the corresponding responses of biomass, riboflavin, and FMN are listed in Table 2.1. The riboflavin and FMN peaks in Table 2.1 were normalized by the associated biomass concentration for each sample. These normalized values were used as the responses to fit two linear regression models, one for each compound. The models included only first order categorical terms for each of the seven main factors in the experiment. Levene s Test was used to test the equality of variances among the groups [20]. The results of Levene s test gave no suggestion of unequal variances between the groups. With the equal variances assumption met, analysis of variance (ANOVA) was used to evaluate the significance of each factor s effect to explain the observed variation. The resulting F-statistics and P-values for each factor in the riboflavin and FMN model have been summarized in Table 2.2 and Table 2.3, respectively. None of the factors in either model provided sufficient evidence of influencing flavin compound production.

30 Figure 2.1: 5 µm FMN Standard Chromatograms for A) 4.6 mm x 250 mm C18-5µm, 30% MeOH/5 mm ammonium acetate; B) 4.6 mm x 250 mm C18-5µm, 30% MeOH/1% glacial acetic acid; C) 4.6 mm x 150 mm C18-5µm, 20% MeOH/1% glacial acetic acid; D) 4.6 mm x 150 mm C18-5µm, 30% MeOH/1% glacial acetic acid 16

31 Figure 2.2: HPLC standard degradation during 12 days at 4 o C for a) riboflavin, and b) FMN 17

32 18 Figure 2.3: Effect of storage on riboflavin chromatogram a) 0 days and b) 12 days at 4 o C Figure 2.4: Effect of storage on FMN chromatogram a) 0 days and b) 12 days at 4 o C

33 PO 3 4 SeO 2 4 Na + Biomass Riboflavin FMN Treatment Mg 2+ Ca 2+ K + NH + Number (mm) (µm) (mm) 4 (mm) (mm) (µm) (mm) (gafdw L 1 ) (Peak Area) (Peak Area) Table 2.1: One-Eighth Factorial Design Setup and Results 19

34 20 Factor Degrees of Freedom F-Statistic P-Value Mg Ca K NH PO SeO Na Residual 8 Table 2.2: Categorical ANOVA Summary for M1 Media Component Influence on Riboflavin Concentration Factor Degrees of Freedom F-Statistic P-Value Mg Ca K NH PO SeO Na Residual 8 Table 2.3: Categorical ANOVA Summary for M1 Media Component Influence on FMN Concentration Metal Ion Response Surface A central composite experimental design was used to evaluate the role of Mg 2+, Ca 2+, and K + in regulating S. oneidensis electron shuttle production. The design

35 21 was used to allow each factor to be tested at five levels and thus give greater insight to the second order effects of each factor. The metabolic sensitivity of the organism to each of these metal ions was enhanced by omitting trace vitamins and minerals from the test media. The concentration of each factor, along with the resulting biomass, riboflavin, and FMN response for each of the twenty runs is summarized in Table 2.4. The response of each flavin was normalized by its biomass growth to give a per gafdw basis. These responses were independently fit with a linear model containing terms for each main effect and all possible combinations of second order interactions. Again, Levene s Test was used to test the equality of variances among the groups [20]. The results of Levene s test gave no suggestion of unequal variances between the groups, and thus the equality of variances was assumed. The riboflavin response data linear fit provided a R 2 value of ANOVA testing on the riboflavin model revealed that all factors in the model except K K had p-values well above the 0.05 significance cut-off (Table 2.5). The p-value of for the term K K indicates a significant second-order effect of K + concentration on the production of riboflavin. The effect of each factor can be illustrated using a box plot. The rectangle of the box plot represents the interquartile range where the bottom end is the first quartile and the top is the third quartile. A bold line within the box represents the group mean. The max and min of the data set are illustrated by a line extending from the edge of the box to the extreme point. In the case of outliers, this line is omitted and only a point is drawn for the value. Qualitative review of riboflavin production vs. K + concentration reveals that the

36 22 second-order curvature is primarily the result of an extremely low mean for the center runs (Figure 2.5). Riboflavin concentrations at other K + treatment levels seem to be very uniform and thus it is not clear where the observed curvature begins within the range from 1.42 and 4.83 mm K +.

37 23 Treatment Treatment Factor Concentrations Biomass Riboflavin FMN Number Mg 2+ (mm) Ca 2+ (µm) K + (mm) (gafdw L 1 ) (Peak Area) (Peak Area) Table 2.4: Central Composite Design Setup and Results

38 24 Factor Parameter Estimate P-value Mg Ca K Mg Mg Mg Ca Mg K Ca Ca Ca K K K Table 2.5: Riboflavin Coded Parameter Estimate and ANOVA Statistics for Central Composite Design The model fit for the normalized FMN data provided a R 2 of 0.81, much higher than that of riboflavin. ANOVA testing of the FMN model revealed several significant terms in the model (Table 2.6). Mg 2+ was identified to be the most influential term in the model, returning a p-value of for its linear contribution and for its second order contribution. A qualitative review of FMN response vs. Mg 2+ concentration indicates that there is a decrease in FMN production as Mg 2+ concentration is increased (Figure 2.6). This linear relationship observed between FMN production and Mg 2+ concentration was the most dramatic relationship observed in this set of experiments. A second-order interaction of Ca 2+ was also identified as significant by a calculated p-value of The boxplot of FMN production vs. Ca 2+ concentration illustrates that this second-order relationship is characterized by a low FMN production at the center run and higher production at the lower and upper runs. (Figure 2.7). Finally, the interaction term between

39 25 Figure 2.5: Central Composite Design: Boxplot of Riboflavin response vs. K + Concentration Ca 2+ and Mg 2+ is returned as a significant term with a p-value of This relationship is illustrated in Figure 2.8 with a surface plot of the FMN response as a function of the two ion concentrations. At low concentrations of Mg 2+, increasing concentrations of Ca 2+ increase the production of FMN. However, at high concentrations of Mg 2+, the interaction with Ca 2+ has the opposite effect and increased Ca 2+ lowers the FMN production.

40 26 Factor Parameter Estimate P-value Mg Ca K Mg Mg Mg Ca Mg K Ca Ca Ca K K K Table 2.6: FMN Coded Parameter Estimate and ANOVA Statistics for Central Composite Design Role of Mg 2+ The results from the central composite design indicate Mg 2+ significantly influences the production of FMN by S. oneidensis. However, the limited number of experimental runs occurring on the perimeter of the experimental space prevents the results from being reported with high confidence. An additional experimental design was constructed to validate the influence of Mg 2+ on FMN concentration by constructing a single factor, two level test. Equation 2.1, below, uses the concept of statistical power to develop the relationship between mean difference, experimental variation, and minimum number of replicates required per group [19]. n = 2σ 2 ( z β + z α/2 ) 2 (2.1) δ Equation 2.1 can be parameterized using the results obtained in previous experiments. A conservative estimate for the difference in mean FMN concentration

41 27 Figure 2.6: Central Composite Design: Boxplot of FMN response vs. Mg 2+ Concentration at the lowest (0.25 mm) and highest (6 mm) Mg 2+ concentration, δ, is 1.2 µm FMN gafdw 1. The standard deviation, σ 2, can be estimated as 0.5 using the six center runs from the previous experiment. A value of 0.05 was used for α to represent 95% confidence, and the value of 0.9 was used for β to represent 90% statistical power (the probability of not making a type II error). Using this parameterization and the associated z-statistics, it was determined that five replicates per treatment would be sufficient to prove the observed treatment effect with 95% confidence. Seven replicates per treatment were used to ensure sufficient resolution

42 28 Figure 2.7: Central Composite Design: Boxplot of FMN response vs. Ca 2+ Concentration was available. Mg 2+ was determined to have a significant effect on both riboflavin and FMN concentration. The 5.75 mm difference in Mg 2+ concentration produced a 0.40 µm gafdw 1 difference in riboflavin concentration and a 0.95 µm gafdw 1 difference in FMN concentration (Table 2.7). However, these differences in flavin concentrations were in opposite directions for the two compounds. An ANOVA test confirmed that these two differences were significant with a p-value of for riboflavin and a p-value of for FMN. The net increase in flavin com-

43 29 Figure 2.8: Central Composite Design: Surface of FMN response vs. Mg 2+ and Ca 2+ Interaction pound production for the 0.25 mm Mg 2+ treatment as compared to 6.00 mm Mg 2+ treatment was 0.55 µm gafdw 1. A 95% confidence interval for the difference between treatment means can be calculated according to Equation 2.2 [18]. c ± t α 2,N t MSE 2 i=1 1 r i (2.2) In Equation 2.2, c represents the difference between treatment means, t is the value from the t-distribution with N - t degrees of freedom (N is the population size and t is the number of treatment groups) at 1 α confidence, MSE is the mean squared error from the seperate-means model, and r is the number of replicates in

44 Mg 2+ Concentration Mean Riboflavin Concentration FMN Concentration (mm) µm gafdw 1 µm gafdw Table 2.7: Mean Flavin Concentration from Mg 2+ Treatments 30 each group. The calculation results in the 95% confidence interval of (0.099,1.000) for the difference in total flavin concentration between groups. Figures illustrate these effects. Figure 2.9: Boxplot of Riboflavin Response vs. Mg 2+ Treatment Level

45 31 Figure 2.10: Boxplot of FMN Response vs. Mg 2+ Treatment Level 2.4 Discussion Analytical Methodology The relative peak elution times observed for riboflavin and FMN is consistent with those made by Covington et al. who observed a retention time of 9 minutes for FMN and 15 minutes for riboflavin using a 4.6 mm x 150 mm Eclipse XBD-C18 column operating at 30 o C column temperature, 1 ml min 1 flow rate, and mobile phase of 30% methanol and 1% glacial acetic acid in water [9]. Additionally, the magnitude of flavin compounds observed in this study closely match those

46 32 Figure 2.11: Boxplot of Total Flavin Response vs. Mg 2+ Treatment Level obtained by others. For example, the 0.41 µm L 1 average FMN concentration and 0.06 µm L 1 average riboflavin concentration that was observed during the Mg 2+ treatment experiments is similar to 0.55 µm L 1 average FMN concentration and 0.03 µm L 1 average riboflavin concentration obtained by von Canstein et al. under similar growth conditions [48]. This small difference in magnitude could be the result of differences in media composition, growth condition, or analytical technique. An ideal method development would include the use of more definitive compound identification methods such as liquid chromatography followed by mass spectrometry (LC-MS). This confirmation could be run by collecting aliquots of the

47 33 HPLC mobile phase aligned with the timing of the peaks of interest and analyzing the unique mass spectra through mass spectrometry technique. However, even with the lack of LC-MS data, the consistancy between the results obtained in this study and those cited in the literature provides adequate validity for the conclusions drawn herein. The rapid degradation of the flavin compounds creates difficulty in the quantification process. Riboflavin degradation has been studied previously and can be attributed to its sensitivity to light. A study conducted by Ahmad et al. found significant photodegradation of riboflavin into the compounds cyclodehydroriboflavin (CDRF), formylmethylflavin (FMF), lumichrome (LC), and lumiflavin (LF), with CDRF and LC dominating [2]. These compounds are likely responsible for the observed peaks at 11.1, 16.0, 17.4, and 23.2 minutes in Figure 2.3, however, a technique such as LC-MS or comparison to chemical standards would be needed for confirmation. Similarly, the products of FMN photodegradation have been identified as lumichrome and the lumiflavin derivatives dihydroxymethyllumiflavin, formyllumiflavin, and lumiflavin-hydroxy-acetaldehyde [13]. Review of Figure 2.4 also implicates riboflavin as a possible degradation product of FMN, perhaps through the dissociation of the phosphate group. The relative stability of FMN over riboflavin may explain its observed dominance as a secretion compound used by S. oneidensis for electron mediation. The ability of the riboflavin degradation products to also mediate electron transfer for anaerobic respiration has not previously been studied. The rapid degradation of flavin compounds is a source of potential error in

48 34 the analysis. Degradation of either the collected samples or the chemical standards could introduce errors in the quantification procedures. The phenomenon was only observed after the analysis of the samples for both the initial screening experiment and the metal ion study utilizing the CCD design, therefore, no actions were taken to prevent sample exposure to light. As a result, both of these experiments can be assumed to have some degree of photodegradation. In both cases, the photodegradation manifested itself as a result of either sample exposure to light or delay time between sample preparation and analysis. Although studies have previously identified the kinetics of photodegratation, it is impossible to recount the intensity and precise duration of light exposure a posteriori, and thus, any attempt to extrapolate flavin concentrations based on delay time is unreliable. However, even as the absolute flavin concentrations in these two experimental runs can not be reported with confidence, it is possible to analyze each experimental dataset through a comparative analysis within its own sample set because each experimental run was exposed to identical conditions. Using this method, the relative effects of each factor were identified using peak area, not absolute metabolite concentration, as a primary indicator. During the final experimental run to isolate the effects of Mg 2+, the samples were analyzed on the HPLC immediately upon sample preparation and with freshly prepared standards. These results, therefore, have been reported as absolute concentrations with a high degree of confidence. Although several studies have used a similar approach to quantify the concentrations of flavins, all studies fail to mention controls on the amount of light that the compound is exposed to or lag-time between sample preparation and

49 35 sample analysis. For example, once the phenomenon of photodegradation had been observed in these sets of experiments, further experiments were controlled to eliminate any time lapse between sample preparation and analysis. Additionally, standards were freshly prepared each time an analysis was preformed. In the event that a time lapse is necessary, efforts should be made to keep samples in the dark. Further characterization of flavin compound photodegradation under temperature conditions of -4 o C, a temperature commonly used to preserve metabolite samples, should also be considered to properly control against this source of experimental noise Mg 2+ Influence on Flavin Production The results of these experiments demonstrate a strong relationship between the concentration of Mg 2+ and the rate of in vivo flavin compound synthesis and secretion. The 5.75 mm difference in Mg 2+ concentration induced a 0.55 mm change in the concentration of flavin compounds secreted per gram dry weight. The majority of this change was the result of a change in the concentration of FMN, which has been previously identified as the dominate electron shuttle secreted by S. oneidensis [28], [48]. Riboflavin had only a small change in overall concentration due to its relatively small abundance in the supernatant. Interestingly, the influence of Mg 2+ was in opposite directions for FMN and riboflavin. The consensus RFN element sequence, which has been implicated in the control of riboflavin synthesis, was identified upstream from the 3,4-dihydroxy-2-butanone-4-phosphate

50 36 synthase (ribb) coding genes [46]. Because riboflavin and FMN are in series after this control point, modification of 3,4-dihydroxy-2-butanone-4-phosphate synthase activity should effect both metabolites in the same direction. The unexpected concentration change suggests alternative roles for Mg 2+ in influencing the synthesis, transportation, or utilization of flavin compounds. Mg 2+ is well known to control the activity of isocitrate dehydrogenase, for example, which irreversibly converts isocitrate to α-ketoglutarate [47]. The global regulatory role of Mg 2+ makes it an attractive tool for the manipulation of metabolic activity, however, also makes it difficult to predict the precise response mechanism. The influence of Mg 2+ concentration on flavin compound secretion was found to be highly sensitive to the presence of other compounds in the media. Trace minerals, trace vitamins, NaCl, and SeO 4 were all identified as non-essential compounds in the minimal media for microbial vitality and were removed for all experiments after the initial screening. The removal of these components resulted in a heightened sensitivity by the organism to changes in the remaining media component concentrations. This was particularly evident by the lack of Mg 2+ influence on flavin compound secretion by S. oneidensis during the screening experiment. Previous in vitro studies of the RFN element have identified Mg 2+ to be the metal ion responsible for coordinating the FMN bond, however, have also demonstrated this role can be partially substituted by structurally similar ions such as Mn 2+, Co 2+, or Ca 2+ [39]. These compounds are all contained in the trace mineral solution at adequate concentrations to modify the activity of the RFN element. Further characterization of flavin compound synthesis and secretion would be required to

51 37 identify which compounds in the trace solutions are resposible for modifying the role of Mg 2+ and to what extent they do so. Although the use of Mg 2+ to influence the rate of flavin compound secretion has been demonstrated, more study is required to identify the mechanisms of its influence. Future study should focus on not only the secreted amounts of flavin compounds, but also on the amounts contained within the cell. This information would help decouple the roles of Mg 2+ in the synthesis of flavin compounds and their subsequent transportation outside the cell. Furthermore, the influence of phosphate, nitrogen, and sulfur concentrations on flavin compound synthesis should be reevaluated without the confounding influence of the trace minerals and vitamins which occurred in the screening experiment. The availability of these element could have strong influences on the rate of ribulose 5-phosphate and guanosine 5-triphosphate production, the precursors to the flavin compound synthesis pathway. 2.5 Conclusions This study successfully demonstrated a role for Mg 2+ in the control of the flavin compound synthesis in Shewanella oneidensis MR-1. In the absence of confounding trace minerals and vitamins, decreased amounts of Mg 2+ resulted in increased FMN secretion and decreased riboflavin secretion, while high concentrations of Mg 2+ resulted in the opposite. The differing directional change of riboflavin and FMN concentrations suggests a more global role for Mg 2+ in the regulation of S.

52 38 oneidensis metabolism. Further elucidation of Mg 2+ regulatory mechanisms and its robustness to the presence of other metals should be addressed in future studies.

53 39 Chapter 3 Modified Mg 2+ Concentration influence on Shewanella oneidensis MR-1 Current Generation in a Microbial Fuel Cell 3.1 Background Microbial fuel cells (MFCs), which are used to convert biological substrates to electrical energy, are being researched as an alternative energy source. However, the application of MFCs as a viable technology for energy generation will require its application at scales much larger than those currently being studied in the laboratory. One challenge faced with the scale-up of MFC technology is that the internal resistance, the resistance inherent in the system components, increases dramatically with the size of the equipment, which leads to reduced power output [26]. The trade-off between internal resistance and MFC size is particularly evident in anode design. Increasing anode surface area creates a larger catalytic surface area available to microbes for electron transfer, however, also increases the internal resistance in the circuit. Several techniques have been applied to increase the available anode surface area including the use of a graphite brush design and decorating the surface of the anode with gold or palladium nanoparticles [24], [10]. These techniques were successful at the bench-scale, but have potential technological and cost issues associated with scale-up. Another approach to overcome the lack of surface area available to the microbial community is to instead in-

54 40 crease their ability to remotely access the anode surface through the use of soluble electron mediators. Many compounds have been evaluated in MFCs for their ability to mediate electron transfer between the microbial community and anode surface. Studies on glucose metabolism in MFCs, for example, have confirmed the ability of the compounds neutral red, thionine, and methyl viologen to mediate electron transfer between an anode and microbial organism [34], [44], [36], [38]. Although these compounds are capable of electron mediation, the exogenous addition of compounds to an MFCs is not ideal in scale-up scenarios due to the costs and difficulties associated with the manufacturing and handling of the compounds. Shewanella oneidensis MR-1 has a unique ability for de novo electron mediator synthesis and secretion. The compounds used by S. oneidensis for electron mediation have been identified as riboflavin and flavin mononucleotide (FMN) [28]. The contribution of these two compounds to the total current generated in an MFC using S. oneidensis has been observed to be as high as 73% [28]. This large percentage makes the metabolic production of electron shuttling compounds an important characteristic of biofilm community dynamics and MFC design in general. This study evaluates the effect on current generation by a pure culture of Shewanella oneidensis MR-1 in a single-chamber MFC when the metabolic rates of electron shuttle compounds are modified through environmental perturbation.

55 Method and Materials Bacterial Strains and Media Conditions Shewanella oniendensis MR-1 (ATC ) was grown aerobically in shake flasks at 30 C and 150 r.p.m. overnight in LB medium. Cells were pelleted by centrifugation at 3000 r.p.m. for 8 minutes, washed twice in 20 mm phosphate buffer solution (ph 7.0), and resuspended in test media to serve as the inoculum for the MFC. Test media contained 30 mm PIPES buffer, 28 mm NH 4 Cl, 4.35 mm NaH 2 PO 4 - H 2 O, 0.25 mm MgSO 4-7H 2 O, 100 mm sodium D,L-lactate, 1.34 mm KCl, 6.8 µm CaCl 2 and either 0 (low treatment) or 6 (high treatment) mm MgCl 2-6H 2 O MFC Specifications The MFCs used for all experiments were of the single-chamber, air-cathode design [22]. The anode and cathode were placed in a plastic cylindrical chamber with a length of 3 cm and a diameter of 3 cm for a working volume of 21 ml. The anode and cathode were each 7 cm 2 in area and spaced 3 cm apart on opposite sides of the chamber. The cathodes were composed of CC6P carbon cloth (Fuel Cell Earth, Stoneham, MA). Three layers of 30% polythetrafluoroethylene (PTFE) (Sigma- Aldrich, St. Louis, MO) were applied to the air exposed side of the cathode, and a 20% platinum/carbon powder mix (BASF Somerset, NJ, USA) was combined with Nafion binder (Sigma-Aldrich) for a platinum concentration of 1 mg cm 1 and applied to the chamber exposed side of the cathode as in previous designs [21], [7],

56 42 [6]. The anodes were composed of CC6P carbon cloth (Fuel Cell Earth, Stoneham, MA). Experiments designed to preclude bacterial contact with the anode used a 7 cm 2 disc of Spectra/Por 1 Dialysis Membrane with a molecular weight cut-off of daltons (Spectrum Laboratories, Rancho Dominguez, CA) to seperate the anode from the reactor main chamber [45]. A load resistance of 27800Ω, 8250Ω, 1100Ω, or 677Ω was applied to the circuit connecting the two electrodes MFC Operation All MFC components were sterilized in an autoclave prior to experimentation. Dialysis membranes were soaked in distilled water, rinsed, and then sterilized in an autoclave while submerged in water to sterilize. Each MFC was constructed and inoculated with a cell suspension. The MFC was partially enclosed in a plastic bag to minimize contamination sources and placed in a constant temperature room set to 30 C. The cell voltage was measured approximately every 5.5 minutes using a Keithley 2700 Multimeter / Data Acquisition System (Keithley Instruments, Cleveland, OH). When voltage was observed to drop, the cells were recharged with substrate by replacing 10 ml of the reactor volume with fresh media. Recorded voltages were converted to current according to Ohm s law, I = V R (3.1) where I is current in amperes, V is the potential difference in volts and R is the resistance in ohms.

57 Dialysis Membrane Characterization A test reactor was constructed in the shape of a box with two circular openings on opposite lateral sides. Circular discs of dialysis membrane were fit into the openings of the reactor, sealed with o-rings, and clamped shut. The reactor was filled with DI water and submerged into a 500 ml stirred water bath containing concentrations of riboflavin and FMN at 5 µm each. Aliquots were pulled from inside the reactor through a sampling port at elapsed times of 0, 5, 15, 30 and 60 minutes. These samples were analyzed for flavin compounds on the HPLC according the procedures described previously. A similar method was used to verify that the membrane would prevent diffusion of S. oneidensis cells by submerging the reactor into a stirred water bath containing a cell suspension and monitoring the optical density of the reactor interior. 3.3 Results Mediatorless MFC Operation Six MFCs with a load resistance of 27800Ω were inoculated with Shewanella oniendensis MR-1 cells: three with media containing 0.25 mm Mg 2+ (104, 108, 205) and three containing 6 mm Mg 2+ (103, 107, 220). The operation of cells 103, 104, and 205 was terminated after two days due to chronic leaking and restarted. As a result, these two groups use slightly offset scheduling for load resistance changes. Table 3.1 contains detailed operational conditions for each cell.

58 44 MFC Mg 2+ Initial Biomass Load Resistance Changed(day) (Cell) (mm) (gafdw L 1 ) Ω 8250 Ω 1100 Ω Table 3.1: Summary of MFC Operating Parameters The MFCs containing media with low concentrations of Mg 2+ significantly outperformed those with high concentrations of Mg 2+. This relationship was consistent across the duration of the experiment and at each magnitude of load resistance applied to the circuit (Figure 3.1 and Figure 3.2). This difference in performance, however, is much less pronounced early in the experiment under a load resistance of 27800Ω. Cell 220, for example, actually outperforms its low Mg 2+ counterpart during the first day of operation. This initial phase of the timeline is characterized as a period of biofilm attachment and growth, and thus, can be assumed to be highly variable. After the first day, however, cell 104 overtakes cell 220 in current generation and maintains that relationship for the duration of the experiment. The performance difference between treatments becomes more pronounced as the experiment progresses and the resistances are lowered. There are several excursions in the trend that can be explained by lab errors. The low initial performance of cell 205 on day 10 is the result of a loose connection in the circuit after the resistance was changed. Once this problem was addressed, the cell resumed its superior performance. The root cause of the noisy signal in

59 45 cell 220 beginning on day 7 is unknown, however. This could also be the result of a loose electrical connection in the system setup. Figure 3.1: MFC Current Generation in Cells 205, 108, 107. Low Mg 2+ Treatment (dashed) and High Mg 2+ Treatment (solid) The maximum MFC current output achieved at each magnitude of load resistance was recorded. These values were used to calculate means and standard deviations for each media treatment (Figure 3.3). As observed in the time-based plots of current generation, the lower Mg 2+ treatment consistently outperformed the higher Mg 2+ in maximum current output achieved. At the highest load resistance setting of 27800Ω, the media treatment with low Mg 2+ resulted in a 52% higher maximum current output than the high concentration treatment. This gap widened as the biofilm matured and the applied resistance was reduced with 74%

60 46 Figure 3.2: MFC Current Generation in Cells 104, 103, 220. Low Mg 2+ Treatment (dashed) and High Mg 2+ Treatment (solid) higher maximum current at the 8250Ω setting and 151% higher maximum current at the 1100Ω setting. The average maximum current for low Mg 2+ concentration at the 1100Ω setting was 260 ± 72 µa. In addition to the applied load resistances discussed above, the load resistances on cells 205, 107, and 108 were reduced from 1100 Ω to 677Ω after day 14. This drop in resistance was accompanied by a reduction in current generation by each of the cells. A resistance of 1100Ω was therefore assumed to be an optimal value for maximum current generation and was used as a lower limit for further experimentation.

61 47 Figure 3.3: Maximum Current Generation in MFCs at Each Resistance Preclusion of Direct Anode Contact Dialysis membrane was added to the MFC to preclude direct contact between the bacteria and the anode surface. Functionality of the dialysis membrane was confirmed by tests run to quantify the diffusion of flavin compounds across the membrane and to ensure the passage of S. oneidensis cells was prevented. Both riboflavin and FMN were observed to pass through the membrane (Figure 3.4). Riboflavin and FMN that diffused through the membrane were first detected in the sample taken at 15 minutes. The diffusion of these compounds continued over the duration of the experiment with riboflavin moving more quickly through the membrane than FMN. The higher transfer rate of riboflavin is presumably due to its smaller molecular weight relative to FMN ( g mol 1 vs g mol 1 ). In a similar experiment, a suspension of S. oneidensis cells was added to the bulk solution at a concentration of gafdw L 1. The internal concentration was monitored for 24 hours with no observed diffusion of biomass through the

62 48 membrane. The performance of the dialysis membrane was deemed sufficient for application to the MFC. Figure 3.4: Characterization Flavin Compound Diffusion through Dialysis Membrane Sterile MFCs containing dialysis membranes to separate the main reactor chambers, which house the growing biomass, from the surface of the anode were constructed. S. oneidensis cells harvested at late-log phase were resuspended at concentrations of gafdw L 1 in the low Mg 2+ treatment and gafdw L 1 in the high Mg 2+ treatment. The cells were inoculated, set to an load resistance of 1100Ω, and the current output was monitored through time. The difference in performance between the two treatments was evident within the first two days of the experiment (Figure 3.5). The current output from cells containing the media treatment with a low concentration of Mg 2+ was observed to ramp up faster and to higher magnitudes than that with high concentrations of Mg 2+. MFCs containing low treatments of Mg 2+ averaged maximum current outputs of 53.5 ± 5.8 µa while

63 49 those containing the high treatment averaged a maximum current output of only 12.6 ± 9.1 µa. Figure 3.5: MFC Start-up Performance with Membrane Precluding Anode Contact The MFCs were allowed to run continuously until the current output ceased for all cells (Figure 3.6). The current output sustained by cells containing the low concentration of Mg 2+ changed very little after the initial two day period with only slight increases observed in cells 205 and 108. Current output in cells with the low Mg 2+ treatment began falling during day 4. Cells with high Mg 2+ concentrations tended to achieve peak current outputs much later in the experiment. Cells 103 and 220, for example, reached peak currents during days 5 and 6, respectively. Cell 220, specifically, had a very large current increase beginning on day 4 that significantly outperformed the other cells in its group. The large deviation of cell 220 is suspected to be the result of membrane failure, which if occurred, would have led to direct contact between bacterial cells and the anode surface.

64 50 Figure 3.6: MFC Lifetime Performance with Membrane Precluding Anode Contact The moving average of current output was plotted to generalize the performance trends of each treatment mean (Figure 3.7). This plot illustrates the faster current ramp and maximum current generation of the low Mg 2+ treatment, while the higher Mg 2+ treatment is characterized by a slower ramp period but longer sustained current generation. 3.4 Discussion MFC The findings in this study confirm that manipulation of Mg 2+ concentration has a significant effect on current production in an MFC. The increased current production observed under low Mg 2+ treatments is consistent with findings that these media conditions promote a shift in S. oneidensis metabolism towards the syn-

65 51 Figure 3.7: Moving Average of Current Output in MFC by Mg 2+ Treatment thesis of higher concentrations of electron mediating compounds as compared to growth media containing higher levels of Mg 2+. However, because the concentrations of electron mediators were not directly measured in the MFC experiments, the direct role of MgCl 2 in current generation must be considered. Salt concentrations have previously been identified as a critical operating parameter in MFCs. A study by Gil et al. demonstrated that an increase in the NaCl salt concentration increased the current generated by the MFC [11]. The current generated in this study, however, was reduced with increasing MgCl 2 concentration which supports the hypothesis that the influence of Mg 2+ is exerted on S. oneidensis metabolism and not directly on the electron transfer kinetics of the system. Furthermore, with the stability conferred by buffering agents added to the media treatments, differences in proton transfer dynamics between the anode and cathode for the two treatments can be assumed negligible. These findings, therefore, provide sufficient evidence that manipulating the metabolic rates of electron mediator production

66 52 in microbial communities is a viable method of controlling current generation in MFCs. Media treatments with low Mg 2+ concentration successfully increased the current generation in cells both with and without a dialysis membrane installed to preclude microbial contact with the anode. The low Mg 2+ treatment produced an average of 151% more current at 1100 Ω external resistance than the high Mg 2+ concentration with the membrane absent and produced 124% more current over the high Mg 2+ concentration treatment with the membrane installed. The greater influence of media treatment on MFCs containing no membrane may indicate that a significant portion of the increased electron transfer is originating from the biofilm and not only planktonic growth. An increased concentration of flavins available to a growing biofilm should provide greater availability of oxidized electron shuttles and allow biofilms to grow to greater thicknesses. Thicker biofilms are desirable because of the increased current density provided to the anode and because this biomass is retained during batch changes to the MFC. Future studies should seek to quantify the changes, if any, to the developed anode biofilm. The central role of flavin compounds in MFC current generation must be considered for scale-up efforts. For example, the performance of a batch reactor could be significantly different from a continuous reactor due to the accumulation of flavins in the system. Converting to a continuous reactor process would dilute the level of flavin compounds and seriously alter the current generation characteristics. Additionally, the identification of Mg 2+ as a regulator of flavin compound metabolism could be used to further control the dynamics of a reactor. For ex-

67 53 ample, quick bioflim formation is a priority during the startup of a new chamber and a high Mg 2+ concentration would reduce the competing synthesis of flavin compounds. Conversely, as a biofilm reaches anode saturation, further growth is not essential. At this time, a low Mg 2+ concentration is appropriate to promote the formation of electron mediators. As the metabolism of metal reducing bacteria becomes more clearly understood, the trade-off between growth, flavin compound metabolism, and anaerobic respiration should be a primary concern of any future scale-up efforts. 3.5 Conclusions The concentration of Mg 2+ within Shewanella oneidensis MR-1 growth media has previously been identified to have direct influence on the concentration of FMN produced by the organism. This study has demonstrated that the FMN concentration resulting from different Mg 2+ treatments directly correlates to the magnitude of current produced in an MFC. Low Mg 2+ concentrations produce higher concentrations of FMN, therefore producing higher current. This relationship was consistent under both normal MFC operating conditions and when a dialysis membrane was used to preclude direct contact with the anode.

68 54 Chapter 4 Shewanella oneidensis MR-1 Flux Balance Analysis Using a Genome-scale Model 4.1 Background Engineering fields have conventionally relied on implementing first principles in the design of new systems. However, the quantity of chemical species in biological systems, several layers of self-regulating interactions, and a general lack of kinetic data makes a successful design-based approach in biological engineering more difficult to achieve. There have been several techniques, however, which have been developed to address this issue. The field of systems biology has created a paradigm shift in the broad field of biology by approaching biological systems with a holistic view to identify emergent system properties. This is in contrast to the traditional reductionist approach of scientific based research. One technique used by system biologists to identify system properties is stoichiometric constraint-based modeling. This technique has demonstrated success, especially in the context of microbial systems. Constraint-based modeling is based on the principle of mass conservation: any metabolite taken-up by the cell must be balanced by an equal mass of metabolite either secreted by the cell or accumulated as cellular biomass. The biochemical pathways available to the cell to convert these substrates into biomass compo-

69 55 nents (protein, carbohydrates, lipids, nucleic acids) or secreted metabolites are represented with the appropriate stoichiometry of each reaction. Each of these reactions must maintain the conservation of mass. The compilation of all metabolite and reaction stoichiometry results in a set of constraints for the flux of mass through the cell s biochemical network. The scales of published constraint-based models has varied from those representing only central carbon metabolism to those representing the entire genome. Once a set of stoichiometric constraints has been identified, an objective function is imposed on the biochemical network. The objective function is a mathematical cost function which is optimized by finding an optimal set of metabolic fluxes which satisfies all the stoichiometric constraints. Several objective functions have been used to simulate microbial systems including the maximization of biomass and the maximization of energy production. A fully developed model has many potential applications. First, the model can be used to make inferences about the states of unobservable reactions. A calibrated model will make available the complete distribution of mass flux through the network for any observed uptake and growth rate. This offers a time and cost efficient approximation to alternative methods involving C 13 doping in conjunction with mass spectroscopy (MS) and nuclear magnetic resonance (NMR) spectroscopy to trace the internal cellular metabolic fluxes. Second, the model can be used to make predictions about cellular growth and secondary metabolite production rates based on alternative growth conditions. Third, the model can be used to simulate the phenyotypical responses of the organism to genetic modification. Gene knockouts

70 56 are simulated by constraining the metabolic flux to zero of any reaction associated with the enzyme targeted for knock-out. Similarly, genetic overexpression can be simulated by imposing higher constraints on the reaction of interest. These types of simulations give insight into the network response to such perturbations and are useful in refining metabolic engineering hypothesis before committing to recombinant DNA procedures. This study uses a previously built genome-scale S. oneidensis model, validated under aerobic conditions, to evaluate the organism s metabolic capabilities under anaerobic growth. The validity of the model under these conditions is evaluated by direct comparison of the model output to experimental data. The model is used to evaluate some of the key design considerations for biotechnological application of S. oneidensis. Specifically, it addresses the relationship between cellular growth, flavin compound production rates, and anaerobic respiration rates. 4.2 Method and Materials Flux Balance Analysis Model A flux balance analysis (FBA) model was setup as a linear program to solve for the metabolic flux rates of S. oneidensis metabolites and growth rate. A biochemical network was constructed as a i x j matrix, S ij, representing the corresponding stoichiometry of each metabolite, i, in each reaction, j. A column vector, v j, was used to represent the flux of each reaction in the network. Two sets of constraints

71 57 were implemented in the model. First, the product of the flux vector, v j, and the stoichiometric matrix, S, is constrained to zero. This constraint maintains the conservation of mass in the stoichiometic network. Secondly, an upper and lower boundary are placed on each flux variable. These boundaries are based on either previously observed experimental data or theoretical thermodynamic limits (e.g., Gibb s free energy, diffusion). A biologically relevant objective function to maximize the biomass reaction flux was used throughout this study. The resulting linear program is represented in Equation 4.1. Max v biomass s.t. S ij v j = 0 (4.1) lb v j ub The genome-scale FBA model built by Pinchuk et al. to simulate aerobic Shewanella oneidensis MR-1 metabolism was used as a base for compiling the set of metabolites and reactions [35]. Included in this set of reactions were the reactions representing biomass synthesis and a non-growth associated maintenance energy requirements. The biomass equation was originally developed through experimental measurement of lipid, carbohydrate, protein, and nucleic acid contribution to biomass. Representative molar concentrations of the metabolites associated with the synthesis of each biomass component, along with energy requirements, were combined into a single reaction to represent the formation of biomass. The units used for biomass basis were grams of ash-free, dry weight (gafdw). This value represents the grams of combustible biomass after being thoroughly dried of all

72 58 moisture. The non-growth associated maintenance energy requirement was originally developed by extrapolating the relationship between growth rate and substrate uptake to the point of no growth. The theoretical amount of ATP that could be derived from the corresponding substrate uptake rate was calculated to be 1.03 mm ATP gafdw 1 hr 1, which was used as the maintenance energy constraint. Units of mm gafdw 1 hr 1 were used for all reaction fluxes. In addition to the reaction set obtained from Pinchuk et al., reactions representing the presence of the electron shuttling compounds riboflavin and FMN in the extracellular environment were included in the model. These reactions consisted of both the compounds secreted and their subsequent involvement in redox reactions with extracellular compounds. The resulting model contained 881 reactions and 719 metabolites that were segregated into cytoplasmic and extracellular compartments. All linear programing was computated using GAMS software (Washington, DC) Dynamic Flux Balance Analysis Model The flux balance analysis model was adapted to simulate dynamic growth and metabolite fluxes through time by integrating the static results of the linear optimization across time. The initial biomass and media concentrations were used as the boundary conditions for the simulation. The model was implemented as in Equation 4.1, with additional constraints to maintain non-negative values for the metabolite pool. The resulting linear program, adapted from Mahadevan et al., is

73 59 represented in Equation 4.2 [27]. Max v biomass s.t. S ij v j = 0 lb v j ub z i (t + T ) 0 (4.2) z i (t + T ) = z i (t) + X(t)S ij v j T X(t + T ) = X(t) + v biomass X(t) T The variable, z(t), represents the metabolite concentrations at time, t, and the variable, X(t), represents the concentration of biomass at time, t. The last term of the last two constraints in Equation 4.2 contain an additional biomass concentration term because all flux values returned by the model have units with biomass concentration as the basis. A value of one hour was used as the time step for the dynamic modeling done in this study. GAMS software (Washington, DC) was used to solve the linear program at each iteration and Python v2.6.5 (Python Software Foundation) was used to call GAMS with the appropriate constraints and track all metabolite and biomass pools.

74 Results Model Validation with Experimental Data Shewanella oneidensis MR-1 growth and metabolite flux data was collected under anaerobic conditions using lactate and fumarate as the carbon source and electron acceptor. The observed bacterial growth occurred entirely within the first 48 hours following inoculation. The data indicates the interval between 48 and 72 hours represents a non-growth stationary phase. The stationary phase coincides with the full depletion of fumarate in the growth media, suggesting the availability of an electron acceptor was the limiting substrate. The observed concentrations of metabolites are consistent with the reactions involving the conversion of fumarate to succinate as an electron sink and the secretion of acetate as a fermentation byproduct. A plot of metabolite and biomass concentration through time is presented in Figure 4.1. In addition to the measurements of organic acids, the concentration of riboflavin and FMN were quantified during the growth experiment. The high initial concentration of both flavin compounds is the result of flavin compounds contained in the vitamin supplements added to the media. The data indicates that these compounds were taken up by the cell during the 24 hour period following the initial inoculation (Figure 4.2(a)). The large error bars observed on the data at 0 hours is the result of the imprecise addition of the vitamin supplements to the anaerobic tubes. The time interval from 24 to 48 hours, however, is consistent with the previously observed secretion of flavin compounds by S. oneidensis (Figure 4.2(b)).

75 61 Figure 4.1: Observed Biomass Growth and Organic Acid Flux Under Anaerobic Growth Conditions Metabolite flux and biomass growth rates were determined for the 24 to 48 hour time interval of the observed data. These rates were normalized to the average biomass observed for the same time period to yield units consistent with those of the FBA model (mm gafdw 1 hr 1 ). The FBA model was then optimized for biomass growth while the observed lactate and fumarate uptake rates, as well as the observed riboflavin and FMN secretion rates, were imposed as constraints. Table 4.1 provides a comparison of the biomass growth and metabolic flux rates observed in the lab to those obtained using the FBA model. There was good agreement between the model and the observed data for the flux of acetate secreted by the cell with a difference of only 7.5% between the two. However, the secretion of succinate calculated in the model was underestimated by

76 62 Figure 4.2: Observed Flavin Flux Under Anaerobic Growth Conditions: a) 0-72 hrs, and b) hrs 50.0% while the biomass growth rate was overestimated by 182.9%. A portion of this error can be mitigated by placing additional constraints on the succinate and acetate exchange fluxes. When the exchange rate of acetate is held at the previously calculated value of 6.33 mm gafdw 1 hr 1, a trade-off between increased succinate exchange flux and biomass growth rate is observed. An increase of only

77 63 Observed Model Output Metabolite mm gafdw 1 hr 1 mm gafdw 1 hr 1 Lactate* Fumarate* Riboflavin* FMN* Acetate Succinate Biomass(hr 1 ) Table 4.1: Comparison of Observed Flux to Model Output Under Anaerobic Growth Conditions. (*) model constraint imposed 0.85 mm gafdw 1 hr 1 from the previously calculated succinate flux for a total of mm succinate gafdw 1 hr 1 results in a reduction of the calculated biomass growth rate to the experimentaly determined rate of hr 1. The error observed in the static model is propagated at each iteration of the dynamic model resulting in a growth profile that is grossly exaggerated (Figure 4.3). However, despite the over-estimation of biomass growth, the model qualitatively represents the expected dynamics of the system, including an exponential growth curve for biomass formation. The lack of obvious exponential growth in the experimental data may suggest inaccuracy in the lab procedure and not necessarily the result of an invalid model. The model is assumed qualitatively valid for the remaining simulations, and the idea of error originating in the laboratory data set is revisited in future discussion.

78 64 Figure 4.3: Modeled Anaerobic Growth Conditions using dynamic FBA Metabolic Trade-off Analysis The model that was qualitatively validated for fumarate growth was used to explore the metabolic implications of increased flavin compound production. A range of lower bounds from 0 to 0.5 mm gafdw 1 hr 1, in intervals of 0.1, were imposed on riboflavin and FMN secretion rates. The model was maximized for biomass growth at each combination of constraints, and the resulting biomass growth and fumarate reduction rate were plotted (Figures 4.4 and 4.5, respectively). The results indicate that the relationship between biomass growth rate and flavin compound synthesis rates are inversely related. Under the simulated anaerobic growth conditions with lactate and fumarate as substrates, a maximum of 0.5 mm gafdw 1 hr 1 of flavin compounds may be produced by the cell before growth becomes infeasible. The relation between decreased biomass growth and increased flavin compound production is linear at a ratio of and gafdw mm 1 for riboflavin

79 65 and FMN, respectively. The slightly higher cost for FMN production is the result of the additional phosphorylation requirement during the synthesis of the compound. Figure 4.4: Response of Biomass Growth Rate to Increased Electron Mediator Production Each mole of fumarate reduced in the extracellular space is the result of 2 moles of electrons respired to the outer membrane (OM) of the cell, and therefore, this reaction was used to estimate the theoretical number of electrons available for anode reduction during MFC application. Increasing the metabolic production of either flavin compound resulted in a reduced flux of electrons to the OM. The ratio of electron flux to flavin compound synthesis was linear with constants of and mm e mm 1 for riboflavin and FMN, respectively Extreme Case Analysis Two extreme cases were selected from the trade-off analysis to explore changes in the flux distribution of the organism. The two cases examined were the complete absence of flavin compound secretion and the secretion of 0.5 mm FMN gafdw 1

80 66 Figure 4.5: Response of Outer Membrane Electron Flux to Increased Electron Mediator Production hr 1. The exchange fluxes were first examined to identify global differences between the two extreme cases (Figure 4.6). As previously identified, the biomass growth rate is significantly reduced when a high demand for FMN synthesis is imposed on the cell. Additionally, the model identifies an increased demand for both nitrogen and phosphorous uptake by the cell to produce FMN, which is more abundant in these elements than biomass. Similarly, the decreased biomass synthesis rate reduces the sulfur uptake demand by the cell. A tremendous benefit of genome-scale models is that internal flux distributions can be inferred based on observed extracellular fluxes. The distribution of flux through central carbon metabolism was analyzed for the same two extreme cases (Figure 4.7). The activity of enolase and phosphoglyceromutase to convert phosphoenolpyruvate (PEP) to 3-phosphoglycerate (3PG) was determined to be much greater when an increased demand for flavin compound synthesis was imposed on the cell. This flux was directed towards the pentose phosphate pathway from which the riboflavin precursor, ribulose 5-phosphate, could be synthesized.

81 67 Figure 4.6: States Exchange Flux Values Resulting from Extreme Flavin Production This additional flow of mass through the pentose phosphate pathway was partially supported by the increased transport of fumarate into the cell. This additional fumarate was converted to oxaloacetate via citric acid cycle intermediates and then to PEP by phosphoenolpyruvate carboxykinase. The increased flux of fumarate into the cell leaves less extracellular fumarate available for reduction, thus providing a rationale for the trade-off between flavin compound synthesis and OM electron respiration Implementation of Commericial Production Strategy Riboflavin, also known as vitamin B2, is produced commercially for industrial use. Several biotechnological processes using microbial organisms have been de-

82 68 Figure 4.7: Selected Internal Flux Values Resulting from Extreme Flavin Production States veloped for its synthesis. One of the available organisms that has been developed is Bacillus subtilis. The metabolic engineering strategy used to overproduce riboflavin using B. subtilis is to increase the availability of the purine nucleotide precursor guanosine triphosphate (GTP). This is accomplished by increasing the flux from inosine monophosphate (IMP) to xanthosine monophosphate (XMP) and sequentially from XMP to guanosine monophosphate (GMP), while decreasing the competing pathway of IMP conversion to adenosine monophosphate (AMP) [43]. This strategy was implemented in the S. oneidensis genome-scale model by constraining the corresponding GMP synthesis reaction fluxes to a value three times the magnitude of the wild-type flux. The increase in flux through the purine metabolic pathways resulted in a 700 fold increase in the amount of riboflavin produced (Table 4.2). The exact magnitude of the increase in GMP production in

83 69 commercially viable strains of B. subtilis is unavailable and a three fold increase is likely over-estimated. However, the exaggerated result of increased riboflavin synthesis indicates that a similar strategy could be successful in S. oneidensis. The formation of GMP is an irreversible reaction, and using the existing reaction network, the only available sink for the purine is riboflavin secretion. Thus any additional flux that can be directed towards purine synthesis will likely result in increased flavin compound synthesis. Wild Type Mutant Reaction mm gafdw 1 hr 1 mm gafdw 1 hr 1 IMP XM P XMP GM P Ribof lavin F MN Biomass Table 4.2: Implementation of Commercial Riboflavin Production Strategy on S. oneidensis Model Reaction Knockout Analysis Single reaction knockouts were simulated using the FBA model to search for phenotypes which exhibit superior flavin compound synthesis or electron respiration characteristics. All 881 reaction were constrained to zero, one at a time, and the optimized flux distribution was recorded for each iteration. Fatal phenotypes resulted from 32% of the reaction knockouts, 66% retained similar growth rates, and

84 70 2% had stunted growth rates (Figure 4.8). A single reaction had an increased growth rate corresponding to a knock-out of the non-growth associated energy requirement. Figure 4.8: Simulated Growth Profile of Reaction Knockout Mutants None of the simulated knock-outs resulted in phenotypes with increased flux to the synthesis of flavin compounds. However, many of the knockouts that resulted in decreased growth rates also resulted in increased respiration of electrons to the outer membrane (Figure 4.9). The single reaction knockouts leading to increased OM electron flux were examined in more detail (Figure 4.10). The reaction knockouts resulting in the greatest increase to OM electron flux involve removal of the acetate synthesis and secretion pathway (R28, R39, R619). This pathway is responsible for a critical substratelevel phosphorylation step, and its removal requires alternative energy production, presumably by anaerobic respiration. The use of only anaerobic respiration, how-