The role of 1,3-propanediol production in fermentation of glycerol by Clostridium pasteurianum

Bioresource Technology 209 (2016) 1–7

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The role of 1,3-propanediol production in fermentation of glycerol by Clostridium pasteurianum Erin E. Johnson a, Lars Rehmann a,b,⇑ a b

Department of Chemical & Biochemical Engineering, The University of Western Ontario, 1151 Richmond St., London, Ontario N6A 3K7, Canada Department of Biochemical Engineering, AVT – Aachener Verfahrenstechnik, RWTH Aachen University, Worringer Weg 1, 52074 Aachen, Germany

h i g h l i g h t s
Redox potential and fermentation products were measured under controlled pH values.
Carbon balances revealed a carbon redistribution toward butanol as pH decreased.
Reducing pH favors butanol formation at the expense of the fermentation rate.
PDO production rate is multimodal, indicating pathway regulation.

a r t i c l e

i n f o

Article history: Received 22 December 2015 Received in revised form 18 February 2016 Accepted 20 February 2016 Available online 27 February 2016 Keywords: Butanol Fermentation Redox Online measurements Biorefinery

a b s t r a c t Waste crude glycerol from biodiesel production can be used to produce biobutanol using Clostridium pasteurianum with the main products being n-butanol, 1,3-propanediol (PDO) and ethanol. There has been much discrepancy and mystery around the cause and effect of process parameters on the product distribution, thus a better understanding of the pathway regulation is required. This study shows that as process pH decreased, the rate of cell growth and CO2 production also decreased, resulting in slower fermentations, increased duration of butanol production and higher butanol concentrations and yields. The production rate of PDO was multi-modal and the role of PDO appears to function in redox homeostasis. The results also showed that C. pasteurianum displayed little biphasic behavior when compared to Clostridia spp. typically used in ABE fermentation due to the alternative glycolysis-independent reductive pathway of PDO production, rendering it suitable for a continuous fermentation process. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction Commercially produced biodiesel generates approximately 10% (w/w) of the ester as crude glycerol (Adewale et al., 2015; da Silva et al., 2009). This waste stream however, can be potentially contaminated with catalyst, soap, methanol, free fatty acids, glycerides and methyl esters, rendering it useless for the existing glycerol markets unless costly purification is employed. This waste stream represents a unique opportunity as a new carbon source for biobutanol production, requiring minimal upgrading. Co-locating with biodiesel plants, would allow the utilization of established infrastructure and add significant value and productivity to the existing biodiesel industry. Reports suggest that for the resurrection of the biobutanol process, there needs to be improvements in volumetric ⇑ Corresponding author at: Department of Chemical & Biochemical Engineering, The University of Western Ontario, 1151 Richmond St., London, Ontario N6A 3K7, Canada. E-mail address: [email protected] (L. Rehmann). http://dx.doi.org/10.1016/j.biortech.2016.02.088 0960-8524/Ó 2016 Elsevier Ltd. All rights reserved.

productivity during fermentation and reductions in operating and capital costs of downstream purification (Bankar et al., 2013). There are many known microorganisms that can naturally utilize glycerol, a common alcohol in nature, as sole carbon and energy source, however their product profiles are very different (da Silva et al., 2009; Khanna et al., 2012). Unlike others, Clostridium pasteurianum produces a unique product profile containing: butanol, ethanol, PDO, and trace amounts of organic acids (acetic and butyric). C. pasteurianum have been shown to ferment biodiesel-derived crude glycerol, requiring minimal upgrading (Biebl, 2001; Dabrock et al., 1992; Gallardo et al., 2014; Khanna et al., 2013; Malaviya et al., 2012; Moon et al., 2011; Taconi et al., 2009; Venkataramanan et al., 2012). The product distribution of C. pasteurianum is variable and the metabolic regulation is little understood (Biebl, 2001; Dabrock et al., 1992; Gallardo et al., 2014). In contrast to the 1,3-propanediol-forming enteric bacteria, little is known about the enzymes responsible for glycerol breakdown in Clostridia spp. Of the Clostridia spp., the greatest

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body of work in the area of enzyme characterization has been for Clostridium acetobutylicum and Clostridium butyricum. The genome sequencing for C. pasteurianum has not yet been done and currently genetic tools are being developed for the manipulation of C. pasteurianum (Pyne et al., 2013). The proposed biochemical pathways and that may exist for C. pasteurianum, are currently based on what is known in the literature for Klebsiella spp., Citrobacter spp., Clostridium spp. and Enterobacter spp., who can metabolize glycerol both oxidatively and reductively, and can be found elsewhere (Daniel et al., 1995; Forage and Lin, 1982; Luers et al., 2006; Macis et al., 1998; Menzel et al., 1998; Németh et al., 2003; Skraly et al., 1998; Toraya et al., 2010). There appears to be inconsistency among and/or incomplete knowledge of the biochemical pathways between Clostridia spp. For example, the pathway for glycerol oxidation in Clostridia spp. has been found to vary such that C. butyricum appears to utilize a glycerol dehydrogenase and a dihydroxyacetone kinase, while C. acetobutylicum appears to utilize a glycerol kinase and a glycerol-3-phosphate dehydrogenase (Vasconcelos, 2006). C. butyricum is one of the few microorganisms found that use a B12-independent glycerol dehydratase, thus resulting in commercial interest for the production of PDO. For C. butyricum, the B12-independent pathway converting glycerol to 1,3-propanediol has been recently characterized (Raynaud et al., 2003; Saint-Amans et al., 2001). Of interest to this study, the main oxidative pathway involving glycolysis produces CO2, H2, pyruvate and electrons in the form of reducing equivalents (NADH2). NADH2 is also released during biomass formation. The highly reductive state of glycerol results in twice the amount of reducing equivalents compared to fermentation with glucose. These electrons require an acceptor for redox potential homeostasis. Under anaerobic conditions, the ‘competing’ reductive pathways function to accept electrons produced in glycolysis. The most active reductive pathways observed in C. pasteurianum are: (1) the production of solvents (ethanol and butanol) from the glycolysis-dependent central intermediate, pyruvate and (2) the glycolysis-independent pathway of PDO production. Fig. 1 is a summarized biochemical pathway diagram, with dashed lines representing the flow of electrons. Regulation of glycolysis and the level of NAD+ and NADH2 in the cell is achieved largely by the enzyme NADH-ferredoxin oxidoreductase which can produce or oxidize NADH2 (depending on cellular conditions). Acetyl-CoA is an obligate activator of the NADH-ferredoxin reductase activity and NADH2 is a competitive inhibitor of ferredoxin-NAD+ reductase activity (Jungermann et al., 1971; Petitdemange et al., 1976). This regulation allows these glycolysis enzymes to function in concert with G3P dehydrogenase, at the point of entry of the substrates glucose and glycerol. Of particular interest, it was found that the NADH-ferredoxin oxidoreductase functions reversibly in C. pasteurianum and C. acetobutylicum. Also, glycolysis is pH dependent. It is because of this regulation that C. pasteurianum has been shown to maintain constant intracellular levels of NAD+ and NADH2 during different growth phases (Petitdemange et al., 1976). Parameters such as extracellular pH are easy to control and can potentially influence the molecular pathways. Therefore, there is a need for real-time process monitoring of industrial anaerobic processes such as butanol production from glycerol. The extracellular redox potential (ORP) reflects the overall electron transfer and redox balance involved in intracellular metabolism (Graef et al., 1999), while the intracellular ORP is dominated by the ratio of NAD(P)H2/NAD(P)+. Gene expression has been shown to be effected by ORP through redox sensitive proteins which subsequently control enzyme synthesis to adjust the intracellular redox balance and metabolism (Pei et al., 2011; Wietzke and Bahl, 2012).

Few studies can be found in the literature where controlled pH was used in fermenting glycerol by C. pasteurianum. The typical pH range for fermenting glycerol by C. pasteurianum in pH controlled bioreactors is 4.5–6.0 (Kao et al., 2012; Jensen et al., 2012a,b; Malaviya et al., 2012; Biebl, 2001). Previous studies on the effect of pH control on the product profile of C. pasteurianum have indicated that there was great variability in product formation (Biebl, 2001; Dabrock et al., 1992). One study went as far as to conclude that under equal or slightly different conditions, product variability was believed to be due to weak pathway regulation and/or multiplicity effects (Biebl, 2001). Other small scale studies without pH control found some correlation to initial pH (Ahn et al., 2011; Khanna et al., 2013). The control of pH is an acceptable and industrially feasible solution to manage the product profile. Thus, pH control is a parameter that should be further investigated on its own in a well-controlled study. It was the goal of this current study to investigate C. pasteurianum fermenting glycerol under varying pH control while monitoring redox potential and fermentation products to better understand the metabolism and control of the product distribution. 2. Methods 2.1. Chemicals All chemicals were purchased from Sigma–Aldrich (Missouri, USA) unless otherwise noted. Yeast extract, peptone and beef extract were purchased from BD-Becton, Dickinson and Company (New Jersey, USA). Soluble starch and sodium acetate were purchased from Alfa Aesar (Massachusetts, USA). Dextrose was purchased from Amresco (Ohio, USA). CaCl22H2O was purchased from EMD Millipore (Massachusetts, USA). (NH4)2SO4, MgSO47H2O, KH2PO4, and K2HPO4 were purchased from Caledon (Ontario, Canada). Pure glycerol, FeSO47H2O and NaCl were purchased from BDH (Georgia, USA). Pure nitrogen gas was purchased from Praxair, London, Canada. 2.2. Microorganisms and media C. pasteurianum DSM 525 was purchased from DSMZ, Braunschweig, Germany. The following reinforced Clostridium media (RCM) was used for all seed cultures (amounts per liter of deionized water): peptone, 10.0 g; beef extract, 10.0 g; yeast extract, 3.0 g; glucose 25.0 g; NaCl, 5.0 g; soluble starch, 1.0 g; sodium acetate, 3.0 g; pH adjusted to 6.8. The following medium was used for all bioreactor fermentations (amounts per liter of deionized water): KH2PO4, 0.5 g; K2HPO4, 0.5 g; (NH4)2SO4, 5 g; MgSO47H2O, 0.2 g; CaCl22H2O, 0.02 g; FeSO4, 0.05 g; yeast extract, 1.0 g; glycerol, 30 g; trace element solution (SL7), 2 ml; Antifoam 204 (Sigma A6426), 0.2 ml. The following trace element solution (SL7) was used for all bioreactor trials (amounts per liter of deionized water): FeCl24H2O, 1.5 g, dissolved in 10 ml HCl solution (25% solution); CoCl26H2O, 0.19 g; MnCl24H2O, 0.1 g; ZnCl2, 0.07 g; H3BO3, 0.062 g; Na2MoO42H2O, 0.036 g; NiCl26H2O, 0.024 g; CuCl22H2O, 0.017 g. It should be noted that CaCO3 (buffer) was not used in any media since it releases CO2 and interferes with the measurement of the metabolic CO2 production rate. 2.3. Fermentation parameters The fermentations were performed in a 7 L bioreactor (Infor HT, Bottmingen/Basel, Switzerland, model: LabFors 4). The working volume was 5 L. Five bioreactor trials were performed in total, one for each pH setting (4.7, 5.0, 5.3, 5.6, 5.9) and controlled using

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Fig. 1. Potential metabolic pathway of glycerol in Clostridium pasteurianum. The dashed lines represent the flow of electrons. Modified from Venkataramanan et al. (2012). 3HPA, 3-hydroxypropionaldehyde; DHA, dihydroxyacetone; DAP, dihydroxyacetone phosphate; NAD+, oxidized form of nicotinamide adenine dinucleotide; NADH2, reduced form of nicotinamide adenine dinucleotide; PDO, 1,3-propanediol; ADP, adenosine diphosphate; ATP adenosine triphosphate.

3 M KOH/3 M H2SO4. The temperature was controlled at 35 °C and agitation to 150 rpm. Pure nitrogen was used for sparge gas at a rate of 0.12 vvm, to promote an anaerobic environment and to ensure the minimum supply of off-gas flow for off-gas analysis and thus mass balance calculations. The bioreactor was inoculated with seed culture of 10% v/v, prepared using a three step protocol initiated from 500 ll glycerol stocks stored at 80 °C and transferred at a rate of 10 v/v% in exponential growth phase having, an optical density at 600 nm of 1.2–1.4 at each stage. Seed cultures were prepared in an anaerobic chamber (Plas-Labs, MI, USA, model 855-ACB-EXP). The chamber gas mixture was 10% H2, 5% CO2 balance N2. The liquid media were sparged with nitrogen for a minimum of 30 min at 1.0 L/min, 400 rpm, 35 °C prior to inoculation and the bioreactor pH was adjusted to the desired value immedi-

ately after inoculation. During fermentation the pH was controlled to the desired value ±0.02 using a PID controller. 2.4. Analytical methods The inlet gas flow was controlled using a Red-y series flow controller (Vögtlin Instruments AG, Aesch BL, Switzerland, model GSC-C3SA-BB12, 0–10 L/min). The off-gas was analyzed for CO2 concentration (v/v%) using a continuous emissions analyzer (Servomex, MA, USA, model: 4900C1) with infrared CO2 transducer (1520-IR, 0–25%). A Veriteq data logger (Veriteq Instruments, Inc., Richmond, BC) with software (Spectrum) was used to log the data on-line in real time. An Aalborg thermal mass gas controller (model GFC171S, 0-5 LPM) and an Aalborg totalizer input/output (model

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TIOS-010008) was used to measure and log the total off-gas volumetric flow (L/min) in real time (Aalborg, Orangeburg, New York). The pH was controlled using a Hamilton EasyFerm Plus K8 325 probe and transmitter with PID (Hamilton, NV, USA). The redox was monitored using a Mettler Toledo Ingold probe (model PT4805-DPAS-SC-K8S/325) and transmitter (Mettler Toledo, Mississauga, Canada). The optical density (OD) was monitored on-line using the Finesse TruCell2TM cell density sensor (Finesse Solutions, LLC, CA, USA) equipped with transmitter and software. The light source was a vertical cavity surface-emitting laser (VCSEL) emitting at 850 nm and the detector was a silicon photodiode. The dry cell weight (DCW) for all samples was performed gravimetrically in duplicate at the same time that liquid samples were removed for HPLC analysis. The optical density and DCW data were fit using regression analysis (Levenberg–Marquardt algorithm) in MatLab (The MathWorks, Inc., Natick, MA, USA) and the following curve fit equation:

  xPU yAU ¼ A þ B 1  eð C Þ þ D  xPU

ð1Þ

where yAU is optical density reading; xPU is the DCW (g/L, dry basis); A, B, C, D are the curve fitting coefficients. Inlet gas flow, redox potential, pH, OD, temperature, rpm, gas mix were all logged to PC in real time using the multi fermenter control system software (Iris V5 PRO for LabFors, 65605, Infor HT, Bottmingen/Basel, Switzerland). Rates were estimated via numerical differentiation of the raw data (centered finite differences). Liquid samples from the fermentation broth were analyzed by a high performance liquid chromatography (HPLC) using an Agilent 1260 system (Agilent, Mississauga, Canada). Samples were filtered using 0.2 lm cellulose acetate filters and diluted to within range of the calibration curve. The HPLC was equipped with a refractive index detector (RID) (Agilent G1362A), and operated at 40 °C for analysis of the soluble components: glucose; glycerol; acetic acid; 1,3-propanediol; ethanol; butyric acid and butanol. The quaternary pump (Agilent, G1311B) was operated with isocratic flow at 0.4 ml/min using 5 mM H2SO4 as mobile phase. The column used in the HPLC analysis was an Agilent HiPlex-H column (PL11706830) operated at 35 °C. An autosampler was used (Agilent G1329B) with an injection volume of 20 ll. 3. Results and discussion The effect of pH on product distribution was investigated through identical fermentations in highly controlled bioreactors equipped with online monitoring tools. The pH values were controlled at 4.7, 5.0, 5.3, 5.6 and 5.9, respectively. The fermentation proceeded in all conditions irrespectively of the fixed pH and

resulted in near full substrate consumption and high levels of solvent formation (Table 1) clearly demonstrating that a sufficiently low pH value is not responsible to start solvent production in C. pasteurianum. A carbon balance was performed for each bioreactor trial using on-line analysis of total volumetric inlet and outlet gas flow, the volumetric concentrations of inlet and outlet gases (CO2 and N2) and the off-line liquid phase analysis of carbohydrates and fermentation products by HPLC (glucose, glycerol, acetic acid, PDO, ethanol, butyric acid, butanol). Mass balances were achieved in all trials with 90% or greater mass closure (Table 1). Table 1 summarizes the mass yields (gprod/gsub) and molar yields (molprod/molsub) of: butanol, PDO, ethanol, total PDO/butanol/ethanol (PBE), DCW and CO2, as well as concentration of butanol, PDO, ethanol and DCW. All analysis was calculated at the first sample point in time when the substrate was consumed by 95% or greater. This is an important aspect for comparative analysis, mainly due to the fact that the fermentation time decreased as pH increased. As will be discussed below and from an analysis of the kinetic data, as pH increased, so did the accumulative cell mass. It should be noted that most of the work on biobutanol production from glycerol in the open literature has been done without pH control in systems that did not allow for a full look at the carbon balance or the kinetics. To the authors’ best knowledge this is the most comprehensive dataset available in the literature and the first full carbon balance at various controlled pH levels. The data shows that lower pH values favored the formation of butanol, while at higher pH values, the amount of carbon diverted to PDO increased as did the cell growth rate. This will be discussed in more detail below. The ethanol yield was not effected until the pH was lowered to 4.7, at which point the yield increased considerably from 0.04 to 0.13 mol/mol and the concentration increased from 0.60 to 1.87 g/L (see Table 1). The molar yield of cells was based on an assumed molar weight of 101.104 g/mol, consistent with the formulae C4H7O2N (Biebl, 2001).

3.1. CO2 production and Redox In C. pasteurianum, carbon dioxide is produced as a by-product of glycolysis, enabling energy intensive cellular functions such as anabolism and cell growth. Carbon dioxide is an inevitable by-product of the butanol pathway, while no CO2 is formed when glycerol is converted to PDO. The state of the cells’ metabolism can be deduced from the redox potential in the reactor, hence the two parameters are discussed jointly. Carbon dioxide production was monitored on-line during fermentations and was prominently affected by process pH. As the pH increased from 4.7 to 5.9, the maxima of the CO2 production rates increased and were reached earlier, while the duration of CO2 production was shortened (Fig. 2A). The cell concentration was linearly and positively correlated to CO2 production

Table 1 Analysis at completion of fermentation (defined as >95% utilization of glycerol) for different controlled pH in 5 L batch fermentations. Yields are expressed as g product per g substrate consumed, g/g with the molar yield in parenthesis, mole product per mole of substrate consumed, (mol/mol), MFcells = C4H7O2N (101.10438 g/mol). Analysis at completion

pH 4.7

pH 5.0

pH 5.3

pH 5.6

pH 5.9

Carbon balance closure, % Yield butanol, g/g (mol/mol) Concentration butanol, g/L Yield PDO, g/g (mol/mol) Concentration PDO, g/L Yield ethanol, g/g (mol/mol) Concentration ethanol, g/L Yield DCW, g/g (mol/mol) Concentration DCW, g/L Yield CO2, g/g (mol/mol) Total yield PBE, g/g (mol/mol) Glycerol utilization, % Time of analysis, h

97 0.29(0.37) 8.58 0.07(0.08) 2.03 0.06(0.13) 1.87 0.07(0.07) 2.13 0.39(0.84) 0.42(0.58) 95 28

90 0.29(0.36) 9.05 0.05(0.06) 1.65 0.02(0.04) 0.60 0.08(0.07) 2.46 0.35(0.76) 0.36(0.47) 96 20

93 0.26(0.33) 8.49 0.07(0.08) 2.13 0.02(0.04) 0.61 0.10(0.10) 3.34 0.35(0.76) 0.35(0.45) 95 16

99 0.24(0.30) 7.80 0.09(0.11) 2.96 0.02(0.04) 0.69 0.10(0.09) 3.33 0.40(0.85) 0.35(0.46) 97 14

98 0.20(0.25) 6.61 0.14(0.17) 4.63 0.02(0.05) 0.80 0.10(0.09) 3.33 0.34(0.74) 0.36(0.48) 99 12

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Fig. 2. CO2 production rate and redox potential for glycerol fermentation by C. pasteurianum at varying controlled pH values. The vertical lines represent the end of the redox homeostasis, determined as the inclination point of the CO2 production rate.

at all pH (data not shown). For the bioreactor trial controlled at pH 4.7, the CO2 concentration and rate of production cycled in a sinusoidal manner after 20 h. This cycling was also observed in three other independent on-line monitors: on-line pH signal; on-line off-gas total volumetric flow rate (data not shown); on-line redox potential signal (Fig. 2B), indicating a true metabolic response. A small perturbation in the on-line CO2 concentration profile is shown in all bioreactor trials between 5–7 h (Fig. 2A). At the same time changes were observed in the redox signal (Fig. 2B). The redox potential signal for all fermentations resulted in a reproducible characteristic profile which can be broken down into three regions. The perturbation observed in the CO2 production appears to end the first region, a region of net electron accumulation (increasing electronegativity) at the beginning of fermentation when glycolysis and cell growth is very active. The electron flux is then balanced (zero slope) in the subsequent section in the middle of fermentation for which the term ‘redox homeostasis’ is suggested. The beginning of this region appears to coincide with the beginning of butanol formation. The butanol concentration was obtained through off-line analysis (every 2 h) and no butanol could be detected in any reactor in the first 4 h. Butanol could be detected after 6 h at pH 5.6 and 5.9 and at 8 h for the lower pH values. The values are in good agreement with the beginning of ‘redox homeostasis’ which occurs between 4 h and 6 h for pH 5.6 and 5.9 and between 6 h and 8 h for the lower pH values. The third region represents an electron net consumption (decreasing electronegativity) at the end of fermentation. The ‘homeostasis’ portion of the redox signal occurred during the highest rate of CO2 production and its duration coincided with the duration of CO2 production such that as the duration of CO2 production lengthened so did the duration of the redox homeostasis. The vertical lines in Fig. 2 represent the point of steepest decline in the CO2 production rate (determined numerically) and it can be seen to clearly coincide with the end of the redox homeostasis. This numerical determination of the end of redox homeostasis was not suitable for the

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Fig. 3. Biomass growth and glycerol consumption during glycerol fermentation by C. pasteurianum at varying controlled pH values. The DCW symbols (open circles) represent off-line measured DCW, while the solid lines represent the estimated value based on an on-line optical density probe. The symbols in the glycerol plot represent off-line data measured via HPLC, while the solid lines (first order splines) are added for visual clarity only.

fluctuating signals at pH 4.7. Also, as the controlled pH increased, the redox potential was driven to more negative values, indicating more electrons were accumulating at the higher pH during this time. The redox data indicates that an increased flux of carbon through the glycolytic pathway occurred with higher pH. This increased flux through glycolysis coincided with increased PDO production (Table 1), presumably as a means to balance electrons (electron consuming reductive pathway). Notably, PDO formation could be detected 2 h earlier than butanol for all five pH conditions. If the cells can change their metabolic pathway flux to achieve redox balance, then artificially changing the redox balance might be able to alter their metabolic pathway flux.

3.2. Glycerol consumption and cell growth Glycerol consumption was also clearly affected by process pH. As the pH increased from 4.7 to 5.9, glycerol was utilized faster and exhausted from the media sooner (Fig. 3A). In all pH trials, >95% of the available glycerol was consumed and product inhibition was not evident. When the pH was controlled at 5.9, the glycerol feedstock was 99% consumed in 10–12 h, while for pH 4.7, glycerol was consumed by 95% in 28–32 h. The resulting increase in the rate of substrate utilization with increasing pH can be partially explained by the increased cell biomass accumulation (Fig. 3B). Other factors may have also been causal such as pHdriven enzymatic activity. Thus increasingly higher cell concentrations were achieved sooner with increasing process pH, even though the final cell concentrations were similar for pH trials 5.3, 5.6 and 5.9 (3.3–3.4 g/L DCW). For pH 5.0 and 4.7 the maximum cell concentration was lower; 2.46 and 2.13 g/L respectively. It can be seen that glycerol consumption continued at the end of the fermentation without additional DCW increases, particularly at lower pH values.

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Fig. 4. Butanol and PDO formation during glycerol fermentation by C. pasteurianum at varying controlled pH values. The symbols (open circles) represent off-line measurements via HPLC, while the solid lines (first order splines) are added for visual clarity only.

Fig. 5. Butanol and PDO production rates during glycerol fermentation by C. pasteurianum at varying controlled pH values. Rates were determined via numerical differentiation of the data shown in Fig 4.

3.3. PDO and butanol production As expected, butanol and PDO were formed throughout the fermentation. Butanol formation started later than PDO formation and followed a typical sigmoidal pattern (Fig. 4A). The profile of PDO formation however appears irregular, as seen in Fig. 4B. As the process pH increased, the accumulative PDO concentrations increased (Fig. 4B). Also, as pH increased, butanol production commenced sooner and ceased production earlier when glycerol was exhausted from the media (Figs. 4A and 3B). Thus, fermentations with pH 5.6 and 5.9 had lower final butanol concentrations than the fermentations at lower pH values (Fig. 4A). The maximum butanol production rates can be divided into two clusters. Equally high maximum rates of approximately 1.4 g L1 h1 were achieved for pH 5.3, 5.6 and 5.9, while maximum rates of 0.9 g L1 h1 were achieved for pH 4.7 and 5.0 (Fig. 5A). However, the duration of butanol production increased with decreasing pH (Fig. 5A), resulting in higher overall butanol concentrations (Fig. 4A) and yields (Table 1). These results indicate that there is a clear advantage to slowing down the fermentation rate to produce more butanol and less PDO. The butanol production rate (Fig. 5A) closely mimics the CO2 formation rate (Fig. 2A), while the PDO production rate appears not to be correlated. This can be explained by the fact that CO2 is an inevitable by-product on the pathway leading to butanol, while no CO2 formation occurs when converting glycerol to PDO. However, PDO formation appears to occur in at least two separate stages (Figs. 4B and 5B), resulting in multimodal rate-profiles, as particularly evident for the data-sets at pH 5.9 and 5.3. The PDO production rates in these case go through an initial maximum at 4 h followed by a second maximum at 10 and 14 h, respectively. The first maximum coincides with exponential cell growth and the second maximum coincides with the end of the redox homeostasis (Figs. 3A and 2B). Thus the production of PDO functions to balance redox during the peak production of cell growth and glycolysis when electrons and NADH2 are produced. To date, the effect of process pH on the product distribution of C. pasteurianum is not well understood and the small amount of

literature on the subject is contradictory and difficult to compare due to inconsistent process parameters: media, limiting nutrients, microbial strain, scale of study and experimental design and analysis. A closely related study used 500 ml batch cultures controlled at pH between 4.5 and 7.5 using 50 g/L pure glycerol as substrate and a similar media formulation otherwise as the current study (6.54 mM phosphate) (Biebl, 2001). The study reported finding great variation in product formation, however no correlation to pH was found accept for ethanol. Cell growth was found to be more or less equal over the pH range applied, in contrast to the data reported in this study. In general there was great variability in product formation under equal or slightly different conditions, a cause that was hypothesized to be due to weak pathway regulation and/ or multiplicity effects. However, it is likely that the use of 50 g/L glycerol could have led to multifactorial effects involving substrate and/or product inhibition, masking the single variable effect of pH. The pH has been shown elsewhere to effect cell growth in continuous 1 L cultures of C. pasteurianum using glucose as substrate (40 g/L) over a pH range from 4.8 to 7.0 (Dabrock et al., 1992). It was reported that for pH below 5.5, growth and substrate utilization decreased and at pH below 4.8 steady state conditions could not be obtained. Using a phosphate-limited (0.5 mM) minimal medium it was concluded that there was almost no effect of pH on solvent production (ethanol and butanol). Unfortunately, data on PDO production was not provided. However, the different substrates make a meaningful comparison difficult. Variation between PDO and butanol production from crude glycerol have been reported elsewhere (Gallardo et al., 2014), however the pH was not controlled and the amount of crude glycerol, including the associated impurities, was varied instead. Studies investigating the initial pH (no control after inoculation) with pure glycerol show increased butanol yields with lowering pH by C. pasteurianum in 50 ml batch cultures (Ahn et al., 2011), in good agreement with the results reported here. Similarly an optimization study on

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four variables: agitation rate; temperature; initial pH and initial glycerol concentration also concluded that the initial media pH was the most critical factor for total alcohol production from pure glycerol (Khanna et al., 2013). There have been many studies showing that redox control has shifted the metabolism from reductive to oxidative and vice versa. It was shown that artificial electron carriers such as methyl viologen and neutral red caused significant carbon flow shift from acids to alcohols production in C. acetobutylicum accompanied by decreased hydrogen evolution (Girbal, 1995). Microaerobic conditions were found to shift the metabolism from reductive to oxidative and reduce PDO production substantially in C. butyricum (Pachapur et al., 2015). Similarly, it was found in this study, the PDO production was reduced at low pH values, which in turn resulted in slightly higher redox potential (Fig. 2B). It can be postulated that the redox potential was controlled through low pH (this study) and microaeration (Pachapur et al., 2015), in both cases effecting the product distribution. 4. Conclusions Unlike C. acetobutylicum, C. pasteurianum does not display strong biphasic behavior. In the absence of significant product, substrate or other inhibition, decreasing fermentation pH resulted in slower fermentations, higher butanol and lower PDO yields. The rate of PDO production fluctuated in a multimodal manner, unlike the production rate of CO2 and butanol, suggesting that PDO production is regulated and further that its regulation may serve to function in redox homeostasis and allow C. pasteurianum to behave non-biphasic. In batch culture, process pH can be used as a tool to control the product profile at the expense of fermentation time. Acknowledgements The authors are grateful to the Natural Sciences and Engineering Research Council of Canada, the Canada Foundation for Innovation, Newalta, BioFuelNet Canada and the Alexander von Humboldt Foundation for financial support. References Adewale, P., Dumont, M.-J., Ngadi, M., 2015. Recent trends of biodiesel production from animal fat wastes and associated production techniques. Renewable Sustainable Energy Rev. 45, 574–588. Ahn, J.H., Sang, B.I., Um, Y., 2011. Butanol production from thin stillage using Clostridium pasteurianum. Bioresour. Technol. 102, 4934–4937. Bankar, S.B., Survase, S.A., Ojamo, H., Granström, T., 2013. Biobutanol: the outlook of an academic and industrialist. RSC Adv. 3, 24734–24757. Biebl, H., 2001. Fermentation of glycerol by Clostridium pasteurianum – batch and continuous culture studies. J. Ind. Microbiol. Biotechnol. 27, 18–26. da Silva, G.P., Mack, M., Contiero, J., 2009. Glycerol: a promising and abundant carbon source for industrial microbiology. Biotechnol. Adv. 27, 30–39. Dabrock, B., Bahl, H., Gottschalk, G., 1992. Parameters affecting solvent production by Clostridium pasteurianum. Appl. Environ. Microbiol. 58, 1233–1239. Daniel, R., Stuertz, K., Gottschalk, G., 1995. Biochemical and molecular characterization of the oxidative branch of glycerol utilization by Citrobacter freundii. J. Bacteriol. 177, 4392–4401. Forage, R.G., Lin, E.C.C., 1982. DHA System mediating aerobic and anaerobic dissimilation of glycerol in Klebsiella pneumoniae NCIB 418. J. Bacteriol. 151, 591–599. Gallardo, R., Alves, M., Rodrigues, L.R., 2014. Modulation of crude glycerol fermentation by Clostridium pasteurianum DSM 525 towards the production of butanol. Biomass Bioenergy 71, 134–143. Girbal, L., 1995. How neutral red modified carbon and electron flow in Clostridium acetobutylicum grown in chemostat culture at neutral pH. FEMS Microbiol. Rev. 16, 151–162. Graef, M.R..De., Alexeeva, S., Snoep, J.L., Mattos, M.J.T..De., 1999. The steady-state internal redox state (NADH/NAD) reflects the external redox state and is

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