Biotechnology Letters 21: 1107–1111, 1999. © 1999 Kluwer Academic Publishers. Printed in the Netherlands.
1107
Catalytic and biocatalytic oxidation of glucose to gluconic acid in a modified three-phase reactor T. Doneva1,∗, C. Vassilieff2 & R. Donev3 1 Institute
of Chemical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Street, Bldg. 103, Sofia 1113, Bulgaria; Present address: Department of Chemical and Biological Process Engineering, University of Wales Swansea, Singleton Park, Swansea SA2 8PP, UK 2 Department of Physical Chemistry, Faculty of Chemistry, Sofia University, 1 James Bourchier Ave., Sofia 1126, Bulgaria 3 Institute of Molecular Biology, Bulgarian Academy of Sciences, Acad. G. Bonchev Street, Bldg. 21, Sofia 1113, Bulgaria; Present address: Human Cytogenetics Laboratory, Imperial Cancer Research Fund, P.O. Box 123, Lincoln’s Inn Fields, London WC2A 3PX, UK ∗ Author for correspondence (Fax: + 44 (0) 1792 295701; E-mail:
[email protected]) Received 16 September 1999; Revisions requested 27 September 1999; Revisions received 18 October 1999; Accepted 18 October 1999
Key words: fermentation, Gluconobacter oxydans, microfiltration, oxidation
Abstract A comparative study of catalytic and biocatalytic glucose oxidation was carried out. Gluconobacter oxydans NBIMCC 1043 strain was used for biocatalytic glucose conversion. In the case of cell recycle coupled with cross-flow microfiltration the productivity and biomass concentration reached 40% and 3 g l−1 respectively, in comparison to those of batch fermentation (21% and 2.3 g l−1 , respectively).
Introduction The oxidation of glucose to gluconic acid by Gluconobacter oxydans and Aspergillus niger in batch cultures was investigated by Velizarov & Beschkov (1994). The cell concentration in a batch reactor was too low (about 2 g l−1 ) and growth was totally inhibited at gluconic acid (glucose) concentrations higher than approximately 0.7 M (Velizarov & Beschkov 1998). Three factors strongly influence gluconate formation: pH, the bacterial and glucose concentrations. Generally, the biocatalytic transformation involves two problems: (1) low productivity resulting from the reactant (glucose) high concentration or product (acid) inhibition (Velizarov & Beschkov 1994, 1998), and (2) acid separation from the medium. The former could be avoided by continuous extraction of the product from the medium, either by electrodialysis or by continuous operation of the fermentation. A good solution is the combination of continuous operation
schemes with a membrane filtration technique. This method presents a possibility to separate solid components and products and to eliminate the inhibitors: the recycling of the cells increases the cell concentration and the reactor productivity compared to the conventional continuous operation (Lafforgue et al. 1987, Mota et al. 1987). With a tangentially-fed reactor suspension and an ideal semipermeable membrane filter (ideally permeable for solvent, ideally impermeable for soluteparticles) filtration leads to cake accumulation, according to the convective model (Vassilieff 1992, Vassilieff et al. 1996). With a flowing cake, steady-state filtration flux ν = Qf /A (Qf – steady-state filtration flow rate, A– filtration area) and transmembrane pressure Pf can be used to estimate the thickness at the end of the filtration path (Vassilieff et al. 1996). Pf /ν = Rm + (2/3)βδ,
(1)
1108 1992) with a longer filtration path (three rectangular slits with overall length L = 39 cm, height and width of the filtration channel h = 510 µm and W = 0.4 cm, respectively). The pore size of the polyamide microfiltration membranes MF 45 PA (Spartak Ltd., Bourgas, BG) was 0.45 µm. Phase description
Fig. 1. Experimental set-up: 1 – bioreactor, 2 – stirrer, 3 – automatic pH meter, 4 – thermostat, 5 – feed tank, 6 – pumps, 7 – three-way valves, 8 – microfiltration device, 9 – pressure gauge, 10 – filtrate outlet, 11 – level control.
where Rm is the filtration resistance of the ‘bare’ membrane, δ is the cake layer thickness, β is the specific filtration resistance. The formation of a dense cake with specific behaviour during the filtration of different particular and cellular suspensions was confirmed by experimental evidence obtained during the recent years (Benkahla et al. 1995). Here we show that the selective reaction of glucose with oxygen can be intensified by the application of cross-flow microfiltration using biocatalytic transformation and we compare the possibilities of the catalytic and biocatalytic methods.
Materials and methods Experimental set-up and operating conditions The experiments were performed in a reactor (Trinquart-Toulouse) coupled with a microfiltration unit (Figure 1). The reactor consists of two parts: a removable cap with four holes and a vessel. The pH value was measured and controlled by an automatic titrator (Radelkis). The temperature was maintained constant (32 ◦ C for a biocatalytic conversion and 55 ◦ C for a catalytic conversion) using a thermostat (MLW). A propeller stirrer (Janke and Runkel) was used for mixing the slurry. A modified cross-flow filtration laboratory device was used for filtration of the fermentation suspension. The filtration module used was constructed on the basis of the laboratory cell (Vassilieff
A catalyst consisting of 0.5% Pd on aluminium tablets was used for the catalytic oxidation of glucose. The catalyst was ground to fraction below 15 µm. The experiments were performed at a catalyst concentration 35 g l−1 at an active metal concentration 0.175 g l−1 . Polydispersed bentonite (0.4–2 µm) was used as a model system for the filtration experiments. The strain used in all fermentation experiments was provided from the Bulgarian National Bank for Industrial Microorganisms and Cell Cultures as Gluconobacter oxydans NBIMCC 1043 (Velizarov & Beschkov 1994, 1998). Anhydrous D-(+)-glucose was used as a reactant. The experiments were performed with 0.4 M glucose. The pH of the slurry in catalytic experiments was kept constant (pH = 9) by titration with NaOH. Fermentation medium of 72 g glucose l−1 and 10 g yeast extract l−1 as a growth factor was used. The medium was autoclaved for 30 min at 121 ◦ C. The viscosity of the reactor medium was measured by a rheometer (Rheotest 2, Germany). The measured value was µ = 1.8 × 10−3 Pa s−1 . The pH was between 4.5 and 5. Glucose oxidation was carried out with air as an oxidising agent at atmospheric pressure. The equivalent saturation pressure of the oxygen dissolved in the slurry was measured with an oxygen probe (Ingold sterilizable electrode). Analytical methods The content of gluconate was determined using Perkin–Elmer Series 10 HPLC system described in details by Velizarov & Beschkov (1994). Glucose was estimated enzymatically by the GOD/PAP method of Randox-Laboratories Ltd., UK. The biomass concentration was determined turbidometrically at 590 nm. Batch filtration The filtration resistance was measured with predeposited layers of different thickness (Stepner et al. 1985). The value of the specific resistance, β, of the
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Fig. 2. Time traces of glucose conversion during biocatalytic transformation (curve 1 – batch fermentation; curve 2 – continuous fermentation; curve 3 – continuous fermentation coupled with cross-flow microfiltration) and catalytic transformation (curve 4) at a starting glucose concentration 0.4 M.
cake above the membrane filter was obtained from linear best fits in the form: R = Rm + βδ.
(2)
The slope β depends on the assumed value of the close-packed concentration of the dense cake φ c . Reasonable volume fraction values for Gluconobacter oxydans (φ c = 0.5) and for the bentonite suspension (φc = 0.06) were used for comparison.
Results and discussion Comparison between catalytic and biocatalytic conversions Both the catalytic and biocatalytic oxidation of glucose were carried out with an initial glucose concentration of 0.4 M in a reactor with a volume, V = 1 l (Figure 1). This allows to compare the kinetics of glucose oxidation for these two methods (Figures 2, 3). It is seen in Figure 2 that the catalytic glucose conversion reaches 100% in 2 h. On the other hand gluconolactone and free gluconic acid can be produced biocatalytically (Table 1). The bioconversion degrees of glucose oxidation are presented in Figure 2. An expected higher conversion degree of glucose –
Fig. 3. Time traces of biomass concentration during biocatalytic transformation: curve 1 – batch fermentation; curve 2 – continuous fermentation; curve 3 - continuous fermentation coupled with cross-flow microfiltration.
99% under the conditions of continuous cell recycle coupled with cross-flow microfiltration – was registered experimentally. The continuous performance of biocatalytic oxidation eliminated inhibitors in the reactor and, combined with microfiltration, increased the productivity by 47% in comparison to that of batch fermentation. The optimal dilution rate D = 0.1 h−1 (D = Q/V , where Q is feed flow-rate) was determined experimentally. All continuous experiments have been carried out with the optimal dilution rate. The biomass concentration obtained under the conditions of continuous cell recycle coupled with crossflow microfiltration was 23% higher than the biomass concentration obtained in batch fermentation (Figure 3 and Table 1). The microfiltration membrane filter with nominal pore size 0.45 µm successfully retains Gluconobacter oxydans (size approximately 1 µm). In this way the cross-flow microfiltration unit simultaneously separates biocatalyst from the product and increases cell concentration. Finally, the comparison between the catalytic and biocatalytic methods shows that the highest rate of the glucose oxidation to gluconate is reached faster by catalytic conversion. Biocatalytic transformation has advantages with respect to the quality and selectivity of the products (free gluconic acid and gluconolactone) but the process is slower. In this case the effect of continuous cell recycle coupled with cross-flow mi-
1110 Table 1. Comparison of catalytic and biocatalytic conversions of glucose K gluconolactone and gluconic acid. Operation conditions
Final biomass concentration (g l−1 )
Final concentration of products (g l−1 )
2.3 2.5 3.0
56 66 71
Conversion %
Productivity (mM l h−1 )
Biocatalytic conversion Batch Continuous Continuous with microfiltration Catalytic conversion Batch
78 92 99
21 31 40
100
200
Na-gluconate –
Fig. 4. Results from direct batch measurement of filtration resistance of bentonite (1) and Gluconobacter oxydans (2) cakes.
crofiltration, compared to batch transformation, was positive: 23% enhancement of biomass concentration, 47% increase of productivity.
Filtration behaviour The filtration resistance of the bacterial cake (Gluconobacter oxydans) was measured during a batch filtration experiment (β is determined from Equation (2)). The data are presented in Figure 4 together with the data for a polydispersed bentonite sample. The β value for Gluconobacter oxydans (β = 3.7 ×
72
Fig. 5. Time traces of filtration flow-rates at different flow regimes: (1) Qin = 330 ml h−1 (peristaltic pump); (2) Qin = 15 l h−1 (pulsating pump).
1014 N s m−4 ) is much higher, compared to the filtration resistance of bentonite cakes (β = 2.1 × 1012 N s m−4 ) and yeast cells (β = 3 × 1012 N s m−4 ) (Malinowski et al. 1987). This result indicates that different conditions are required to control the thickness of different cakes. The higher filtration resistance of the bacterial cake could be a result of an eventual deformability of bacterial cells. The time traces of filtration flow-rates during cross-flow filtration of Gluconobacter oxydans at two different flow rates of feeding in the filtration unit are shown in Figure 5. It should be pointed out that the higher flow-rate is a result of a pulsating feeding in the
1111 filtration module. In both cases a steady-state filtration flow-rate is reached after an initial transient decrease, corresponding to the accumulation of a cake with an increasing thickness. The steady-state Qf is enhanced 3 times at the higher feed flow-rate compared to the lower flowrate. The steady-state filtration flow-rates (Qf 1 = 2.3 × 10−5 m3 h−1 and Qf 2 = 0.7 × 10−5 m3 h−1 ), the directly measured value of filtration resistance of bacterial cake (β = 3.7 × 1014 N s m−4 ), and Equation (1) allow to estimate the thickness at the end of the filtration path (the measured pressure at the filtration channel inlet is 0.1 atm) for the different feed flowrates. The values of the thickness are: δ = 10 µm and δ = 33 µm for Qf 1 and Qf 2 respectively. At the lower feed flow-rate the filtration of the reactor medium does not lead to a measurable increase in the biomass concentration. At the higher feed flow-rate both biomass production and process productivity are improved (see Figures 2, 3 and Table 1). Approaches about the enhancement of permeate flux by flow pulsation in microfiltration were carried out by Gupta et al. (1992). The quantitative estimation of the pulsating effect of feeding on the process productivity is an object of supplemental further investigations.
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